Innovative Computing and Information, Part I - ICCIC 2011

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Communications in Computer and Information Science

231

Minli Dai (Ed.)

Innovative Computing and Information International Conference, ICCIC 2011 Wuhan, China, September 17-18, 2011 Proceedings, Part I

13

Volume Editor Minli Dai Suzhou University No. 1, Shizi Street Suzhou City, 215006, China E-mail: [email protected]

ISSN 1865-0929 e-ISSN 1865-0937 ISBN 978-3-642-23992-2 e-ISBN 978-3-642-23993-9 DOI 10.1007/978-3-642-23993-9 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: Applied for CR Subject Classification (1998): C.2, H.4, I.2, H.3, D.2, J.1, H.5

© Springer-Verlag Berlin Heidelberg 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface

The present book includes extended and revised versions of a set of selected papers from the 2011 International Conference on Computing, Information and Control (ICCIC 2011) held in Wuhan, China, September 17–18, 2011. The ICCIC is the most comprehensive conference focused on the various aspects of advances in computing, information and control providing a chance for academic and industry professionals to discuss recent progress in the area. The goal of this conference is to bring together researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of computing, information and control. Being crucial for the development of this subject area, the conference encompasses a large number of related research topics and applications. In order to ensure a high-quality international conference, the reviewing course is carried out by experts from home and abroad with all low-quality papers being rejected. All accepted papers are included in the Springer LNCS CCIS proceedings. Wuhan, the capital of the Hubei province, is a modern metropolis with unlimited possibilities, situated in the heart of China. Wuhan is an energetic city, a commercial center of finance, industry, trade and science, with many international companies located here. Having scientific, technological and educational institutions such as Laser City and the Wuhan University, the city is also an intellectual center. Nothing would have been achieved without the help of the Program Chairs, organization staff, and the members of the Program Committees. Thank you. We are confident that the proceedings provide detailed insight into the new trends in this area. August 2011

Yanwen Wu

Organization

Honorary Chair Weitao Zheng

Wuhan Institute of Physical Education, Key Laboratory of Sports Engineering of General Administration of Sport of China

General Chair Yanwen Wu

Huazhong Normal Universtiy, China

Program Chair Qihai Zhou

Southwestern University of Finance and Economics, China

Program Committee Sinon Pietro Romano

Azerbaijan State Oil Academy, Azerbaijan

International Program Committee Ming-Jyi Jang Tzuu-Hseng S. Li Yanwen Wu Teh-Lu Liao Yi-Pin Kuo Qingtang Liu Wei-Chang Du Jiuming Yang Hui Jiang Zhonghua Wang Jun-Juh Yan Dong Huang JunQi Wu

Far-East University, Taiwan National Cheng Kung University, Taiwan Huazhong Normal University, China National Cheng Kung University, Taiwan Far-East University, Taiwan Huazhong Normal University, China I-Shou University, Taiwan Huazhong Normal University, China WuHan Golden Bridgee-Network Security Technology Co., Ltd., China Huazhong Normal University, China Shu-Te University, Taiwan Huazhong University of Science and Technology, China Huazhong Normal University, China

Table of Contents – Part I

A Study on Cloud Backup Technology and Its Development . . . . . . . . . . . He Zhonglin and He Yuhua

1

Research on the Engineering Management Reform of the Yellow River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deng Yu and Gu Lieya

8

Research on Hospital CRM System Model Based on Multi-Agent . . . . . . . Wang Suozhu and Fu Yan

14

Risk Assessment Based on the Life Cycle of Virtual Enterprise . . . . . . . . . Xia Wang, Zhimin Xie, and Xianjun Guan

21

Research on Financial System Computing Simulation . . . . . . . . . . . . . . . . . Tang Chuan and Chen Ling

29

The Construction and Evaluation of the Regional Innovation System of Zhejiang Province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cai Ning and Huang Chun

36

Design of an Improved Method of Rijndael S-Box . . . . . . . . . . . . . . . . . . . . Chunxia Tu

46

Implementation of AES S-Box Based on VHDL . . . . . . . . . . . . . . . . . . . . . . Zhichao Yu

52

Research on Security of VoIP Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaojun Liu and Chunxia Tu

59

The Analysis on Network Security and Protection . . . . . . . . . . . . . . . . . . . . Zhou Jing

66

The Analysis of the Safety Defects Based on ASP.NET . . . . . . . . . . . . . . . Zhou Jing

71

Spatial Distribution and Vertical Variation of Cu Concentration in Guangdong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fang Yuan and Chen Li-yan

76

The Quantitative Application of Information Extraction by Remote Sensing in Aranbaotai Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fang Yuan and Chen Li-yan

83

VIII


Research on the Sustainable Development of Export Trade in China . . . . Fei Wang

88

The Game Analysis of the Reasons for Chinese Defeat in Iron Ore Negotiation—Based on the Bargain Model . . . . . . . . . . . . . . . . . . . . . . . . . . Xianyong Zheng and Hanmin Huang

94

Research on Coal Mine Safety Accident Based on Grey Relational Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xue Yang and WenSheng Li

101

E-V Utility Function and Its Application in Shanghai Securities Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qiang Shao, Zhongbing Wu, and Feng Zhou

109

Bender’s Algorithm for Facility Location Problem with Uncertain Demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Haibin Li, Jun Yan, and Mingming Ren

115

A Kind of Coal Mine Safety Control Model Based on Cybernetics . . . . . . Lixia Qi and Xue Yang

124

The Research and Progress of Global Digital Content Industry . . . . . . . . . Han Jieping, Cong Rijie, and Wei Yaqiong

132

A Novel Smoothing Method for Symmetric Conic Linear Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaoni Chi and June Liu

143

Supply Chain’s Function in Improving the Innovation of Building Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhang Xi ping and Zhu Ming qiang

150

On Innovative Impetus Driving China’s Sustainable Economic Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wu Yong

156

Highway Operation Safety Management Decision-Making Model . . . . . . . Zhang Huili, Sun Hailong, and Kang Yongzheng

161

Question and Countermeasure Existing in the University Finance Informationization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Liyu and He Zhonglin

166

Study of the Training for a Financial Informationization Talented Person in Electronic Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Liyu

172

The Impact of Technology Acquisition Mode on Innovative Performance of Listed Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chengyu Wen and Zhixin Liu

177


IX

Institutional Arrangements for Knowledge Sharing in R&D Team . . . . . . Tu Jing and Zhang Wenping

184

Study on the Forming Mechanism of Brand Alliances Based on the Brand Community . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wang Chujian

191

Arrangement of Venture Enterprise Financing Contract with Taking Entrepreneurs as Center Contractors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fumin Wang

198

Knowledge Management’s Functions in E-Commerce Implementation . . . Zhang Xi ping and Zhu Ming qiang

206

Research and Practice Based on GIS to Improve Commercial Network Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Li Hengkai and Liu Xiaosheng

213

Pricing and Revenue Sharing Analysis on Platforms and Content Providers under Tri-networks Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chonglu Wang, Rong Luo, and Zhanhong Xin

222

Research on the Application and Development Prospects of Accounting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wang Na

233

Review of Customer Citizenship Behaviors Scales in Service Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Song Yang and Ma Qinhai

238

China’s Low Carbon Economic Rise and Countermeasures of Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tao Yu

244

Undergraduate Accounting Major’s Main Curriculum’s Situation Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jin Huixin, Zhao Rui, Guo Yanzhen, and Li Guohong

248

How to Build the Knowledge Resources Framework of Real Estate Enterprises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shen Liang-feng

255

Explore and Analyse of Computer Network Security Technique and Defence Tactics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wang Fengling and Wang Zhiqiang

262

On the Countermeasures of Consummating Bank Internal Accounting Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaohui Wang and Yong Zhang

269

X


Analysis on Strategy of Human Resource Management in Economy Hotel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xuan Fuhua

275

Research on the Index System and the Evaluation Method of Logistics Service Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mai Ying

280

Social Benefits Evaluation of Reverse Logistics – Case of the Automobile Recall System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiang Chengcheng and Li Congdong

288

Study on Trust Model in P2P . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gan Zhi-gang

295

Information Technology and Economic Growth – The Empirical Research Based on Spatial Econometric Model . . . . . . . . . . . . . . . . . . . . . . . Zhou Qin and Zhang Hong-li

302

The Practice Teaching Model of Accounting Research . . . . . . . . . . . . . . . . Zhou Xiaona, Zhao Rui, Mao Jiuzhi, and Zhang Yin

313

Research about Broadband Media Distribution Protocol on Media Stream System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiang Guo-song and He Xiao-ling

320

Research about Media Location Registry and Content Distribution Base on MSA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiang Guo-song and He Xiao-ling

328

IUP Modeling Method and Its Application for Complex Information Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yingyong Bu, Libin Zhu, and Jinyu Wang

335

Study on International Competitiveness of Tire Industry Based on Factor Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Jing-xin and Wang Xiao-ying

343

Study on Quantitative Evaluation of Enterprise Core Competence Based on Resources and Capabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Jing-xin and Liu Wei

351

Automobile Insurance Pricing with Bayesian General Linear Model . . . . . Cheng Gao, Qi Li, and Zirui Guo

359

Risk Identification Based on Strategic Steps of Brand Alliances . . . . . . . . Wang Chujian

366

The Application of Fuzzy Synthesis Evaluation Method Based on ANP in E-Business Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhang Xinzhong and Qin Yamin

373


XI

Research and Application of Three Dimensional Visualization of Geological Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hua Li and Hao Wu

380

The Control and Measure of Requirements Stability in Software Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Ting

387

A Novel Initial Radius Selection with Simplify Sphere Decoding Algorithm in MIMO System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Song Yang, Li Jianping, and Cai Chaoshi

395

The Research of Customer Relationship Management between China and Foreign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xinbao Guo

403

The Process Reengineering of Accounting Information System . . . . . . . . . Xinbao Guo

409

The Model of Optimal Price and Leadtime in the Decentralized Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Quan Jie

413

Urban Residential Land Automatic Recognition from Remote Sensing Image Based on Combined Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yunjun Zhan

421

Decision Support System for Emergency Response of Geological Hazards in Three Gorges Reservoir Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . Haifeng Huang and Shimei Wang

428

To Promote the Development of Retail E-Commerce in Depth with Regional E-Commerce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bo Zhang, Haijun Zhang, and Bingwu Liu

437

Research on Management Accounting for SMEs Innovation in China . . . . Min Pan

446

Web Services Technology and Its Application in Geophysical Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianbo Lian, Minghua Zhang, and Chengxi Wang

451

The Analysis of Strengths and Weaknesses of Online-Shopping . . . . . . . . . Li Milong

457

Confusion of Franchisor of Chain Business and Development Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Li Yuhong, Lu Hong, and Han Weixi

465

XII


On Early Warning Evaluation Index System of Enterprise Purchasing Risk Based on the Balanced Scorecard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yongsheng Liu and Chunlei Ma

471

Investment Value Analysis for Listed Companies of China Communications Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hua Han and Fei Tang

478

E-Comeerce Extension Multi-factor Assessment . . . . . . . . . . . . . . . . . . . . . . Sunxu and Wan Haixia

484

SWOT Analysis of E-Commerce Development in Yunnan Province . . . . . Sun Liangtao and Chen Gang

492

Application of Analytic Network Process in Agricultural Products Logistics Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaolin Zhang and Chunhui Wang

500

SMEs Contest between Asymmetric Rivals in Financial Market from an Evolutionary Viewpoint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zheng Zhou and Fanzhao Zhou

507

Study on Fuzzy Evaluation of Train Operation Dispatching System for China Passenger Dedicated Lines Based on AHP . . . . . . . . . . . . . . . . . . . . . Sunqi, Zhangyanpeng, Liyulong, and Liminzhi

513

Disruption Management Optimal Decisions of Supply Chain under Uncertain Environment Based on Dynamic Network . . . . . . . . . . . . . . . . . . Xiaonan Cai and Jing Lu

519

Visual Angles and Reference Systems of Management Theory . . . . . . . . . . Sun Bo

526

Process Improvement Model and It’s Application for Manufacturing Industry Based on the BPM-ERP Integrated Framework . . . . . . . . . . . . . . Liu Hongjun and Li Nan

533

A Study of Business Process Reengineering Based on Petri Net . . . . . . . . Kang Zhiyuan

543

Combined Noise Reduction in CT-Image Based on Adaptive Median Filter and Wavelet Packet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Houjie Li, Jiyin Zhao, Shuang Xu, and Yanqiu Cui

550

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

559

A Study on Cloud Backup Technology and Its Development He Zhonglin1 and He Yuhua2 1

Computer College of Science and Technology, Huanggang Normal University, Huanggang, Hubei, China. 438000 2 Chinese Teaching and Research Group, Tuanfeng Experimental High School, Tuanfeng, Hubei, China. 438800 [email protected]

Abstract. With the rapid development of computer technology, IT hardware price continues to decrease. Equipment is no longer important, while data is becoming increasingly vital. Cloud backup service is ideally suitable for those who wish to provide valuable data backup solution and hold data safely beyond data center. In this paper the development of cloud backup technology is illustrated. Compared with conventional backup software, the advantages of cloud backup technology and its challenges are analyzed. Combined with cloud backup service platform, B-Cloud, the cloud backup service mechanism is introduced. Moreover, it makes a simple conjecture on the future development of cloud backup technology. Keywords: Cloud backup, PaaS, B-cloud.

1 Introduction In recent years, with the emergence of SaaS (Software-as-a-Service)[1][2] and Cloud Computing [3][4], Cloud backup service gradually become a hot topic in IT field and its core concept is to realize customer value through services. As data scale and data safety is sharply increasing, a third party is urgently needed to provide professional online data backup service. Cloud backup service software is the core technology to establish professional online data backup service, which has great social and economic benefits. Cloud backup service platform software can realize online backup and restore services of file set, database and operating system under heterogeneous WAN environment consisting of Microsoft Windows and Linux platform, which is favored by users. Compared with traditional software, it has many advantages, like low cost, quick returns, easy management, easy and flexible operation, etc. Due to the importance of data backup and the many advantages of cloud backup service, it has gradually become a new direction of storage application field. Bill Gates has said openly several times that software will eventually become a kind of service.

2 The Development Status of Cloud Backup Cloud backup is to automatically store data located at the client into the center of cloud data of SSP (Storage Service Provider) through network so as to recover data in time. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 1–7, 2011. © Springer-Verlag Berlin Heidelberg 2011

2

H. Zhonglin and H. Yuhua

About ten years ago, there were some SSPs who began to hype online backup service concept, but because of the technical problems and bandwidth limitation, it wasn’t put into practice. In recent years, along with the thriving of SaaS and cloud computing, cloud backup experiences a rapid development. A. The Overseas Development Status of Cloud Backup American Berkeley Data System Company was established in 2005. The Mozy software it developed can provide online backup service, and has a great deal of enterprise and individual customers. EMC acquisitioned Berkeley data System Company in September 2007 with $76 million, and eventually acquired Mozy software. It took SaaS as the core direction of its future products. In May 2009, McAfee officially announced its cooperation with EMC, and provided online backup service with Mozy department of EMC together. In July 2009, EMD takeover data companies in duplicated data deletion field with $21 billion, and engaged in new generation of disk backup and recovery solutions. Tool software vendor Symantec announced its business in cloud backup market in April 2007, and launched its product: Symantec Protection Network. Later, it acquisitioned Network backup service provider SwapDrive in 2008 with $123 million. In June 2009, Symantec and Hewlett-Packard (HP) reached cooperation. HP resales the cloud backup services of Symantec through its personal computers. PC users must pay the fee yearly after a month free trial of online backup. In addition to the above representatives like EMD and Symantec that provide software backup solution, Amazon's simple storage service is based on the concept of service infrastructure, and takes a charge according to the volume of data being stored. Nirvanix Company also claimed that its cluster structure of warehousing and distribution networks can provide higher reliability and usability for the recovery of backup data. There are other major manufacturers that enter into cloud backup field through acquisitions, such as Iron Mountain who takeover PC data online backup and restore service provider Connected in 2004 with $1.17 billion, and LiveVault Company in 2005 with $50 million. It continues to expand its product line and service range through acquisitions, and in 2007 the company's revenues reached $27 billion. The hardware manufacturer Seagate takeover Evault with $1.85 billion at the end of 2006. It binds SaaS products on hardware products for sales. The giant IBM bought Arsenal Digital Company with $1.1 billion in 2007, for Arsenal Digital Company has been committed to the high-end online backup market. B. The Domestic Development Status of Cloud Backup New research of Datacenter of the China Internet shows from 2006 to 2011 the compound growth rate of cloud backup market will reach 33.3% and by 2011 the yearly income will reach $715 million, but this data does not include China. The reason that foreign firms did not introduce cloud backup service into Chinese market lies that some large domestic enterprises have already set up their own data centers, and those small and medium-sized enterprises still have consumption habit obstacles to accept this service. While the cloud backup market abroad is thriving, the domestic cloud computing has also raised [5]. Shanghai Eisoon Software Company together with Shanghai telecom launched "biz navigator – Eisoon enterprise online backup" service in 2006. The purpose is to provide disaster tolerance service at different locations for Chinese

A Study on Cloud Backup Technology and Its Development

3

enterprises. The initial service only covers Shanghai city, and now gradually develops in a nationwide area. China telecom also launched its file storage service -- e cloud online backup software [6]. Free users can possess a 2G space, and for larger space, fee is needed. Through e cloud online backup, private chatting and transaction records, family photographs and video, music files and other important computer files can be protected. The largest IDC service provider launched a cloud computing platform--CloudEx in 2008, providing elastic computing services for Internet enterprises and storage and backup services for individuals and small and medium-sized enterprises. Cloud backup has become an important direction in storage industry, while there is less foreign literature about the systematic discussion of cloud backup in the academic filed. In Internet backup, peer-to-peer (P2P) network backup is often used [7] [8]. The equivalent node stores the backup data of other nodes. Each node makes a contribution of its idle storage resources, at the same time, they complete data backup corporately. By this mode, the mutual trust between nodes, as well as the management of multiple nodes becomes challenging problems. Some experts suggest a service-oriented backup method [9], which brings peer-topeer network backup into client/server backup mode, taking use of the idle resources of application servers to constitute a virtual backup server. However, as it involves many factors, this method is only applicable to backup services in fixed geographical scope, not for the WAN. Some scholars put forward the idea of combining client/server and peer-to-peer model together, designing a backup and recovery system servicing JTang files [10]. Some industry delegates propose general data center architecture based on network storage and backup [11], which divides the data of application system into fixed data and variable data, and respectively backup and stored so that the application system can be recovered in time. Blue Whale Backup System (BWBS) [12] developed by Computing Technology Research Institute of Chinese Academy of Sciences is for data backup and management of Blue Whale virtual storage equipment system. The development of many current backup systems more or less takes a reference of open source network backup system Bacula [13]. Bacula can realize many backup and restore functions perfectly, but it doesn’t solve gateway penetration problem well, and the backup server is responsible for connecting the backup client actively, so the software can only be used in LAN within enterprises, but not for the WAN, and it cannot turn from software mode to service mode. Another open source backup recovery software called Amanda [14], developed by Maryland University, is based on traditional UNIX backup tools such as dump and tar, which supports the capability of saving workstation data into tapes, and is widely used.

3 Analysis of Cloud Backup Technology Cloud backup service mode has many advantages compared with backup software, and also conforms to the trend of current software evolution. The important factor that influences its acceptance lies in users’ consumption habit. At present, most users favor to backup their important data in storage equipment in the side, while online storage service allows users to store their data in the online data center of storage service providers, which will undoubtedly make many users worry about data security problem. Thus, from the technical angle, to capture the market, cloud backup must guarantee the safety and reliability of users’ data. When accident occurs, it can guarantee 100% data recovery, at the same time, it also needs enough network resources to ensure the speed of backup services. Technical problems will directly

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cause the failure of cloud backup promotion. In April 2008, HP Upline cloud backup service was formally online, but in early 2009 it had no choice but close. When Hewlett-Packard first launched cloud backup, it failed. The reason is that the infrastructure is unable to keep pace with the increasing users brought by free trial, and system overload causes machine crash [15]. There are some other examples of failure, such as S3 cloud storage service of Amazon that failed because of software malfunction [16], Google's Gmail that cannot operate for several hours due to system faults, and Linkup that has to stop service after losing nearly half of data being stored. Cloud backup service system under WAN environment must satisfy various needs. It must be compatible with the heterogeneous data platform of the client, and satisfy the high extensibility of end storage devices and the storage organization form of mass data. It must both consider network transmission efficiency, and ensure the security of data. It satisfies data integrity not only at the block and file level, but also at the application layer. Moreover, it also must provide concurrent access for a large number of users, and have active control over service quality. To take overall consideration of these problems means that cloud backup system faces more complex technical problems during the development process than conventional backup software. The efficient solution of these problems is the key that determines whether cloud backup is accepted by users or not. The differences between cloud backup and traditional backup are: from the aspect of users, what users concern include: first, security problem, namely, how to ensure the data on the cloud is not theft, tampered and leaked; second, performance problem, namely, is backup quickly enough to satisfy users demands; third, reliability problem, namely, whether data recovery is reliable. From the aspect of service, what service providers concerns include: how to deploy and provide stable backup service? how to realize easy extension, upgrade and management? how to reduce service cost? From the aspect of research, what researchers need to solve include the system structure of cloud backup, the security policy of backup data, concurrent scheduling of multi-user backup jobs and the effective management of the mass data etc. Therefore cloud backup is going to face challenges from five aspects [17], the first is to meet user needs at a lower cost; the second is to solve cross-regional centralized management and concurrent access problems brought by centralized storage of mass data; the third is to guarantee the high reliability and privacy of backup data; the fourth is to ensure service quality within limited bandwidth; the fifth is to consider backup information sharing so as to satisfy fast expansion of new business.

4 B-Cloud B-Cloud is based on the idea of PaaS (Platform as a Service), which provides a development framework, submitted to users in SaaS mode. It is also a kind of application of SaaS mode, but it can accelerate the development of SaaS, especially the development speed of SaaS applications. Based on the above concept, high reliable, extensible and upgradable applications can be developed. One application can have several instances at the same time, and there is no single point of failure. Application servers can make lateral extension and automatically acquire maintenance, do not need manual maintenance. Huazhong University of Science and Technology and Wuhan Hexun Computer Engineering Co., LTD. jointly developed a cloud backup service platform (B-Cloud) [18], which adopts backup technology, providing online backup services for education network users. The deploy structure is shown in figure 1. This


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system includes three-level backup: the upper layer is wide-area cloud (public cloud), covering areas accessed by all backup users through WAN. The wide-area cloud servers include the wide-area manager and the wide-area cloud storage nodes. The middle layer is regional cloud, generally divided according to the geographical areas (such as provinces, municipalities, etc.). The corresponding service nodes include the regional managers and regional storage servers. The lower layer is local cloud (private cloud), which can be divided according to smaller geographical area or specific entities, such as campus, enterprises or organizations. It can run both in the WAN or LAN. Users are limited to the local area. Service nodes include the local managers and private cloud storage servers. Regional cloud and private cloud, similar to wide-area cloud, has multiple local storage servers that provide services for multiple backup clients corporately.

Fig. 1. The deployment structure of B-Cloud

The topology of the above B-Cloud backup system may be described as: wide-area cloud is taken as the root node, regional and local cloud as branch nodes, and a tree structure is formed Each node has its own backup managers and storage servers, which are to realize the backup task scheduling and backup data access at the local area. There is physical connection between wide-area cloud, regional cloud and local cloud. The relationship between the adjacent layers is called father-son relationship, and the child node can be considered as a special customer of the father node. This structure has good expansibility. At present, only three layers have been defined. With the increasing of user scale and the expanding of service area, nodes at a certain layer can be split as needed, and new nodes can be added. The B-Cloud backup system includes three modules: cloud backup client, cloud backup manager and storage server. A. Cloud Backup Client Cloud backup client software is installed on the host machine that is geographically distributed and needs to accept backup services. It can be a common customer terminal, a WWW server, and database server or file server. The communication between the client and the manager is mainly to make preparation before backup and restore operation and record state feedback during and after the operation, including user registration, creating backup objects, assigning backup objects corresponding

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backup policy, obtaining the address of the storage servers and session key information, and feedbacking status information to the scheduling servers at a regular interval. The client and the storage server merely complete backup and restored data transmission. During data backup, the client is responsible for acquiring all source data needed backup, and sending it to the storage server according to the manner set by the system. During recovery, the inverse operation is done. The storage server sends the required data to the directory specified by the client so as to recover the data. B. Cloud Backup Manager Cloud backup manager is the monitor and management center of the whole service system, which is responsible for registration and management of users and storage servers, task scheduling, status monitoring during job execution and metadata management. When a client logins in the system, it does identity authentication to make sure whether it is a legitimate user. It scans task queue regularly. When the execution time is end, another service thread is started. According to load balancing policy, connection between the client and server is established, and task execution is monitored. At the same time, each storage server status is also monitored and regular space arrangement and fragment recovery is done. The database needed for execution is maintained by managers, which backup registration information of the client and the storage server, as well as some dynamic information related to job execution such as backup object information, task list information, version information of successful backup, error log information, etc. The correct recovery of backup data is realized through the mapping relationship between logical files stored in cloud backup managers and physical data blocks. C. Storage Servers The storage server is a valid storage medium node accredited by the manager. Under the centralized management of the manager, it makes real-time responses to data backup and recovery queries from multiple clients, accepts backup data, manages data storage and sends recovered data to the backup client. To support efficient execution of backup and recovery operations, reasonable organization mode and management methods of backup data must be designed for the storage server. At the same time, the system must support multiple storage servers and multiple files single server, realize high expansibility of the storage side, and satisfy mass data storage requirements.

5 Conclusions From cloud computing to cloud storage, cloud backup, and to more future applications, there is still a long way to go for both research and industrialization. As the 10 big predictions of information industry and telecoms industries in 2010 announced by Internet Data Center, cloud computing will expand and become mature, many new public cloud and private cloud services, cloud applications and services related public cloud and private cloud together are emerging. Cloud backup provides users a new way of data disaster tolerance, and it is an application of cloud storage. Of course, compared with traditional distributed storage technology, deeper study must made on underlying data organization, parallel task scheduling and security strategies.


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References 1. Laplante, P.A., Zhang, J., Voas, J.: What’s in a Name? Distinguishing between SaaS and SOA. In: IT Pro., May/June 2008, pp. 46–50 (2008) 2. Namjoshi, J., Gupte, A.: Service oriented architecture for cloud based travel reservation software as a service. In: Proceedings of 2009 IEEE International Conference on Cloud Computing (CLOUD), pp. 147–150. IEEE, Piscataway (2009) 3. Hayes, B.: Cloud Computing. Communications of the ACM 51(7), 9–11 (2008) 4. Lin, G., Dasmalchi, G., Zhu, J.: Cloud computing and IT as a service: opportunities and challenges. In: Proceedings of 2008 IEEE International Conference on Web Services. IEEE, Piscataway (2008) 5. Zheng, W.: The Curtain of Cloud Computing Is Opened. Communications of CCF 6, 6–7 (2009) 6. http://www.zaix8.com/html/zaixiancunchu/eyun.html 7. Tran, D.N., Chiang, F., Li, J.: Friendstore: Cooperative online backup using trusted nodes. In: Proceedings of the 1st Workshop on Social Network Systems, pp. 37–42. Association for Computing Machinery, USA (2008) 8. Lluis, P.-J., Pedro, G.-L., Marc, S.-A.: Rewarding Stability in Peer-to-Peer Backup Systems. In: Proceedings of 16th IEEE International Conference on Networks, pp. 1–6. IEEE Computer Society, United States (2008) 9. Cheng, H., Ho, Y.H., Hua, K.A., et al.: A Service-Oriented Approach to Storage Backup. In: Proceedings of 2008 IEEE International Conference on Services Computing, pp. 413– 421. IEEE Computer Society, United States (2008) 10. Su, Y.: Design and Implementation of Backup and Recovery Tool for Distributed File Storage System. Library of Zhejiang University, Hangzhou (2008) 11. Zhang, Z., Zhang, X.: Generalized Data Center Architecture Based on Network Storage and Backup. In: Proceedings of 2008 ISECS International Colloquium on Computing, Communication, Control, and Management, pp. 166–169. IEEE Computer Society, United States (2008) 12. Xu, W.: Blue Whale Backup System. Computer Engineering 34(19), 9–11 (2008) 13. Bacula, http://www.bacula.org 14. da Silva, J., Guthmundsson, O.: The Amanda network backup manager. In: Proceedings of the Seventh System Administration Conference, pp. 171–182. USENIX Assoc., Berkeley (1993) 15. http://storage.doit.com.cn/article/2009/0302/6947880.shtml 16. Gohring, N.: Amazon’s S3 down for several hours (2008), http://www.pcworld.com/businesscenter/article/142549/ amazonss3downforseveralhours.html 17. Li, J., Zhou, Y.: Innovations of Online Backup Service based on Cloud Storage. Technology forum 3, 35–37 (2010) 18. http://www.backupcloud.com.cn

Research on the Engineering Management Reform of the Yellow River Deng Yu and Gu Lieya Yellow River Institute of Hydraulic Research Research Center on Levee Safety Disaster Prevention MWR Zhengzhou, china [email protected]

Abstract. For further improving and perfecting the level of engineering management, the engineering management database of Yellow River is established, which is an effective means to realize the share and distributed storage of basin engineering management information and serves the function of regulating development of the Yellow River engineering management. At the same time, the system framework of new management mode is established preliminarily and the level of engineering management is reformed dramatically. Keywords: engineering management, database, management mode, Yellow River.

1 Introduction The reform of water management system concentrating on separation of management and maintenance conducted by YRCC, which is related to the further development of 76 water management departments under YRCC, has very important significance. Facing the total new system, how to establish matching management mode which is “management scientifically and running canonically “has been paid much attention by each sides from the beginning of reform and specially studied by YRCC following the issue of related regulations and large –scale training. The “Digital Yellow River” project has the function of data collection, real–time transmission, storage management and on-line analysis and process, so it can realize effective management of the flood control projects. The establishment of Yellow River engineering management database is an important means to realize the share and distributed storage of basin engineering management info and serves the function of regulating development of the Yellow River engineering management database. At present, the system framework of new management mode is established preliminarily and the level of engineering management is reformed dramatically. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 8–13, 2011. © Springer-Verlag Berlin Heidelberg 2011

Research on the Engineering Management Reform of the Yellow River

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2 Database of Engineering Management A. Establishment Contents According to the characteristics of the Yellow River flood control engineering management and practical situation, the large quantity basic info generated in the longterm management and operation of the Yellow River flood control projects is analyzed, sorted, compiled. Thus the management info is classified into three types, i.e. basic info of engineering management, management info of project operation and safety monitoring info of flood control. The basic info of engineering management is the original data describing basic features about the Yellow River flood control projects, including declaration to project site, engineering structure and technology. The management info of project operation is generated in operation and maintenance process of the Yellow River flood control projects and includes the management info about daily project maintenance, detection for hidden defect, project inspection etc. In addition, the management info of maintenance for biology protection engineering and pertain establishment is included, too. The safety monitoring info of flood control is collected by the inner-outer sensors and nondestructive examination technology from the flood control projects, such as dike, danger spot, river training project, water gate etc. B. System Management The database structure construction of the Yellow River engineering management database had been finished in the end of 2003 and the test operation run in the Yellow River Transaction Agency Zhengzhou foremost. The database is late-model according to unified standards of “Digit Yellow River” (ORACLE 91, ARC/INFO). So far, the database has been logged in a lot of transaction agencies. [1] 1) Info Acquisition There are two manners for database info acquisition of the Yellow River engineering management database. One is on-line real time acquisition, such as sensor collecting data on site, which can realize real-time monitoring, regular observation and entering warehouse automatically, and the other is non-on-line and non-real-time acquisition, including file info of project history and late data of artificial acquisition. 2) Info Log-in The info of the Yellow River engineering management is collected by county engineering management departments and checked to log in base by town engineering management departments. The staff of logging data is authenticated safely. 3) Authority of System Management The administrative organization for the Yellow River flood control projects is ranked to four grades, whose authority can be set according to application function and user demand.

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•

•

• •

The county administrative departments are the basic net station. They are in charge of logging data and the logging data staff should pass the safety authentication. In addition, they have the access to call the relevant info of one’s county, call-on the superior public platform. The city project departments manage the county project departments within their domain. They are in charge of the work of check and log-in data, authenticating log-in data and the staff entering warehouse. They have the access to call data info of all county engineering management stations within their domain, call-on the superior public platform. The provincial engineering management departments manage the city departments. They have the access to call the data info of all city and county project departments within their domain, call-on the superior public platform. The Yellow River Conservancy Commission engineering management department manages the provincial project departments and directly under project departments. And it has the access to call the data info of the departments within its domain.

3 Management Modes The research on management and operation modes of the Yellow River engineering should be under the guidance of “the implementation proposal of the reform on management system of hydraulic engineering “issued by the state council, and the precondition of guaranteeing the integrity and safe-operation afar the separation of management and maintenance. The unified, scientific and canonical criteria system which is “management scientifically and running canonically” should be formed step by step, and restriction mechanism including trade restriction, restriction between departments and restriction inner department should be established , to establish the supervision modes in which the quality safety, fund spending and schedule of engineering management work and maintenance processing were supervised by superior administrator, water management department and supervision department according to related regulations ;to establish the stimulation modes with the core of competition and the measures of engineering check, bidding and bid, integrated appraisal, strict and impartial reward and penalty ,as well as encouraging innovation; to establish the guarantee mechanism including organization guarantee, fund guarantee, system guarantee, labour resources guarantee and benefit keeping.[2-3] A. Reform Meausures Consulting to the experiences of construction management of infrastructure in the Yellow River and other trades as highway maintenance, focusing on the characteristics of maintenance processing and requirement of the present work in the Yellow River harnessing, YRCC established the overall framework of the research on management and operations modes of the Yellow River engineering, and worked out matching management regulations and methods. As a result, the work processing and


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crucial stages of the management and maintenance of the Yellow River engineering were standardized effectively, and the further performance of the reform on water management system were promoted ,founding the base of the transformation of management and maintenance work of the Yellow River engineering running under new mechanism. Specifically, including: •

• • •

Dividing the range of professional work responsibility between engineering management and maintenance definitely, working out demonstration text of maintenance contract, making the authority clear, privilege and responsibility definite in both sides,. Key stages related to maintenance work such as contract sign, plan workout, maintenance criteria, and engineering supervision, quality monitoring and project acceptance were standardized systematically. Systematic quality management system of engineering maintenance was established, moreover, supervision and quality monitoring mechanism were imported into maintenance work. Eleven training class on management modes were held, staff of water management department and maintenance enterprise were trained in large scale.

B. Effect of Implementation 1) Standardized System Has Been Preliminarily Established andTaken Effect The issue of standardization method for management effectively stipulated the work process and main stages of the management and maintenance of the Yellow River engineering. The departments under YRCC matched and constituted detailed implementing rules according to their own situation, which further stipulated the development of operation management, and realized the canonical operation of engineering management and well running of the maintenance market.

一

2) The Status of Water Management Department as non Profit Institutional Department Has Been Confirmed, the Way of Fund Is Smooth The water management department has been defined as complete non-profit institutional department, the fund of engineering maintenance is considered into the budget of national finance. Both the management and maintenance fund are guaranteed, which can financially guarantee to keep engineering intact and improve flood control capability. 3) The Professional Team Is on Duty, the Management of Contract Is Enhanced The well management mode of maintenance for the Yellow River engineering has been established, the on duty of professional team changed the way of segmental contract by employing and quickened the process of professional team construction and standardized management, which effectively promoted the further development of

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engineering management. Simultaneously， contract management between water management department and Maintenance Company is implemented, so that contact sign, supervision and acceptance are enhanced, and the engineering strength and quality are so that guaranteed. 4) The work passion of staff is improved, the appearance of engineering has been improved dramatically Broad and further propaganda made the staff know the further significance of reform and realize the care of nation to the Yellow River affairs is also the care to their work; the increase of various fund in the reform scheme will greatly change the past condition of which income was less than expense， so the work confidence of the staff was enhanced. The reform insisted on the principle of“ publicity， justice and equity ”and performed“sunlight processing"， and the establishment of endowment insurance system after retirement released the further misgivings of the enterprise staff, so the condensation strength of the staff is enhanced. Management system and measures of reward and penalty have been established and perfected in management department and maintenance enterprise respectively， the passion of staff for working well on own duty has been improved. The improvement of passion in both maintenance enterprise and their staff, with the refining of the regulations in check， evaluation, reward and penalty， which has made the forming for good work phase of chancing "passiveness" into "initiative"， changing "let me do" into "I would do”. The daily management of engineering has been enhanced and the appearance of engineering as been improved greatly. C. Recommended • • • •

Clarifying the responsibility of water management department, realizing harmonious and unified management. Supply and revise related standards and methods, improve the management and operation mechanism of the Yellow River engineering. Improve the cognition to market, enhance the management of contract. Enhance team training; improve the modernization level of management.

4 Conlusion The management system reform is very important in the national water conservancy engineering management; which indicates there is a great step in the water conservancy reform and development. In 2006， Water conservancy reform of Yellow River Water Conservancy Committee has fully implemented, the management of water engineering has improved gradually .And there are more problems have emerged as well. As long as the problems are solved continuously Yellow River Water Conservancy engineering management lever will become better in the future.


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References 1. Li, G.: Practice Digital Yellow River Project construction and its result. Chinawater, 30–32 (July 2008) 2. Chang, C., Liang, S.-k.: Management and Maintenance of Yellow River′s Water Projects after the Reform of Water Management System. Journal of North China Institute of Water Conservancy and Hydroelectric Power, 101–103 (August 2009) 3. Zhao, Y., Zhu, T.: Promoting reform of water management system and enhancing level of water project management. Chinawater, 17–19 (October 2007)

Research on Hospital CRM System Model Based on Multi-Agent Wang Suozhu and Fu Yan Department of Information Engineering Capital Normal University Beijing, China [email protected]

Abstract. In order to change the customer relationship management in hospital lacks of flexibility, adaptability, initiative, we research a model based on MultiAgent is proposed to overcome these shortcomings. By using Multi-Agent technology, the traditional customer relationship management system of hospital is constructed to a Multi-Agent system. In the paper, every part’s functions of this model are discussed. Keywords: hospital customer relationship management, Multi-Agent system, data mining.

1 Introduction For a long time, hospital administrators, doctors and patients generally agreed that patients were asking hospital for help when they were ill, so the hospitals did not find ways to attract patients. In China, medical service is a special area. As the industry’s peculiarities and shortcomings, the main medical resources focus on the state of public hospitals[1]. However, with the deepening of China’s medical and health system reform, especially after the accession to WTO, a large number of foreign hospitals entered the domestic market, which bringing a new competition pattern of medical service market. If our domestic hospitals want to win in the competition, they must improve core competitiveness[2]. The competition among hospitals whose strength is considerable is the competition for customers in fact. Hence, the hospitals pay more and more attention to market, and the “customer” concept is gradually introduced to hospital management. By integrating hospital business philosophy, business processes, medical technology and customer relationship into enterprise customer relationship management (CRM, Custom Relation Management), the hospital establish a "patient-centered" management system HCRM (Hospital Custom Relation Management). The system’s purpose is to maintain and retain existing customers, to absorb potential customers, to expand the ranks of loyal customers, and to get the customers’ lifetime value ultimately[3]. But HCRM system is still in the initial stage. Hospitals for reference CRM not only lack of intelligence and initiative, but also impossible to mine customers’ information M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 14–20, 2011. © Springer-Verlag Berlin Heidelberg 2011

Research on Hospital CRM System Model Based on Multi-Agent

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well. In this paper, a HCRM system model based on Multi-Agent is proposed to improve the system activity, so the system can provide better service.

2 Multi-Agent A. Agent Technology Agent technology is one hot research of the distributed artificial intelligence in recent years. Until now, there is still no unified definition about Agent. Agent is generally believed as a computer system which is packaged in a certain environment, it can achieve the purpose flexibly and automatically [4]. Agent general has the following characteristics[4]-[5]: a) Autonomy. It is one of the basic characteristics of Agent. Agent is running without the direct intervention of person or other Agent, its actions and behavior are based on its knowledge, the internal state and the perception from the external environment to control. b) Social ability. Agent and the other Agents can communicate through a language, which is Agent has the ability to cooperate with other Agents in external environment, and there are the relationship of interdependence and constraints between them. They can cooperate when they meet conflict. c) Pro-activeness. Agent can not only react to the outside world, but also do the basic behaviors by accepting some revelation of information. d) Reactivity. Agent has perception on the surrounding environment, and it can change the environment through their own behavior. e) Initiative. Agent can get and analyze patient information on its own initiative; it also can take initiative services depending on the patients’ needs. B. Multi-Agent System Multi-Agent Systems (Multi-Agent System, MAS) is composed of multiple Agents. It is a distributed autonomous system, and its basic idea is to arrange these Agents based on their objectives, resources, so that every Agent can complete its tasks as can as possible. In the system, each Agent is an autonomous computing entity which has objective, knowledge and ability. Lots of Agents work together to solve the problems. In the expression of the actual system, MAS expresses the system’s structure, functions and behavioral characteristics through Agents’ communication, cooperation, mutual solution, coordination, scheduling, management and control. Because the Agents in the same MAS can be heterogeneous, multi Agent technology is important for complex system, it provides a unified model for a variety of practical systems, and a unified research framework for their research. The system’s application is very broad, and it’s potentially market is huge. By the definition of Agent and the function of MAS, it is clear that the system using multi-Agent technology can response to changing circumstances rapidly and makes timely action. The features of Agent ensure the interaction and interoperability between the system with users and external system.

3 Customer Relationship Managemeing In the current competitive market, the concern of all manufacturers is how to seize the customers, how to retain customers, and how to maintain competitiveness. If the

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hospital wants to gain the advantage in the market, they must master the needs’ trend of customers, at the same time, they must strength ties with customers, and manage customers. CRM (Customer Relationship Management customer relationship management) is to meet the needs, and it is developing rapidly. CRM is a customer-centric business, by using information technology, it resigns business program and makes arrangement for workflow, in order to maintain regular customer, and to attract new customers. CRM was first proposed by the Gartner Group in the United States, he thought that CRM is a system which is constituted by marketing automation, sales, customer service and back office. It can make customers process more efficient and business process clear and better. The system includes three levels of applications: customer access, business processes, decision support. In the increasingly competitive market conditions, hospitals had to change the traditional concept and establish HCRM (Hospital Customer Relationship Management). HCRM (Hospital Customer Relationship Management) is a “patientcentered” management system in which enterprise CRM management experience is fused into hospital business philosophy, business processes, medical technology and customer relationship. HCRM needs to make effective cases for human resources, medical service process, information management process, and medical technology, etc, and then they may improve customers’ satisfaction and loyalty as can as possible.

4 HCRM System Based on Multi-Agent (MAHCFM) A. The Overall Structure of MAHCRM System The basic functions of HRCM must include the following aspects: a) to get different needs of customers by analyzing and evaluating the information of inpatients and outpatients in HIS (Hospital Information System); b) to include clear customer feedback channels, for which customers’ views and suggestions can be reflected; c) to include convenient channels. Hence, customers can get hospitals’ service easily by using their own tools (such as telephone, fax, internet, face to face conversation, etc); d) to disseminate hospitals as can as possible, so that all kinds of customers including potential customers will be know hospitals; e) to establish a feedback system in which the exchange of information among hospitals’ policy makers, managers, medical personnel, logistics personnel and customers is completely smooth. So that all the management system can be integrated together; f) to analyze and evaluate the customer relationship strongly[6]. Consequently, the implementation of HRCM system should be dynamic. It not only should have strong adaptability, but also have the characteristics to eliminate heterogeneous among systems. Based on Agent’s characteristics and the idea of Multi-Agent system, this paper establishes a MAHCRM system, its system structure is shown in Fig.1.


Phone service

Fax service

Information processing Agent

Web service

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Email service

Mobile Agent

Interface Agent

GUI level User Agent Customer Service Agent

HIM A Hospital Marketing Agent

Intelligent Decision Agent

DW

Customer Care A Operation control level DM level DA Agent

Rule

Model

Medical Quality Agent Customer Rescores Agent

Data Model Agent

KB

Fig. 1. MAHCRM system structure

B. MAHCRM Interface Management Agent Customer contact layer is the interactive platform of information between hospitals and external environment. Its forms include: fax, website, email and other multimedia forms. Interface management. Agent is to set all kinds of information to the hospitals’ unified interactive platform. On the one hand, it passes the information to the other Agent in system based the user’s requirements; on the other hand, it receives the request from system Agent and sends it to the appropriate destination by moving Agent. The interface management Agent can word 24 hours uninterrupted and make quick response to customers’ need for hospitals’ service, it is composed of the following three parts: 1) Interface Agent. Different interfaces will be displayed for different types of customers; it can record the customers’ habits and sick, and then make adjustments. 2) Mobile Agent. It can move according to certain rules in the heterogeneous network, and complete a specific task on behalf of users by dealing with or using the right computer resource, information resource and software resource. 3) Information processing Agent. It is responsible for receiving the input data from customers or other external application, such as website, voice, mail, fax and

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other information, while it is responsible for converting them into the common data format in MAHCRM system for the lower Agent processing. C. MAHCRM Business Process Management Agent Business process management includes almost all the business process management modules in MSHCRM. From the point of business logic, it is the core of HCRM. 1) User Agent. It is the inherent sign of user in system. At some moment, the user may not appear in their work space, so the user Agent should receive the information about user, and send user information to other Agent. In some cases, the user Agent completes certain tasks on behalf of the user. 2) Application Agent. They are the Agent who completes the co-application work in fact, and they belong to particular applications. Depending on the need of application, application Agent will start or terminate the work. In the system, they provide each other service and communicate each other, so that, they can complete a business process together. There are six specific parts in application Agent: a) Hospital information management Agent. It connects MAHCRM system and hospital information system (HIS), so MAHCRM system service can be extended into HIS, and HIS can be integrated into MAHCRM system. In hospital information management Agent, resources can be shared, and hospital information work can play a better role on hospital construction; b) Customer service Agent. Its tasks including receiving the user service requests, processing the requests, establishing service tasks and service response, tracking the tasks; c)Medical quality Agent. It is responsible for receiving customers’ complaints from Agent-interface layer, providing processing and feedback mechanisms, supervising and inspecting the health care quality; d) Hospital marketing Agent. Its tasks include the establishment of the hospital marketing plans, the implement of marketing activities, the collection and market analysis of competitor information; e) Customer care Agent. Based on users’ demands, customers are classified by the Agent to carry out personalized service, so that hospitals can

OLAP

data source

data of patient and custome

abstract clean f

data mining of business system customers data warehous e

core of data mining Mining algorithm

data mining plug-in

model design; hospital service; project recommendation; response, obtaining, value, segmentation of customer

Fig. 2. MAHCRM system’s data mining structure

provide medical information and treatment information timely. The medical reminding service based on users’ demands improves the awareness of hospitals’ initiative service. f) Customer resource management Agent. The Agent is responsible for the establishment of customer resources database and the classification for customer resources, it needs to classify and evaluate the customers based on their importance, and it also needs to provide basic data resources for the analysis of customers’ value.


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D. MAHCRM Data Management Agent The primary duty of data management Agent is to provide various data analysis services for MAHCRM, to provide users with decision analysis. There are mainly three parts in MAHCRM data management Agent: 1) Intelligent decision Agent. Based on decision-making needs of other subsystems in HCRM, this Agent uses heuristic methods to find the appropriate data sets automatically from databases, and then it cleans the corresponding data and runs the appropriate data mining method. 2) Data analysis Agent. This Agent is to complete the statistical analysis and forecasting by using database, knowledge base and rule base, it also is used to support the decision-making. 3) Data modeling Agent. This Agent is responsible for monitoring the results of decision support, updating the outdated information and data in database, improving the information and knowledge extracted from database, so that the information and data can play a better role in future decision-making support services. E. MAHCRM Data Mining In MAHCRM System, data mining take the guiding role. Data mining is the only way to change lots of database data to a description of the characteristics of the images. By analyzing the images, we can obtain much information about customers, and let customer (patient) information and knowledge to flow and share effectively at hospital. So it makes the hospital to be timely and accurately on the patient information processing, satisfy patient personnel services to enhance the efficiency. MAHCRM system’s data mining structure is shown in Fig.2. As in Fig.2, data mining construction is divided into three aspects. First level is the hospital management system, which provides original data. Second level is data mining reference server. Through extracting, clearing and transforming, it takes the first level’s data putting into data washhouse, then analyze the data with data mining algorithm. Third level uses the data mining plug-in for the application of technology in MAHVRM.

5 Conclusions In recent years, there is more fierce competition between hospitals and hospital information management especially the research for hospital customer management is developed rapidly, so the design and development of hospital customer relationship management system is playing an important role in enhancing the core competitiveness of hospitals. In this paper, the MAHCRM system based on Multi-Agent system is constructed. It has used the popular artificial intelligence techniques—Agent technology, and the design idea of Multi-Agent system. In order to overcome the defects in existing hospital customer relationship management system such as inflexible and static, the MAHCRM system brings the concept of Multi-Agent system, in the system, different Agent works together to solve the above defects. At present, the analysis and design for the model has been completed basically, but there is a lot of work before the system is used into practical application.

20


References 1. Guo, x.: The implementation of CRM strategy in public hospital. Economist, 1004–4914, 05-217-02 (2008) 2. Li, x., Dong, j.: The implementation of CRM to improve the core competitiveness of the hospital, vol. 6(12), pp. 30–33 (2002) 3. Shang, w., Wu, h.: The discussion about the implementation of hospital customer relationship management. Hospital of Chinese mathematics 1, 2 (2007) 4. Idgem, W., Jenn Ings, N.R.: Intelligent Agents: Theory and Practice. The Knowledge Engineering Review (1995) 5. Wang, d., Guo, s.: The theory and application of Agent and Multi-Agent system. Computer Technology and Automation (2006) 6. Chen, x.: The functions’ overview and development trend of customer relationship management system. Technology Square (2008) 7. Yi, p.: Customer relationship management system- CRM. Computer Age 12, 14–17 (2001)

Risk Assessment Based on the Life Cycle of Virtual Enterprise Xia Wang, Zhimin Xie, and Xianjun Guan School of economics and management Tongji University Shanghai, China [email protected]

Abstract. The ambiguity and uncertainty of various endogenous and exogenous risks in virtual enterprise cause some difficulty to risk assessment, leading to subjectivity and inaccuracy of risk assessment in the virtual enterprise. Aiming at this problem, based on the analysis of various risk factors during every period of life cycle of virtual enterprise, this paper proposes the use of two-level fuzzy comprehensive evaluation to analyze the specific risks existing in every period of virtual enterprise, and then conducts an effective evaluation on the risk of specific virtual enterprise, which proves the feasibility of using fuzzy comprehensive evaluation method to assess the risk of virtual enterprise. Keywords: Virtual Enterprise, Risk Comprehensive Evaluation.

Assessment, Life cycle, Fuzzy

1 Introduction Virtual enterprise, a new form of organization and mode of operation, is increasingly being applied by more and more enterprises under the background of economic globalization, marketing dynamic change and demand individualization [1]. However, when the partners of virtual enterprise enjoy the common profits, they must take greater risks than the traditional companies. According to the study of Laciyt, for outsourcing typed virtual enterprises, 13% were of total failure, 19.6% in high-risk status, only 47.8% were completely successful. That means proportion of high risk and complete failure accounted for 32.6% of the total. So the negative effects caused by risks cannot be ignored, which could result in failure of virtual enterprises, and bring irretrievable losses to the companies [2]. Because of the ambiguity and uncertainty of various endogenous and exogenous risks in virtual enterprise, there are some difficulties in risk assessment. Risk assessment is to determine the acceptable level of risk in the whole company with the basis of individual risk assessment. The evaluation methods commonly used are breakeven analysis, sensitivity analysis, and probability analysis, which are all from a profit point of view to find the simple relationship between profits and the related parameters, and then give a description with the use of simple mathematical or probability analysis M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 21–28, 2011. © Springer-Verlag Berlin Heidelberg 2011

22

X. Wang, Z. Xie, and X. Guan

method. However, enterprise, especially the virtual enterprise is a complex system composed of many parts with specific functions. The risk assessment for such a complex system should use system analysis method, from a system perspective, based on a comprehensive analysis of system objective and functions of its sections and the relationship between them, study the operating rules of various risks, and finally determine the overall risk level. Furthermore, the probability analysis in the risk assessment of virtual enterprise has failed, because the virtual enterprise is a temporary form of dynamic alliance to seize emerging market opportunities. There are no raw data for reference, and the objective probability distribution is unknowable, entirely reliance on the experience and subjective judgments, so there is great ambiguity [3, 4, 5]. Therefore, form the system point of view, this paper establishes a risk assessment model of virtual enterprise with the use of fuzzy mathematics theory.

2 Theoretical Basis of Risk in Virtual Enterprise A. The Meaning of Risk in Virtual Enterprise In the process of operation, enterprises may encounter risks anytime. If risks cannot be dealt with properly, they will lead to business failure. The word “risk” has three versions: one refers to the possibility of accident happening; the second refers to the unfavorable consequence caused by accident; the third refers to the condition of accident happening [6]. The three claim that there is a large degree of uncertainty in the occurrence of risk, and that the likelihood of risk and the severity of its consequence are associated with the condition of its happening. According to the definition of risk, risk of virtual enterprise can be described as the uncertainty of access to income in the process of operation, including both the uncertainty of gaining unexpected profits and the possibility of encountering unexpected losses. In the business process of virtual enterprise, because of the complexity of production process and the particularity of management mode, there are lots of uncertain factors that can bring loss to enterprise, if not being coped with, they would not only bring obstacles to the normal operation, but lead to complete failure of virtual enterprise [6]. So, the risk studied in this paper mainly refers to the uncertainty of encountering losses. B. The Type of Risk in Virtual Enterprise The risk of virtual enterprise can be divided into two categories: endogenous and exogenous risks. Exogenous risks are caused by external factors, including political risk, market risk, technical risk and financial risk; endogenous risks caused by the business activities can be controlled if enterprise takes appropriate strategy [7 8].

，

1)

Exogenous risks a) Political risk. It mainly includes changes in the law and policy, social instability and the government's intervention. b) Financial risk. It mainly includes changes in interest rates and exchange rates, changes in the stock market, global or regional financial crisis and so on.

Risk Assessment Based on the Life Cycle of Virtual Enterprise

23

c) Technical risk. It mainly refers to the uncertainty and difficulty associated with the technology project undertaken by virtual enterprise. d) Market risk. It mainly includes changes in consumer demands, market competition, changes in the upstream market, economic decline and so on. 2) Endogenous risks The endogenous risks are different in different stages of life cycle of virtual enterprise. Then we will introduce them respectively. a) Risks in identification stage i. Identification risk of market opportunity. It refers that the core business mistakes the market opportunity of little value for the promising one because of inaccurate market information or the mischoice of analysis tool of market opportunity. ii. Identification risk of core competency. It is caused by mischoice of the realization mode because the core business overestimates or underestimates its core competency. iii. Selection risk of strategy formulation. It refers to failure to achieve market opportunity due to the selection of improper strategy formulation. b) Risks in formation stage i. Selection risk of partner. It refers to the loss caused by changing partner halfway for selecting improper partner at first. ii. Risk of resources integration. It refers that due to the failure of resources integration virtual enterprise loses flexible and cannot respond to market changes quickly. iii. Adverse selection risk of partner. Because of information asymmetry, partner may exaggerate its capacity to enhance its own value, resulting in the core business to make wrong decisions. iv. Risk of benefits distribution. If the benefits distribution is unreasonable, the partners may withdraw halfway or their enthusiasm may be impacted, and the virtual enterprise may breakup halfway. v. Risk of task assignment. It refers that the core business assigns tasks to inappropriate partners, leading to partners can not complete subtasks, which delays the total duration. c) Risks in operation stage i. Communication risk. It refers to the chasm in the time process due to the poor communication channel or lack of communication enthusiasm. ii. Risk of cultural differences. As partners come from different countries and regions, cultural differences will generate lots of friction and conflicts, which may lead to disintegration of the virtual enterprise halfway. iii. Liquidity risk. Virtual enterprise is an open organization, and partners are free to join or leave. Such liquidity could lead to postponement or collapse of projects and is not conducive to the accumulation of knowledge for virtual enterprise. iv. Risk of task coordination. There are conflicts in the task completion time and quality among partners, which may cause the project cannot be completed on time. v. Quality risk. It refers to the risk due to substandard products.

24


vi.

Moral hazard of partner. It refers that some member or members in transactions, contrary to the general requirements or ethics of the market mechanism, seek to maximize their own interests and let other partners bear losses. vii. Time risk. It refers to the loss of failure to achieve market opportunity caused by poor management. d) Risks in termination stage In the termination stage, the possible risks still cannot be ignored. First, the legal disputes will arise due to unreasonable benefits distribution or contradiction between the implementation and the distribution scheme, and they could affect the image of core business or partners. Second, because the virtual enterprise does not exist legally, the legal disputes are easy to arise in the settlement stage due to the ambiguous property rights.

3 The Basic Principle of Fuzzy Comprehensive Evaluation The process of fuzzy comprehensive is outlined as follows [9]. 1) Factor set U Assuming the influenced factors can be classified into n categories, marked as u1 , u 2 , " , u n . The n factors form a factor set

U = {u1, u 2 , " , u n

}

(1)

Remark set V The remark on each factor can be divided into m degrees, marked as v1 , v 2 , " , v m , so we can get the remark set

2)

V = {v1 , v 2 , " , v m 3)

}

(2)

Membership matrix R R is the fuzzy mapping from factor set U to remark set V. The element rij in

matrix denotes the possibility of factor i belonging to remark Grade j , also called membership grade of remark Grade j for factor i . If fix i , (ri1 , ri 2 , " , rim ) is a fuzzy set of V , representing the remark of the single factor i . We can get the fuzzy membership matrix R by combining the remarks of each factor. 4) Weights Usually the importance of each evaluation factor is different. So the weights of evaluation factors can be regarded as a fuzzy set W of factor set U , and n

∑ W (u ) = 1 i

(3)

i =1

5)

Comprehensive evaluation model S =W D R

Where W is the weighting set corresponding to the factor set U.

(4)


6)

25

Determine the evaluation grade According to the evaluation model, generally we select the remark of

s k = max{s i }

(5)

1≤i ≤ m

as the remark grade of the subject, in which si is the element of S . But when the following occurs, appropriate adjustments should be made. k −1

a) Calculate

∑ i =1

k −1

m

s i and

∑

s i . If

i = k +1

∑ i =1

1 si ≥ 2

m

∑

m

s i , or

i =1

∑

1 si ≥ 2 i = k +1

m

∑s

i

, then

i =1

select s k −1 or s k +1 . b) If the number of equal maximum number in S = {s1 , s 2 , ", s m } is q ( q ≤ m ), make shift calculation respectively according the rule of a). If the evaluation degree is still discrete after shift, then take the evaluation of the center grade. If there are two center grades, then select the one with higher weight. 7) If there are several subsets in factor set, first use fuzzy comprehensive evaluation for the underlying indexes, and then combine the results to form the evaluation matrix of upper-layer indexes adjacent. By analogy, the value of total evaluation can be gained [10].

4 Case Analysis of Risk Assessment of Virtual Enterprise This paper takes virtual enterprise A for an example. Currently Enterprise A is in the identification stage. Its exogenous risks include political risk, market risk, technical risk and financial risk; the endogenous risks are identification risk of market opportunity, identification risk of core competency and selection risk of strategy formulation. 1)

Fuzzy comprehensive evaluation of endogenous risk of Enterprise A a) Factor set

{

U1 = u11 , u12 , u13

}

(6)

Where u11 represents the identification risk of market opportunity; u12 represents the identification risk of core competency; u13 represents selection risk of strategy formulation. b) Remark set

V = {higher ， high ， medium ， low ， lower

}

c) Fuzzy membership matrix According to investigation, the evaluation vector of factor u11 is (0.5,0.2,0.2,0.1,0 ) , that means 50% think the selection risk of partner is higher, 20% think it is high, 20% think the risk is medium, 10% think it is low, and nobody considers the risk is lower. Similarly, we can get the evaluation vectors of other

26


factors: the evaluation of factor u12 is (0.1,0.3,0.3,0.2,0.1 ) , and that of factor u13 is (0,0.1,0.2,0.6,0.1 ) . So we can get the fuzzy membership matrix of endogenous risk: ⎡0.5 0.2 0.2 0.1 0 ⎤ R1 = ⎢⎢ 0.1 0.3 0.3 0.2 0.1⎥⎥ ⎢⎣ 0 0.1 0.2 0.6 0.1⎥⎦

(7)

d) Weights W = {0.45,0.3,0.25

}

(8)

e) Fuzzy comprehensive evaluation model S1 = W D R = (0.45,0.3,0.3,0.25,0.1)

(9)

f) Determine the evaluation grade 5

s11 = max {s1i } = 0.45

,

1≤ i ≤5

5

Because

∑

s1i >

i=2

∑s

= 0.95

1i

i=2

1 2

,

1 2

5

∑s

1i

= 0.7

.

i =1

5

∑s

1i

, we select the remark of 0.3 as the evaluation result of

i =1

endogenous risk, that means the endogenous risk of Enterprise A is high. 2) Fuzzy comprehensive evaluation of exogenous risk of Enterprise A a) Factor set U = {political risk, market risk, technical risk, financial risk} 2

b) Fuzzy membership matrix ⎡0 ⎢0.4 R2 = ⎢ ⎢ 0 .3 ⎢ ⎣0.4

0.1 0.1 0.5 0.3⎤ 0.3 0.2 0.1 0 ⎥⎥ 0.3 0.2 0.1 0.1⎥ ⎥ 0.4 0.2 0 0⎦

(10)

W2 = {0.2,0.4,0.1,0.3}

(11)

c) Weights

d) Comprehensive evaluation model S 2 = (0.4,0.3,0.2,0.2,0.2 )

(12)

e) Determine the evaluation grade

s 21 = max{s 2i } = 0.4 , 1≤i ≤5

5

∑ i=2

s 2 i = 0 .9 ,

1 2

5

∑ i =1

5

s 2i = 0.65 . Because

∑ i=2

s1i >

1 2

5

∑s

1i

,

i =1

we select the remark of 0.3 as the evaluation result of exogenous risk, that means the exogenous risk of Enterprise A is high.


3)

27

Fuzzy comprehensive evaluation of overall risk a) Factor set U = {endogenous risk, exogenous risk} b) Fuzzy membership matrix ⎡0.45 0.3 0.3 0.25 0.1⎤ R=⎢ ⎥ ⎣ 0.4 0.3 0.2 0.2 0.2⎦

(13)

W = {0 . 65 ，0 . 35 }

(14)

c) Weights

d) Comprehensive evaluation model S = (0.45，0.3，0.3，0.25，0.2 )

(15)

e) Determine the evaluation grade

s1 = max{s i } = 0.45 , 1≤i ≤5

5

∑s i=2

i

= 1.05 ,

1 2

5

∑s

i

= 0.75 , 1.05 > 0.75 . So we select

i =1

the remark of 0.3 as the evaluation result, that means the overall risk of Enterprise A is high.

5 Conclusions Virtual enterprise is creature of economic globalization and rapid development of information technology. It helps businesses improve the ability of response to market changes, but also brings some new problems. For example, the negative effects caused by risks throughout the entire life cycle of virtual enterprise cannot be ignored. Therefore, the risk control of virtual enterprise plays a decisive role in the entire process of management, and assessing the risks effectively and appropriately is the key step for virtual enterprise to adopt effective risk control measures. This paper analyzes the specific risks existing in every period of virtual enterprise with the use of two-level fuzzy comprehensive evaluation, aiming to provide theoretical guidance to virtual enterprise to estimate the magnitude of its risk. Acknowledgment. Zhimin Xie wishes to express thanks to Pro. Xia Wang and Dr. Xianjun Guan for the valuable discussion and suggestions. Without their help, this thesis cannot be accomplished.

References 1. Dai, F.: Study on Risk Management of Virtual Enterprise. Zhejiang University of Technology (April 2006) 2. Gao, W.: Study on the Construction and Benefits and Risks of Virtual Enterprise. Harbin Institute of Technology (January 2004)

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3. Zeng, Z., Li, Y., Li, S.: Evaluation of Risks in Virtual Enterprise Based on Fuzzy AHP. Fuzzy Systems and Mathematics 20(4), 135–139 (2006) 4. Yan, K., Li, J.: Application of Fuzzy Integrative Evaluation Method on Risk Management of Virtual Enterprises. Industrial Engineering Joural 07(3), 40–43 (2004) 5. Huang, M., Wu, X., Wang, X., Ip, W.H., Yung, K.L.: PSO based single strategy risk programming problem for virtual enterprise. In: Proceedings of 2006 America Control Conference, pp. 4506–4510 (2006) 6. Wang, M.: Study on Risk Management of Virtual Enterprise. Ocean University of China (March 2005) 7. Ye, F., Sun, D.: Study on Risk Management of Virtual Enterprise Facing life cycle. Science of Science and Management of S&T 11, 130–133 (2004) 8. Zhang, D.: The Risk and its effective control of Virtual Enterprise. Group Economy 173, 89–90 (2006) 9. Zhang, Y., Wu, T., Wang, M., Sun, Z.: Systems Engineering, pp. 307–308. China Meteorological Press (1997) 10. Gong, C.: A Study on Virtual Enterprise’s Risk Based on Entropy Coefficients Multi-level Fuzzy Comprehensive Evaluation. Harbin University of Science and Technology (June 2005)

Research on Financial System Computing Simulation∗ Tang Chuan and Chen Ling Dept. of computer science & technology Guangdong University of Finance Guangzhou, China [email protected]

Abstract. This paper presents a multi-agents modeling method based on agent micro-interaction about financial system. Build micro-layered model between agents interaction under the ideally financial system. Offer a decision way to deal with the variation trend of financial system. Keywords: multi-agent, financial system, modeling, computing simulation.

1 Introduction Towards integration in the global economy environment, the world's financial system has been gradually integrated into an age of the global economy and the financial system. To maintain the stability of the financial market system is running one of the core works for the national economies in the world. To effectively prevent and manage financial risk and to maintain financial market stability is a common goal for all levels of our government and investment institutions. The complexity of the financial system and the speculation of financial markets have determined fluctuations for the unpredictable and non-equilibrium financial markets in state level. From a series of major financial risk events and the global financial crisis in the 90's of last century, we know that the complexity of a financial system and its risk management is very important. Establishment and use of security and controllable system of financial resources in the national economies and the strategy of financial system development have guaranteed an important part of the national economy under smooth and healthy development. In a process of a strategy of developing countries financial resources, we need to consider the suitable use of financial products, but also to consider the carrying capacity for the states, enterprises and people and to take into account the functions of national, local, collective, individual, fairness and efficiency, etc. They are a highly complex, implementation of prediction and controlled process. ∗

This work is partially supported by Guangdong Nature Science Foundation of China (81510521000009).

M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 29–35, 2011. © Springer-Verlag Berlin Heidelberg 2011

30

T. Chuan and C. Ling

2 The Financial System Complexity With the development of science system theory, cybernetics and information theory and in-depth study dissipative structural system under the physics, we found that there are specific observation periods for the non-equilibrium open system in the nature system and widespread in sociological systems. Their macroscopic characteristics show self-organization and chaos. They would a mutation and a motion of a system with uncertainty and complexity. A complex system in the nature means that a system with the physical quantities far from equilibrium, the time coordinate space is not reversible and a non-linear trajectory and behavioural characteristics can’t be determined. There are a large number of studies concerned about the complexity by the domestic and foreign scholars. They think that the complex system is composed of multiple elements, with complex nonlinear relationship between elements of the system. According to the numbers of subsystems in complex system, the number of sub-level categories, the interaction between the subsystems associated with the complexity of the relationship between openness and dependence on the environment, we know that the complex system can be divided into single large-scale systems, complex giant system and open complex giant system. [l]. A financial system is characterized by a great number of components of a system and its participants, which including individual investors, institutional investors, producers, financial intermediaries and government. There are more complex between subsystems interaction. It is an open complex giant system [2]. The financiers, investors and financial intermediaries in a financial system deal with economic activities under the environment of interdependence and mutual restraint. The government use fiscal policy and a monetary policy tool to control the macroeconomic in a system so that the financial system can be smooth development as expected. Affect the factor of a financial system operating is not only by the acts of government at all levels, but also by the behaviours of the financiers and investors. The financial activities of the participants, consumers, investors, producers, financial intermediaries, or government have their own subjective. The information obtained from those numbers of participants and decision makers has not symmetry, risk in different and profit preferences. It is seemingly random to make their profit targets and operation of different decision-making in their investment in all levels and time points so that the whole financial market becomes very complicated in the product price changes. To study the law of price changes of the financial products in a financial system, we aimed at understanding the internal laws of system operation in order to better control and use of a financial system. The system administrator has concerned about its smooth and efficient operation. The investor has concerned about the lowest investment cost and the most returns of the profit. From the microscopic point of view, although a financial product price changes on the performance in the time frame is very complicated, but from a macro perspective, in general, the financial system operating is relatively stable and convergent. It only occasionally shows up nonlinear characteristics with oscillations, local instability and trajectory divergence. It is very meaningful and useful to study those nonlinear characteristics and turning point.

Research on Financial System Computing Simulation

31

3 Modelling Method of a Financial System The study of the complexity of a financial system is an intersection field of science and the social sciences. It is a combination subject of physics, mathematics, computing, economics, and finance. Their study method contains of the modelling method and information technology. Their knowledge area includes non-linear dynamics, thermodynamics, fractal geometric theory, chaos theory, financial market theory, econometrics, mathematical statistics and computer science. To study the complexity of a financial system is usually first need to establish a research object model. The way to build a modelling is a basic method in the risk of a financial system. At present, we know that the main methods of the modelling are including physical modelling, mathematical modelling, and graphical modelling and computer simulation modellings. From the financial system modelling level they can be divided into a top-down model, a bottom-up model and a mixed model. From the mathematical methods they can be divided into a linear model and a nonlinear model. From the research methods they are divided into a simulation modelling and an optimization modelling. We know that the financial system over the risk management model in the early stages is based on the description of macroscopic physical structure and the optimization of macro-physical parameters. It is also emphasized by the macro-laws in a system and the qualitative description of macro features. For the difference of micro level and initiative problem in the product exchanges in a system, we usually take the shield method and ignore market transactions complexity of time and space. Macro-quantitative research in traditional are taking the way of linear extension of time-coordinate-data and macro-statistic methods and be short of optimization model of evolution mechanism and marginal effect of non-linear trend extrapolation model so that we are difficult to explain them by the system involved in the main external factors and internal interaction between the macro-economic data. Since it is oversimplified for the relationship of the structure of a system in the traditional equilibrium economic model and ignores the difference between subject participation, micro component systems and participatory and active learning. We can’t understand the complex characteristics of a financial system well. Therefore, it can be happened some errors on models and calculation when we have done a prediction and evaluation for the complexity of a financial system.

4 Based on Multi-Agent Simulation Model in a Financial System In recent years, the method of ABM (Agent-Based Model) is considered about as a most effective method in studying the complexity problem. Its studying method is so different from the traditional modelling way. It has an own way, i.e. a concept of AGENT. This agent is a cell of the basic unit of a system and has self-target, internal micro-structure, survival and learning initiative power. It can through self-modify their behaviour to adapt to the surrounding environment. The ABM generally uses multi-agent system (MAS). We are modelling under the description for all kinds of micro-agent interaction. At the same time, we use a modelling method of a complex system combined with the discrete event simulation of computer simulation

32


technology, agent action simulation and micro-agent interaction simulation as our study method. [4]. The core idea here is that we have simulated the exchange between the agents in a complex system and out outside of the material or information, the exchange between the agents and sub-agents and agent interaction so that we get that the changes of macro variables and the changes of micro-agent interaction. [5]. We use a MAS-ABM modelling method as our researching method in this paper so we get our goal by a micro-agent interaction in a system from a macro in the system. We also claim that a multi-agents modelling method based on micro-agent interaction about a financial system. Using role with agent binding mechanism and agent layered mechanism; this model describes investment behaviour abstractly and set up the system structure of dynamic investors in a financial complex adaptive system. A. The Modelling Assumption a) The financial products involved in a transaction are completely electronic and no logistics barriers for free flow in the network. b) Agent contains the financial market authorities, securities companies, institutional investors, the main investors. c) There are no different and non-symmetry in cross-layer information for all kinds of agents from the different layers. d) Every agent nearby get together and forms a small group or secondary structure. The agents inside a small group follow criterion of micro-structure interaction. The neighbor agents inside a small group follow criterion of micro-structure interaction from the neighbor agents. e) All kinds of agents has action free, information exchange, learning perception, inference, optimization, response, collaboration and self-evolution. f) The behavior of the agent follows criteria for bounded rationality and pursues the most satisfactory solution, not an optimal solution in a real system. B. The Modeling Construction Our research is focus on modeling process in the system module using structured modeling from an angle of systems engineering. We first have decomposed the functional structure of complex systems into several independent subsystems. Secondly, we have separated the subsystems to establish an objective model and an ideal model for those subsystems. Finally, we have considered the relationship between those subsystems and established the behavior path model for those subsystems to form the simulation model for the whole system. I) Master Process Model (MPM) Definition 1: MPM= < system level, organizational structure, group class, role, goal, path >

Fig. 1. Primary process model

Master process model has showed in the Figure 1 above. It describes the whole structure in the system modelling process. System layered structure modeling process


33

divides level for system goal. Group structure modeling process divides agents into several groups, to form a secondary structure on the primary structure, there for can analyses group independently. Using layered method, this model divides layer into several groups and reduces system complexity. Based on the results from front modelling process, Group layered modeling process extract group and role class, then binding role, define group expected goal. Behavior path modeling process build group behavior path model, finish system primary modelling process design. From the Figure 1, the output value of each sub-process is the input value of next subprocess. In multi-agent modeling process, each sub-process can be interacted and roll back. II) System layered model(SLM) To reduce modeling complexity, we use the hierarchy structure modularization modeling method [6]. First, according framework and function requirements divided the whole system into several independent lower dimensional substructure systems; then on the basis of some combination principle, level system are divided into several group tissues. Each group tissue can be analyzed separately, role modeling respectively, reduce the complexity and accuracy of system analyst.

Fig. 2. MAS layered model

System layered model has showed in the Figure 2 above. Multi-Agent system is divided into several layer groups. The interactions with agents inside group are greater than interactions with agents outside group. III) Group internal construction Definition 2: Role model (RM) Agents and groups are the most powerful relating within role. Each agent can be bound with one or some roles. Group can adapt to the changing conditions through dynamic roles translation. Agent can achieve group’s global goals through role share specific tasks. The formal definition of RM is: RM= Name denote group tissue name. r denote probable equities of business operations. O denote business operations that be performed probably. ST denotes transfer quantity of business status. Definition 3: Tissue model (TM) In the course of systematic modelling, the group tissues denote a set of agent role aggregate according to agent behaviour principle of clustering. Group tissues are

34


encapsulated specific behaviour functions of sub-system and have certain behaviour goals. The formal definition of TM is: TM= Name denote group tissue name. R denotes all agent roles aggregate in group tissues. G denotes behavior goal aggregate of group. C denotes the relevance between agent roles and group behavior goals. IV) Group class model (GCM) Group class modelling is the result above two steps modelling will be encapsulated to the group agent class, then forming multi-agent system. Definition 4: Group class model The formal definition of GCM is: GCM = Name denote group tissue name. R denotes all agent roles aggregate in group tissues. G denotes behavior goal aggregate of group. MO denote the aggregate belong group layer. TC denotes the aggregate of group communication. Group model is established in role model and communication mode. Through the binding agent and role of groups, determine the role of groups and organization’s layers. GCM of financial products trading system has showed in the Figure 3 below. There are three classes of principal trades agents in GCM: individual trade class, agency trade class and organization trade class. All trade classes are bound three roles: trade monitoring, normal trade and emergency trade.

Fig. 3. Groups class model of financial products trading system

V) Group goal model(GGM) First, from the initial environment identify group goals. Then, quantitative logic group goal and form layer. The lower layer is son. Our research method is according operation procedure to obtain group goals. Goal model can be described using a set of simplified variables and constraint condition. The formal definition of GGM is: GGM= Name denote group tissue name. V denotes variable aggregate. CC denotes constraint condition aggregate. VI) Behavior path model(BPM) The behaviour path is related to goal. Each path implement a goal, then a goal can be implemented by several paths. Using generator of concurrency form and compound IF statement to design path [7]. The formal definition of BPM is:


35

BPM=< name, R, G, PA, CF> Name denote group tissue name. R denotes all agent roles aggregate in group tissues. G denotes behaviour goal aggregate of group. PA denotes behaviour parameter aggregate. CF denotes aggregate of concurrency form.

5 Conclusion From the systems engineering point of view, presents a multi-agents simulation modelling method based on the complex financial market system. The simulation process microscopic behaviour of the complex systems was divided into sub-process and the system sub-model: system layered model (SLM), role model (RM), tissue model (TM), group class model (GCM), group goal model (GGM) and behaviour path model(BPM) as the basic elements of computing simulation. Thus, we can reduce the complexity of a system and use dynamic mechanism way in the lowest layer agent to understand changeable-performance in the complexity of a financial system. We also provide a way to measure for a method research of the financial system and its complexity. Our computing simulation method allows us to understand the rules in lower agent layer and to emerge macro surge. We also know what it happens in the interaction mechanism in the system architecture agent and its subsystems (groups) in the complexity of a financial system. Finally, in order to reduce complexity, we have set some initial idealized assumptions in modelling starting. Our simulating result is only fit some simple relationship between agents and subsystems in ideal condition. Well, for an actual financial system we have some deficiencies, we need to take some revise in the results from its modelling. Acknowledgment. The authors would like to acknowledge the financial support of Guangdong Nature Science Foundation of China (81510521000009) for this work.

References 1. Qian, X.-s., Yu, J.-y., Dai, R.-w.: A new discipline of science—the study of open complex giant system and its methodology. Chinese Journal of Nature l, 3–10 (1990) 2. Song, X.-f.: Survey and Prospect on the Science of Complexity. Complex Systems and Complexity Science 2, 10–17 (2005) 3. Li, T., Yan, Q., Qi, Z.-c.: Research on the Software Development Methods Based on MultiAgent Systems. Computer Engineering & Science 28, 118–130 (2006) 4. Liao, S.-y., Dai, J.-h.: Design Pattern and Software Framework for Agent-Based Modelling and Simulation. Journal of System Simulation 17(4), 863–866 (2005) 5. Kolp, M., Giorgini, P., Mylopoulos, J.: A goal based organizational perspective on multiagent architectures. In: 8th International Workshop on Intelligent Agents VIII, WA, USA, pp. 128–140 (August 2001) 6. Muller, J.P., Pischel, M., Thiel, M.: Modelling Reactive Behaviour in Vertically Layered Agent Architectures. In: Wooldridge, M.J., Jennings, N.R. (eds.) ECAI 1994 and ATAL 1994. LNCS (LNAI), vol. 890, pp. 261–276. Springer, Heidelberg (1995) 7. Wu, J., Feng, C., Peng, H.: A Role-based Dynamic Multi-Agent Cooperative System RBDMAS. Yunnan Nationalities University (Natural Sciences) 7, 246–249 (2008)

The Construction and Evaluation of the Regional Innovation System of Zhejiang Province* Cai Ning and Huang Chun College of Public Administration Zhejiang University HangZhou China [email protected]

Abstract. Concerning the economic development situation of Zhejiang Province, a set of evaluation indicators urgently need to be established to reflect the regional development demand and fit for the regional innovation of the Province. Yet, since the economic and social development in Zhejiang is unbalanced, there are still obvious differences in regional innovation among the 11 prefecture-level cities. Thus, how to objectively evaluate the creativity of one region and make countermeasures to raise the regional innovation in accordance with the differences among the regions has become an urgent theoretical problem and practical requirement. The paper constructs an evaluation system of Zhejiang’s regional innovation by theoretical and empirical selection. Based on the evaluation indicator system and combined with the specific data material, the paper conducts practical measurement and horizontal comparative analysis to the regional innovation of the 11 prefecturelevel cities of Zhejiang Province. Keywords: regional innovation, innovation system, construction, evaluation.

1 Introduction The creativity of one region is closely related with its economic development. The differences in social foundation, system environment, economic structure, and investment factors of the regional development definitely lead to the unbalanced regional economic development of the Province. There have been obvious differences in the degree and the route of economic development among the Eastern Zhejiang Economic Circle (including the six cities of Hangzhou， Ningbo， Jiaxing, Huzhou, Shaoxing and Zhoushan)， the Wenzhou-Taizhou Economic Circle in Southern Zhejiang (including Wenzhou, Jinhua and Taizhou), Jinhua-Quzhou-Lishui Economic Circle in southwestern Zhejiang. Thus, we need to conduct comparative analysis to Zhejiang’s regional innovation based on the distinction of the differences in regional *

Funded by the NSF China : “The Transform and Diffusion Path and Control the Risk of Enterprise Cluster Caused by the Fading of Focal Enterprises”.（ No.70973103） and the NSF China : No. 70573109.


The Construction and Evaluation of the Regional Innovation System

37

innovation of the 11 prefecture-level cities, and at the same time work out development policies according to the different regional creativities. Then how to evaluate the creativity of one region and what are the differences among the regions? Which indicators influence regional innovation? From which aspects can we work out policies to raise regional innovation? All these issues need the academic circle to conduct indepth theoretical analysis and empirical research based on the distinctive evaluation of the regional innovation.

2 Theoretic Construction of Regional Innovation System The evaluation system of regional innovation can directly evaluate one regional innovation, evaluate the strength of sub-factors (capabilities) of the regional innovation, establish the platform for mutual comparison of the various regional creativities, and thus explore the general trend and advantages and disadvantages of the regional innovation, and put forward policy measures to raise the regional innovation and competitiveness, and promote the sustainable development of the regional economy and society. Furman and Hayes(2004) hold that comprehensive indicator system shall include the infrastructure for creation, the environment for the creation of industrial cluster, and the link between science and technology departments and the industrial departments. Gu Guofeng（ 2003） applies the obscure mathematics comprehensive determination method based on the connotation, structure and operation route of the regional scientific and technological creation, and conducts value evaluation to the five indicators with key roles in affecting regional innovation. Shen Juhua（ 2005） takes Lianyungang as an example, and applies factor analysis method and layer analysis method to separately establish the evaluation indicators of regional scientific and technological creativity both from horizontal aspect and vertical aspect. Yin Xiaoli (2005) believes that the creativity indicator system shall be made up of creation potential, development capability, output capability and contribution capability of the science and technology. These research achievements provide sound foundation to the establishment of scientific evaluation system of regional innovation and the scientific countermeasures by actual measurement. Generally speaking, there are obvious shortcomings in the previous researches, which can be reflected in the following four aspects:（ 1） concerning the theoretical selection of evaluation indicators: the subjectivity and randomness are strong, and the candidate indicators lack certain rationality and objectivity;（ 2） concerning the empirical selection of evaluation indicators: there lacks the analysis, subordinate degree analysis and the distinction analysis to the evaluation indicators of theoretical selection, which leads to the fact that there exists a high degree of relativity among the evaluation indicators, and there lacks enough distinction leading to the repetitive use of information and the evaluation results are not scientific;（ 3） concerning the ratification of research results: there is no ratification to the credibility and effectiveness of the research result, and the system lacks credibility and effectiveness；（ 4） concerning the countermeasures and suggestions: There is no experiment research or research to the mental simulation of policy suggestions (including policies) to the research.

38

C. Ning and H. Chun

3 The Construction of Evaluation System of Zhejiang’s Regional Innovation The regional innovation is the result of the integration of multi-strength. Based on the previous documents and the lectures by the experts, and in the principle of indicator selection, the paper selects 90 indicators to form the first round indicator system X from the five aspects of regional innovation input capability, regional innovation allocation capability, regional innovation supporting capability, regional innovation management capability and regional innovation output capability. As shown in Table 1, the laddered theoretical model is formed by evaluation modular layer, evaluation field layer and the evaluation indicator layer. Maintaining the Integrity of the Specifications (1 )

Table 1. The first round evaluation indicator

X

(1 )

of the regional innovation

A. Analysis and Consultancy of the Experts In the research, the author selects 30 experts from Zhejiang in the field of regional creation, and organizes three expert consultancy meetings with 10 experts attending each meeting. The author conducts in-depth discussion, analysis and evaluation to the first round of evaluation indicator system X of Zhejiang’s regional innovation, and revises and optimizes the indicator system. By the above adjustment and revision, the paper obtains 50 evaluation indicators for the second round evaluation indicator system X of Zhejiang’s regional innovation. (1 )

(2)

B. Analysis of Subordinate Degree The researcher selects 100 experts from the Zhejiang provincial government and the colleges, enterprises and institutions, makes the second round evaluation indicator system X into expert consultancy table, sends the table to experts by post, e-mail or interview, and selects 20 evaluation indicators with the most importance by combing their knowledge and experience. By the statistical analysis to the 63 valid expert survey tables, 50 subordinate degrees of evaluation indicators is obtained. By the subordinate degree analysis, it’s found that of the 50 evaluation indicators, the subordinate degree of 13 indicators is lower than the absolute value. By eliminating these evaluation indicators, 36 are retained to form the third round evaluation indicator system X of Zhejiang’s regional innovation. (2 )

(3）


39

C. Relativity Analysis (3）

In the third round evaluation indicator system X of Zhejiang’s regional innovation, there exists certain relativity among various evaluation indicators, and it’s easy to be repeatedly endowed when the indicators are endowed with rights, thus the persuasiveness and credibility of the evaluation result are reduced. Hence, the influence of the information repetition to the evaluation result needs to be minimized by eliminating the indicators with big relative coefficient in the analysis. In this way, the scientific nature and rationality of the evaluation indicator system can be raised. The researcher collects the relative indicator data of 11 prefecture-level cities of the Province in 2008, and applies SPSS statistics software package to analyze the evaluation indicators. The following 6 pairs of indicators with high relativity have been obtained. The paper eliminates 6 indicators with relatively low relativity, retains the remaining indicators, and forms the fourth round evaluation indicator system X of Zhejiang’s regional innovation. (4)

D. Perception Analysis The paper applies SPSS statistics software package to conduct variance analysis to the indicators, and based on the analysis to calculate the variation coefficient of 30 indicators in the fourth round evaluation indicator system X . By calculation, it eliminates and adds certain indicators in the 30 indicators, and forms the fifth round evaluation indicator system X of Zhejiang’s regional innovation. (4 )

(5)

E. Evaluation System of Zhejiang’s Regional innovation By experts’ selection, subordinate degree analysis, relativity analysis and perception analysis, the first round of evaluation indicators has been turned into the fifth round of evaluation system X with 25 indicators. By using V to express the variable sign of the evaluation indicators, the paper establishes the evaluation system to measure Zhejiang’s regional innovation as shown below. ( 5 )

Table 2. The fifth round evaluation indicator system Table Head

Regional

Zhejiang Province

(5)

of Zhejiang regional innovation

Table Column Head Evaluation

innovatio n of

X

input capabilities

No

Evaluation indicators

Unit

1

The percentage of scientific and technological activities to GDP

%

2

The percentage of R&D expenditure to GDP

%

3 4 5 6 7

Expenditure of technology introduction per 10,000 persons technological development fees for enterprises with 10,000 persons The number of technicians per 10,000 persons The number of scientist and engineers per 10,000 persons ratio of high tech industrial employees to total employees

10,000Yuan 10,000Yuan persons persons %

40

C. Ning and H. Chun Table 2. (continued) Table Head

Table Column Head Evaluation

No

8 9 supporting capabilities

10 11 12 13

Regional innovatio n of

managemen t capability

Province

number number 10,000Yuan 10,000 households %

ratio of financial expenditure to GDP

%

15

ratio of financial tech payment of the level to the financial expenditure of the level

%

science popularization activity fees per capita

Yuan

16

18 19

output capabilities

Unit number

14

17

Zhejiang

Evaluation indicators The number of higher institutions per 10,000 persons The number of public libraries per 10,000 persons The number of R&D institutions per 10,000 persons The number of postal services per 10,000 persons The number of international internet users per 10,000 persons ratio of urban residents’ remaining deposits to GDP

Tax reduction and exemption to technological development enjoyed by various governments per 10,000 persons fees of the tech items at provincial level and above the number of invention copyright endowment per 10,000 persons

10,000Yuan Yuan items

20

electricity consumption per 10,000 Yuan GDP

Kilowatt hour

21

agriculture labor production rate

%

per capita GDP

Yuan

22 23 24 25

the ratio of VA of high-tech products to industrial VA percentage of high-tech products to total export production rate of new industrial products

% % %

4 The Actual Measurement and Comparative Analysis of the Regional Innovation of 11 Prefecture-Level Cities in Zhejiang Province A. Collection of and Treatment to the Data of Evaluation Indicators The indicators of the evaluation system of Zhejiang’s regional innovation constructed in the paper are all objective evaluation indicators. There are mainly four sources: first source is the Statistics Yearbook and the Technology Statistics Yearbook by Zhejiang Provincial Statistics Bureau, the second source is the Statistics Yearbook published by the 11 prefecture-level cities of the Province, the third comes from the tech monitoring data of Zhejiang Provincial Technology Office (for different data sources, the data with different indicators take the technological monitoring data as the basis), and the evaluation indicators at the last part come from the government website and the statistics report of the 11 prefecture-level cities. The paper applies the dimensionless method to


41

these data to reduce the big errors caused by the dimensional indicators, thus raising the credibility of result evaluation. And it calculates and gets the evaluation value of regional creation input capability, regional creation supporting capabilities, regional creation management capabilities and regional creation output capability of Zhejiang, and gets the evaluation value of regional creation comprehensive capabilities, by referring to the utility value and weight value of various evaluation indicators. F = ∑ Wi × V i

Of which, F is the evaluation value； W is the weight value of No. i evaluation indicator； Vi is the utility value of No. i evaluation indicators. i

By comparison, it concludes that Hangzhou scores the highest in regional creation input capability, regional creation management capability, regional creation output capability and the regional creation comprehensive capability at last. Zhoushan scores the highest in regional creation supporting capability. As shown in Table 3: Table 3. comprehensive evaluation value of the regional innovation of 11 prefecture-level cities in Zhejiang Province Table Column Head Table Head

comprehen sive evaluation value of the regional innovation of 11 prefecturelevel cities in Zhejiang Province

Regions

Regional innovation input （ F1）

Regional innovation support （ F2）

Regional innovation management （ F3）

Regional innovation output （ F4）

comprehensiv e regional innovation （ F）

1

Hangzhou

18.710

6.762

26.399

29.757

81.628

2

Ningbo

9.841

5.008

17.679

23.347

55.875

3

Wenzhou

4.304

1.641

9.359

12.425

27.730

4

Jiaxing

9.690

0.951

8.845

20.973

40.459

5

Huzhou

5.004

1.989

14.386

20.194

41.574

6

Shaoxing

7.338

0.770

15.767

17.719

41.593

7

Jinhua

6.936

2.280

8.615

10.425

28.256

8

Quzhou

2.029

1.382

2.574

18.082

24.068

9

Zhoushan

3.341

8.210

11.108

14.997

37.656

10

Taizhou

6.955

0.945

7.191

17.356

32.446

11

Lishui

0.150

2.409

6.695

1.392

10.646

No.

B. Analysis of the Specific Indicators of Regional innovation of the 11 Prefecture-Level Cities in Zhejiang Province This part is based on the analysis to the regional innovation to conduct comparative analysis to the indicators forming the field layer, with an aim to find key indicators of raising the creativity. Based on the analysis to the weight and importance of the four big fields, the paper further analyzes the indicator layer. The following ranking is made based on the utility value of regional creation output capability, creation management capability, creation input capability, and creation supporting capability：

42

C. Ning and H. Chun

Table 4. Ranking of the utility value of the regional innovation output capability evaluation indicators Table Head

Table Column Head

Regions Hangzhou

Ranking Ranking Ranking Ranking (V19) (V20) (V21) (V22) 1 9 5 1

Ranking (V23) 4

Ranking (V24) 1

Ranking (V25) 7

Ningbo

2

6

4

2

6

2

8

Wenzhou

6

7

11

9

2

7

10

Ranking of Jiaxing the utility value of Huzhou the Shaoxing regional innovation Jinhua output capability Quzhou evaluation indicators Zhoushan

8

2

2

5

8

3

2

7

4

3

6

5

5

4

5

3

6

3

7

9

3

3

5

8

8

9

4

9

9

1

10

10

1

10

6

10

11

1

4

10

8

1

Taizhou

4

10

7

7

3

6

5

Lishui

11

8

9

11

11

11

11

Table 5. Ranking of the utility value of regional innovation management capability evaluation indicators Table Head

Ranking of the utility value of regional innovation managem ent capability evaluation indicators

Table Column Head

Ranking (V19)

Ranking (V20)

Ranking (V21)

Ranking (V22)

Ranking (V23)

Hangzhou

5

1

1

1

7

Ningbo

4

4

2

2

8

Wenzhou

6

5

7

9

11

Jiaxing

10

7

3

6

10

Huzhou

7

2

4

4

4

11

3

6

3

5

Jinhua

8

5

9

10

6

Quzhou

3

11

11

7

2

Zhoushan

2

6

5

5

1

Taizhou

9

9

8

8

9

1

10

10

11

3

Regions

Shaoxing

Lishui


43

Table 6. Ranking of the utility value of the regional innovation output capability evaluation indicators Table Column Head Table Head

Ranking Regions (V19) Hangzho 1

Rankin g(V20) 1

Rankin g(V21) 2

Ranking (V22) 1

Ranking (V23) 1

Rankin Ranking g(V24) (V25) 1 1

u

Ranking of the utility value of the regional innovation output capability evaluation indicators

Ningbo

5

5

4

3

2

3

3

Wenzhou

8

8

10

9

8

2

6

Jiaxing

3

2

1

4

3

7

5

Huzhou

6

6

8

5

7

5

8

Shaoxing

2

3

3

2

4

11

9

Jinhua

7

7

6

7

6

8

2

Quzhou

10

10

9

10

10

10

7

Zhoushan

9

8

5

8

9

4

10

Taizhou

4

4

7

6

5

9

4

11

11

11

0

11

6

11

Lishui

Table 7. Ranking of the utility value of the regional innovation output capability evaluation indicators Table Column Head Table Head

Ranking of the utility value of the regional innovation output capability evaluation indicators

Ranking Rankin Rankin Ranking Ranking Ranking Rankin Regions (V19) g(V20) g(V21) (V22) (V23) (V24) g(V25) 1 1 2 1 1 1 1 Hangzhou Ningbo

5

5

4

3

2

3

3

Wenzhou

8

8

10

9

8

2

6

Jiaxing

3

2

1

4

3

7

5

Huzhou

6

6

8

5

7

5

8

Shaoxing

2

3

3

2

4

11

9

Jinhua

7

7

6

7

6

8

2

Quzhou

10

10

9

10

10

10

7

Zhoushan

9

8

5

8

9

4

10

Taizhou

4

4

7

6

5

9

4

11

11

11

0

11

6

11

Lishui

44

C. Ning and H. Chun

5 Countermeasures to the Uplifting of Regional Innovation in Zhejiang The cultivation of regional innovation is a complex and systematic project. In the twelfth Five-year-plan period, Zhejiang puts forward the complete road of regional innovation: to continue deepening the reform of science and technology management system, giving full play to the leading role of the government, playing the fundamental role of the market in the allocation of creativity resources, establishing the main party role of the enterprises in the creation, and fully playing the backbone and leading role of the science and technology research institute within and outside the Province. The realization of these policies needs substantial cutting-in path, hence, to quicken the establishment of the creativity system and the cultivation of the creativity of the 11 prefecture-level cities in Zhejiang Province, the construction of the following three points needs to be pressed ahead. To optimize the regional innovation input system, and forcefully raise the creativity input: to establish and optimize the regional innovation input system in Zhejiang, the construction can be made from the following four aspects: firstly, establishing and optimizing the regional legal guarantee mechanism of the science and technology input in Zhejiang; secondly, securing the stable growth mechanism of the science and technology input by the financial offices of Zhejiang Province; thirdly, optimizing the input structure of the science and technology input by the financial offices of Zhejiang Province; fourthly, establishing multilateral science and technology input system in Zhejiang; fifthly, strengthening the introduction and cultivation of creative talents in Zhejiang Province. To establish regional innovation platform system and forcefully raise the capability in creativity support: the establishment of regional innovation platform system of Zhejiang, in the principle of optimizing external environment for regional innovation, can be realized by the following three aspects. Firstly, establishing a platform for regional R&D coordination in Zhejiang; secondly, establishing a platform for transferring the regional science and technology achievement in Zhejiang; thirdly, establishing a platform for sharing the regional science and technology resources in Zhejiang. To optimize the regional innovation management system and forcefully raise the creativity management capability: although the functions and roles of the regional innovation management system varied, the core is the same, i.e. to solve the incentive and restraint issues of the regional innovation. The effect of incentives and restraint can be achieved by reducing the transaction cost of regional innovation and the externality and uncertainties of the creativity, and creating cooperation opportunities. Firstly, the evolution system of the performance of the party and legal leaders of various levels needs to be optimized. Secondly, the preferential policy system of the technological creativity of the Province needs to be optimized. Thirdly, protection system of intellectual property rights of the Province needs to be optimized. Fourthly, the management system of the science and technology institutions of the Province needs to be optimized.


45

References 1. Acs, Z.J., Anselin, L., Varga, A.: Patents and Innovation Counts as Measures of Regional Production of New Knowledge. Research Policy 31, 1069–1085 (2002) 2. Adler, P.S., Shenbar, A.: Adapting Your Technological Base: The Organizational Challenge. Sloan Management Review 25 (1990) 3. Arrow, K.J.: The Economic Implications of Learning by Doing. Reviews of Economic Studies 29 (1962) 4. Asheim, B.T., Isaksen: Regional Innovation Systems: The Integration of Local “Sticky” and Global “Ubiquitous” Knowledge. Journal of Technology Transfer 29, 77–861 (2002) 5. Burgelman, R.: Strategic Management of Technology and Innovation. McGraw-Hill, New York (2004) 6. DeBresson, C.: Estimating Gaps Fisparities, Seminar on the Measurement of Innovation Activities in OECD and Non-OECD Countries. Pretoria 29 (March 2001) 7. Cooke, P.: Introduction: Origins of the Concept (A). In: Braczyk, H., Cooke, P., et al. (eds.) Regional Innovation Systems: The Role of Governance in a Globalize World. UCL Press, London (1998) 8. Dolor, E.: What We Should Know about Regional Systems of Innovation. Technology in Society 24, 243–263 (2002) 9. Evangelista, R., Iammarino, S., Mastrostefano, V., Silvani, A.: Measuring the Regional Dimension of Innovation (2001) 10. Feldman, M.P., Audretsch, D.B.: Innovation in Cities: Science- based Diversity, Specialization and Localized Competition. European Economic Review 43, 409–429 (1999)

Design of an Improved Method of Rijndael S-Box Chunxia Tu School of Computer Huanggang Normal University Hubei Huanggang 438000 China [email protected]

Abstract. According to the design criterion of S-box in Rijndael algorithm, a number of S-boxes with good cryptographic properties were constructed, and the avalanche probabilities of these S-boxes were analyzed from variance point of view. Based on these studies, a key-controlled Rijndael algorithm with multiple S-boxes was proposed with the improvement of SubBytes algorithm in Rijndael. Experimental results show that the improved algorithm has stronger ability to resist differential attack, and the avalanche effect of the algorithm is more reasonable. Keywords: Rijndael algorithm, S-box, differential attack, avalanche effect.

1 Introduction The Advanced Encryption Standard (AES) was specified in 2001 by the National Institute of Standards and Technology . The purpose is to provide a standard algorithm for encryption, strong enough to keep U.S. government documents secure for at least the next 20 years[1]. Since Rijndael was identified as the AES ,it has been a hot spot study.Rijndael was carried out all aspects of the study hope to break AES. Years of research show that the differential attack is still an effective way to attack block cipher. S box is the only nonlinear components in Rijndael algorithm, directly affecting their security, thus improving the S-box against differential attacks performance has been the research focus. An enhanced Rijndael algorithm was proposed through improving bytes replacement algorithm.The improved algorithm has stronger ability to resist differential attack, and the avalanche effect of the algorithm is more reasonable[1-3].

2 Differential Attack on 2 Round Rijndael Key A simple differential attack implement on two round of Rijndael key described as follows : First, select two plaintext X(1), X(2) and the corresponding ciphertext Y (1), Y (2), the first of two expressly 8,11,14 Bytes are for the '00 ', the encryption key for the K=K1K2K3……K16. Secondly, the streamlining of the algorithm described in the following relationship can be established: [2] M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 46–51, 2011. © Springer-Verlag Berlin Heidelberg 2011

Design of an Improved Method of Rijndael S-Box

47

Y1(1)=S((‘02’ ⊙ S(X1(1) ⊕ K1(0))) ⊕ (‘03’ ⊙ S(X14(1) ⊕ K14(0))) ⊕ (‘01’ ⊙ S(X11(1) ⊕ K11(0))) ⊕ (‘01’ ⊙ S(X8(1) ⊕ K8(0))) ⊕ K1(1)) ⊕ K1(2) (1) Y1(2)=S((‘02’ ⊙ S(X1(2) ⊕ K1(0))) ⊕ (‘03’ ⊙ S(X14(2) ⊕ K14(0))) ⊕ (‘01’ ⊙ S(X11(2) ⊕ K11(0))) ⊕ (‘01’ ⊙ S(X8(2) ⊕ K8(0))) ⊕ K1(1)) ⊕ K1(2) (2) According to the characteristics of the selected explicitly, the equation (1), (2) can be simplified, respectively (3), (4): Y1(1)=S((‘02’ ⊙ S(X1(1) ⊕ K1(0))) ⊕ (‘03’ ⊙ S(K14(0))) ⊕ (‘01’ ⊙ S(K11(0))) ⊕ (‘01’ ⊙ S(K8(0))) ⊕ K1(1)) ⊕ K1(2) (3) Y1(2)=S((‘02’ ⊙ S(X1(2) ⊕ K1(0))) ⊕ (‘03’ ⊙ S(K14(0))) ⊕ (‘01’ ⊙ S(K11(0))) ⊕ (‘01’ ⊙ S(K8(0))) ⊕ K1(1)) ⊕ K1(2) (4) Suppose the elements of the outermost layer of S-box were δ1, δ2, the following equation can be established: Y*=Y1(1) ⊕ Y1(2)=S(δ1) ⊕ S(δ2) δ1 ⊕ δ2=(‘02’ ⊙ S(X1(1) ⊕ K1(0))) ⊕ (‘02’ ⊙ S(X1(2) ⊕ K1(0)))

(5) (6)

Finally, though processing (5) and (6) , we can get the possible range of K1(0) . And then repeatedly select the express and make the same treatment, until the only determining K1 (0) or K1 (0) up to the possible range of small. For the Ki(0)(1≤i≤16),a similar approach can be taken. Obviously, the main principle of the simplification and attacks on the Rijndael algorithm in references [2] is because that Rijndael block cipher using only one S-box. From that point too, the paper proposed an improved scheme.Ease of Use

3 Key-Controlled Rijndael Algorithm with Multiple S-Boxes In this paper, we improve the algorithm though the steps of the ByteSub. The S-box, which is used by each byte of intermediate state, is selected from a given number of Sboxes. The proposal below is based on the following rules to select the S-box: For the first n-bytes of state, the first n-bytes of the round keys decided to select which S-box. A.

Algorithm Description

(1) Bytes substitution algorithm in Rijndael: ByteSub(a[4][MAXBC],box[256]) /*Encrypted using the S box, decryption using the inverse S-box */ { int i,j; for(i=0;i (2) by IIS using integrated windows authentication against Web application's virtual root directory for anonymous access[8]. Authorized to:(1)ASP.NET Web application is configured to use the "file under"; (2)to configure the web server user license the right to limit the use of resources, in order to simplify the management of the user to the windows group and the use of groups in the ACL; (3) ASP.NET web application according to documents related to permissions that using the client's identity implementation of the access check. The implementation of the IIS integrated windows authentication to use intemet explorer. In a mixed browser environment, you can use other authentication scheme, such as basic authentication and SSL, client certificates, forms authentication, in these programs, the authentication must use encrypted communications: SSL (Secure Sockets Layer, Secure Sockets Layer). 2. The security program of internet application

①

②

Most Web applications are based on intemet users, the application have the following characteristics: users have many different browser types; anonymous users can browse the unrestricted application page; users must register or log in (through HTML form) to have access to restricted pages; SQL server database according to validate the user credentials[9].

③

④

74

Z. Jing

Based on these features, common safety measures are: Authentication:(1)HS configured to allow anonymous access;(2)ASP.NET web applications configured for forms authentication:Edit the application's virtual root directory web.config. element is set to: ;(3)use the database to store user name and password, but password is not stored directly, but to convert the value of the password hash with a salt value, in order to reduce the threat associated with dictionary attacks to verify. Authority: the ASP.NET Web application is configured to "URL authorization" . Forms Authentication, you must use SSL to protect the initial login credentials, the same time, the resulting forms authentication ticket must be protected, you can use SSL for all pages to protect the votes, it can be web.config surface element protection attribute is configured to All or Encrypt, to encryption. web server URL authorization allows unauthenticated users to view web pages unrestricted, and restricted the page to force authentication.

5 ASP.NET Application, Common Security Flaw ASP.NET programmers to bring a vast new program of space, but because it contains many new technologies, in terms of each There are still a lot of programmers need to learn, programming, they also inevitably some flaws . 1. Excessive trust of user input ASP.NET that page as an intermediary with the user interaction, the user will enter the website legal information, and therefore the user's input does not carry out verification and inspection, in fact, now many hackers will attack with a lot of methods and tools to the input box, enter the specific information with a bad purpose, to achieve its other objectives. This vulnerability is easy to be hackers to SQL injection attacks and XSS attacks, and thus defrauding the trust and access to confidential data on servers and other hazards. This vulnerability is the low level of security loopholes. 2. The use of information leakage caused by Cookie To use the Cookie, do not need to programmatically create and read them explicitly. If you use session state and forms authentication implementation will implicitly use the Cookie[3]. Of course,ASP.NET support without Cookie session state, but if ID can be embedded in the URL, so more vulnerable. 3. Pass parameters from the URL security vulnerability Using a variety of development languages used by Web programmers almost all URL parameters passed by value, with the ASP.NET programming, too, it can easily get to the next page on the page associated with a value, simplify code writing, however, it vulnerable to hacker attack vulnerability. 4. The page directly Script Language Many programmers are accustomed to a web page (that is .Aspx file) [4] to add language to deal with Script pages the user insertion of information (such as form input), without any network transfer data back and forth, so when the user enters a items of information, it need not pass through the server (Server) address, and

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transmits it back to the process, the client directly can be handled by the application. This can speed up access to a good speed. Since it is generally only the client implementation, and its source code client can directly see, with the server client is not necessary connection, but it can be in the client offline, so hackers can easily attacked, so from security considerations should be avoided.

6 Conclusion This paper discusses the asp.net environment based on common security flaws and security architecture asp.net environment. Also studied the application IIS and ASP.NET authentication mode and authorization mechanisms, and their intranet and internet environment, security configuration and did not be related to the background database security issues. But as the intemet application developers, we should recognize that ASP.NET applications use a large number of users, many potential uses and a variety of different security requirements, so the application process to ensure the appropriate use of defense mechanisms, while must also ensure efficient. Acknowledgment. First and foremost, I would like to show my deepest gratitude to my colleague Dr. Fang Yuan, who has provided me with valuable guidance in every stage of the writing of this thesis. I would also like to thank reviewers for constructive reviews and suggestions that improved the quality of this manuscript. This work was funded by the project of Huanggang teacher Bureau (2009CE19) and the project of Science and Technology of Hubei Province Department of Education research(B20102905).

References 1. Zhou, j.: The Exploration of Data Transfer Mode between ASP and ASP.NET Page. Microcomputer Information 5-3, 114–115 (2006) 2. Zhou, j., Liu, q.: The System Safety Research and Design based on.NET Framework. Communications Technology (May 2008) 3. Wei-yuxin: Network Invasion Examination System Key Technologies Research. Beijing University of Posts and Telecommunications doctorate paper (2008) 4. Jing, Z., Yuan, F.: The component code of each call analyze and compare based on .NET. In: Proc. Int. Symp. Intelligent Inf. Technol. Appl., IITA 2009 (EI 20101012756764). IEEE Computer Society press, Los Alamitos (2009) 10.1109/IITA.2009.60 5. Wang, W.: Asp.net Techniques. people’s press, Beijing (2005) 6. Yang, K., Meng, F., Wen, C.: Inflammation. Asp.net + SQL SERVER Dynamic Web Development from the Foundation to Practice. Electronic Industry Press, Beijing (2005) 7. Chu,Y.: Asp.net Application Security Flaws and Prevention Strategies. Journal of Anhui: Anhui (2007) 8. Li, X., Shuan, l., Zou, J.: Asp.net Technology Development (January 2005) 9. Jing, Z., Yuan, F.: The examinational technology of invasion analysis based on network security. In: Proc. IITA Int. Conf. Control Autom. Syst. Eng., CASE 2009 (EI 20094712474583), pp. 624–627. IEEE Computer Society press, Los Alamitos (2009), doi:10.1109/CASE.2009.145

Spatial Distribution and Vertical Variation of Cu Concentration in Guangdong Fang Yuan and Chen Li-yan Department of Computer Science and Technology Huanggang Normal University Huanggang, China [email protected]

Abstract. Based on GIS with Geo-statistics analyst software (Surfer 8.0), total of 261 soil profiles were reported to investigate the Cu spatial distribution and vertical variation in Guangdong province. Cu spatial distribution presented similar patterns that high Cu concentration mainly located in fault, basin, and delta areas, indicating that soil Cu distribution was dependent on regional basin. Moreover, from A- to C-horizon Cu mean concentrations had an increasing tendency. Regional extensive distribution of granite and the fault mainly decided the spatial distribution of Cu concentration. Soil organic matter and clay content also, to a certain extent, affect the spatial distribution of Cu concentration. Keywords: component, Geo-statistics, spatial distribution, Cu Concentration.

1 Introduction Soil Cu is a potentially toxic element of most heavy metals and is present in soils, rocks, water, and the biological chains of animal and plant lives. Soil Cu environmental background value refers to the original Cu content in the soil without obvious pollution and destruction in a certain area during a certain period, which reflects the original condition of Cu element in the soil environment. The study of soil Cu background values is a basic work in soil environment science. Whether seeking the evaluation of soil Cu abnormity and the reference of the pollution degree, or setting up soil Cu pollution control measures should take the original condition of Cu as a reference. The determination of Cu content is of great significance for judging soil Cu pollution degree and developing soil environment quality standards. During the seventh Five-Year Plan period (1986-1990), a large-scale investigation and research of soil environmental background values was launched in Guangdong Province, and a rich basic data of soil environmental background values has been accumulated, based on which, Xu Lianfeng did a preliminary study on zonal differentiation of soil environmental background values and critical content in Guangdong Province[3]. However, the acquired basic data have not been fully excavated due to the objective condition at that time. The soil background value hasn’t been taken as a regionalized variable with spatial structure when considering its spatial M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 76–82, 2011. © Springer-Verlag Berlin Heidelberg 2011

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variability, therefore, the information of the spatial structure and spatial distribution of Guangdong soil environmental background values has not been fully utilized. In this paper, the geo-statistical method is used to reveal the spatial distribution and vertical variation of the soil Cu environmental background values in Guangdong, and the factors affecting the variation of Cu background values are also been analyzed.

2 Overview of the Study Area and Research Methods A. Description of the Study Area

～

～

Guangdong Province is located at 20°13′ 25°31′north latitude, 109°41′ 117°20′east longitude, and the Tropic of Cancer is running through the province. From west to east, it is adjacent to Guangxi, Hunan, Jiangxi, and Fujian Province. In the south, it is on Qiongzhou Strait opposite Hainan Province. The total land area is 178,100 square km, accounting for 1.86% of the country's total area. In Guangdong Province, the North terrain is higher than the south. Nanling is lying to the north and the South China Sea is to the south. The mountain has a northeast to southwest trend. ost parts of the province have a subtropical monsoon climate, and some has a tropical monsoon climate. Summer is long, and winter is short and warm. The rainy season is long, and the rain is plentiful. Wet and dry seasons are obvious. The average annual temperature is18~23.2oC, and the annual rainfall is generally 1700 mm, with the coastal areas 1900 ~ 2000 mm. Geological structure is rather complicated. The soil parent material is as shown in Figure 1B. There are granite, sandstone and shale, limestone and basalt, etc. The main soil types include: latored soil, red soil, laterite, mountain yellow soil, red limestone soil and the sea (river) alluvial soil. The distribution of soil elements is highly heterogeneous. B. Data Sources and Research Methods The original data source used in this research is coming from the seventh five-year National scientific and technological issue- "Investigation and Research on Soil Environmental Background Values in Guangdong Province”. The total sampling profiles is 261. The Global Positioning System (GPS) is used to reposition the original data for sampling points. With the support of GIS software, the attribute data is validated, modified and conducted with projection coordinate conversion (mainly for matching with other geo-data), the distribution of samples as shown in Figure 1C. In this study, the main data processing methods are conventional statistical analysis and geo-statistical methods. Samples data statistical analysis adopts SPSS software, and geo-statistical methods use Surfer 8.0 software to fit semi-variance function and to conduct Kriging interpolation. The corresponding spatial analysis is using ArcGIS 9.0 software. Semi-variance function is also known as semi-variogram. It is not only the basis to explain the spatial variability structure of soil properties in geo-statistic, but also can reflect the changes between the values observed from different distances. Therefore, it is the key to the success of spatial interpolation [4] [5]. The semi-variance function is expressed as the following form:

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F. Yuan and C. Li-yan

r (h) =

1 N (h ) ∑ [ Z ( xi ) − Z ( xi + h) 2 N ( h ) i =1

]2

Where N(h) is the number of pairs of observation points taking h as the distance. The semi-variance function graph of a specific direction is often achieved by r(h) through h. Generally, the value of the semi-variance function becomes larger as the distance between samples increases,

3 Results and Discussion A. Statistical Characteristics of Cu and Soil Properties The analysis of Cu background values and part of soil characteristics in 261 profiles shows that the background values of soil Cu is close to the world average, but lower than the national average level [1]. Soil Cu with the highest background value (146.75 mg kg-1) appears in B layer, and Cu background value of each soil layer shows a positive skew distribution. Data is consistent with the logarithmic distribution, so the logarithmic transform is carried out in the relevant geo-statistics treatment. The content of organic matter in A layer of soil ranges from 1.7 ~ 9.94%, in B layer is 0.07~3.83%, and in C layer is0.03~3.56%. The highest and lowest values of the content of the organic matter appear respectively in A layer and C layer. The particle diameter distribution of each layer in the soil profile is almost in line with the normal distribution. From A to C layer, the arithmetic mean values of sand content are 50.4, 43.4 and 44.6%, and of clay content are 18.4, 20.4 and 20.1% respectively. Soil pH values show a weak growth trend from A to C layer. Both the maximum value and the minimum value appear in C layer. B. Correlation Analysis on Cu Concentration and Soil Properties A large number of studies have shown that the soil containing more clay minerals and richer organic matter tends to have higher level of metal elements, and they have the characteristics of combining with metal elements[9][10]. Because of strong weathering and the rock's mineral composition and structural characteristics, the soil of the study area under hot and humid climatic conditions has a relatively short period of soil age, and the above correlation is not obvious. Through the statistical analysis of the 261 soil profiles in Guangdong, we can see from table 1 that the soil Cu background value has great correlation with the clay content and the organic matter, has no correlation with the pH, and has weak negative correlation with the sand. The correlation between soil Cu background value and the organic matter strengthens as the soil depth increases. The correlation coefficient of C layer is 0.276. The biggest coefficient 0.393 of correlation between soil Cu background values and the clay appears in A layer, while the biggest coefficient(0.114) of correlation between soil Cu background values and the pH appears in B layer. The negative correlation between soil Cu background values and the sand decreases as the soil depth is increasing.

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In general, there is no obvious linear relationship between soil properties and soil Cu background values. It reveals that the organic matter and clay content is not the main factor of determining the variability and spatial distribution of soil Cu background value. The weak correlation between soil Cu background values and the organic matter and clay should be the result of the strong and rapid weathering of rocks in the study area. C. Analysis on the Spatial Distribution and Vertical Variation of Cu Use exponential model fitting variation curve and Kriging interpolation method for interpolation on Cu background values conducted with logarithmic transformation in Guangdong Province. From fig. 2, we can see that the spatial distribution of the variability of A, B and C layer is consistent because of the approximating content. From table 2, we can see that the distribution of soil Cu in Guangdong Province is highly heterogeneous. A, B, C layer show medium spatial correlation, and the ratio between larger pieces of gold block value and base value shows a small-scale variation existing. However, as a large-scale spatial variability research and analysis of influencing factors, it is insignificance to study the small-scale variation. From Table 3 we can see that Cu background value has medium correlation close to the scale of 150km ~ 200km. Greater than this scale, the variation degree becomes stable. Use variable-range and the log-log curve of semi-variance to calculate the fractal dimension D. It is 1.96, 1.94 and 1.91 of A layer, B layer and C layer respectively, which on the whole shows higher heterogeneity of soil Cu background value in a large-scale in Guangdong Province. The topsoil reflects the mutual interaction between the atmosphere, the biosphere and the lithosphere. B layer is usually used to study the process of soil pedogenesis, while C layer, represents lithosphere components of samples, namely, the geological background values [7]. The average soil Cu concentrations of A, B, C layer of the 261 soil profiles are 17.35 mg kg-1, 18.99 mg kg-1 and 20.65 mg kg-1, showing a growth trend. Contour map of Cu concentrations show a similar spatial distribution, which shows that the soil sample with a high concentration of copper is usually located mainly in areas of granite (Figure 2 and Figure 1B). It reveals that in Guangdong Province the spatial distribution of soil Cu is mainly depend on the regional characteristics of rock, and doesn’t have obvious relationship with clay and soil organic matter content. It also proves that the input of Cu is not an important influence factor at the regional scale. The Cu concentration shows an increasing trend from A to C layer in the soil profile, but there is no obvious bottom enrichment phenomenon, which may be closely related to the following factors: the organic matter content contained in the topsoil is low (the average is 2.75%), which cannot function as a natural biogeochemical barrier, and therefore, cannot effectively prevent the soil element from percolation with the downward of water seeping ; At the same time, low soil pH value and high permeability of widely distributed semi-decomposed granite rock can make Cu migrate from topsoil to C layer. In addition, the limestone and sandstone areas are often broken by the cuttings in the study area (Figure 1) , which provides paths for soil Cu downward migration. D. Spatial Variability Analysis of Topsoil Cu Background Values under Regional Geological Context The background value data of Cu in major soil rock in China shows that the soil Cu comes from a variety of rock, the soil Cu background value to a large extent is

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determined by the Cu content of rock itself[1]. From Figure 1 we can see that the acidic granite is the main rock, followed by limestone and sandstone and shale. As a result of strong chemical weathering and weak water permeability, the layer of soil developed in the limestone and sandstone-shale soil is often very thin, water and soil erosion is more serious, and the weathering profiles of granite with thickness greater than 20m are widely distributed. In view of strong weathering, the influence of regional granite on the Cu content contained in the topsoil in a certain extent is closely related to the role of soil-forming. The impact is likely to cover up the distribution characteristics of Cu in the adjacent areas. Therefore, under the conditions with rich hydrothermal resources, for the relatively young soil in Guangdong, the low content of a variety of mineral elements contained in the widely distributed granite rock is the main factor to determine the attachment and the distribution of soil Cu. With the support of ArcGIS, make an overlay analysis on the geological structural map of Guangdong and the spatial variability map of soil Cu in A layer obtained by Kriging interpolation (Figure 2A). The result show that the spatial distribution characteristics of surface soil Cu are closely related to regional geological setting. As can be seen from the Figure, the overall spatial variability mode of soil Cu in A layer is as follows: the soil Cu background value decreases from north to south; under the natural background, the soil samples with low concentrations are often located in the normal region with no obvious structural features, while soil samples with high concentrations of heavy metals are usually located in fault zone, basin and delta regions; soil Cu samples with high concentrations is distributed along with the regional fault, and is corresponding to the spatial distribution of regional basins. This distribution pattern is to some extent the result of frequent hydrothermal activity caused by the regional fracture during the period of Cenozoic tectonic movement, and also influenced by the negative effects of basin topography during the pedogenesis process. The overall statistical results (table 3) show that the soil Cu concentration in A layer from high to low is: the Pearl River Delta≥ Basin ≥ fault>> normal area. The geometric mean value of soil Cu concentrations in basin and delta region is almost 2.1-3.1 times of that in normal areas.

Fig. 1. Location of Guangdong Province in China (A), geological sketch indicating the distribution of the parent rock (B), and sampling locations (C).


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Fig. 2. Spatial distributions of Cu concentrations in A-, B-, and C- B-horizon soil in Guangdong

4 Results The background value of soil Cu is lower than the national average level of soil Cu content. The soil Cu concentration of each layer is in line with the lognormal distribution characteristics. Variogram fitting theoretical model is an exponential model. Geo-statistical analysis shows that the spatial structure of Cu background values has a medium correlation and high heterogeneity as a whole, and the overall spatial variability of A, B, C layer is almost in line. The surface soil Cu background value decreases from north to south. Soil samples with high concentrations of Cu are usually located in fault zone, basin and delta regions, and are corresponding to the spatial distribution of regional basins. From A to C layer the concentration of Cu has an obvious trend of growth. The contour map of Cu concentration displays similar spatial distribution features, but there is no obvious phenomenon of underlying enrichment. Widely distributed granite rock in the region and the distribution of regional faults structure are the main influencing factors to determine the deposit and distribution status of soil Cu. soil organic matter and clay content, to a certain extent, also affect the variability and spatial distribution of soil Cu concentration. layer. Acknowledgment. We thank Professor Wu Zhifeng and reviewers for constructive reviews and suggestions that improved the quality of this manuscript. The work was

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funded by the Technologies R&D Program of Guangdong Province 2004B32501004 , the Doctor Fund of Huanggang Normal University (08cd159) and the project of Education Department of Hubei Province.

References 1. Chen, M., Ma, L.Q., Hoogeweg, C.G., Harris, W.G.: Arsenic back-ground concentration in Florida, U.S.A. surface soil: determination and in-terpretation. Environmental Forensics 2, 117–126 (2001) 2. Cressie, C.: Statistics and data analysis in geology, 2nd edn. John Wiley & Sons, New York (1991) 3. Gee, G.W., Bauder, J.W.: Particle-size analysis. In: Klute, A. (ed.) Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods, pp. 377–382. ASA, Madison (1986) 4. Tangestani, M.H., Moore, F.: Iron oxide and hydroxyl enhancement using the Crosta Method: a case study from the Zagros Belt. Fars Province, Iran.. JAG 2(2), 140–145 (2000)

The Quantitative Application of Information Extraction by Remote Sensing in Aranbaotai Area Fang Yuan and Chen Li-yan Department of Computer Science and Technology Huanggang Normal University Huanggang, China [email protected]

Abstract. The study was focused on Aranbaotai Region of Taxkorgan Tajik Autonomous County In Xinjiang. Lineament and circular structures were interpreted from ETM images. According to the spectral characteristics of typical altered rock, mineralized alteration information were extracted by band ratio and principle component analysis. The spatial distribution of remote sensing interpretation results was consistent with known ore deposits, which showed its good application prospect of mineral resources exploration and assessment in Taxkorgan. Keywords: component, structure interpretation, remote sensing alteration information, ore prospecting, Aranbaotai.

1 Introduction (Heading 1) The situation between resources’ supply and requirement contradiction is serious, so it is urgent to find new method for reducing minal exploration cost and time. The study area is abundant in mineral resources and has been found several ore deposites. Adverse natural and traffic conditions bring difficulties in basic geological data development and mineral exploration. The remote sensing technology is the only practical way to obtain data from inaccessible regions, relatively cheap and rapid method of acquiring up-to-date information over a large geographical area.Landsat data have been used for a number of years in arid and semi-arid environments to locate areas of iron oxides and/or hydrous minerals [Abrams et a/, 1983; Kaufman,1988; Ranjbar & Roonwall, 1997;Majid Hashemi Tangestani,2000]which might be associated with hydrothermal alteration zones. The aim of the present study is to use ETM data, in combination with field,mineralogical, and geochemical investigations to define typical characteristics of alteration zones. The ETM image data were used to extract alteration zones using principal components analysis (PCA) of mineralogic indices extracted from the band ratios. Finally, the fractional abundances of significant alteration minerals are detected using a matched filtering technique. The result can provide basis for further prospecting potential prediction and comprehensive exploration. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 83–87, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Geology Aranbaotai district lies between latitudes 74°50’ and 75°20’N and longitudes 37°20’ and 37°50’E at the west part of Taxkorgan Tajik Autonomous County.The geotectonic location of the area lies in karakorum block and exposure strata are paleoproterozoic hebron sarikol group metamorphic strata, Permian and very little quaternary eluvium, river alluvium. Structurally, Taxkorgan fault was on the east of the study area, which was part of karakorum fault. The NNW-trending fault cross cut the west kunlun, Pamirs and karakorum and was composed of several small faults. Magmatic rocks were mainly composed of Yanshan and Himalayan granite. Outcrops are composed of alkaline syenites, subalkaline, aranbaotai, xingungou, buyiale, kuokejiaerwen and gelinale granitoids. There are at lest 4 types of mineralization: siderite type Cu-Ag mineralization produced around granitoids(e.g. kalajieligan deposite,pisiling cu deposite and aranbaotai siderite deposite); quartz vein type Cu mineralization produced in metamorphic schists(e.g. gandadieer deposite);cu-pb-zn mineralization related to granodiorite (e.g. kalaguorumu Cu-Pb-Zn deposite,helewate cu deposite and ganxiangjielie cu deposite); pb-zn mineralization related to carbonate (e.g. akexilake deposite).

3 Structure Interpretation The ETM data must be preprocessed before interpretation. Firstly, remove the effect of snow on displaying useful geological information by the band ratio threshold method. Secondly, fuse the multispectral band and pan band images to improve spatial resolution so that the structure interpretation precision and accuracy are improved. Finally, the false color composited map of ETM743 bands was selected for geological interpretation. Linear and circular structures were depicted using the man-computer interaction interpretation method by comparing geological geometry, color, texture and spatial relationship between bodys. Favorable zones for ore prospecting were delineated by analysing the structural characteristics with geological data in the study area. The structure interpretation result was shown in Figure 1. NW-trending(F5) , NNWtrending(F2) , and NE-trending(F6) main faults controled the distribution of circular and structure and secondary faults. Most of the secondary faults were NW-trending. Circular structures are superimposed compound. The main combination relations among those circular structures were overlapping, intersecting, tangent, and satellite types, which indicated that magmatic activities happened frequently in the study area. A. Classification of Wall-Rock Alteration Intrusive mass was widely distributed in the study area, which provided good conditions for hydrothermal deposits. According to previous research work (e.g. zhaoling,2009;wanghe 2008), the main types of wall-rock alteration were ferritization, chloritization, kaolinization, alunitization, carbonatization, silication and so on. Those alteration types indicated the degree of hydrothermal solution erosion to wall rock and had different geological significance to ore prospecting. Due to wide range of ETM bands, it was difficult to discern all those alteration types above

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Fig. 1. The ETM743 image and structure interpretation of the study area

respectively. Wall-rock alteration was classfied into 3 types: ferrous alteration(ferritization for Fe2+,Fe3+); clay alteration(carbonatization for CO32- and chloritization for OH-); silicified alteration(SiO2 enriched). After classfied, wall-rock alteration could be discernd by band ratio and principal component analysis methods.The 3 types of wall-rock alteration extraction could provided decision support for mineral prediction.

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B. Effective Bands Selection Identification of alteration minerals was based on the wavelength, intensity, and shape of absorption band and by comparison with speatra of the minerals concerned. The typical spectrum of alterated rocks was drawn from the ETM data,and the spectral characteristics were shown in Figure 2 . According to the absorption and reflection features, ETM3/1, ETM5/4 can usde to identify limonitization and ferrous oxide(10) respectively. The methodology for iron oxid emapping by PCA on ETM3/1 and ETM5/4 is to examine the eigenvector loadings in PC1. The PC1 image best discriminates iron oxid -bearing minerals.

Fig. 2. The spectral characteristics of typical altered rock

Extraction of clay alteration can use ETM5/7. The spectral characteristics of vegetation in TEM5,7 were similar to clay altertioan. ETM4/3(vegetation index) was added to control the interferences of vegetation. The PC2 image that best discriminates iron oxid -bearing minerals. The reflection of SiO2 alteration was strong in ETM6. The experimental results showed that ETM6/5 highlighted SiO2-bearing minerals as light pixels, vegetation and shadow as dark pixels. C. The Model of Alteration Information Extraction Statiscal Characteristics of ETM bands and ratio results obeyed nearly the normal distribution law. When doing abnormal slicing ,σ(Standard deviation) expressed normal distribution curve scale, and μ(mean value) expressed the background value. So the formula (μ+kσ) can fix the lower limit.

4 The Spatial Distribution of the Altered Information According to geological data and the understanding of this study, Taheman-Kongmu metallogenic belt, Tarxi-Xiruo metallogenic belt and Kalasu-Mingtiegai metallogenic belt were subdivided. It was shown in Fig 3. Kalasu prospective area, Zankan-Xiruo prospective area and Mingtiegai prospective area were predicated. Two metallogenic targets were determined, which were respectively Zankan-Xiruo cu, Au target and Mingtiegai cu target. The main romate sensing alteration anomaly areas were delineated. They were Tanheman anomaly area, Tizinapu anomaly area, Kalasu anomaly area, Mingtiegai anomaly area and Zankan-Xiruo anomaly area.

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(a)

(c)

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(b)

(d)

Fig. 3. The distribution of RS alteration information

References 1. Chen, M., Ma, L.Q., Hoogeweg, C.G., Harris, W.G.: Arsenic back-ground concentration in Florida, U.S.A. surface soil: determination and in-terpretation. Environmental Forensics 2, 117–126 (2001) 2. Cressie, C.: Statistics and data analysis in geology, 2nd edn. John Wiley & Sons, New York (1991) 3. Gee, G.W., Bauder, J.W.: Particle-size analysis. In: Klute, A. (ed.) Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods, pp. 377–382. ASA, Madison (1986) 4. Ives, A.R., Cardinale, B.: Food-web interactions govern the resistance of communities after nonrandom extinctions. Nature 429, 174–177 (2004), doi:10.1038/nature02515 5. Tangestani, M.H., Moore, F.: Iron oxide and hydroxyl enhancement using the Crosta Method: a case study from the Zagros Belt. Fars Province, Iran. JAG 2(2), 140–145 (2000)

Research on the Sustainable Development of Export Trade in China Fei Wang School of Business Sias International University Xinzheng, P.R. China [email protected]

Abstract. China’s economy has been guided by export-orientation policy in which export trade has played a very important role in our national economy. This article used econometrics model and deeply analyzed the internal relationship between export trade and economy growth, and inferred that to develop the general export trade is the necessity of developing export trade sustainably. At last some policies for the changing of export trade pattern were also mentioned. Keywords: export trade, sustainable development, trade pattern.

1 Introduction Since the reform and opening up, China’s export trade has developed rapidly. According to the statistics of WTO, the amount of China’s export in 1908 is 18.19 billion dollars, 62.09 billion in 1990 and research 183.76 billion in 1998. At the end of 2008, the total amount of China’s export is 1.42855 trillion U.S. dollars, increased by 17.2%, in which, the amount of general trade is 662.58 billion, increased by 22.9%, and the growth rate is more than that of processing trade for nearly 14 percentage points. During the same period, the value of Chinese processing trade reached 1.05 trillion U.S dollars, an increase of 6.8%, accounting for nearly half of the gross national foreign trade. Among them, the value of export is 675.18 billion, an increase of 9.3%, and the value of import is 378.4 billion, an increase of 2.7%. So the trade surplus in this area is nearly 3000 billion. Clearly, the general trade and processing trade have a tremendous role in promoting China’s economic development and the upgrading of the industrial structure. Based on the above analysis, this article will use the co-integration model to do in-depth study of the relationship between the Chinese export pattern and economic growth.

2 The Relationship between China’s Export Trade and Economic Growth A. Empirical Analysis 1) Preliminary analysis of data In this paper, we select the sample data among 1995 and 2007.Among the data, China’s export status are measured by the total exports, short for X, total exports of general trade, M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 88–93, 2011. © Springer-Verlag Berlin Heidelberg 2011

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short for GT, total exports of processing trade, PT, and other trade exports, OT. The gross domestic product, short for GDP, is the representative of China’s economic growth. Specific data is shown in Table 1 (The Unit is Hundred Million Dollars). Table 1. Data Of China’s Export And Economic Growth YEAR

GDP

X

GT

PT

OT

1995

7002.527

1487.800

620.100

819.200

44.000

1996

8164.899

1510.500

632.500

835.400

44.900

1997

8982.436

1827.900

765.300

1010.800

54.300

1998

9463.009

1837.100

769.100

1015.900

54.600

1999

9913.569

1949.300

815.200

1076.900

57.900

2000

10807.41

2492.000

1043.400

1378.400

74.100

2001

11757.25

2661.600

1116.400

1474.900

79.300

2002

12706.57

3255.700

1362.100

1799.400

94.200

2003

14165.99

4383.700

1820.300

2418.500

144.900

2004

19316.40

5933.700

2436.400

3279.900

217.400

2005

22256.80

7620.000

3150.900

4164.800

304.300

2006

26458.09

9689.4

4162.00

5103.55

423.81

2007

33089.89

12177.8

5384.57

5175.60

617.69

Source: China Statistical Yearbook Of 1995-2008 and website of Commerce Ministry.

In order to remove the impact of price changes on economic variables, we use index of CPI (base period of 1978) to deflate each nominal economic variables on table 1.Meanwhile, in order to eliminate heteroscedasticity that exist in the data, we logarithmic each variable, namely: LGDP = log (GDP), LX = log (X), LGT = log (GT), LPT = log (PT), LOT = log (OT). The corresponding first differential variables and second differential variables were iLGDP, iLX, iLGT, iLPT, iLOT and iiLGDP, iiLX, iiLGT, iiLPT, iiLOT. In Eviews, the data of each variable generate line graph (omitted in article). From the figure, we can see that the line graph has a clear trend. So the data may be non-stationary series, we need a stationary test. 2) Stationarity tests Here, we use Augmented Dickey-Fuller Test to do the smooth tests on variables of LGDP, LX, LGT, LPT, LOT, iLGDP, iLX, iLGT, iLPT, iLOT, iiLGDP, iiLX, iiLGT, iiLPT and iiLOT. The results show that, LGDP, LX, LGT, LPT , LOT and iLGDP, iLX, iLGT, iLPT, iLOT are non-stationary time series, and iiLGDP, iiLX, iiLGT, iiLPT, iiLOT are Stationary time series. So LGDP, LX, LGT, LPT and LOT are second-order integration series. 3) Cointegration test We have identified that all variables are same order integration, then, we use EG two–step method, respectively, to do regression on LGDP and LX, LGDP and LM, LGDP, and

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LXM, LGDP, and LNX, and do a stationarity test on residual sequence(Figures in brackets are T-test values).The co-integration equation is: LGDP= 5.5261 + 0.4613*LX (19.5446) (12.6024) Adjusted R-squared=0.9293 DW=1.2282

(1)

LGDP= 5.9776 + 0.4539*LGT (25.7041) (13.3848) Adjusted R-squared=0.9369 DW=1.3424

(2)

LGDP= 5.5739 + 0.4948*LPT (14.7030) (9.2727) Adjusted R-squared=0.8763 DW=1.0716

(3)

LGDP= 7.6282 + 0.3376*LOT (84.8303) (16.3470) Adjusted R-squared=0.9569 DW=1.6379

(4)

Here, we order E1, E2, E3, and E4 as the corresponding residuals of the above equations, and then, do unit root test for the residuals of each equation. The results showed that: LGDP and LX, LGDP, and LGT, LGDP, and LPT, LGDP, and LOT have relationship of cointegration, that is, there exist long run equilibrium. 4) Granger causality test To further illustrate the causal relationship between variables, there will be variable Granger Causality Test. The results are showed in Table 2. Table 2. Result of Granger Test Test Variables LGDP does not Granger Cause LX LX does not Granger Cause LGDP LGDP does not Granger Cause LGT LGT does not Granger Cause LGDP LGDP does not Granger Cause LPT LPT does not Granger Cause LGDP LGDP does not Granger Cause LOT LOT does not Granger Cause LGDP

F-value

Probability

Result

0.74346

0.41094

LGDP ⇒ / LX

15.0417

0.00374

LX ⇒ LGDP

0.42071

0.53278

LGDP ⇒ / LGT

15.3189

0.00354

LGT ⇒ LGDP

1.85953

0.20581

LGDP ⇒ / LPT

13.3486

0.00529

LPT ⇒ LGDP

0.7571

0.40684

LGDP ⇒ / LOT

27.3974

0.00054

LOT ⇒ LGDP

Note: Significance level is 1%, GS means Granger Causality


91

From Table 2, we can see that for LGDP and LX, the probability is 0.41094 indicating that at significance level of 1%, 5% and 10%, the probability that LGDP is not LX’s granger causality is large, and we can not reject the original hypothesis. The probability of the second test is 0.00374, indicating that LX can be considered as LGDP’s granger causality at confidence level of 99%. By the same token, LGDP is not the granger causality of LGT, LPT and LOT, while at confidence level of 99%, LGT, LPT and LOT can be considered as the granger causality of LGDP. B. Conclusions and Reasons 1) Conclusions First, the stationarity test shows that all variables are second-order integration, and the cointegration analysis shows that there is cointegration relationship between Chinese economy and the total value of Chinese export, total value of general trade, value of processing trade, other trade. Second, the Granger test shows that, at the confidence level of 99%, the total value of Chinese export, total value of general trade, value of processing trade, other trade can obviously promote the Chinese economic growth. Third, equation (1)-(4) can be used for the basis of elastic analysis. They show that China’s economy would grow by 0.4613 percentage points while the Chinese total trade value increased by one percent, and China’s economy would grow by 0.4539 percentage points while the Chinese general trade value increased by one percent, and China’s economy would grow by 0.4948 percentage points while the Chinese processing trade value increased by one percent, and China’s economy would grow by 0.3376 percentage points while the other trade value increased by one percent. So, we can see that China’s processing trade plays a leading role in promoting economic growth, which is a Chinese current reality. Therefore, China’s export is largely a form of “quantitative” and “extensive”, which can not support the sustainable development of export. 2) Reasons Generally speaking, China's economy is export-oriented, except for 1993, China has maintained a trade surplus, and exports have accounted for more than 50% of the foreign trade. However, as China's sustained economic growth, the main drawbacks of the traditional "extensive" mode have increasingly shown a serious constraint on sustainable development of China's export trade. Raising the proportion of the general trade, changing export growth mode and realize the trade pattern transformation from the traditional "quantity" to "efficiency-type" are objective requirements of sustainable trade development and China's economic development. General trade refers to unilateral export trade operated by enterprises with operate right of import and export. The main objective of "Benefit-type" mode is not export volume, but to improve the efficiency, save energy, optimize trade structure, improve trade conditions and promote economic well-being. Based on the above empirical analysis we can find that under the same technological conditions, the processing trade has more contribution to GDP than that of general trade, about 0.04 percentage points higher. This confirms that the trade basis of China's economic growth is engaging in lower economic value-added processing industries based on the theory of comparative advantage in the. Clearly, this should not be sustainable development of China's exports in the long run. The reasons are as follows: First, the processing trade is easy to trigger trade frictions. China's import source and export destination of processing trade seriously dislocate. The import market of China's

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processing trade is mainly in Southeast Asian, and the export markets, mainly in the United States, Europe, Japan and Hong Kong. Such dislocation is very easy to form China’s trade surplus, and Europe and the United States’ trade deficit, but in the essence it is a false trade surplus, the actual exports and trade surplus is not so large. China’s huge false surplus has become United States’ major bargaining chip, and China is in a very passive position in the negotiations of China-US trade friction. Second, driving effects by the processing trade is less than general trade. A significant portion of China's processing trade is still in the stage of simple processing, and technical content is not high. The chain is short, and production and processing capacity concentrate in the downstream industries. The parts and raw materials rely heavily on import, especially high-tech key component. Local procurement ratio for materials and parts is low and it did not full play the role of stimulating development and export of domestic raw materials and spare parts industries. Many processing trade of foreign-invested enterprises neither use domestic raw material, nor exist demonstration effect and expansion effect for other enterprises, but only use preferential policies to set up processing bases. Some industries and projects are low-level redundant construction. The leading role of this processing trade on China's upstream industry is small, and value-added and value-added sectors of assembly processing are low. It is contrary to the sustainable development of export trade, because sustainable development of export trade requirements for balanced development in different sectors and regions. Third, we are unlikely to get the core technology from abroad through the processing trade, and only positive development of general trade is the fundamental way. Because South Korea, Taiwan, Singapore's development experience has taught us: When a developing country or region made use of global industrial chain upgrade of multinational corporations to get the core technology, the country or region can not be access to core technology through the processing trade. On the contrary, only through general trade exports, the country or region can get its own long-term development.

3 Policy Implication In order to achieve the sustainable development of export trade, the following aspects should be considered: First, development of export processing trade should adapt to the local conditions, in areas where conditions permit can develop deep export processing trade, improving products’ added value, enhancing export quality and efficiency, paying attention to environmental protection. After 20 years of reform and opening up the eastern coastal region has accumulated a certain amount of processing trade experience, the level of industrial base is comparatively high, capital is comparatively abundant. So in the future, we should speed up the upgrade of processing trade of the eastern region, from the traditional labor-intensive into high value-added, technology-oriented mode. As for the central and western regions, in the light of local conditions, make use of the comparative advantages, and take over the processing trade. We should be very careful not to take the old way of "pollution first, treatment later" in the process. Second, follow the development law of export trade. We want the rapid development of processing trade, but we can not one-sided pursuit of volume growth in trade. On the contrary, we should pay attention to the quality pursuit of trade growth. The development of


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general trade is superior to the processing trade not only in the contribution to the GDP but also in the industry correlation, added value, and for the control of environmental protection. Third, make use of strategic trade policies to establish support system of China's general trade export industry. During 1960s, the Japanese government has adopted a range of government measures of indirect subsidies to boost auto exports in order to development of the automobile industry's competitiveness in the international market, such as low-interest loans from government financial institutions, special discounts, tariffs reduction and exemption for the import of necessary equipment and tariffs priority arrangements for the import of the required technology. Under the joint action of the above measures, the Japanese auto industry began maturing after 1960s, and the volume of production and exports are on the rise. There is international trade theory basis when made use of export industrial policy to promote exports, and the theory is strategic trade policy theory whose core idea is that the government should effectively nurture and enhance the export capacity of domestic enterprises to expand its share in the international market, and to improve their welfare. Over the past decade the most prominent feature of the use of strategic trade policy on export industries support for major international trading power is the combination of trade policy and industrial policy, or the integration trade protection and industrial support in the other way, together constituting a policy as a whole. Fourth, establish and improve the promotion of information services function of general trade. It is an inevitable choice to provide financial resources to establish and improve information services functions for export for Chinese government to promote exports of under the new situation. With the globalization of information and social-oriented development, and widespread adoption of information technology in international trade, the information transmission is faster and faster which triggered structural business revolution in the world and made the international trade more depend on information resources. It’s a common choice for all countries to develop and extensively use international economic and information resources, enhance their competitiveness in the international market to promote the exports development. The globalization and information of the world economy required that we must pay more attention than ever to the important of information in international trade, and we must pay more attention than ever to development and utilization of all kinds of information resources.

References 1. Jaleel, A., Somchai, H.: Unit roots and cointegration in estimating causality between exports and economic growth: Empirical evidence from the ASEAN countries. Economics Letters 49, 329–334 (1995) 2. Ma, W.: Cointegration Theory and Application. Nankai University Press, Tianjin (2004) 3. Tao, Y.: The positive and negative effects of processing trade. Economic Aspect 5, 21–24 (2005) 4. Chen, H.: Meet the new round of global element configuration and the transfer of industries. Foreign Trade Practice 4, 59–67 (2005) 5. Zhang, X.: China’s processing trade challenges and responses. Economic Aspect 2, 4–8 (2004) 6. Feng, L.: Economic Globalization and China’s Trade Policy. Economic Management Publishing House, Beijing (2005)

The Game Analysis of the Reasons for Chinese Defeat in Iron Ore Negotiation ——Based on the Bargain Model Xianyong Zheng and Hanmin Huang School of Business Administration Zhongnan University of Economics and Law Wuhan, P.R. China [email protected]

Abstract. Chinese needs of ironstone have been increased sharply since the new century. China has been the biggest buyer in the demanding market since 2003. But it’s puzzling that, the status of biggest buyer hadn’t given China sufficient authority of ironstone pricing since China entered the ironstone negotiation. The reasons are worth pondering. This paper will combine the related theory of bargain model to analyze the mechanism of ironstone negotiation and then to identify some of the reasons of defeat. Keywords: negotiation of ironstone, bargain model, incomplete information.

1 Introduction Because of the quick of China’s economy and the rapid release of another new round of iron and steel production capacity, the needs of ironstone caused expanding sharply since 21st century. In 2003, China’s import of ironstone reached 1.4818 billion tons, surpassing Japan the first time and becoming the biggest ironstone import country. In 2008, China obtained the right to negotiate the starting price. But in contrast with this favorable situation, Chinese enterprises failed the negotiation again and again and fallen into a passive position. No matter how much ironstone was imported annually, China forced to receive the international price of ironstone higher than expected. As the below Table 1 shows, we can see that the international price of ironstone is gradually climbing between the year of 2003 to 2008. In 2009, beside a temporarily relative benefits of 36% decreasing of price from FMG corporation (on December 2nd, 2009, FMG declared to terminate the agreement abruptly and unilaterally), China had to reluctantly accept the facts and bought ironstone from the spot market because the three giants who dominate the ironstone supplying market, which include Vale do Rio Doce Australian Rio Tinto BHP Billiton Ltd, didn’t make a slightest concession for China’s requirement. All the truths above predict that the negotiation in 2010 will be harder. At the meantime we have to think about the following questions: what are the reasons for negotiations’ failure? What measures we should take to deal with these facts? In this paper, it will use bargain model to analyze the theory of ironstone negotiation and try to answer the two questions.

、

、


The Game Analysis of the Reasons for Chinese Defeat in Iron Ore Negotiation

95

Table 1. The Rising Range of the Prices of Ironstone Imported in China FROM 2003 TO 2009 Year

2003

Rising range（ %）

8.9

2004

2005

2006

2007

18.6

71.5

19

9.5

2008

2009

96.5

-32.95

Source: according to the related materials from the website of China Iron and Steel Association

2 The Game Analysis of the Reasons for China’s Failure in Negotiation of Ironstone A. Inpatient Bargain Model on Asymmetrical Conditions We suppose that in the bargain model, buyers and sellers negotiate for one price. The buyers (called B for short) are willing to buy the product at 300 Yuan at highest, while the seller (called S for short) can’t accept the price lower than 200 Yuan. Thus, only there is a positive difference between the highest and the lowest price of them, can the negotiation continue. In our model, we also suppose that these are known by the two sides. 300 Yuan, the highest price B is willing to pay, is the reserve price for B. And the lowest price of S is also the reserve price for S. The difference between the negotiation price and reserve price of each own is the benefit that B and S can receive. Obviously, the benefits’ range is from 0 to 100 Yuan. It’s easily to use a dynamic model to describe the price game between B and S. That is: B presents a bidding price and S has two options. If S receives the price the game is over. If S refuses and puts forward its own bidding price, the same is for B. Supposing the costs of the buyers’ delaying deal is more than the sellers’, then B will be eager for the deal and has “more impatience”. Again suppose that the delay will reduce 6% of B’s benefits from the deal and 3% of S’s. On this occasion, the buyers will be more anxious and inpatient than the sellers. We can say at this time the players have asymmetrical patience. In this situation, we suppose there are 100 times to ask price in turn between B and S. Backward concluding method can be applied. First, consider that the 100th time is for S to ask price and the most suitable bidding price is 300 Yuan. Then S can attain all of the 100 Yuan benefits because he knows that B will accept this price. Then the 99th price is put forward by B and the price will be 397 Yuan. S loses 3 Yuan (100×3%=3) because of the delay and B gets 3% of the benefits (That is to say B obtains a surplus of 3%). If these are back to the 98th time, we should take into account that B has to wait and costs 0.18 Yuan (3×6%=0.18), so the price of S will be 97 Yuan and S obtains last time plus a surplus of 0.18 Yuan. That is to say that the bidding price should be 297.18 Yuan. The backward continues like this. In accordance with the laws above we can use Microsoft Excel to calculate the results in the following Table 2. What we can see from table 2 is that the optimal initial bidding price of B should be 265.66 Yuan, from which he was entitled to 34.34 Yuan. S would accept the bidding price rather than unnecessarily delay for solutions. In the end, B and S spit the surplus in an approximately 1:2 ratio. It’s negative for the more inpatient buyer B. If the model doesn’t change other assumptions, we increase the round time from 100 to 150, the spit unfavorable for B still exists. Therefore, it’s not difficult to find that the predicted results in the inpatient bargain model under the asymmetric condition have something to do with the following factors: the comparison of cost between negotiators and the round times for bidding price. If the cost of

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X. Zheng and H. Huang

B is higher, B will be more inpatient than S and B will be in an unfavorable position. This can explain partly for China’s defeat in negotiations of ironstone. Chinese enterprises led by China’s Baosteel are always in a passive position. The reason is that they have no more patience and the delay cost is higher, which are totally in line with the bargain model under asymmetrical conditions. Table 2. The Optimal Bidding Price in 100 Times Round 100 99 98 97 96 … 5 4 3 2 1

The price bidder S B S B S … B S B S B

The surplus earning of S 100 97 97.18 94.26 94.60 … 65.60 67.66 65.63 67.69 65.66

The surplus earning of B 0 3 2.82 5.74 5.40 … 34.40 32.34 34.37 32.31 34.34

In particular, Chinese enterprises led by Baosteel of China are inpatient than the ironstone sellers for the following reasons: First, the concentration of the sellers is far higher than the buyers. Through continuous mergers and reorganizations, the ironstone reserves、 production capacity and capital scale increase dramatically. The three biggest ironstone suppliers have controlled over the amount of world’s more than 70% ironstone and kept up a reservation of more than 10 billion tons. On the premise of buyers’ rigid presenting, any seller will reasonably believe the other two sellers will not be easily to reduce the range of price increasing. The three ironstone giants always reach the degree of conspiracy in the negotiating process. As to the buyers represented by Baosteel in our country, the industry concentration is not high enough to form a unified voice. The longer the negotiation delays, the stronger the prediction of ironstones’ price being increased in domestic. In addition, some small and medium steel mills bid up the spot price regardless of the overall situation because of blind imports. The delays costs of negotiations are comparatively high. Second, the buyers are lack of strategic reserves. Although there are also a number of ironstone supply from China’s domestic mines annually, the quantity and quality are far to meet the demands of domestic steel mills in recent years. Then promotion of investment in mines is increasing, but the capacity has been largely in full load operation. Besides, the overseas mining resources controlled by our country are limited. Therefore, once the negotiation has impasse, China will face the stock-out situation of ironstone. B. The Bargaining Model under Incomplete Information According to the results of Fudenberg and Tirode's research, a bargaining model can be established as follows: Suppose there are a seller and a buyer. The utility evaluation of the items purchased by a buyer can be divided into two categories: low utility buyers---B100 and high utility buyers---B150, in which the probability of the buyer belonging to B100 is γ, and the probability that the buyer belongs to B150 is (1-γ). The process of the game is as

The Game Analysis of the Reasons for Chinese Defeat in Iron Ore Negotiation

97

follows: The seller bids first---P1, and if the buyer accepts, the game ends. If the buyer refuses, the seller re-bids---P2, and then the buyer decides whether to accept or not. Since in the incomplete information game at least one participant does not know other participants' payment function, therefore, under the conditions of the incomplete information, knowledge will be changed with the game carried on. The negotiations are likely to continue for more than one round under the equilibrium. The party which is lack of information may identify its type by observing the other party, which has the information, to see which program is accepted and which is abandoned. 1) The high possibility of the buyers is low utility type At this point, we assume that γ is 0.5, and the discount factor δ is 0.9. In the first round, the B100 type of buyers will accept this price in the condition of P1 P(B100)l=100; the B150 type of buyers accepts at Pl P(B150)1=105. In the second round, the B100 type of buyers accepts in the condition of P2 P(B100)2=100; the B150 type of buyers will accept at P2 P(B150)2=150. At this time, the equilibrium outcome is P1=100 and the buyers accept. This equilibrium is the perfect Bayesian equilibrium.

≤

≤

≤

≤

2) The low possibility of buyers is low utility type. Now we assume that γ is 0.05, and the discount factor (δ) remains at 0.9. In the first round of P1=150, the B100 type of buyers will accept this price ifP1 0,U ′ > 0 ,the denominators of formula (7) and formula (9) are greater than zero. Sufficiency: because +∞

+∞

∫ U ′( E + σZ )Zf (Z ;0,1)dZ = ∫ U ′( E + σZ )Zf (Z ;0,1)dZ

−∞

0

0

∫ U ′( E + σZ ) Zf ( Z ;0,1) dZ

+

(10)

−∞

and +∞

0

∫ U ′( E + σZ )Zf ( Z ;0,1)dZ = − ∫ U ′( E − σZ )Zf (Z ;0,1)dZ

−∞

(11)

0

So, +∞

∫ U ′( E + σZ )Zf ( Z ;0,1)dZ

−∞

+∞

= ∫ [U ′( E + σZ ) − U ′( E − σZ )]Zf ( Z ;0,1)dZ

(12)

0

In addition, for U ′′ and U ′( E + σZ ) − U ′( E − σZ ) have the same symbol, we can judge the symbols of numerator in the formula (7) and formula (9) by U ′′ . It is shown in Table 1. Table 1. The relation between U ′′ and formula (7) and (9)

U ′′

Numerator of (7)

(7)

Numerator of (9)

(9)

Risk aversion

0

>0

0

0

0

>0

Risk neutral

=a

=0

=0

=0

Risk preference

>0

>0

)

= ∑t ω k b (j k ) j =1

(2)

C. AHP（ Analytic Hierarchy Process） Analytic hierarchy process (AHP) is a structured technique for dealing with complex decisions. Rather than prescribing a "correct" decision, the AHP helps the decision makers find the one that best suits their needs and their understanding of the problem. Based on mathematics and psychology, it was developed by Thomas L. Saaty in the 1970s and has been extensively studied and refined since then. The AHP provides a comprehensive and rational framework for structuring a decision problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. It is used around the world in a wide variety of decision situations, in fields such as government, business, industry, healthcare, and education. The calculation steps are as follow: 1) Formation of judgment matrix Above all, compare the importance among all the indexes under the same higher level index to reduce the influence of subjective factors, And then the judgment matrix is formatted. For example, the judgment matrix of Bj (j=1, 2,… ,m) under index A is a mdimensional matrix that shows in table I. bij means the importance degree of Bi relative to Bj in table I. The importance degree generally uses the scale of 1-9 advanced by Saaty. Table 1. The of general form judgment matrix A B1 B2 … Bm

B1 b11 B21 … Bm1

B2 b12 B22 … bm2

… … … … …

Bm b1m B2m … bmm

Social Benefits Evaluation of Reverse Logistics

291

2) Calculation of ranking value The ranking value methods include power method, sum product method and square root method. The article uses the square root method to calculate ranking value. a) Calculating the product of each line in judgment matrix: M i = bi1 × bi 2 × " × bin (i, j)=1, 2， …， n

(3)

b) Calculating the n-th root of Mi: Wi Wi = n M i

(4)

c) Generalization of the root vector: n

W i = Wi / ∑ W i i =1

(5)

d) Calculating the largest eigenvalue of the judgment matrix: λmax n

λ max = ∑ [( AW ) i / nWi ] i =1

(6)

(AW)i is the i-th element of vector AW in formula (6). 3) Consistency check Consistency check is usually applied to every judgment matrix so as to ensure the obtained weight reasonable enough. CR =

λ max − n ( n − 1) RI

< 0.1

(7)

RI means the average random consistency index in formula (7).

4 Case Study An automobile company recalled 1182 Pentium cars, which were produced from March 5, 2009 to March 30, 2009. The reason of expanded recall lies in: the general contracting suppliers of skylight glasses have not established product traceability management system, which affected the determination of the automobile recall scope. The skylight glasses of recalled automobiles would have cracking rubber and then cause abscission, which would lead to potential safety hazard. Chongqing Chang'an Ford Mazda Automobile company and FAW Car company provide free inspection to those automobiles in expanded recalled range to eliminate hidden dangers. 13 experts respectively evaluate the social impact of the recall. The evaluation matrix shows in table 2. Let the triangular fuzzy numbers of the positive ideal indexes H11-H14, H22, H31H33, H42, H43 be： Low: (0.1, 0.2, 0.3); Lower: (0.3, 0.4, 0.5); General :( 0.4, 0.5, 0.6);

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J. Chengcheng and L. Congdong

High： (0.5, 0.6, 0.7); Higher ： (0.6, 0.7, 0.8); Very higher ： (0.7, 0.8, 0.9). Let the triangular fuzzy numbers of the negative ideal indexes H21, H23, H41 be： Higher: (0.1, 0.2, 0.3); High (0.3, 0.4, 0.5); General (0.4, 0.5, 0.6); Low (0.5, 0.6, 0.7); Lower (0.6, 0.7, 0.8); Very lower (0.7, 0.8, 0.9). First step: the experts evaluate the three levels index system and put the result into the software of YAAHP. The calculation result shows in table 3-7. Table 2. Evaluation matrix given by decision-makers Expert 1 2 3 general higher general 1

4 Very high lower high higher high 2 lower higher general Very 3 high Expert 8 9 10 11 high general lower lower 1 high higher general general 2 3

high

general

low

5 lower

6 high

7 general

general high higher lower higher General 12 lower low

13 lower low

lower general general

Table 3. Secondary level index weights H

H1

H2

H3

H4

Wi

H1

1

3

5

5

0.3886

H2

1/3

1

3

3

0.2605

H3

1/5

1/3

1

3

0.1930

H4

1/5

1/3

1/3

1

0.1580

CR=0.0075 0, it means that the impact is complementary; ρ < 0, indicates that there is a mutual competition. In 2007 SLM model in this article, ρ = 0.152 (it passes the 10% level of significance test), which shows that there is a mutually reinforcing relationship between regions. There is mutual promotion

Information Technology and Economic Growth

311

relationship between China's provinces but the role of network effects is not obvious which means that the development of IT around neighbors does significantly promote the provinces own IT development.

4 Conclusions In order to study the characteristics of the relationship between economic growth and IT development of China’s provinces, this paper uses the methods of exploratory spatial data analysis to investigate the spatial distribution and interaction pattern of the economic growth and IT development in 31 provinces based on the data of 1997 – 2007’s. Based on it, we also constructed the spatial econometric model to explain the relationship between these two factors and proposed conclusions and directions as follows. (1) There is significant characteristic of spatial concentration in the economic growth and IT development of China's provinces. It indicates that economic growth and IT development in China’s different provinces maintains a serious and sustained non-equilibrium situation, which is corresponding to the imbalance of China's region economic growth. In China IT and economic growth in eastern and western provinces have obvious and contrasting characteristics of spatial concentration. The eastern provinces are clusters of high level of IT development while most of the western provinces are concentrated by a low level. Sichuan is a growth pole for the economy growth and IT development in western areas, and should be given focus and policy support to promote its lead effect in the west. The central region is still in a equilibrium stage of development of lower level without significant difference. In addition, most of the province and its neighbors have relatively spatial stability, the structure of the detected spatial concentration of power during the entire period does not show evidence that IT development has a strong path dependence. (2) Geographical space is the basic carrier of economic growth. The spatial econometric model shows the mechanisms and effects of IT development and regional economic growth, which makes the model have more explanatory power. In the traditional models without considering the spatial interaction, IT development role in promoting regional economic growth is usually overestimated. In this model, IT has significantly positive effect in promoting regional economic growth and regional aggregation, but still, capital is the main engine of economic growth. There is an apparent spillover effects on economic growth remains among the provinces. But it also demonstrated that IT development plays a limited role in promoting China's economic growth and the network effects of IT are still not obvious. One of the most important issues must be how to promote IT development and its network effects. (3)This study is only an exploration of the impact of IT and its network effects on economic growth. There are still many issues to be discussed in depth later. For example, IT, communications systems and socio-economic effects should be considered together and make an empirical research on communication network’s (including the postal network, telephone network and the Internet) impact on economic development. IT penetration in economy and society and its diffusion effects should be further studied. Moreover, apart sectional panel data, using panel data with spatial effect to make econometric model is also a important content of our following study.

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References 1. Anselin, L.: Spatial Econometrics: Methods and Models. Kluwer Academic, Dordrecht (1988) 2. Anselin, L.: Local Indicators of Spatial Association-LISA. Geographical Analysis 27(2), 93–115 (1995) 3. Anselin, L., Florax, R.: Small Sample Properties of Tests for Spatial Dependence in Regression Models. In: L. New Directions in Spatial Econometrics, pp. 21–74. Springer, Heidelberg (1995) 4. Brynjolfsso, E.: The Productivity Paradox of Information Technology. Communication of the ACM 36(12), 67–77 (1993) 5. Cron, W.L., Sobol, M.G.: The Relationship between Computerization and Performance: A Strategy for Maximizing the Economic Benefits of Computerization. Journal of Information and Management 6, 171–181 (1983) 6. Goetzke, F.: Network Effects in Public Transit Use: Evidence from a Spatially Autoregressive Mode Choice Model for New York. Urban Studies 45(2), 407–417 (2008) 7. Loveman, G.W.: An Assessment of the Productivity Impact of Information Technology. Mit Management in the 1990s Working Thesis 88-054 (1990s) 8. Oliner, S., Sichel, D.: Computers and Output Growth Revisited: How Big is the Puzzle? Brookings Thesiss On Economic Activity: Macroeconomics 2, 254–285 (1994) 9. Oliner, S.D., Sichel, D.E.: The Resurgence of Growth in the Late 1990s: Is Information Technology the Story? Journal of Economic Perspectives 14, 3–22 (2000) 10. Solow, R.M.: We’d Better Watch Out. New York Times Book Review 7, 12–36 (1987) 11. Wen, M.: E-commerce, productivity, and fluctuation. Journal of Economic Behavior and Organization 55, 187–206 (2004) 12. Wu, Y.: Spatial Analysis on China’s Economic Growth and Income Disparities, vol. 8. Economic Science Press (2005) 13. Zheng, Y., Zhong, C.: An Analysis about the Mechanism of Influence of Information Network on Regional Economic Development. Quantitative & Technical Economics 12, 85–88 (2002) 14. Zhong, G., Wang, F., Xing, X.: Information Technology, Economy Growth and Labor Productivity Growth. Journal of Industrial Engineering and Engineering Management 4, 13–18 (2005)

The Practice Teaching Model of Accounting Research Zhou Xiaona, Zhao Rui, Mao Jiuzhi, and Zhang Yin Hebei Normal University of Science & Technology Qinghuangdao, China [email protected]

Abstract. As social and economic development, particularly in the 21st century, the comprehensive ability is paid more attention for accounting professionals in the market, thus the practice teaching of accounting are also increasingly important. In this paper, all aspects of accounting practice teaching are researched, better teaching methods of accounting are considered. Keywords: practice teaching of accounting, practice teaching system of accounting, elements of the practice teaching system of accounting.

1 The Necessity of Constructing Practice Teaching System of Accounting A. The Practical Aspect With the integration of social and economic development, the environment of accounting profession has changed deeply. Not only a simple accounting operation and the provision of accounting information are needed, but also the availabilities of financial analysis, general management, resourcefulness, solving practical problems are needed for accounting people in the market. Accounting people both have profound theoretical knowledge and strong practical abilities could meet the market demand to promote economic development and make their contributions for the country. Traditional teaching model for cultivating talents have many defects, and it has profound practical significance to build a practice teaching system of accounting for training compound talents to meet the market demand. B. The Theoretical Aspect Accounting is a discipline of close combination of theory and practice, but also a theoretical system which is needed to reform and improve with the development of social economy. Practice teaching of accounting is not just a simple complement and extend to its theory, but also play an active role in promoting theoretical system of accounting. Constructing Practice Teaching System of Accounting is further reform and improvement for the theoretical system of accounting, and promotes the study of accounting theory in our country. Practice is the sole criterion for testing truth, theory achieves a qualitative leap by practice. New theory and method of accounting can be verified through practice and the original hypothesis can be improved and amended according to the results of accounting practice, so as to promote innovation and development of accounting logic. Currently, accounting theory and methods is studied M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 313–319, 2011. © Springer-Verlag Berlin Heidelberg 2011

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a lot, but the theory of accounting teaching methods is studied seldom. To build practice teaching system of accounting is great significance for improving and developing accounting theory systems, speeding up the process of accounting reform.

2 The Composition of the Practice Teaching System of Accounting Practice Teaching System of Accounting is a framework which is formed by elements of the structure with a scientific system approach. The practice teaching system of accounting includes the objective of practice teaching of accounting, the content of practice teaching of accounting, teaching the management of practice teaching of accounting, the teaching conditions of practice teaching of accounting and the teaching platform of practice teaching of accounting. practice teaching system of accounting as shown in Figure 1.

Fig. 1. The practice teaching system of accounting

The following is the objectives of practice teaching of accounting: students not only study theoretical knowledge of the accounting profession, but also have accounting skills ; Students not only have ethical, but also have the professional ability to judge; Students not only have the ability to collect right messages solve problem , but also have the ability to communicate and cooperate; Students not only learn innovation, but also have the ability to continuously self-improvement, and ultimately improve their practical ability and competence to practice. The goal of practice teaching of accounting is to establish a precise content of practice teaching of accounting, teaching management, and teaching conditions and other factors based on content.

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The content of practice teaching of accounting is the content of practical teaching courses in various specific set in order to achieving teaching objectives of accounting practice, including accounting experiment about accounting theory, relevant case studies, research training, graduation design and social attachments. The content of practice teaching of accounting is the core of the practice teaching system of accounting, is the external expression of the objective of the practice teaching of accounting. The management of practice teaching of accounting is a management agency which is established to achieve the goals of practice teaching of accounting, which develops the management system and evaluation about the people, equipment and facilities, laboratories, practice base. It smoothes the basis for the work of practice teaching and protects the outcome of practice teaching. The condition of practice teaching of accounting is related hardware to achieve the objective of the practice teaching of accounting, including teaching faculty about accounting practice, teaching materials, simulation equipment and facilities about accounting and so on. It play a supporting role, is the important factor to impact the practice teaching of accounting.

3 Problems of Practice Teaching of Accounting Sound practice teaching system of accounting is the prerequisite for the effect of accounting practice teaching. There are still some problems about our current practice teaching system of accounting in some areas, which result to the effect of practice teaching accounting is difficult to achieve well. These problems should not show in the following areas: A. The Content about Practice Teaching of Accounting Is Not Quite Reasonable First, the content about practice teaching of accounting is not comprehensive. The accounting profession teaching tends to focus only on the content of practice teaching of accounting, such as the practice of theory courses, the school test and a social practice and ignores a series of professional financial personnel necessary practice habits and work ethics such as honesty, integrity and self-discipline, objective and fair and so on in the process of practice teaching of accounting. Second, the content of practice teaching of accounting is unreasonable. We pursuits excessive standardization and unification in the process of teaching, in order to the accounting practices of teaching content is too simple and idealistic, which is very different with knowledge used in practice business, causing students don't have excellent career ability of judgment and practice. Third, the practice teaching of accounting lacks rich, forward-looking, hierarchical, and focused content. In the process of teaching, test data can not effectively enable students to master a single operational picture of the economy and the content is old that can't follow the social and economic development, related policy, so that students are learning out-of-date knowledge. In accounting practice, each joint has its specific purpose, but information on accounting practice is basically the same, lack of hierarchy and targeted.

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B. The Staff Can Not Meet the Requirement of Practice Teaching of Accounting Teachers are the most important practitioners in teaching, teachers almost determine the level of students. The plan of practice teaching, the outline of the development, teaching materials and many other details need teachers' rich practical experience and ability to judge accurately in practice teaching of accounting model. At present, many teachers in the educational system is both the theory and practice of testing teachers, but mostly these teachers directly go to the education career after graduating from college, they don't have participated in the work of the accounting practice. Many of these teachers are lack of accounting skills and experience in practical operation, don't have rich guidance and simulation knowledge of accounting, do not play the guiding role of the accounting test. In addition, many colleges and universities have not conducted continuing education for teachers training and assessment teaching management plan because of the time, funding and other issues, which makes a lot of teachers to be disconnected of theory and practice. Because teachers are lack of accounting practice, that makes the accounting practice teaching lack of knowledge of replicability, the instance cited, even divorced from theory and practice, which seriously affects the quality of teaching of accounting practice. C. The Construction of Accounting Experiment Is Not Quite Reasonable Professional accounting experimental facilities and effective management is critical to promote the combination of theory and practice, to train ability of practical operation, to enhance students' Career awareness, which ensure the effectiveness of practice teaching of accounting. Currently, many schools have related accounting labs, but also show some outstanding issues. On the one hand, many schools focus only on the expense of the hardware and ignore software development in the accounting lab construction. They don't know how to build, what kind of standards, how to play the issue of teaching function. On the other hand, many schools are lack of effective accounting laboratory management system, they are not clear to how to make it an effective laboratory teaching function, which is a barrier to practice teaching in a certain extent. D. The Practice Teaching Platform of Accounting Is Not Good Deeply accounting practice of students in the real business is a very important part in teaching. In this session, students can experience the true accounting of the specific details, and get some work experience, improve job skills, integrate theory and practice closely and schools can learn specific requirements to accounting students from business. However, many schools now have little self-built base for professional practice, school-enterprise cooperation and relatively practice base, can't give students effective practice guidance and management. Currently, the students can practice jobs recommended by the school internships few, many practice jobs are linked by themselves. In this way, on the one hand, the contact does not necessarily correspond to the students, they may only do free jobs in the unit without a professional internship opportunities, and even worked on site, walked around a formality; On the other hand, the contact which is linked by students may not necessarily a formal business unit, students may be cheated. In short, the accounting practice of teaching and learning platform is not good which greatly influences the effect of the accounting practice teaching.


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4 Related Measures to Improve the Practice Teaching of Accounting A. Rationally Designing Practical Teaching of Accounting First of all, we should enrich the content of the practice teaching of accounting. Teachers should not only explain professional ethics to accounting students, but also make the accounting professional ethics and professional practices throughout every aspect of accounting practice teaching. At the same time, a good moral environment should be built in which students can build a good moral value from the life and values. Second, we should rationally organize content about practice teaching of accounting. In practice teaching of accounting, we should minimize simple and uniform assumptions about practice teaching content, increase true content, leave students more space of learning, thinking and using knowledge, so that initiative and independence of students could be increased overall. Third, we should continuously improve the content of practice teaching of accounting. In order that students can fully grasp the accounting processes and systems operation, the content of practice teaching should involve industrial enterprises, commercial enterprises, public institutions and other comprehensive teaching materials. The content and forms of practice teaching of accounting should be improved with the economic development and the business needs, so that the knowledge that students learned is more practical and useful. In addition, the quality and quantity of practice teaching of accounting should be improved in all aspects. We should prepare and select practical information according characteristics of this session and accounting knowledge, and continuously strengthen all aspects of relevance content of practice teaching. B. Strengthening "double" Teachers Training Only by improving accounting practice teaching faculty level, we can ensure the teaching quality of the accounting practice teaching model. Accounting Practice requires "double" teachers not only understand the accounting theory, but also have the skilled operators, guide and organize students to implement accounting practices. Therefore, educational institutions should adopt scientific and necessary measures to improve the professional quality of teachers, optimize the structure of teachers. First, the level of accounting practice teaching faculty can be improved by regular training in accounting, accounting practice symposium, observing practice teaching accounting lectures, etc. Second, schools can take "go and come in" approach which can make school and community closer together, and increase opportunities for teachers to learn and share experience, so that can improve teachers' professional quality of education. At the same time, effective incentive system should be established in the school. The teachers' ability of practice teaching should be as one of the indicator to evaluate teachers. We should enhance teachers' active learning and sense of self-improvement by incentives, that can improve teaching quality of accounting practice.

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C. Paying More Attention to Build Accounting Laboratory, Strengthening Laboratory Management 1) We should pay more attention to build simulation laboratory to provide a good accounting practice teaching environment to students, which can greatly promote the improvement of teaching quality of accounting practice. We should consider simulation, hardware, software and the experimental data to build the laboratory. We should provide real accounting work conditions and working environment to students from the laboratory layout, equipment, tools and other details so that students can have a certain sensibility know about their future work. We should important investment in hardware, such as the large accounting laboratory equipment, computers, projection equipment and other facilities in accounting simulation lab, so that can provide a solid material foundation. At the same time, we should important software building, provide students with wealth accounting information and learning software, become the accounting laboratory to be the second class of students. 2) Enhancing the effective management of the accounting lab, playing full use of the accounting lab and teaching functions a) Open management to accounting lab. We should create conditions for the full use of the accounting lab. Students can use accounting laboratory to review and practice according experimental subject after school hours. Through open management, we should fully mobilize the enthusiasm of students and cultivate the abilities of students, identify problems, think, analyze and solve problems. b) effective management to equipments of the accounting laboratory. We could create the file to record the use of equipment such as using time, returning time, maintenance, updates, etc. D. Strengthening Cooperation with Enterprises, Making a "dual" of Teaching In the educational system of accounting practice , the platform of accounting practice teaching plays an irreplaceable role as the base of training students' practical ability. At present the separation of school and enterprise is not conducive to the quality of students training, we should develop school-enterprise cooperation or cooperation projects in schools and enterprises to strengthen the cooperation of schools and social enterprise education. Colleges, enterprises and educational model shown in Figure 2: School-enterprise education is the business that school and the community together participate the process of personnel training, combine classroom teaching and practical work to cultivate students that meet the social needs. In the schoolenterprise education, we develop a "dual" of teaching mode, the "dual" refers to the school and external training base. In the "dual" of teaching model, students must first study the theoretical knowledge and simple accounting experiments of accounting profession in the school. After finished learning knowledge in expertise, student enter into the enterprise for professional and practical training, So that students can have perceptual awareness to the actual work of accounting, find and correct defects of their knowledge and ability in the practice. This school-enterprise education makes great contribution to cultivate compound, applied accounting personnel that meet the social needs, and ensures the quality of teaching practice of accounting.


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Fig. 2. The key point of school and enterprise training mode

References 1. Yu, Y.: Accounting experimental study. Economic Science Press (2004) 2. Shi, H.: Information perspective of accounting practice teaching system research and study. China’s Management of Information 14 (2008) 3. Yan, D.: Reform of accounting series courses for the 21st Century teaching research. Economic Science Press, Beijing (2000) 4. Sun, S., Zhang, Z.: Establishment of the accounting practice teaching system. Information Development and Economy 30 (2007) 5. Yao, J.: Elements and development of the accounting practice teaching system. The Meet of Friends 3 (2009) 6. Qu, H.: Enhance the Quality of Internal Control and Management of Teaching Practice and Exploration. China’s Vocational and Technical Education 25 (2007) 7. Zhen, C.: Construction and Implementation of Practical Teaching System Whose Aim Is to Cultivate Innovation Capacity. China’s Higher Education Research 4 (2007) 8. Hu, X.-J., Ma, S.: Analysis and Thinking on the Policy Environment of Our Vocational Education Development. Vocational Education Forum 12 (2006) 9. Zhou, J.: Speech at the Video Conference of Building Program on National Vocational Institutions Model in 2006 (2006) 10. Xiong, S.: To Improve the Teaching Quality of Accounting Practice. Accounting Communications (Social Sciences) 12 (2005) 11. Qin, S.: Teaching Standard of Accounting Practice in the University. Accounting 4 (2006) 12. Fan, Q.: Study on Teaching System of Accounting Practice. Information Development and Economy 30 (2007) 13. Mok, Y.: The Key to Reconstruction of Teaching Quality Control System Combing with Engineering. Education and Occupation 2 (2007) 14. Hu, J., Guan, P.: Optimizing Post Practice Mechanism to Train Professional Quality of students

Research about Broadband Media Distribution Protocol on Media Stream System Jiang Guo-song1 and He Xiao-ling2 1 School of Computer Science and Technology, Huanggang Normal University, Huanggang 438000, China 2 School of Journalism and Communication, Huanggang Normal University, Huanggang 438000, China [email protected]

Abstract. The BMDP is implemented with several modules in the system, Media Stations forms a content distribution hierarchy, Layer 7 protocol for media distribution and roaming, Content are classified with different availability class based on its popularity, Segments of live contents are cached on every Media Station, Each segment is stored in at least two different nodes for redundancy, Contents are duplicated to a node on demand based on an intelligent caching algorithm. Keywords: BDMP, MLR, CM, MAM.

1 Introduction Media Switch[1] system consists of a number of geographically distributed subsystems covering a number of large metropolitan areas or a country. In such a large-scale system, content distribution management is a vital component for effectively managing and distributing the contents[2][3], as well as reducing the operational costs. In Media Switch, the content distribution and tracking are controlled using the Broadband Media Distribution Protocol (BMDP)[4][5][6]. BMDP is implemented with several modules in the system, namely, Media Location Register (MLR[7]) running in the data centers, and MLR agent running on each Media Station. Other modules such as Media Asset Management (MAM[8]) and Content Manager (CM) are also involved in the protocol. Figure 1 shows the physical distribution of the system. It is assumed that the system covers multiple cities. By “city” we mean a metropolitan area network (MAN). All cities have similar configurations except that only one city, the head-quarter, has the MAM module. That is, all new contents are introduced from the head quarter. In the future version, new contents can be introduced into the system from multiple cities. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 320–327, 2011. © Springer-Verlag Berlin Heidelberg 2011

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It is MAM’s task to decide when and where to distribute a program, and MLR’s task to distribute the data, and CM’s (Content Manager) task to publish the program at specified time. City 1 (Headquarter)

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Fig. 1. Media Switch subsystem distribution

Each subscriber has a fixed Media Station to serve its streaming request. Logically, the content distribution system is a hierarchical system as shown in Figure 2. Header Quarter DC

City 1 DC

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Fig. 2. Hierarchical content distribution

The distribution system is partitioned into two parts, the inter-city distribution, and the intra-city or Metropolitan Area Network (MAN) distribution.

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2 Content Distribution A. Inter-city Content Distribution It is assumed that inter-city network connections have limited bandwidth, and have little or no QoS guarantee. Therefore, the content distribution between the cities will be for VOD only prior to the publishing time in a planned manner. There can be ondemand content copy/movement between cities, but it will not be real-time. That is, the operation can be on a best-effort basis. B. Content Distribution within a MAN For MAN distribution, the media stations are logically viewed as a tree, with the Home Media Station as the root. The tree structure reflects the underline network topology, but not necessarily the same. The media stations directly under the Home Media Station are typically connected to the routers at the top-level network trunk of the MAN. The lower level media stations are typically in a network branch that is one or more level below from the main backbone as shown in Figure 2. The hierarchy is used for data distribution policy, not for data flow. Any Media Station can get data from any other Media Stations, including Home Media Station, directly without going through a third Media Station. Data is distributed using two different but related methods: push contents according to the level of the media stations, and pull contents on-demand as in a cache system.

Fig. 3. The Duo Hierachies

C. Content Distribution Based on Due Hierarchy With BMDP, the Media Stations are organized as groups. For example, Figure 3 is a segment of a MAN, in which a group would consist of all the Media Stations that reside on a ring or branch. Each group would have a group leader. The groups form a hierarchy that goes from data center to the major ring, from the major ring to minor rings and branches. This hierarchy is called station topology hierarchy. Logically they form the tree structure as shown in Figure 2, and the root of a substree is the group leader.


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Each station is also assigned a subscriber coverage level. The MLR maintains the number of local subscribers for each station. By aggregating the subscriber numbers from the bottom up in the station topology hierarchy, the subscriber coverage number can be calculated for each station in the network. Using the subscriber coverage number, the stations can be classified into different coverage levels with the lowest level being the station with the lowest subscriber coverage and the highest level being the Home Media Station. Stations with different subscriber concentration level form a subscriber concentration hierarchy. This hierarchy is overlaid on top of the station topology hierarchy. D. Content Distribution A content distribution policy can specify either the Media Station topology level, or the Coverage, or both. Contents are distributed from the central site to the Media Stations using these two hierarchies. Each piece of content is assigned to an availability class. The availability classification determines whether the first segment or the full copy of the content will be placed on all Media Stations in the network or just some Media Stations that are higher up in the subscriber concentration hierarchy. A hot content that needs to be instantly available to subscribers will be placed in all Media Stations with its full copy. This is the highest availability class. The second availability class would place only the first copy on the lowest level Media Stations in the subscriber concentration hierarchy and its full copy on the second level Media Stations in the subscriber concentration hierarchy. The third availability class would place the first segment on the second level stations from the bottom and the full copy on the third level stations from the bottom so on and so force. Content with lowest level availability are only stored in the central site. E. Caching A media program or its segments can be copied to a Media Station on-demand. This can happen when a subscriber under the Media Station requests a program but the Media Station does not have the program, or not have the entire program. When a program copy is needed, the MLR agent running on the Media Station will find one or more Media Stations that have the segments of the program. The segments can be copied from one source or several sources. The decisions are made according to distance of the source, bandwidth availability, and other parameters. Generally speaking, the source Media Stations should be in the same topology group as the requesting Media Station to avoid traffic on network trunk of higher topology level. Furthermore, all deletion operations need to get approval from the group leader. A group leader can either approve the deletion, or ask the requesting Media Station to copy the program to another Media Station. The group leader makes decision based on either the distribution policy or a group-wide LRU. If the distribution policy indicate that the group should keep at least one copy of the program, and the copy to be deleted is the last copy, the group leader will direct the Media Station to copy the program to another Media Station, which is often the group leader itself. If the distribution policy does not require the group has a copy, a group-wide LRU is used. If the program is the least recently used program of the group or close to be the least

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recently used program, it is deleted. Otherwise, the least recently used program is deleted, and the program is copied over to the space just made available. F. Media Location Registry (MLR) MLR is the module in which all the content distribution “intelligence” is implemented. MLR maintains a network topology database, a content location database, and a content distribution session database, among other information. The network topology database describes the topology of the Media Stations and the network topology among them. As its name implies, the content location database fully describes the location information of every single piece of content in the system. Content Location Register performs fast look up of the content location information for the Media Director’s in the system. Content is copied from one location to another by creating content distribution sessions between two Media Engines in the two locations. These sessions are created and deleted in the Content Distribution Session Database as it happens. This information is used by the MLR to keep track of the bandwidth usage among the Media Stations and the central site. The network bandwidth is a limited resource in the network. The network is configured to allow certain amount of assured media traffic on each of its internal links. MLR needs to ensure the usage of the bandwidth in the network does not exceed the assured traffic amount at all network segments at all times. G. Dynamic Content Redistribution At each station, content visitation statistics are kept for each piece of content. These statistics are aggregated through the subscriber concentration hierarchy. Based on these statistics, a content’s availability classification can be adjusted. This would result in a redistribution of the content to reflect the actual using pattern of the content. By the same token, a hot content in one geographical/topological areas can be redeployed network wide to cope with an unexpected surge in demand for the content.

3 Protocol Illustration A. Distributing a New Program A new program is loaded and distributed in steps given in Figure 4. MAM 5. Distribution parameter

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B. Push a Media Program Figure 5 shows the sequence of actions taken place when MLR initiates the operation to push a media program to from one Media Station to another. MLR can plan to the push sequence from Media Station to Media Station so the push operation can be done in shortest time to all Media Stations. For example, it can follow the tree structure shown in Figure 2 by asking all Media Stations at the top level to get the segments from Home Media Station, and then ask next level Media Stations to get from their group leaders.

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Fig. 5. Pushing a media program to a top level media station

C. Partial Content Distribution The thought of the scheme is to classify both media interest for media content and subscriber capacity level for media stations. Under the fulfillment of these two preconditions we can work out the best location a media program should be distributed to. Since the media distribution is actually based on a group of segments, we always treat segments as distributed data units for the scheme. D. Get a Program/Segment On-Demand The message sequence shown in Figure 6 are for a Media Station to get a program or segments from another Media Station on-demand by a subscriber.

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Fig. 6. Media Station gets a program on-demand

E. Move or Delete a Program by Request of MLR The message BMDP_MLR_DEL_PROG can be sent from headquarter MLR to an MLR in a city to cause the program being delete from all Media Stations in the city.

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BMDP_COPY_SEG BMDP_SEND_SEG BMDP_COPY_SEG_DONE BMDP_ADD_SEG_LOC BMDP_MOVE_PROG_DONE Interal deletion msg

Fig. 7. Delete or move a program by MLR

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Fig. 8. Deleting a program

F. Delete a Program by Request of Hosting Media Station This is the sequence of message that started by a Media Station requesting deletion of a program from its storage. It is most likely caused by a clean up operation on the Media Station that is trying to reclaim storage spaces by applying LRU algorithm.

4 Conclusions Media Stations forms a content distribution hierarchy, Layer 7 protocol for media distribution and roaming, Content are classified with different availability class based on its popularity, Segments of live contents are cached on every Media Station, Each segment is stored at at least two different nodes for redundancy, Contents are duplicated to a node on demand based on an intelligent caching algorithm.

References 1. Ofek, Y.: Ultra scalable optoelectronic switching fabric for streaming media over IP. In: Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, pp. 245–252 (2005)


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2. Yoshida, M., Ohzahata, S., Nakao, A., Kawashima, K.: Controlling File Distribution in the Share Network Through Content Poisoning. In: Proceedings of 2010 24th IEEE International Conference on Advanced Information Networking and Applications, pp. 1004–1011 (2010) 3. Liao, K., Xin, Z., Cao, J.: A Novel Design of Internet Digital Content Distribution Platform. In: Proceedings of 2010 Second International Conference on MultiMedia and Information Technology, pp. 25–30 (2010) 4. Luling, R.: Managing Large Scale Broadband Multimedia Services on Distributed Media Servers. In: Proceedings of 1999 IEEE International Conference on Multimedia Computing and Systems (ICMCS 1999), vol. 1, p. 9320 (1999) 5. Lu, J.: An Architecture for Delivering Broadband Video over the Internet. In: Proceedings of International Conference on Information Technology: Coding and Computing, p. 0542 (2002) 6. Chiu, R.-F., Yeh, Y.-S., Chi, S., Lee, R., Wu, A., Chang, H.-J., Chang, L.: Kaohsiung County Broadband Mobile Network. In: Proceedings of 2009 10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, pp. 36–41 (2009) 7. Corbal, J., Espasa, R., Valero, M.: Three-Dimensional Memory Vectorization for High Bandwidth Media Memory Systems. In: Proceedings of 35th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2002), p. 149 (2002) 8. Body, M., Cousin, B.: Efficient Media Asset Transfer in a Unified Framework Managing Broadcasting Systems. In: Proceedings of First International Conference on Distributed Frameworks for Multimedia Applications (DFMA 2005), pp. 121–127 (2005)

Research about Media Location Registry and Content Distribution Base on MSA Jiang Guo-song1 and He Xiao-ling2 1

School of Computer Science and Technology, Huanggang Normal University, Huanggang 438000, China 2 School of Journalism and Communication, Huanggang Normal University, Huanggang 438000, China [email protected] Abstract. The Content Location Register performs fast look up of the content location information for the Media Director’s in the system. Content is copied from one location to another by creating content distribution sessions between two Media Engines in the two locations. These sessions are created and deleted in the Content Distribution Session Database as it happens. At each station, content visitation statistics are kept for each piece of content. Based on these statistics, the content’s availability classification can be adjusted. This would result in a redistribution of the content to reflect the actual using pattern of the content. By the same token, a hot content in one geographical/topological areas can be redeployed network wide to cope with an unexpected surge in demand for the content. Keywords: MS, BMDP, MLR, DRM.

1 Introduction Media Switch[1] is a complete end-to-end solution for streaming high quality multimedia data, such as movies and TV program, over broadband networks. The following main criteria and design philosophy are reflected throughout the architecture: Media Acquisition Control

Content Engi ne

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Media Console

Media Console/Terminal

Fig. 1. Layered Architecture of Media Switch M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 328–334, 2011. © Springer-Verlag Berlin Heidelberg 2011

Research about Media Location Registry and Content Distribution Base on MSA

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A Broadband Media Distribution Protocol[2][3] (BMDP) carries out content distribution from the central content storage in the data center to the Media Stations and among the Media Stations. At the central data center site, Media Location Registry [4](MLR) is responsible for keeping track of all the content locations in the system. The Media Directors at Media Stations participate in BMDP. The design and implementation of BMDP is network-friendly in the sense that it has data transfer rate control and congestion control.

2 The Duo Hierarchies With BMDP, the Media Stations are organized as group. In the case of BB TEC’s network, a group would consist of all the Media Stations that reside on a ring or branch. Each group would have a group leader. The groups form a hierarchy that goes from central data center site to the major ring, from the major ring to minor rings and branches. This hierarchy is called station topology hierarchy[5].

Fig. 2. The Duo Hierachies

Each station is also assigned a subscriber concentration level. The MLR maintains the number of local subscribers for each station. By aggregating the subscriber numbers from the bottom up in the station topology hierarchy, the subscriber concentration number can be calculated for each station in the network. Using the subscriber concentration number, the stations can be classified into different concentration levels with the lowest level being the station with the lowest subscriber concentration and the highest level being the central data center site. Stations with different subscriber concentration level form a subscriber concentration hierarchy. This hierarchy is overlaid on top of the station topology hierarchy. Contents are distributed from the central site to the Media Stations using these two hierarchies. Each piece of content is assigned to an availability class. The availability classification determines whether the first segment or the full copy of the content will be placed on all Media Stations in the network or just some Media Stations that are higher up in the subscriber concentration hierarchy. A hot content that needs to be instantly available to subscribers will be placed in all Media Stations with its full copy. This is the highest availability class. The second availability class would place

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only the first copy on the lowest level Media Stations in the subscriber concentration hierarchy and its full copy on the second level Media Stations in the subscriber concentration hierarchy. The third availability class would place the first segment on the second level stations from the bottom and the full copy on the third level stations from the bottom so on and so force. Content with lowest level availability are only stored in the central site.

3 Media Location Registry MLR maintains a network topology database, a content location database, and a content distribution session database. The network topology database describes the topology of the Media Stations and the network topology among them. As its name implies, the content location database fully describes the location information of every single piece of content in the system. Content Location Register performs fast look up of the content location information for the Media Director’s in the system. Content is copied from one location to another by creating content distribution sessions between two Media Engines in the two locations. These sessions are created and deleted in the Content Distribution Session Database as it happens. This information is used by the MLR to keep track of the bandwidth usage among the Media Stations and the central site. The network bandwidth is a limited resource in the network. The network is configured to allow certain amount of assured media traffic on each of its internal links. MLR needs to ensure the usage of the bandwidth in the network does not exceed the assured traffic amount at all network segments at all times. A. MLR Overview MLR controls program data distribution in Media Switch, and keeps track of all copies of segment about which media stations hold it. MRL controls to which Media Stations a new program should be distributed according to a set of algorithm. (TO BE FINISHED) MLR maintains a simple database. Each entry of the database has the following format: SegmentID

Size

Bitmap (128 bits)

where the bitmap is used to indicate which Media Station has a copy of the segment. Each bit represents one Media Station, and maximum 128 Media Stations can be represented. The bitmap can easily be extended to large size to represent more media stations. B. Network Topology Map MLR builds a map of the network topology and the bandwidth of each connection. The map is used to decide segment copy target. Both distance (hops) and bandwidth are parameters when deciding copy target. C. Segment Copy Sequence Figure 3 shows the sequence of events taking place when copy a segment between Media Stations.


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15

MLR agent seg table 10

MLR agent

5

7

4

6 14

MD main thread

MD main thread

EPG/MAS 8

9 12

1

2

ME

3

ME 13

11 MC

Fig. 3. Segment copy sequence

1. MC browses the EPG, selects a program, and goes through the billing check, and eventually starts the player. 2. MC sends streaming request with program ID to MD. 3. MD checks segment table and finds that it does not have the requested program. It replies to MC and asks MC to retry in 200 ms. 4. MD sends a copy request to the MLR agent. 5. The MLR agent checks its database and decides from which Media Station to get the first segment. It sends a request to the remote MD of that Media Station. 6. The remote MD checks its segment table and finds which ME holds the segment, and replies with the IP of the ME. 7. The MLR agent sends the IP and segmentID to the MD. 8. MD decides which ME should receive the segment, and sends the request to that ME. 9. The ME replies to confirm that the place holder of the segment has been set up. 10. MD puts the record into its segment table. At this point, when MC retries, MD will reply with the ME’s IP. 11. MC receives the ME’s IP and sends streaming request with the segment ID over. The request will be delayed until the first frame is copied over. 12. This happens in parallel with steps 10 and 11. The ME sends copy request to the remote ME. 13. The remote ME starts to send data over. 14. Once the copy is done, ME sends a completion notice to the MLR agent. 15. The MLR agent sends a change notice to MLR in data center, which causes the change record being propagated to all MLR agents and their databases.

4 Dynamic Content Redistribution At each station, content visitation statistics are kept for each piece of content. These statistics are aggregated through the subscriber concentration hierarchy. Based on these statistics, a content’s availability classification can be adjusted. This would

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result in a redistribution of the content to reflect the actual using pattern of the content. By the same token, a hot content in one geographical/topological areas can be redeployed network wide to cope with an unexpected surge in demand for the content. A. Centralized Deployment Architectures MediaSwitch solution supports both centralized and distributed architectures. The Central Media Station, generally located at the data center (headend), is the content storage and distribution center for all encoded programs. The Central Media Station also houses the Authentication & Configuration Server, Application Server, EPG Server and the License (DRM) Server. In large scale deployments, these servers can be deployed in a distributed configuration. Program contents are introduced into a MediaSwitch system by loading them into Media Engine Server blades of its Central Media Station. In a centralized architecture, video contents are streamed from the Central Media Station to the customer’s SetTop-Box or PC clients. Figure3 illustrates MediaSwitch centralized architecture. To minimize network impact and user access time, a service provider may deploy series of intermediate tier and edge Media Stations in a hierarchically distributed structure. Intermediate-tier Media Stations hold contents popular in their vicinity as Edge Media Stations store starter segments of most recently accessed contents. In a distributed architecture, the Media Location Register (MLR) server, located at the Central Media Station, is responsible for system-wide location of all available programs. The content distribution between Central Media Stations to Edge Media Stations or among Media Stations is carried out by The patent pending Broadband Distribution Protocol (BDMP). B. Dual Distribution Hierarchy Architecture The Media Switch solution supports a duo hierarchical distributed architecture where Media Stations are classified based on their physical location within the network and their subscriber coverage. The duo hierarchical architecture enables service providers to dynamically distribute video contents using pre-defined distribution policies that are based on attributes such as content classification, subscriber viewing demand, and bandwidth availability. In a distributed architecture Media Stations are organized as groups. Media Station groups form a hierarchy that goes from data center to the major ring, from the major ring to minor rings and branches. This hierarchy is called Media Station topology hierarchy. Logically they form the tree structure as shown in Figure 5. The tree structure consists of Central Media Stations at the root of the tree located at data centers, Intermediate Media Stations as group leaders located at COs, and edge Media Stations located at end stations at the edge of the network. Each station is also assigned a subscriber coverage level. The MLR maintains the number of local subscribers for each station. By aggregating subscriber numbers from the bottom up in the Media Station topology hierarchy, the subscriber coverage number can be calculated for each station in the network. Using the subscriber coverage number, Media Stations can be classified into different coverage levels with the lowest level being the Media Station with the lowest subscriber coverage and the highest level being the Central Media Station. Media Stations with different subscriber concentration level form a subscriber concentration hierarchy. This hierarchy is overlaid on top of the station topology hierarchy. Both topology and


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subscriber coverage hierarchy are used for data distribution policy, not for data flow. Any Media Station can receive video content from any other Media Stations, including Central Media Station, directly without going through a third Media Station. C. Distribution Based on Content Classification The Media Content Manager (MCM) allows Service Providers to assign an availability class to one or group of programs at time of introduction. The availability classification determines whether starting segments or the full copy of the media content will be placed on all Media Stations in the network or just some Media Stations that are higher up in the subscriber concentration hierarchy. A hot media content that needs to be instantly available to subscribers will be placed in all Media Stations with its full copy. This is the highest availability class. The second availability class would place only starting segments of the media content on the lowest level Media Stations in the subscriber concentration hierarchy and its full copy on the second level Media Stations in the subscriber concentration hierarchy. D. Distribution Based on Subscriber Viewing Demand At each Media Station, content usage statistics are kept for every program. These statistics are aggregated through the subscriber concentration hierarchy. Based on these statistics, the classification of the media content availability can be adjusted. This would result in a redistribution of the media content to reflect the actual usage pattern of the content. Similarly, in order to cope with unexpected demand for media content, the content that is in high demand in one geographical / topological areas can be redeployed network–wide whenever necessary. E. On Demand Distribution A media program or its segments can be copied to the Media Station on demand. This situation happens when a subscriber under the Media Station requests a program that is either partially available or simply not available at the Media Station. When a copy of the program is needed, the MLR running on the Central Media Station will search for one or more Media Stations that have the segments of the program. The segments can be copied from one source or several sources. The decisions are made according to distance of the source, bandwidth availability, and other parameters. Generally, the source Media Stations is in the same topology group as the requesting Media Station to avoid traffic on network trunk of higher topology level. F. Media Station Content Storage Management A media program can be deleted from a Media Station when space is needed. Program deletion decision is used based upon the Simple LRU (Least Recently Used) algorithm. Furthermore, all deletion operations need to be approved by MLR. MLR either approves the deletion, or asks the requesting Media Station to copy the program to another Media Station. MLR makes decision based on either the distribution policy or a group-wide LRU. If the distribution policy indicates that the group should keep at least one copy of the program, and the copy to be deleted is the last copy, the group leader will direct the Media Station to copy the program to another Media Station, which is often the group leader itself. If the distribution policy does not require the

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group to maintain a copy, a group-wide LRU is used. The program is deleted if it is the least recently used program of the group or close to be the least recently used program. When the least recently used program is deleted, and the new program will be copied over to the space just made available.

5 Conclusions The Media Location Register (MLR) server, located at the Central Media Station, is responsible for system-wide location of all available programs. The content distribution between Central Media Stations to Edge Media Stations or among Media Stations is carried out by The UTStarcom patent pending Broadband Distribution Protocol (BDMP). The Media Switch solution supports a duo hierarchical distributed architecture where Media Stations are classified based on their physical location within the network and their subscriber coverage. The duo hierarchical architecture enables service providers to dynamically distribute video contents using pre-defined distribution policies that are based on attributes such as content classification, subscriber viewing demand, and bandwidth availability.

References 1. Ofek, Y.: Ultra scalable optoelectronic switching fabric for streaming media over IP. In: Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, pp. 245–252 (2005) 2. Le, H.K., Henriksson, D., Abdelzaher, T.: A Practical Multi-channel Media Access Control Protocol for Wireless Sensor Networks. In: Proceedings of 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008), pp. 70–81 (2008) 3. Turaga, D.S., Ratakonda, K., Lai, J.: QoS Support for Media Broadcast in a Services Oriented Architecture. In: Proceedings of IEEE International Conference on Services Computing (SCC 2006), pp. 127–134 (2006) 4. Jeong, E.-J., Lee, G.-Y.: Efficient Location Management Scheme using MLR considering Local Usages. In: Proceedings of International Conference on Information Technology (ITNG 2007), pp. 941–942 (2007) 5. Weiss, K., De Floriani, L.: A High-Level Primitive for Diamond Hierarchies. IEEE Transactions on Visualization and Computer Graphics, 1603–1610 (November 2009)

IUP Modeling Method and Its Application for Complex Information Systems Yingyong Bu, Libin Zhu, and Jinyu Wang College of Mechanical and Electrical Engineering, Central South University, Changsha Hunan 410083, China [email protected]

Abstract. An integrated modeling method was proposed based on IDEF, UML and Petri net (IUP). The IDEF model would be established by IDEF0, IDEF1x and IDEF3. By the mapping rule, the UML model would be transformed from the IDEF model for object-oriented software design. The key processes of the IDEF model and the UML model would be transformed into Petri net to analyze the effectiveness and modify models. For the model transformation could be easier, the mapping rule among IDEF, UML and Petri net was studied in this paper. With this method, a model was designed for a spare part management system in a larger metallurgical company, which is configurable, extensible and reusable. Keywords: IDEF, UML, Petri net, IUP modeling method, mapping rule.

1 Introduction Various methodologies for information systems modeling have been developed in different fields, such as IDEF (ICAM DEFinition Method), UML (Unified Modeling Language) and Petri net. For a complex information system, it’s necessary to build models with different modeling methods in different modeling stages. However, some problems exist here, such like lacking of consistency, complex model transformation and difficult model verification. In this paper, an integrated modeling method, IUP modeling method was proposed to solve these problems. It provided a practical modeling method for complex systems modeling.

2 IUP System Modeling Method IDEF can describe the semanteme of a model accurately, but lacks object-oriented design and software programming. It is appropriate for function analysis, information analysis and process analysis in the early stage [1]. UML supports software engineering in the whole cycle. It is used widely from modeling to software programming. However, it’s difficult to understand for the lack of precise semantic definition. So it fits for detailed design and software programming [2]. Petri net is mainly used for process modeling and simulation analysis in system modeling [3]. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 335–342, 2011. © Springer-Verlag Berlin Heidelberg 2011

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IDEF, UML and Petri net have some similarities in the modeling mechanism and syntax, existing mapping rule. References [4-11] integrated IDEF and UML modeling method or combined UML and Petri net, so that the modeling process was more concise and flexible. The scalability and reusability of the system model were improved. But the mapping rule among the three models didn’t research deeply. For a complex information system, the model transformation is time-consuming and may generate semantic deviation without detailed and effective mapping rule. Comparing the three modeling methods, IUP system modeling method was proposed for complex information systems. To display the advantages and avoid theirs shortcomings, different methods were used in different stages. The modeling frame was put forward and shown in figure 1. The whole modeling process was divided into four stages: requirement analysis, preliminary design, detailed design and programming. Function

Requirement analysis

Preliminary design

Detailed design

Programming

IDEF0

Action

Information Organization Analysis resource

IDEF3

UML Use Case diagram Sequence diagram Collaboration diagram Activity diagram State diagram

IDEF1x

UML Class diagram

Modeling Petri method of Nets organization and resource

Programming language

Fig 1. Modeling frame of the IUP method

A. Requirement Analysis In the stage of requirement analysis, the function model was established by IDEF0, the process model by IDEF3 and the information model by IDEF1x. To make semantic association of three models, the same thing should be described in a same concept. For the consistency of models and transformation in the next stage, each IDEF3 UOB should correspond to a box of the IDEF0, and each IDEF1x entity should be related to a box of the IDEF0 or a UOB of the IDEF3. The key processes of the IDEF0 model and the IDEF3 model were transformed into Petri net model to analyze the effectiveness and improve models according to the result. B. Preliminary Design In preliminary design, use case diagram, sequence diagram, collaboration diagram, activity diagram and state diagram of UML were transformed from the IDEF model by the mapping rule. Then these would be transformed into class diagrams for the preliminary design of the class.

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C. Detailed Design In detailed design, the UML model was designed detailedly according to the programming requirement. Then the classes were consummated including its attribute and operation. A further step, made sure the relationship among different classes. In order to analyze the effectiveness and improved models, the key processes of the UML model were transformed into Petri net model. D. Programming In this stage, a database was designed on the basis of the IDEF1x information model. Then a suitable programming language was chose to complete detailed design according to its requirements.

3 Mapping Rule among IDEF, UML and Petri net Mapping relationship among IDEF, UML and Petri net has rule, called mapping rule. The research of mapping rule is beneficial to build the mapping for model transition, so it plays an important role for the coherence of modeling steps [5]. In IUP model method, the overall relationship of mapping rule was shown in figure 2. Therefore, the rule was studied according to the needs of IUP modeling method, which included IDEF mapping onto Petri net, UML mapping onto Petri net and IDEF mapping onto UML A. IDEF Mapping onto Petri net By the analysis of the modeling mechanism and syntax,

User

Requirement analysis

IDEF

UML Use case diagram

IDEF0 Activity diagram Amend

Petri nets

Amend

IDEF3 IDEF3PFN

IDEF3OSTN

IDEF1x

Sequence diagram

Collaboration diagram State diagram Class diagram

Database design

Programming RDB

Software system

Fig. 2. Internal mapping of the IUP method

Petri nets

338


it suggested that tokens’ generation and consumption in Petri net represent on the information in the IDEF0 model. The flow of tokens reflected the running state of a system. UOB of IDEF3PFN corresponded to the transition in Petri net, and the information dealing with UOBs mapped to the flow of Petri net. The IDEF3OSTN object states corresponded to tokens’ production and consumption in Petri net. And the flow of Petri net reflected the transition of system state. The mapping rule of modeling elements between IDEF and Petri net showed in the table 1. B. UML Mapping onto Petri net Activity diagrams are similar with IDEF3PFN. And the function of state diagrams resembles IDEF3OSTN. Sequence diagrams and collaboration diagrams face detail design. So the mapping rule from UML to Petri net was showed in the table 2. C. IDEF Mapping onto UML UML diagrams are the graphical expression of a system, which are usually composed of modeling elements and the connection. UML defines some different functional diagrams that link a number of cases by the connection. Use case diagrams, class diagrams, activity diagrams, state diagrams, sequence diagrams and collaboration diagrams were mapped to IDEF. Table 3 introduced the detailed mapping rule between IDEF and UML. Table 1. Mapping rule from IDEF to Petri net IDEF Models

IDEF0

Petri net

Modeling elements

Modeling elements

Function (Box)

Transition

Information(Arrow)

Place

Input and output

Arc

UOB

Transition

Connection

Arc-Place-Arc

UOB referent

Transition

Entity

Transition

Connection

Arc

IDEF3PFN

IDEF3OSTN

Table 2. Mapping rulefrom UML to Petri net UML

Petri net

Diagrams

Main elements

Modeling elements

Activity diagram

Active state

Transition

Control flow

Arc-Place-Arc

State

Transition

State transition

Arc-Place-Arc

Object

Transition

State diagram

Sequence diagram

Message among different objects Message among the same object

Arc1-Place-Arc 2 Arc-Place-Arc


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Table 3. Mapping rule between IDEF andUML UML Diagram

IDEF

Main elements

Use case

IDEF0

Actor Use case diagram

Use cases relationship

Actors relationship

Source model

IDEF0 Extension

IDEF0

Inclusion

IDEF0

Generalization

IDEF0

Generalization

IDEF0

Class

IDEF1x IDEF3PFN

Operation

IDEF3OSTN IDEF0

Class diagram

Attribute

IDEF1x Generalization

IDEF1x

Aggregation

IDEF1x

Association

IDEF1x

Dependency

IDEF1x

Association

Activity diagram

Mapping rule

Each IDEF0 box corresponds to a use case Identify actors from the staff category of the ICOM code Identify extension from the top level of the IDEF0 model Produce inclusion by the common part of activities Identify generalization from the analyzing semanteme of IDEF0 model Identify generalization from the analysis of the M code in ICOM Define classes from entities Extract operation from UOB of the IDEF3PFN Extract operation from UOB of the IDEF3OSTN Extract operation from UOB corresponding to boxes of the IDEF0 Define class attribute from entity attribute Extract generalization from categorization relationship Extract aggregation from connection relationship Extract association from connection relationship Extract dependency from connection relationship

Action State and Activity State IDEF3PFN

Correspond to the UOB units

Control Flow

IDEF3PFN

Correspond to connection

Swinlane

IDEF3

Identify swinlane from the referent of object

Synchrononization

IDEF3PFN

Correspond to junction including fan-in and fan-out

Decision

IDEF3PFN

Correspond to the fan-out junction

Name

State State diagram

IDEF3OSTN

Internal transition

IDEF3OSTN

Enter activity

IDEF3OSTN

Exit activity

IDEF3OSTN

Initial State

IDEF3OSTN

Terminal state

IDEF3OSTN

Transition

Event

IDEF3OSTN

Extract name from the name of object state Sketch internal transition from state description condition Analyze enter activity from the entry condition set of OSD Analyze exit activity from the exit condition set of OSD Correspond to the object state of transformation arc Correspond to the object state of transformation arc Produce event from referents of transformation arc

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Y. Bu, L. Zhu, and J. Wang Table 3.(continued) Guard condition

IDEF3OSTN

Fork

IDEF3OSTN IDEF3PFN

Object and lifeline IDEF0 Sequence diagram and collaborati Message on diagram

Focus of control

IDEF3PFN IDEF3OSTN

Identify guard condition from the semanteme of object state Convert fork from junction of the IDEF3OSTN Extract object and lifeline from the referent of object Extract object and lifeline from ICOM corresponding to UOB Analyze messages from UOBs and control flow Analyze messages from the referent of UOBs and control flow

IDEF0

Analyze messages from ICOM

IDEF

Confirm the range of focus by transfer time and UOBs acting time

4 Case Application In this chapter, we applied the IUP modeling method on a spare part management system in a larger metallurgical company. Taking IDEF0 diagram for an example, it could map onto use case diagram and Petri net model. The relationship among activities could be easily identified from Fig. 3. According the mapping rule, use case diagram and Petri net model could be generated from IDEF0 model. Use case diagram was shown in Fig.4, and Petri net was in Fig.5.

Fig. 3. A part of IDEF0 diagram


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Fig. 4. Use case diagram generated from IDEF0 model

Fig. 5. Petri net model generated from IDEF0 model

In Fig. 5 each element in Petri net model corresponded to a element of the IDEF0 model: T1 -Plan, T2 -Purchase, T3-Store Management, P1-Anticipated Demand of Spare Parts, P2-Use Demand of Spare Parts, P3-Quaility and Price of Spare Parts, P4Finance, P5-Inventory Information, P6-Purchase Plan, P7-Purchase Contract.

5 Conclusion In this paper, we have introduced IUP modeling method, an integrated method based on IDEF, UML and Petri net. The modeling method could make an accurate definition and support object-oriented software programming. It was used in the modeling of a spare part management system in a larger metallurgical company with good maintainability, scalability and reusability. Based on B/S/D three-tier architecture, the model was built on the platform of LAN and Oracle10g. It was implemented well in practical applications. By the analysis of the modeling syntax, mapping rule of IDEF onto UML, UML onto Petri net and IDEF onto Petri net was obtained. It improved efficiency of the modeling transformation and reduced the loss of the semantic transition, especially for complex information systems. We plan to further validate the method by applying it to more system modeling.

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References 1. Chen, Y.-l.: IDEF Modeling Analysis and Design Method, pp. 3–181. Tsinghua Univerity Press, Beijing (1999) 2. Rumbaugh, J., Jacobson, I., Booch, G.: The Unified Modeling Language Reference Manual, 2nd edn., pp. 18–78. China Machine Press, Beijing (2006) 3. Yuan, C.-y.: The principle of Petri net, pp. 3–99. Publishing house of electronic industry, Beijing (1998) 4. Kim, C.-H., Weston, R.H., Hodgson, A.: The complementary use of IDEF and UML modelling approaches. Computers in Industry, 35–56 (2003) 5. Shin, K., Park, C., Lee, H.-G., Park, J.-W.: Efficient mapping rule of IDEF for UMM application. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Laganá, A., Lee, H.P., Mun, Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3482, pp. 1219–1228. Springer, Heidelberg (2005) 6. Chert, Z.-j., Jian, W., Shao, P.-f.: Research of Mapping UML State. Journal of Hubei Automotive Industries Institute 22(2), 30–34 (2008) 7. Dorador, J.M., Young, R.I.M.: Application of IDEF0, IDEF3 and UML Methodologies in the creation of information models. International Journal of Computer Integrated Manufacturing, 430–445 (2000) 8. Shang, W.-l., Wang, C.-e., Zhang, S.-j., Yin, Z.-w.: System Modeling Method Based on IDEF&UML. Computer Integrated Manufacturing Systems 10(3), 252–258 (2004) 9. Li, L.-s., Hu, Z.-l.: AppIication Analysis and Fomal Modeling of UML Based on Petri Net. Computer Technology and Development 4(4), 76–83 (2010) 10. Lassen, K.B., Tjell, S.: Model-based requirement analysis for reactive systems with UML sequence diagrams and coloured petri nets. In: Innovation System Softwore Engineering, pp. 233–240 (2008), doi:10.1007/s11334-008-0054-3 11. Jiang, J.-l., Zhou, X.-z., Sun, Y.-c., Xu, Y.-y.: Hierarchical Modeling Analysis Method Based on UML and Petri Net. Journal of System Simulation 18(2), 290–293 (2006)

Study on International Competitiveness of Tire Industry Based on Factor Analysis Chen Jing-xin1 and Wang Xiao-ying2 1 2

Langfang Department, Hebei University of Technology, Langfang, China School of Management, Hebei University of Technology, Tianjin, China [email protected]

Abstract. With these years rapid development, Chinese tire industry has become one of the anti-dumping most frequently industry. This paper selected six indices and constructed tire industry international competitiveness evaluation system. Based on Large amount of data gathered, we analyzed the situation of eight major tire produce countries through factor analysis method, particular evaluated Chinese tire industry international competitiveness and drew conclusions. Keywords: international competitiveness, tire industry, industry international competitiveness, factor analysis.

1 Introduction Since 2006, China has become the largest tire manufacturer and exporter in the world. In 2003, Chinese tire production was 193.12 million, and in 2009 it reached to 654.64 million. Except no increasing in 2008, the annual growth rate of other years exceeded 20%. With the rapid growth of export, China attracted more and more anti-dumping trade barriers. Since 2001, nine countries have had anti-dumping investigation launched to China. In September 2009, U.S. President Barack Obama decided to impose restrictive tariff on Chinese tires. In this background, the study of tire industry international competitiveness has important practical significance.

2 The Building of Tire Industry International Competitiveness Evaluation System This paper constructed tire industry international competitiveness evaluation system, as shown in Table 1. Table 1. Tire industry international competitiveness evaluation system The first Level Indices

International competitiveness

The Second Level Indices International market share Competition index Revealed comparative advantage index Revealed competitive advantage index Export contribution rate Export growth advantage index


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A. International Market Share International market share, Mi, is calculated as Mi =

Xi × 100 % Xw

(1)

In the above formula, Xi is a country's tire export volume (amount), Xw is the world's total tire export volume (amount). The greater the international market share is, the stronger the international competitiveness is. The value of international market share of major tire produce countries are shown in Table 2. Values in the table are percentages. Table 2. The international market share of major tire produce countries China U.S Japan France Germany Italy Korea India

2002 4.92 9.52 12.56 8.44 10.77 4.35 6.44 ----

2003 5.52 7.67 13.42 8.82 10.96 4.18 6.17 1.193

2004 7.18 7.22 12.14 8.34 10.7 4.186 6.06 0.99

2005 9.48 6.98 11.8 7.26 10.48 3.48 6.18 1.05

2006 11.2 6.83 11.08 6.97 10.25 3.01 5.93 1.14

2007 12.72 6.45 10.13 6.71 9.2 3.03 5.47 1.003

2008 13.56 6.72 10.21 6.93 8.85 2.65 5.32 1.03

Source: United Nations Commodity Trade Database, National Bureau of Statistics Web site (hereinafter the same)

Seen from Table 2, except China, other countries' value have been little change. Only China's value has increased year by year, from 4.92% of 2002 rose to 13.56% of 2008. B. Competition Index Competition index, TCi, is calculated as TCi =

Ei − I i Ei + I i

(2)

In the above formula, Ei is a country's tire export volume, Ii is a country's tire import volume. The value of competition index is in the range between -1 and 1[1]. When TC 0, indicating that the product has international competitive advantage. When TC 0, indicating that the product has international competitive disadvantage. The value of competition index of major tire produce countries are shown in Table 3.

＞＜

Table 3. Competition index of major tire produce countries China U.S Japan France Germany Italy Korea India

2002 0.92 -0.37 0.73 0.22 0.04 -0.06 0.79

2003 0.88 -0.44 0.77 0.19 0.02 -0.08 0.79 0.9

2004 0.9 -0.44 0.75 0.2 0.04 -0.08 0.78 0.8

2005 0.93 -0.47 0.73 0.17 0.02 -0.1 0.8 0.8

2006 0.91 -0.47 0.71 0.15 0 -0.13 0.79 0.65

2007 0.93 -0.63 0.72 0.11 -0.05 -0.16 0.8 0.5

2008 0.91 -0.42 0.72 0.07 -0.04 -0.16 0.8 0.39

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Seen from Table 3, Only United States and Italy's index were negative; India's index has decreased rapidly; China, Korea and Japan's index were at a higher position, the three countries had international competitive advantage. C. Revealed Comparative Advantage Index Revealed comparative advantage index, RCAi, is calculated as RCAi =

Ei E j

(3)

Wi W j

In the above formula, Ei is a country's tire export volume, Ej is a country's total export volume, Wi is the world's tire export volume, Wj is the world's total export volume. The value of revealed comparative advantage index is in the range RCA≥0. When 0＜RCA＜1, indicating that the products have no revealed comparative advantage. When RCA≥1, indicating that the product have revealed comparative advantage. When RCA＞2.5, indicating that the products have strong revealed comparative advantage. The value of revealed comparative advantage index of major tire produce countries are shown in Table 4. Table 4. Revealed comparative advantage index of major tire produce countries China U.S Japan France Germany Italy Korea India

2002 0.982 0.896 2.000 1.664 1.412 1.118 2.590

2003 0.955 0.802 2.158 1.707 1.107 1.060 2.415 1.625

2004 1.117 0.816 1.983 1.702 1.086 1.093 2.206 1.233

2005 1.305 0.808 2.082 1.643 1.132 0.980 2.281 1.123

2006 1.400 0.795 2.067 1.718 1.112 0.914 2.199 1.142

2007 1.462 0.785 1.985 1.703 0.975 0.848 2.060 0.956

2008 1.528 0.840 2.102 1.842 0.974 0.793 2.209 0.936

Seen from Table 4, Korea, Japan and France's index were greater than 1.5, and their products had strong international competitiveness[2]. China's index reached 1.4 in 2006, indicating that the international competitiveness of Chinese tire increased year by year. The index of other countries have remained at around 1. D. Revealed Competitive Advantage Index Revealed competitive advantage index, CAi, is calculated as CAi = RCAi −

Mi M j

(4)

M wi M wj

In the above formula, RCA is a country's revealed comparative advantage index, Mi is a country's tire import volume, Mj is a country's total import volume, MWi is the world's tire import volume, MWj is the world's total import volume. When CA≥0, indicating that the product has revealed competitive advantage. When CA 0, indicating that the product has no revealed competitive advantage. The value of revealed competitive advantage index of major tire produce countries are shown in Table 5.

＜

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J.-x. Chen and X.-y. Wang

Seen from Table 5, Korea and Japan's index were largest, indicating that the two countries had obvious advantages. In 2008, China reached the third in the world. United States, Germany, Italy's index were all negative, indicating that their tire had no revealed competitive advantage. Table 5. Revealed competitive advantage index of major tire produce countries China U.S Japan France Germany Italy Korea India

2002

2003

2004

2005

2006

2007

2008

0.935 -0.294

0.8925 -0.398

1.053 -0.393

1.245 -0.457

1.317 -0.505

1.393 -0.483

1.438 -0.5

1.6 0.531 0.03 -0.247 2.19

1.798 0.528 -0.273 -0.263 2.094 1.562

1.602 0.534 -0.262 -0.291 1.881 1.127

1.689 0.507 -0.317 -0.28 1.989 1.034

1.661 0.47 -0.363 -0.334 1.913 0.962

1.607 0.425 -0.463 -0.372 1.819 0.729

1.718 0.355 -0.438 -0.374 1.972 0.664

E. Export Contribution Rate Export Contribution rate, Ci, is calculated as Ci = Ai A

(5)

In the above formula, Ai is a country's tire export volume, A is a country's total export volume. The value of export contribution rate of major tire produce countries are shown in Table 6. Table 6. Export Contribution rate of major tire produce countries China U.S Japan France Germany Italy Korea India

2002 0.32 0.28 0.64 0.52 0.36 0.36 0.83

2003 0.31 0.26 0.71 0.56 0.36 0.35 0.79 0.52

2004 0.37 0.27 0.67 0.57 0.37 0.36 0.74 0.4

2005 0.44 0.28 0.71 0.56 0.39 0.34 0.78 0.38

2006 0.46 0.26 0.69 0.57 0.37 0.31 0.73 0.38

2007 0.5 0.27 0.68 0.59 0.34 0.29 0.71 0.33

2008 0.5 0.27 0.69 0.6 0.32 0.26 0.67 0.31

Seen from Table 6, Korea, Japan and France's index were the largest, indicating that their tire export had the largest contribution to total export. Contribution of Chinese tire export has increased year by year. Other countries' index have been little change. F. Export Growth Advantage Index Export growth advantage index, Di, is calculated as D i = ( Ai At ) × 1 0 0 %

(6)

In the above formula, Ai is a country's tire export growth rate, At is a country's total export growth rate.


347

Table 7. Export GROWTH advantage IndEX of major tire produce countries 2002

China U.S Japan France Germany Italy Korea India

2003

2004

2005

2006

2007

2008

96.67 -92.6 190.52 133.62

177.34 137.41 61.2 112.57

183.81 107.41 233.79 15.4

120.66 66.12 58.68 133.34

141.52 128.13 97.98 126.98

93.71 112.35 104.26 128.48

96.67 -92.6 190.52 133.62

96.1 81.56 72.46

104.96 138.21 74.07 11.95

192.22 -73.22 52.91 72.48

65.39 24.47 51.52 102.61

43.96 65.88 78.73 28.47

44.44 -61 44.44 58.5

96.1 81.56 72.46

The larger the index is, the faster the export growth is. The value of export growth advantage index of major tire produce countries are shown in Table 7. Seen from Table 7, United States 's index of 2003 was negative, Italy's index of 2005 and 2008 were negative.

3 Determination of International Competitiveness Based on Factor Analysis This paper selected eight major tire produce countries for factor analysis using SPSS 16.0. Concrete steps are as follows. A. Calculating the Value of Sample's Original Index We taked above data as the original index value for following analysis. B. Defining Variables and Labels In order to ensure accuracy, this paper selected the previous five indices to carry on factor analysis. We assumed x1=international market share, x2=competition index, x3= revealed comparative advantage index, x4= revealed competitive advantage index, x5= export contribution rate C. Carrying on Factor Analysis Then we carried on factor analysis[3][4]. 1) Testing whether suitable for factor analysis: The data were entered into SPSS 16.0 for windows software system, the outputs were as follows. Table 8. KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Approx. Chi-Square Bartlett's Test of Sphericity df Sig.

.646 43.371 10 .000

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J.-x. Chen and X.-y. Wang Table 9. Correlation Matrix

Correlation

x1 x2 x3 x4 x5

x1 1.000 .398 .389 .317 .422

x2 .398 1.000 .717 .953 .719

x3 .389 .717 1.000 .842 .996

x4 .317 .953 .842 1.000 .836

x5 .422 .719 .996 .836 1.000

Seen from the correlation coefficient matrix, most of the correlation coefficients were high and suitable for factor test. The value of Bartlett's Test of Sphericity was 43.371, the probability of P was 0, the value of KMO was 0.646, it was suitable for factor analysis. 2) Extracting factors: The results were shown in Table 10. Seen from Table 10, through principal component analysis, two factors were automatically extracted from the five components. Their cumulative contribution for variance was 90.901%. Therefore, these two factors could be considered provided sufficient information to the final evaluation. 3) Naming factors: Table 10. Rotated Component Matrixa Component 1 x4 x3 x5 x2 x1

.965 .920 .911 .878 .204

2

.112 .219 .256 .207 .978

Seen from the rotated factor loading matrix, competition index, revealed comparative advantage index, revealed competitive advantage index, export contribution rate had higher load in the first factor, they could be defined as the competition index. International market share had higher load in the second factor, it could be interpreted as the market index. Compared with the pre-rotation, factor meaning were clearer. 4) Establishing scoring function: Table 11. Component Score Coefficient Matrix Component 1 x1 x2 x3 x4 x5

-.225 .266 .278 .328 .263

2

1.054 -.035 -.034 -.170 .011


349

The following factors score function were written according to factor score coefficient matrix. F1=-0.225x1+0.266x2+0.278x3+0.328x4+0.263x5

(7)

F2=1.054x1-0.035x2-0.034x3-0.17x4+0.011x5

(8)

5) Two-factor evaluation: Two-factor evaluation were shown in Figure 1.

Fig. 1. Two-factor evaluation Table 12. Total Variance Explained Initial Eigenvalues Component 1 2 3 4 5

Total 3.746 .799 .434 .018 .003

% of Variance 74.913 15.987 8.683 .360 .056

Cumulative % 74.913 90.901 99.584 99.944 100.000

Extraction Sums of Rotation Sums of Squared Squared Loadings Loadings % of Cumulative % of Cumulative Total Variance % Total Variance % 3.746 74.913 74.913 3.419 68.383 68.383 .799 15.987 90.901 1.126 22.518 90.901

Extraction Method: Principal Component Analysis.

Seen from Figure 1, regarding the first factor, competition index, Korea scored the highest, indicating that Korea had relatively large advantage. Japan followed. United States' score was the lowest. Germany and Italy are very weak. China and France were in the middle. Regarding the second factor, market index, China scored the highest, indicating that China had relatively large advantage. Germany and Japan followed. India' score was the lowest. The others were in the middle. 6) Calculating composite scores: After calculating above two principal components F1 and F2, we could establish international competitiveness evaluation model of the world's major tire produce countries according to two principal components' contribution for variance. Z1=68.383F1+22.518F2

(9)

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J.-x. Chen and X.-y. Wang Table 13. 2008 Comprehensive ranking of the world's major tire produce countries Countries China U.S. Japan France Germany Italy Korea India

F1 -1.97 -1.48 -0.76 -0.75 -1.99 -0.47 0.47 0.57

F2 13.97 7.16 9.47 7.18 9.37 2.84 4.5 0.93

Z1 179.86 60.02 161.27 110.39 74.91 31.81 133.47 59.92

Ranking

1 6 2 4 5 8 3 7

Seen from above table, the scores of China's tire international competitiveness was the highest, Japan was the second, Korea and France ranked third and fourth, Italy scored the lowest.

4 Conclusion Although the 2008 financial crisis affected countries in tire industry greatly, through above analysis, Chinese tire industry had a good international competitive position, comprehensive international competitiveness ranking was No. 1, developing trends was very well. But at the same time, we should clearly recognize the weakness of tire industry. The world's three giant almost monopolized tire brand market. Chinese tire export were low value-added export[5]. Measures to further enhance the international competitiveness of Chinese tire industry are as follows. First, China should optimize the export product mix and promote the high-grade tire export. Second, China should strengthen their own brands, create international brands, increase product added value relying on scientific and technological progress. Acknowledgment. This research was supported by PhD Foundation of North China Institute of Aerospace Engineering.

References 1. Jin, B.: China Industry’s International Competitiveness: Theory, Method and Empirical Research. Economics and Management Press, Beijing (1997) 2. Zhang, K.: Study on China Auto Industry’s International Competitiveness and Countermeasures. Learned Journal of Yunnan Finance University (Social Sciences) 6, 100–102 (2008) 3. Xue, W.: SPSS Statistical Analysis and Application, pp. 327–349. Electronic Industry Press, Beijing (2009) 4. Ding, G.-s., Li, T.: SPSS Statistics Tutorial: From Research Design to Data Analysis. Machinery Industry Press, Beijing (2008) 5. Cai, W.-m.: The Measures and Recommendations on Chinese Tires Export Trade Friction. Tire Industry 29, 716–718 (2009)

Study on Quantitative Evaluation of Enterprise Core Competence Based on Resources and Capabilities Chen Jing-xin1 and Liu Wei2 1

Langfang Department, Hebei University of Technology, Langfang, China 2 Department of Economics and Management, North China Institute of Aerospace Engineering, Langfang, China [email protected]

Abstract. Quantitative evaluation of enterprise core competence has great theoretical and practical significance for enterprise strategic management. On the basis of studying related literatures, this paper thought that resources and capabilities are the sources of competitive advantage. It constructed evaluation system of enterprise core competence based on resources and capabilities; proposed Nine Grids Chart on evaluation of enterprise core competence referencing General Matrix; innovatively provided a method on quantitative evaluation of enterprise core competence. Keywords: core competence, quantitative evaluation, resources, capabilities.

1 Introduction According to C. K. Prahalad and Gary Hamel's view, core competence can bring about lasting competitive advantage. The practical experience, including 3M, Honda and other successful companies, have shown that enterprises could gain competitive advantage in complex environment through accumulating their own abilities and carrying on successful strategic management. Therefore, theory and business circles has gradually recognized the core competence theory[1]. However, how to identify and nurture enterprise core competence has become a issue faced by many enterprises. In this context, quantitative evaluation of enterprise core competence has great theoretical and practical significance to enterprise strategic management. It makes it possible for enterprises to understand their own core competence. On the basis of studying related literatures, this paper constructed evaluation system of enterprise core competence and made a useful attempt on quantitative evaluation of enterprise core competence.

2 Related Literatures Review A. Concept of Core Competence In 1990, American strategists C. K. Prahalad and Gary Hamel published an article, “Core Competence of Corporation”, on “Harvard Business Review” and first put forward the definition of core competence. Core Competence is communication, M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 351–358, 2011. © Springer-Verlag Berlin Heidelberg 2011

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J.-x. Chen and W. Liu

involvement, and a deep commitment to working across organizational boundaries. Core Competence is the collective learning in the organization, especially how to coordinate diverse production skills and integrate multiple streams of technologies[2]. B. Views of Western Scholars on Core Competence 1) Coordination-based theory: In 1994, C. K. Prahalad and Gary Hamel published a book, “Competing for the Future”. In this book, they provided more specific definition of core competence. First, a competence is a bundle of skills and technologies rather than a single discrete skill or technology. Second, to be considered a core competence, a skill must meet three tests: customer value, competitor differentiation, extendability. A core competence must make a disproportionate contribution to customer-perceived value. Core competencies are the skills that enable a firm to deliver a fundamental customer benefit. To qualify as a core competence, a capability must also be competitively unique. Core competence is that might be applied in new product arenas. Third, core competence is of outstanding technical elements, which includes technology and technologies stream[3]. According to the view of Coyne, from McKinsey, Core competence is the combination of a series of complementary skills and knowledge within the organization[4]. 2) Resource-based theory: Christine Olive (1997) stressed the effect of resources and capabilities to obtain higher returns and sustainable competitive advantage[5]. Barney believed that only when enterprise resources have characteristics of value, scarce, irreplaceable and difficult to imitate, they can create sustainable competitive advantage. Core competence is the unique capability for enterprise to obtain and possess these special resources[6]. 3) Knowledge-based theory: Bart said that core competence was the proprietary knowledge and information which led to enterprise competitive advantage. It had enterprise features and was difficult to trade. It was their own knowledge system to provide enterprise competitive advantage. It included four dimensions, that is, skills and knowledge set, organization technical system, organization management system, organization values system. Learning was an important way to improve their core competence[7]. 4) Combination-based theory: M. H. Meger and J. M. Utterback believed that, to a greater extent, core competence was the capability which bring products to market based on product innovation. Core competence was divided into four dimensions, that is, product technology, manufacturing capability, capability to understand customer needs, distribution channels capability. Many K. Coulter thought that, core competence were the skills and capabilities that shared by more products or business to create main value in a organization[8]. 5) Culture-based theory: Raff and Zorro thought core competence existed not only in the operation subsystem, but also in the culture subsystem of enterprise. The accumulation of core competence embedded in corporate culture, and permeated throughout the organization[8]. C. Views of Chinese Scholars on Core Competence WU Jing-lian(1999), chinese famous economist, said that core competence was an organizational capability to organic fuse the skills, asset and operation mechanism. It was the result of implementation of internal management strategy and external trade strategy[9].

Study on Quantitative Evaluation of Enterprise Core Competence

353

RUI Ming-jie(2000), professor of Fudan University, pointed that core competence was a unique, key capability of giving a series of products or services leading position. This capability was a synthesis of technology and skills. ZHANG Wei-ying, professor of Peking University, thought that, core competence was internal resources and capabilities of an enterprise, and some enterprise core competence was innate. SHI Dong-ming(2002) thought that core competence was formed by variety of abilities. Various kinds of abilities appeared different levels. From inside to outside, the levels decreased layer by layer, including capabilities of core values, organizing and management, knowledge and skills, software and hardware[10]. D. Characteristics of Core Competence About the characteristics of core competence, now a consensus is largely reached. If a capability is core competence, it must meet the following five characteristics, that is, value, difficult to imitate, unique, irreplaceable, scalability. Core competence is the capability to achieve scope economy. Through the overflow, diffusion, radiation and infiltration, this capability can continuously provide innovative products to consumers[11].

3 Methodology With complex nature of external environment, enterprise capability of affecting external environment became weak increasingly. Improving internal resources and capabilities has become the most important controllable variable of corporate strategy. Resources and capabilities are the sources of competitive advantage. This paper constructed a evaluation mode of enterprise core competence based on resources and capabilities. A. Evaluation Principles 1) Evaluating enterprise core competence with two variables: key resources and key capabilities: Core competence is the synthesis of skills, technology, knowledge[12]. In order to accurately evaluate enterprise core competence, this paper defined two variables, key resources and key capabilities. Key resources are the enterprise's resources which have four characteristics, including value, rarity, irreplaceable and difficult to imitate. Key capabilities are enterprise's comprehensive capabilities existing in research and development, manufacturing, marketing and other business processes. 2) Selecting multiple indices to evaluate key resources and key capabilities: According to number, key resources are divided into high, medium and low thirdclass. Acording to size, key capabilities are divided into high, medium and low thirdclass. 3) Drawing Nine Grids Chart: Referencing General Matrix, enterprise core competence can be drawed in Nine Grids Chart according to scores of the two variables.

354


B. Constructing Evaluation System Based on the principles above[13], we construct the evaluation system of enterprise core competence. Evaluation indices system of key resources and key capabilities are shown in Table 1 and Table 2 respectively. Table 1. Evaluation indices system of key resources Variable Type

Specific Indices Adaptiveness of organizational structure (X1) * Organizational Perfection degree of plan, resources control and coordination mechanisms (X2) * The patent situation (X3) Technical resources

Key resources (X) Human resources

The proportion of annually income received from the exclusive intellectual property rights (X4) The proportion of annually income received from new products(X5) Staff loyalty degree (X6)

Managers and staff training and knowledge (X7) Managers and staff experience and insight (X8) * Brand image (X9) *

Corporate image

Corporate culture

Enterprise image industry (X10) *

in

the

Training degree of core values (X11) * Staff awareness degree of core values (X12) *

Content Matching degree of current organizational structure and strategy Whether enterprise system sound; whether the various coordination mechanisms can play a role The number and importance of patent which enterprise owned X4= Annually income received through patents, trademarks, and others /Total income X5=Sales income of new products / Total sales income Staff turnover rate = The number of staff resignation this year / Total staff number of year beginning， Evaluation staff recognition of enterprise and dedication X7= Training cost this year / Total sales income Whether managers and staff have experience and insight matching with their posts Evaluating brand image according to its value, recognition and reputation Evaluating enterprise image in the industry according to relationship between enterprise, distributors and suppliers, influence on the industry value chain Whether enterprise has common core values and to nurture their degree The degree of staff behavior influenced by core values

Table 2. Evaluation indices system of key capabilities Variable

Type

Specific Indices Market share of main products (Y1) Market growth rate of main products (Y2) Key Marketing Advertising promotions capabilities capability capability of new products (Y) (Y3) *

Content Y1= Product sales / Market sales of similar products Y2= Product sales this year - Product sales last year / Product sales last year Enterprise capability for using advertising to promote new product sales

Existing sales network's effectiveness for Effectiveness of new products market, expanding sales distribution network (Y4) * volume and market information feedback


355

Table 2. (continued) Proportion of R & D personnel (Y5) Research Proportion of R & D and investment (Y6) development New product development capability cycle (Y7) The unique technology of production process (Y8) * Leaders and staffs’ attitudes towards learning (Y9) * Perfect and effective degree of Learning enterprise learning mechanism capability (Y10) * Reaction speed and capability for enterprise to market change (Y11) *

Innovation capability

Capability to integrate

Y5= R & D personnel / Total staff number Y6= R & D investment / Total sales income

The time for New products from pilot production to market The possibility of other enterprises imitating the technology in 3-5 years The learning idea of leaders, staff's attitude towards learning in their work Whether enterprise has mechanism to motivate staffs to learn, whether learning mechanism is effective in promoting organizational learning Enterprise capability to find market demand change, capability timely to adjust products and services Y12=The achievements number which has been Conversion rate of applied and obtained effect / The total achievements achievements (Y12) number Whether innovation mechanism can stimulate Perfect degree of innovation employee awareness of innovation, stimulate the promotion of scientific achievements into mechanism (Y13) * productive forces successfully Effective market-driven relationship between Capability to integrate external enterprise, customers and suppliers, the capability of encouraging suppliers and customers to environment (Y14) * participate enterprise innovation Capability to establish an The ability to cooperate with competitors in order to effective strategic alliance (Y15) innovation * Whether has a sound information management Capability to share information system, strong information analysis and processing (Y16) * capacities

Evaluation indices system of key resources primarily selected intangible resources because they are more potential. From organizational resources, technical resources, human resources, corporate image, corporate culture, this paper selected 12 indices. One with a * is qualitative index. From marketing capability, research and development capability, learning capability, innovation capability, capability to integrate, this paper selected 16 indices of key capabilities. One with a * is qualitative index. C. Evaluation Methods and Process Enterprise core competence is evaluated by using two variables, key resources and key capabilities. X are key resources and Y are key capabilities. X=( X1, X2, X3,……, X12)

(1)

Y=( Y1, Y2, Y3,……, Y16)

(2)

356


1) Determining the weights for each index: According to the degree of importance, we determine the weights for each index by using AHP or gray multilevel evaluation method. The specific process is omitted. It is assumed that the weights of key resources are (a1, a2, a3,……, a12), the weights of key capabilities are (b1, b2, b3,……, b16), then a1+ a2+……+ a12=1, b1+ b2+……+b16=1. 2) Determining the scores for each index according to business condition: This paper chooses Likert five level measurement method. There are both quantitative indices and qualitative indices in the evaluation system of enterprise core competence. In order to ensure evaluation objective and accurate, this paper chooses the advanced standard as evaluation standard. The grade and assignment of evaluation indices are shown in Table 3. For quantitative indices, indices value are direct calculated and compared with the advanced standard. For qualitative indices, due to the difficulty of quantitative description, evaluator's knowledge, ability, experience and level of access to relevant information are important systemic factors of affecting evaluation results. Therefore, we should carefully choose evaluation experts. Experts should have certain theoretical level and practical experience; have certain authority and representation. The members structure should be reasonable. Qualitative indices are scored by experts. 3) Computing scores of key resources and key capabilities: Multiplying the score of each index with its weights, we get to weighted numbers. Summing all the weights numbers, we can obtain specific scores of key resources and key capabilities. The scores of key resources are The scores of X=X1×a1+X2×a2+……+X12×a12

(3)

The scores of key capabilities are The scores of Y=Y1×b1+Y2×b2+……+Y16×b16

(4)

Table 3. The grade and assignment of Evaluation indices Not reached Exceed the At a Great competitive Equal to the the advanced disadvantage advanced advantage advanced level level in the industry level Assignment 1 2 3 4 5 Grade

4) Drawing Nine Grids Chart: According to the scores of key resources and key capabilities, Nine Grids Chart of core competence evaluation is drawed as Figure 1.


High 3.0 Midd le 1.5 Low Key capabilities

A

B

D

C

E

G

F

H

I

High 3.0

Middle 1.5 Key resources

357

Low

Fig. 1. Nine Grids Chart of core competence evaluation

If the enterprise is located in diagram A, B, C, indicating that its core competence is very high. If the enterprise is located in diagram D, E, F, indicating that its core competence is ordinary. If the enterprise is located in diagram G, H, I, indicating that its core competence is very weak.

4 Conclusions and Limitations This paper have studied related literatures and constructed evaluation system of enterprise core competence. It also proposed Nine Grids Chart on evaluation of enterprise core competence. Shortcoming of this paper was that it only provided a method on quantitative evaluation of enterprise core competence and didn’t use data to verify. Acknowledgment. This research was supported by PhD Foundation of North China Institute of Aerospace Engineering.

References 1. Zhang, Y.-x.: Study on Core Competence-based Diversification Strategy of Company Management. Xi’an University of Electronic Science and Technology, Xi’an (2004) 2. Prahala, Hamel, G.: Core Competence of Corporation. Harvard Business Review 68, 79–91 (1990) 3. Hamel, G., Prahalad, C.K.: Competing for the Future. Harvard Business School Press, US (1994) 4. Coyne, K.P., Hall, S.J.D., Clifford, P.G.: Is your Core Competence a Mirage? McKinsey Quarterly, Number 1, 40–54 (1997) 5. Oliver, C.: Sustainable Competitive Advantage: Combining Institutional and Resource– Based Views. Strategic Management Journal 18, 697–713 (1997) 6. Barney, J.B., Clark, D.N.: Resource-based Theory: Creating and Sustaining Competitive Advantage. Oxford University press, New York (2007)

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7. Bart, D.B.: Core Competence for Sustainable Competitive Advantage: A Structured Methodology for Identifying Core Competence. IEEE Transactions on Engineering Management 49, 28–35 (2002) 8. Jiang, Y.-l.: Study on Evaluating and Cultivating the Core Competence of the 3PL Enterprises, pp. 2–4. Tianjin University, Tianjin (2006) 9. Song, J.: Construction of Core Competence of Knowledge- based Firm Based on Knowledge Management Theory, pp. 20–22. Shanxi University, Taiyuan (2008) 10. Shi, D.-m.: Core Competence Theory. Beijing University Press, Beijing (2002) 11. Xu, F.: Strategic Management. China Renmin University Press, Beijing (2009) 12. Yang, X.-h., Wang, J.: Enterprise Strategic Management, p. 104. Higher Education Press, Beijing (2010) 13. Wang, L.-z.: A Research on Structure Model and Evaluation System of the Corporation Core Competence. Jilin University, Changchun (2004)

Automobile Insurance Pricing with Bayesian General Linear Model Cheng Gao, Qi Li, and Zirui Guo Institute of Statistics and Actuarial Science, Jilin University, Changchun, China [email protected]

Abstract. This paper applies Bayesian Model to the automobile insurance pricing in the purpose of solving the problem that the Generalized Linear Model (GLM) applied in actuarial pricing cannot reveal prior information and has too much confidence in the information from data. Under the assumption of Squared Error Loss, the estimation of the parameter in the model is the mean of the posterior distribution which was calculated by Markov Chain Monte Carlo Methods (MCMC). Finally, take the auto-insurance of WASA Insurance Company in Switzerland as an example. Run MCMC in WINBUGS software to get the estimation of the parameters, and design the comparative auto insurance tariff for this company. The comparison between the pricing utilizing Bayesian Model and that according to GLM reveals that owing to the function of prior information, the two automobile tariffs differ distinctively. Moreover, the prior information has been elegantly reflected in the Bayesian Model. Keywords: Relative auto insurance Pricing, General Linear model, Bayesian Theory, MCMC method.

1 Introduction In the field of auto insurance pricing, auto insurance pricing method is continuously developing from the early Method of Marginal Totals (MMT) to the latest General Linear Model (GLM). [1]GLM has its advantages. For example, GLM permits appropriate assumptions concerning the nature of the insurance data and its relationship with predictive variables. [2] However, disadvantages also lie in General Linear Model. For instance, it is based on fixed distributed parameter, and the randomization of parameter is not considered. What’s more, it cannot be integrated with other information besides data. Because of such shortcomings, the utilization prospects of the method are not satisfactory in Chinese insurance companies where there is not enough data of auto claim in a single insurance company. Moreover, along with change of time or macro policies, the previous vehicle insurance data cannot represent the current situation, so the pricing methods completely following the data information can cause irrationality of pricing. Therefore, it is necessary to establish a new auto insurance pricing method which is able to consider the prior information as well as data information. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 359–365, 2011. © Springer-Verlag Berlin Heidelberg 2011

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C. Gao, Q. Li, and Z. Guo

On the basis of Auto Insurance Pricing with General Linear Model, this thesis introduces Bayesian Thought and establishes Auto Insurance Pricing with Bayesian General Linear Model (BGLM). This model can not only remedy the shortage of data amount but also solve the problem of incompletely reliable data in past years due to time effect. Hence, this model will be more suitable to model the Chinese Auto Insurance Pricing.

2 Mathematical Model This thesis mainly focuses on how insurance companies should fairly and reasonably provide different insurance rates for different vehicle insurance applicants. So, this pricing model will only take the influence of claim amount on vehicle insurance rate into account. Meanwhile, this model assumes that each insurance policy is independent and policies of the same type are identical. A General Linear Model Insurance claim amount is the observed response variable in the model, marked as Y

= ( yi )n×1 ; The design matrix of characteristics of insurance bid corresponding to

( )

characterized auto insurance claim amount is X = xij

n× p

； Therein, the row i

characterizes vehicle type, vehicle age and geographic zone corresponding to the ith claim amount; line j characterizes certain characteristics of vehicle insurance claim amount (belonging to some situation marked as 1, otherwise, marked as 0). Suppose parameter vector corresponding to different vehicle types, vehicle ages and geographic zones is

β = ( β j ) p×1 .

According to the basic idea of GLM and the nature of the claim amount, variable Y is reflected by the design matrix X as follows: [2]

Y = EY + ε = e xβ + ε

ε is the error item with mean of 0. From the usual supposition of GLM, each response variable

y1 , y2 ... yn in Y is

independent and follows exponential family of distribution. [1] Besides, claim data are generally positive and have heavy-tailed property, so it is reasonable to assume that yi (i = 1,2...n) has the distribution of Gamma( ai , bi ) , that is:

f ( yi ) =

bia i ai −1 y exp(−bi yi ) τ (ai ) i

Herein, in order to use previous linear supposition, it’s necessary to connect parameter of yi with its mean. According to the property of Gamma distribution we can know that: the mean of

Gamma (ai , bi ) distribution is: u i =

ai ; it also can be known from bi

Automobile Insurance Pricing with Bayesian General Linear Model

previous

u i = exp(∑ j =1 xijβ j ) ; p

assumption:

then

we

can

361

derive

:

bi = θi , ai = θi exp(∑ j =1 xijβ j ) . p

Till Now, under the condition that β , θ are known, the likelihood function is:

L (Y | β , θ ) = ∏ i = 1 f ( y i | β , θ ) n

∏

=

ai

bi

n i =1

ai − 1

γ ( ai)

yi

exp( − bi y i )

∑

, where ai = θi exp(

p

x β j ), bi = θi

j =1 ij

Finally, the method of the traditional general linear model fixes parameter β , θ by maximum likelihood method. Then we can use the parameter to get a reasonable measure of auto insurance pricing. However, as what we have discussed before, this method is not perfect and we could use the Bayesian Thought to improve it. B Bayesian General Linear Model The introduction of Bayesian Thought is to assume prior distribution according to prior information. Then, the posterior distribution is obtained by integrating sample information with such prior information. Generally speaking, information obtained from posterior distribution is closer to true information, because it combines the sample information and expert opinions. In this thesis, suppose there are following rules for the prior distribution of parameters: (1) Assume β1 , β 2 ...β p are independent and β j ( j = 1, 2... p ) follows normal distribution N ( uβ j , σ β2 j ) .That is π ( β j ) ∝

⎧ 2⎫ ⎪ β j − u β j ⎪ . Besides, generally, exp ⎨ 2 ⎬ ⎪ − 2σ β ⎪ 2πσ β2j j ⎭ ⎩

(

1

)

variance value always has something to do with mean value, and the smaller the absolute value of mean, the smaller the variance will relatively be. Therefore, here we suppose variance of parameter is directly proportional to absolute value of mean: that is

σ β2 =| u β | γ β , where γ β is constant. j j

j

(2) Assume

j

θ1 ,θ 2 ...θ n are independent and follows inverted Gamma distribution

θi ∽ IG (mi , ni )

π (θ i ) ∝ θ i−1−m exp(− niθ i−1 ) assumption that β , θ are independent

that is:

i

and the supposition

Therefore, under the above, the prior distribution of the model is: π ( β , θ ) ∝ xp ( − ∑ i =1 n i θ i−1 − n

∑

p j −1

(β j − u βi ) 2 2σ β j 2

) ∏ i =1 n

θ 1− 1 − m σβ

i

2 j

According to Bayesian formula, it can be known that the posterior distribution of parameters β , θ is directly proportional to the product of prior distribution of

θ is fixed: π ( β | θ , Y ) ∝ L(Y | β ,θ )π ( β ,θ ) ∝

parameter and likelihood function of model. Thus, when

362


∏

θ i exp(

θi

n i=1

∑

τ (θ i e x p ( ∑

⋅ ex p (− ∑

n i =1

p j −1

x ijθ

p j =1

n iθ i− 1 −

j

)

θi exp(

x ij β j ) )

∑

(β

p

yi j

p j =1

− u βi )2

2σ

j =1

∑

2

β

x ij β

j

)∏

β

e x p (−θ i yi )

n i =1

j

Similarly, when β is known, the posterior distribution of distribution of

) −1

θ

θ i− 1 − m σ

i

2

β

j

is the same as posterior

in form.

C Estimation Method of Parameter Because this model focuses on the fairness of vehicle insurance pricing, the effect of positive and negative error of estimation is the same. Therefore, the model will obtain estimation value of parameter under Squared Error Loss assumption. Under such assumption, estimation of Bayesian Method is the mean of the posterior distribution. In order to get the mean of posterior distribution under such complex posterior distribution in this model, MCMC Method is applied to solve calculation problem of parameter β = ( β1 , β 2 ...β n ) and the concrete estimation can be accomplished by means of WINBUGS software which is specially used for solving Bayesian problems. D Insurance Tariff After parameter β characterizing the influence degree of final claim amount by different vehicle type, vehicle age and geographic zones is determined, concrete insurance tariff could be subsequently fixed. Without the consideration of such factors as claim amount, operation cost, investment income and market competition, vehicle insurance tariff only contains pure premium and the mean of claim amount of insurance bid can be taken as pricing standard for pure premium. [3] It can be known from the model above that the mean of vehicle insurance amount can

be

represented

( )

matrix X = xij

n× p

by

β = ( β1 , β 2 ...β p )

parameter

and

the

. Then, vehicle insurance amount of ith type is: C = i

p

design

∏e

x ij β

j

.

j =1

Until now, the whole model seems to be complete. However, here parametric solution of model

β = ( β1 , β 2 ...β p )

is not single, which can bring troubles to

discussion. For determining solution, we take insurance rate of a certain type of auto insurance object as the basic value b0 and suppose its parameters as 0. Then, we can obtain the relative insurance rate of set type: Ri0 =

p

∏

e

x ij β

j =1

Actual insurance rate is:

Ci = b0 Ri 0

j


363

3 Application Average sample claim amount data based on 38508 policies and 860 associated claims during 1994 -1999 provided by Switzerland WASA Insurance Company showed in Table 1.2 in [1] are used. Control variables of these data respectively are vehicle type, vehicle age and geographic zone; data of three types comprehensively construct vehicle insurance type Noxyz. Therein, x represents vehicle type: 1 represents vehicle type that has weight over 600kg and more than two gears, and 2 represents others; y represents vehicle age: 1 for less than 1 year, and 2 for 2 years or more; z represents the geographic zone: 1 for central and semi-central parts of Sweden’s three largest cities, 2 for suburbs and medium-sized towns, 3 for smaller cities, except those in 5 or 7; 4 for small towns and countryside, except 5-7, 5 for northern cities, 6 for northern countryside and 7 for island. Meanwhile, we suppose in 2000, vehicle accident rate in three large cities tends to drop because of the completion of road reconstruction in three large cities of Switzerland. The reduction of vehicle claim amount in three large cities is considered as prior information in the model. It can be found by observing data: the average sample claim amount of insurance policies of 3 types is 0 out of 28 types. For application of supposition from Gamma distribution, average claim amount 0.01 is considered to take place of average claim amount 0. Vehicle insurance object located in island with age over 1 year and weight over 600 Kg and have more than two gears is taken as basic value. Then corresponding parameters β 2 , β 4, β11 are 0. Then, when calculating, we can firstly get rid of such variables as vehicle with age over 1 year, vehicle type with weight over 600 Kg and island geographic zone. Then, design matrix X = ( x ij ) changed from matrix n× p

28 × 11 to matrix 28 × 9 . In order to get more information of the parameter and compare the results of the BGLM with that of the GLM, the results of GLM was calculated by SAS software based on the model in the part A of MATHEMATIC MODEL. Table 2 shows concrete parameter β . Taking the reduction of claim amount in three cities and the result of table 2 as prior information, the parameter β in Table 1 was obtained using BGLM and WINBUGS software. By the way, the parameter assumption for the prior distribution of BGLM is as follows: the mean of the distribution of β[5] is assumed as 1 due to the reduction of claim amount and the estimation of parameter by GLM; The mean of prior distribution of other parameters is the predictive value of the parameters in Table 2. γ β j characterizes proportion of

β j ’s variance to its absolute value of mean are all 0.002; θ i

∽ IG(2,10) ;

Then, based on the model presented in this paper and the assumptions above, the program of this model was built in WINBUGS and [4] instructs specific function of WINBUGS used in the model. Run the program to get the mean of the posterior distribution of the model, which is the estimation of parameter shown in Table 1. According to the data from Table 1 and 2, relative insurance rate Table 3 of WASA Insurance Company was designed under two models respectively.

364


The result shows that there is distinct difference between two methods. The result of Bayesian Method not only uses available data fully but also completely integrates information about reduction of claim amount after road reconstruction in three large cities, so BGLM can better suit actual situation. Table 1. Parameter Estimation Result of BGLM Variable β[1] β[2] β[3] β[4] β[5] β[6] β[7] β[8] β[9] β[10] β[11]

Predicted value 0.8928 0.000 0.6998 0.000 1.228 0.8159 0.3168 -0.7567 -1.006 -0.7523 0.000

Standard deviation 0.03673 0.000 0.03477 0.000 0.04353 0.03741 0.02443 0.03842 0.03899 0.03854 0.000

MC error 3.147E-4 0.000 2.753E-4 0.000 3.878E-4 3.386E-4 1.981E-4 2.734E-4 3.14E-4 3.261E-4 0.000

Table 2. Parameter Estimation Result of GLM variable β[1] β[2] β[3] β[4] β[5] β[6] β[7] β[8] β[9] β[10] β[11]

Predicted value 0.8435 0.0000 0.7370 0.0000 1.6815 0.8294 0.3059 -0.7620 -0.8612 -0.7533 0.0000

Standard deviation 0.4624 0.0000 0.4880 0.0000 0.8318 0.8501 0.8278 0.8403 0.9074 0.8491 0.0000

Table 3. Relative Insurance Rate Comparison Under Two Models Vehicle insurance type BGLM rate GLM rate Vehicle insurance type BGLM rate GLM rate Vehicle insurance type BGLM rate GLM rate

No111

No112

No113

No114

No115

No116 No117 No121

No122

No123

23.67

10.01

8.53

2.48

0.15

2.26

5.59

10.96

4.63

3.95

26.1

11.13

6.60

2.27

2.05

2.29

4.86

12.49

5.33

3.16

No124

No125

No126

No127

No211

No215

No216

1.15

0.07

1.04

2.59

9.14

3.87

3.29

0.96

0.06

0.87

1.08

0.98

0.98

2.32

11.23

4.79

2.84

0.98

0.88

0.98

No217

No221

No222

No223

No224

2.16

4.23

1.79

1.53

0.44

0.03

0.40

1.00

2.09

5.37

2.29

1.36

0.47

0.42

0.47

1.00

No212 No213 No214

No225 No226 No227


365

4 Conclusion Considering that vehicle insurance pricing method based on General Linear Model cannot fully integrate prior information and has too much trust in Data, this thesis proposes the improved vehicle insurance pricing method based on Bayesian General Linear Model. The effectiveness of improvement can be seen form example of WASA Insurance Company. Moreover, we think this method should be implemented in actuarial department of domestic insurance company so that vehicle pricing is more reasonable. First of all, this method can fully integrate experiential opinions of actuaries and available vehicle insurance data and is able to make vehicle insurance rate more comprehensively and reasonably. Besides, utilization prospects of formulating method of relative rate based on Bayesian General Linear Model in this thesis are rather broad and it can be easily applied to other vehicle insurance pricing models. Only by changing standard rate, factors such as operation cost, investment income and market competition can be taken into account to establish a new pricing model catering to requirements of different companies. Acknowledgment. We wish to thank Professor Wang in our department who gives us direction when we have problem in our research. We also wish to thank the other members in our group who are Yanfang Li and Haoyu He. Finally, we wish to thank the financial aid for our research from the ministry of education in China.

References 1. Ohlsson, E., Johansson, B.: Non-Life pricing with generalized linear models, pp. 3–5, 9–11, 21–22. Springer, Heidelberg 2. Anderson, D., Feldblum, S., Modlin, C., Schirmacher, D., Schirmacher, E., Thandi, N.: A practitioner’s Guide to Generalized Linear Models, 3rd edn., p. 3, 23–27 (February 2007) 3. Wulan, W.: Risk Theory, 1st edn., p. 144. China Finance and Economy Press 4. Ntzoufras, I.: Bayesian Modeling Using WINBUGS, pp. 83–108. John Wiley & Sons, Inc., Publication, Chichester

Risk Identification Based on Strategic Steps of Brand Alliances Wang Chujian School of Economics and Management, ZhengZhou University of Light Industry, ZhengZhou, P.R. China [email protected]

Abstract. The brand alliance which plays an important informational role for consumers is a double-edged sword. It has positive spillover effects on the individual brands, at the same time, it has potential drawbacks. Based on exploring formation and implementation of the brand alliances strategy, this paper sums brand alliances’ risk factors. This establishes the foundation for formulating the strategy of risk identification and for designing the control mechanism on the risk of brand alliances. Keywords: risk identification, brand alliances, consumer tendency, negative affectivity.

1 Introduction Brands play an important informational role for consumers. However, Prior research on brands has tended to focus on brand portfolio and brand extension in single or multi brand companies which is often called single-brand strategy or multi-brand strategy, rather than on cobrands in more than one different company. Brand alliances are a particular type of strategic alliance which has been growing rapidly in popularity in recent years. With the increasing importance of branding in marketing, companies often seek to enhance their brand power by joining hands with other brands (Spethmann and Benezra, 1994) [1]. Rao and Ruekert (1994) attempted to develop an understanding of the phenomenon of joint branding, to remain consistent with the literature on the strategic alliances [2], they used the term of brand alliances to describe joint branding situations and explore the reasons for such alliances. Then, brand alliances have become a popular brand strategy in practice and are gaining increasing academic attention. In an era when the cost of introducing new brands is high and success rates are low, the advantages of brand alliances become more important (Aaker and Joachimsthaler, 2000; Keller, 2003) [3][4]. Simonin and Ruth (1998) found that the cobranding alliances that were rated positively had positive spillover effects on the individual brands that formed the alliance [5]. Rao et al. (1999) proposed that weak brands should join alliances of strong brands [6]. Similar effects were reported by Washburn et al. (2004) [7], who found that consumers rated cobranded products more positively than each individual M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 366–372, 2011. © Springer-Verlag Berlin Heidelberg 2011

Risk Identification Based on Strategic Steps of Brand Alliances

367

brand. When a high equity brand was paired with a relatively low equity brand, however, the overall equity of the combination did not decline. Thus, there was no negative spillover from the low equity brand to the high equity brand. In general, a second brand provides additional information for potential customers (Abratt and Motlana, 2002) [8]. Brand alliances are believed to have become one means of sharing positive reputations and repairing scandal damages (Becker-Olson and Hill, 2006) [9]. However, does the form of brand alliances only bring about positive spillover effects? Can’t it lead to the risk, this turned out to be premature. While such positive effects of brand alliances are currently being investigated more thoroughly (Gammoh et al., 2006) [10], less attention is paid to the “dark side” of brand alliances that might appear, for example, the current research shows that partnering with high-quality brands may do more harm than good to host brands, and then some authors have acknowledged the negative effects that can derive from brand alliances (Hillyer and Tikoo, 1995; Washburn et al., 2000; Janiszewski and van Osselaer, 2000) [11] [12]. Keller and Aaker (1992) maintained that a prior, successful extension increased consumer evaluation of not only a proposed brand extension but also of a core brand itself [13]. By contrast, a poor brand extension diluted consumer evaluation of a core brand (Loken and Roedder John, 1993; Sullivan, 1990) [14] [15]. Given these potential drawbacks, brand alliances are not necessarily win/win strategies for the alliance partners (Washburn et al., 2000). Pavela and Andre(2006) fount that the blending of luxury and mass-market automobile brands in one corporate portfolio engaged advantages of scale and scope economies, but induced potentially fatal brand corrosion [16]. James’s empirical research on the reapplication of the brand extension framework to brand alliances (2006) indicated that a consumer’s attitude towards brand alliances was up to three factors: quality of original brand, fit and degree of transfer, and difficulty of making, once selecting wrong partner, brand’s character is lack in harmony, it may cause the negative influence toward brand attitude [17].

2 Strategic Steps of Brand Alliances The formation and Implementation of the brand alliances strategy sees Figure 1. A. Defining Goals of Brand Alliances Based on Strategic Objectives and Enterprise Culture Different enterprises have different strategies, strategic objectives and enterprise culture. According to the strategy and culture, the firm should define goals of brand alliances, such as develop new products, open new market. B. Analyzing Consumer Perception and Consumer Tendency Brand can bring high returns and a stable income fundamentally because of it affecting consumers’ psychology and behavior. The value of the brand is not in itself, but in the minds of customers. Therefore, the choice of brand alliances strategy should be based on customer perception. Products by brand alliances should be both advantages together and meet consumer habits.

368

C. Wang

C. Choosing the Right Partner and Brand Party selection is about to consider above all the brand image in the market. Cooperative brand culture, popularity level and similarity degree of their products are always affected the future of co-brand. Pullig et al. (2006) stated that even partners of similar product categories could harm each other if they were positioned on dissimilar attributes [18]. But also a high degree of similarity instead does not protect brands from negative spillovers. Dahlén and Lange (2006) found out that a brand could be affected by a crisis of another brand in the same product category [19]. The effect is stronger the more similar the brand associations of the brand are. Good partners adjust timely coordination of their brands and strategy which can reduce the risk.

Enterprise strategy and culture

Analyze consumer perception and tendency

Define goals

Choose the right partner

Establish operational management

Design cooperative plan

Implementation and evaluation

Fig. 1. Strategic Steps of Brand Alliances

D. Establishing Operational Management and Designing Cooperative Plan The brand alliance is a long process, its success depends on high harmony and cooperation of each member. In this process, the partners have an obligation to bear the cost for fostering co-brand, at the same time, benefit should be justly distributed, that was crucial. If the parties do not coordinate, this will directly lead to the failure of brand alliances. Therefore, it is essential to bind by the system in the strategic brand alliances. E. Implementation and Evaluation of Brand Alliances Strategy In order to adjust strategies in time, we should implement brand alliances strategy and follow up the effectiveness of implementation. Two parties should integrate all devoted resources, in order to ensure efficiency and integration, two partners must establish the appropriate communication and coordination mechanisms. Moreover, two enterprises should establish evaluation mechanisms to ensure the smooth realization of its goal of the brand alliances strategy.


369

3 Risk Identification Based on Strategic Steps of Brand Alliances Risk identification is discovering, defining, describing, documenting and communicating risks before they become problems and adversely affect a project. Accurate and complete risk identification is vital for effective risk management (see Figure 2). In order to manage risks effectively, they must first be identified. The important aspect of risk identification is to capture as many risks as possible.

Risk Identification

Risk Assessment

Risk Control

Risk Communication

Fig. 2. Process of Risk Management

Based on the strategic steps of brand alliances, we can identify the risks of brand alliances, the main risks are as follows. A. Hurting Strategic Coordination One of the key factors for brand alliances success is to maintain a strategic coordination. However, when a company decided to change its brand positioning in the market or strategy, it is possible to bring about big trouble to the other(Fan Xiucheng and Zhang Tongyu, 2003 ) [20], to avoid this problem, the cooperations must specify probable brand positioning in the future in the agreement in advance. Furthermore, when one party involved in brand alliances is purchased or taken over, this will also have an impact on strategic coordination of brand alliances, then even lead to the end of cooperation. For example, that is unhappy ending for Disney’s happy McMeal. The end of the happy meal partnership comes at a time when the processed and fast-food industries are under fire through growing concerns about expanding waistlines, particularly among children. The chief reason is for respective goals and interests. In 2003, McDonald’s wanted to get children’s recognition, McDonald’s used the new “I’m Lov’in It” taking the place of the slogans “Smile”, “Put a smile on” and “We love to see you smile”. However, the value differs greatly from Disney’s value of “Smile”, the strategic brand alliance of McDonald’s and Disney is no more. B. The Unmotivated Purpose of Brand Alliances A “Strategic Alliance” is a formal and mutually agreed partnership arrangement that links specific facets of two or more enterprises or organizations. The partners pool,

370

C. Wang

exchange and/or integrate selected resources for mutual benefit while remaining separate and entirely independent. It is a cooperative arrangement which enables partners to achieve goals together that they could not achieve alone. Strategic alliances are generally viewed as mechanisms for producing a more powerful and effective mode for competing in a globalized world. The strategic alliances have many types, the brand alliance is one of the strategic alliances, the brand alliance is shown often in the sale alliance, R&D alliance, and produce alliance. The brand alliance is diversified, so it’s easy to bring about the brand confusion by both sides, and most likely to generate the error when implementing the brand alliance. The essence of brand alliances is to expand brand awareness, and increase the profits and market value of their own products, yet without clear purpose or effective cooperation modality, that might really make both sides mistaken for the joint promotion, so brand alliances fall through in advance, the two sides should confirmation the purposes and execute mode in the first, otherwise it will cause the consequences that one false move may lose the game. C. Lacking in Harmony The different brand have separate characteristics, the other brand's personality is not always suited to their mind as people do (Blackett and Boad, 1999) [21]. Fit is particularly important for brand alliances. Brand “fit” reinforces brand position effects. If the wrong choice of a joint enterprise brand, consumers will co-brand a negative impression. James’s empirical research on the relationships of quality of original brand, fit and degree of transfer, and difficulty of making shows that once selecting wrong partner, brand’s character is lack in harmony, it may cause the negative influence toward brand attitude. D. Failed to Meet the Consumer's Psychology Brand alliances can improve the brand characteristics and image, at the same time, it can completely change the brand characteristics. Especially, branding alliances will also cause a series of problems about consumer behaviors, such as, can the new product be accepted by your old consumers? How to frame the relevance between the new product and the original? What do drive consumers to pay attention to the new brand? How can the new products link the live style of consumers? Generally speaking, your old consumers can accept the new product or not. Therefore, the first hurdle of co-branding is customers. As well, the purpose of brand alliances is to enter new markets, develop new consumer groups and increase awareness. Consumer tastes and attitudes are often changing. Consumer attitudes to new product or service by brand alliances either change or not. If consumers do not like the conversion, consumers may produce inverse psychology which will threat to each brand image. E. Inherent Risks of Brand Alliances The inherent risk of brand alliances may directly strengthen the power of competitors, thereby worsen competitive environment in the market. Because two sides are engaged in the same or similar business, or sometimes the relationship between upstream and downstream, two sides must share the certain information or technology through brand alliances, while one side is likely to get the key technological


371

breakthrough or channels control. In some cases, even one side may get more complementary effects than the other, and then brand alliances will cause to foster a competitor in the market.

4 Conclusion With the increasing importance of branding in marketing, the advantages of brand alliances is paid attention to, however, the style of brand alliances is a double-edged sword. It enhances competitive advantage, at the same time， its risks may generate in the process of the strategy. According to the idea, this paper analyzes the fundamental strategic steps of brand alliances, then identifies the main risks in brand alliances. This establishes the foundation for formulating the strategy of risk identification and for designing the control mechanism on the risk of brand alliances.

References 1. Spethmann, B., Benezra, K.: Co-brand or be damned. Brand Week, 20–24 ( November 21, 1994) 2. Rao, A.R., Ruekert, R.W.: Brand alliances as signals of product quality. Sloan Management Review, 87–97 (Fall 1994) 3. Aaker, D.A., Joachimsthaler, E.: Brand Leadership. Free Press, London (2000) 4. Keller, K.L.: Strategic Brand Management: Building, Measuring and Managing Brand Equity, 2nd edn. Prentice Hall, New Jersey (2003) 5. Simonin, B.L., Ruth, J.A.: Is a company known by the company it keeps? Assessing the spillover effects of brand alliances on consumer brand attitudes. Journal of Marketing Research 35, 30–42 (1998) 6. Rao, A.R., Qu, L., Ruekert, R.W.: Signaling Unobservable Product Quality through a Brand Ally. Journal of Marketing Research 36, 258–268 (1999) 7. Washburn, J.H., Till, B.D., Priluck, R.: Co-branding: Brand Equity and Trial Effects. Journal of Consumer Marketing 17(7), 591–604 (2000) 8. Abratt, R., Motlana, P.: Managing Co-Branding Strategies: Global Brands into Local Markets. Business Horizons 45(5), 43–50 (2002) 9. Becker-Olson, K.L., Hill, R.P.: The impact of sponsor fit on brand equity. Journal of Service Research 9(1), 73–84 (2006) 10. Gammoh, B.S., Voss, K.E., Chakraborty, G.: Consumer evaluation of brand alliance signals. Psychology and Marketing 23(6), 465–486 (2006) 11. Hillyer, C., Tikoo, S.: Effect of Cobranding on Consumer Product Evaluations. Advances in Consumer Research 22(1), 123–127 (1995) 12. Janiszewski, C., van Osselaer, S.M.J.: A Connectionist Model of Brand-Quality Associations. Journal of Marketing Research 37(3), 331–350 (2000) 13. Keller, K.L., Aaker, D.A.: The Effects of Sequential Introductions of Brand Extension. Journal of Marketing Research 29, 35–50 (1992) 14. Loken, B., John, D.R.: Diluting Brand Beliefs: When Do Brand Extensions Have a Negative Impact? Journal of Marketing 57(3), 71–84 (1993) 15. Sullivan, M.: Measuring Image Spillovers in Umbrella-Branded Products. Journal of Business 63(3), 309–329 (1990)

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16. Pavel, Andre: Brand Corrosion: Mass-Marketing’s Threat to Luxury Automobile Brands after Merger and Acquisition. Journal of Product & Brand Management 15(2), 106–120 (2006) 17. James, D.: Extension To Alliance: Aaker and Keller’s Model Revisited. Journal of Product & Brand Management 15(1), 15–22 (2006) 18. Pullig, C., Simmons, C., Netemeyer, R.: Brand Dilution: When do New Brands Hurt Existing Brands? Journal of Marketing 70, 52–66 (2006) 19. Dahlén, M., Lange, F.: A disaster is contagious: How a brand in crisis affects other brand? Journal of Advertising Research 46(12), 388–396 (2006) 20. Fan, X., Zhang, T.: Brand alliances strategy of multinational corporations. Foreign Economies & Management 09, 2–6 (2003) (in Chinese) 21. Blackett, T., Boad, B.: Co-Branding: The Science of Alliance. St. Martin’s Press, New York (1999)

The Application of Fuzzy Synthesis Evaluation Method Based on ANP in E-Business Risk Zhang Xinzhong and Qin Yamin North China University of Water Conservancy and Hydroelectric Power Zheng Zhou, China [email protected]

Abstract. E-business risk study by the application of the Fuzzy Snapper Evaluation Method based on The Analysis Network Process in project risk, analysis factors of that affect e-business risk. So concerned about the risk of change, in order to take timely measures to prevent risk. Keywords: component, E-Business Risk, risk identification, ANP, Fuzzy Synthesis Evaluation.

1 Introduction This paper draws on the existing risk management thinking and analyzes the meaning of e-commerce risk and characteristics; based on risk management, it focuses on the risk identification in e-commerce risk management and explores the types of risk factors in the process of e-commerce system development. The paper proposes the establishment of e-commerce risk assessment model is based on the evaluation of ANP fuzzy synthesis evaluation approach on e-commerce risk, providing a decision-making method that better reflects the reality of e-commerce.

2 ANP Structure Analysis ANP (The Analysis Network Process) is a decision-making method suitable for non-independent feedback system proposed by Professor T. L. saaty of University of Pittsburgh based on feedback AHP in 1996. ANP generally divides the system elements into two parts; the first part is called controlling factor layer, including issue objective and decision criteria; all decision-making criteria are regarded as independent and only dominated by the target element. The second part is known as the network layer, consisting of elements dominated by the controlling layer, with a mutual-influencing internal network structure. Figure 1 is a typical ANP structure.


374

X. Zhang and Y. Qin

target

controlling layer

criteria

criteria

P

P

element

element

element

network layer

element element

Fig. 1. Typical structure of ANP

ċ3 Decision-Making of Fuzzy Synthetic Assessment The mathematical model of fuzzy synthetic model is composed of three elements, with four steps: 1. Factor set U

= {u1 , u2 , ⋅⋅⋅, un }

= {v1 , v2 , ⋅⋅⋅, vn } 3. Single factor assessment f : U → ζ (V ) 2. Assessment set V

ui → f (ui ) = (ri1 , ri 2 , ⋅⋅⋅, rim ) ∈ ζ (V ) . The fuzzy relation R f ∈ ζ (U × V ) can be induced by fuzzy mapping f , that is: R f (u i , vi ) = f (u i )(v i ) = rij Therefore,

R f can be expressed by fuzzy matrix R ∈ μn×m :

⎡ r11 ⎢ r R = ⎢ 21 ⎢ ⎢ ⎣⎢ rn1

r12 r22 rn 2

r1m ⎤ ⎥ r2 m ⎥ ⎥ ⎥ rnm ⎦⎥

R is known as single factor assessment matrix. And (U , V , R ) constitute a comprehensive decision-making model, with U , V , R as the three factors of this model.

The Application of Fuzzy Synthesis Evaluation Method

4. Comprehensive evaluation, use

model

375

M (•,⊕) to calculate the

weight A = ( a1 , a2 , ⋅⋅⋅, an ) , and the comprehensive evaluation can be obtained.

B = Ai R 4 Establishment of Fuzzy Symmetric Assessment Model Based on Network Analysis Method A. Determine Assessment Factor Set Assume a certain thing is determined by

n factors and constitute evaluation factor set

U = {U1 ,U 2 ,

,U i ,

,U n }

B. Determine Assessment Set Assume such thing may have m reviews and constitute assessment set

V = {V1 ,V2 ,

,V j ,

,Vm }

C. Establish Single Factor Fuzzy Assessment Matrix According to the relationship between factor set and assessment set, establish the fuzzy mapping U − F (V ) of U corresponding V, suppose the evaluation vector of the single factor fuzzy evaluation

i as:

Ri = ( ri1, ri 2, , rij , , rnm ) Ri can be regarded as the fuzzy subset of evaluation set V,

rij shows the grade of

membership of the i factor evaluation on the j level, therefore, the single factor comprehensive evaluation relation matrix can be established:

⎡ r11 r12 ⎢r r Ri = ⎢ 21 22 ⎢ ⎢ ⎣ rn1 rn 2

r1m ⎤ r2 m ⎥⎥ = ( rij )nm ⎥ ⎥ rnm ⎦

These steps are in correspondence with the fuzzy synthetic assessment. D. Determine the Weight by ANP In the system, assume the factors in the controlling layer of ANP model including p1 , p2 , ⋅⋅⋅, pm ; the network layer of the controlling layer has the element set of

C1 , C2 , ⋅⋅⋅, Cn , of which Ci has elements ei1 , ei 2 , ⋅⋅⋅, ei ni , therefore, the index

weight steps for weight calculation can be summarized as: 1. Determine the weight matrix of the element set, also known as the main factor later. Take 0~9 as the scale, take the control layer element ps ( s = 1, 2, ⋅⋅⋅, m) as criterion; and one element of

Ci (i = 1, 2, ⋅⋅⋅, n) as sub-criterion, conduct relative

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influence degree comparison among other factors, constituting n comparison matrixes; calculate the corresponding characteristic vector of each matrix’s maximum characteristic value, and then carry out consistency test. 2. Determine the super-matrix of the sub-factor layer. Take the control layer element ps ( s = 1, 2, ⋅⋅⋅, m) as the criterion, and the element ei k ( k = 1, 2, ⋅⋅⋅, ni ) of

Ci (i = 1, 2, ⋅⋅⋅, n) as the sub-criterion, conduct dominance degree comparison among elements in element group C1 , C2 , ⋅⋅⋅, Cn according to their influence on ei k . It is similar to the weight matrix calculation, construct the weight matrix of the sub-factor n

group to form a

∑n i =1

i

order super-matrix and this super-matrix is composed of

n block matrices. 3. Determine weighted super-matrix. Multiply each matrix element in the weight matrix of the main factor layer with the super-matrix block in the sub-factor layer to constitute weight matrix. Weighted super matrix reflects the main factor’s control on the sub-factor and the sub factor’s feedback to the main factor. 4. Solve the index weight. For the weighted super-matrix, use the corresponding calculation method to determine the relative weight vector, that is, the weight of the n

∑ n element according to their catalogue. i =1

i

E. Comprehensive Evaluation Use model M (•, ⊕) to calculate weight C and get the comprehensive evaluation:

B =C•R ⎧ ⎨bt The corresponding review of Max 1≤t ≤ ⎩ the greatest risk factor/ .

⎫

n

∑ b ⎬⎭ (the maximum degree of membership) is t =1

t

5 The Establishment of a Certain e-Commerce Risk Index System Through the analysis on risk factors influencing a certain e-commerce, conduct investigations and consultations from a number of experts with rich practical experience by Delphi method as well as refer to a lot of existing research data to establish the comprehensive evaluation index system by e-commerce factors; meanwhile, because there is a certain ambiguity in risk measurement, divide the risk degree into five levels. ⎧High risk、relatively high risk、 medium risk、⎫ V =⎨ ⎬ ⎩relatively low risk、 low risk ⎭ = {v1 , v2 , v3 , v4 , v5 }

A. The Establishment of Network Analysis Structure Model Based on the above analysis on e-commerce risk assessment index system, the interaction model of network analysis has collected the scores made by 20 experts on


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the above-mentioned risk sub-factor layer evaluation index factors, and the evaluation results are shown in Table 1: Table 1. Comprehensive Evaluation of risk factors for an e-business Main factor layer

Sub-factor layer Economic policy e11 Market structure e12 Cost budget e13

Cost risk C1

Organization risk C2

System security analysis C5 Technical C6

Low risk 0

0

9

9

2

0

0

5

5

4

6

0

0

8

6

6

Organization structure e22

0

10

5

5

0

0

4

6

4

6

0

5

5

5

5

0

0

10

10

0

0

0

5

5

10

0

5

8

4

3

0

5

7

4

4

10

3

2

5

5

Project management risk e41 risk Project demand risk e42 Environment condition risk e43 Network condition risk e51

risk

Relatively Medium Relatively high risk risk low risk 10 10 0

Human resources status e21 Contract risk e23 Project member efficiency e24 tool Development Development Environment availability e31 risk C3 Development tool quality e32

Project analysis C4

High risk 0

12

5

3

0

0

Operation system risk e52

10

5

4

1

0

Data access risk e53

14

4

2

0

0

Technical difficulty e61

10

4

4

2

0

Technical applicability e62

0

6

5

4

5

Technology life circle e63

16

4

0

0

0

According to Table 1, establish multi-indexes fuzzy evaluation matrix and conduct standardized treatment. B. Determine the Weight and Sorting of Various Risk Factors In the comprehensive evaluation of e-commerce risk factors, the determination of risk factor weight vector is the crucial step of the entire e-commerce risk factor sorting; meanwhile, it is also the core of ANP risk assessment. According to the risk factor influence relation and ANP structure model, the calculation of e-commerce risk factor weight should be carried out according to the following steps: 1. Determine the weight matrix of the main factor layer The influence relation among various evaluation factors can be seen from the e-commerce ANP model. Through constructing judgment matrices, calculate the corresponding eigenvector of each maximum eigenvalue and conduct normalization treatment, thus obtain the weight matrix of main factor layer.

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2. Determine the super matrix of the sub-factor layer (1) In element set C1 (cost risk), take element e11 (economic policy), e12 (market structure), and e13 (cost budget) as criteria, carry out indirect dominance comparison of various factors according to the influence degree to constitute judgment matrix and calculation weight vector. (2) Repeat the above steps and the judgment matrices of elements sets such as C2 (organization risk), C3(development environmental risk), C4(system security risk), C5(system security risk) and C6 (technical risk) can be obtained. (3) According to the same calculation method, the judgment matrix can be obtained and the factor layer super matrix W will be solved; the calculation weight is as follows according to the W structure fuzzy weighted super matrix: ⎡ a11W11 ⎢a W ⎢ 21 21 ⎢a W W = W • A = ⎢ 31 31 ⎢ a41W41 ⎢ a51W51 ⎢ ⎣⎢ a61W61

a12W12 a22W22 a32W32 a42W42 a52W52 a62W62

a13W13 a23W23 a33W33 a43W43 a53W53 a63W63

a14W14 a24W24 a34W34 a44W44 a54W54 a64W64

a15W15 a25W25 a35W35 a45W45 a55W55 a65W65

C. Comprehensive Evaluation Conduct calculation with model M (•, ⊕ ) T

⎡ 0.002 ⎤ ⎡0.00 0.50 0.50 0.00 0.00 ⎤ ⎢ 0.002 ⎥ ⎢0.00 0.45 0.45 0.10 0.00 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ 0.003⎥ ⎢0.00 0.25 0.25 0.20 0.30 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ 0.040 ⎥ ⎢0.00 0.00 0.40 0.30 0.30 ⎥ ⎢ 0.093⎥ ⎢0.00 0.50 0.25 0.25 0.00 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ 0.041⎥ ⎢0.00 0.20 0.30 0.20 0.30 ⎥ ⎢ 0.016 ⎥ ⎢0.00 0.25 0.25 0.25 0.25⎥ ⎥ ⎢ ⎥ ⎢ ⎢ 0.307 ⎥ ⎢0.00 0.00 0.50 0.50 0.00 ⎥ ⎢ 0.307 ⎥ ⎢0.00 0.00 0.25 0.25 0.50 ⎥ ⎥ •⎢ ⎥ B =C•R = ⎢ ⎢ 0.019 ⎥ ⎢0.00 0.25 0.40 0.20 0.15⎥ ⎢ ⎥ ⎢ ⎥ ⎢ 0.022 ⎥ ⎢0.00 0.25 0.35 0.20 0.20 ⎥ ⎢ 0.036 ⎥ ⎢0.50 0.15 0.10 0.25 0.00 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ 0.021⎥ ⎢0.60 0.25 0.15 0.00 0.00 ⎥ ⎢ 0.047 ⎥ ⎢0.50 0.25 0.20 0.05 0.00 ⎥ ⎥ ⎢ ⎥ ⎢ ⎢ 0.027 ⎥ ⎢0.70 0.20 0.10 0.00 0.00 ⎥ ⎢ 0.003⎥ ⎢0.50 0.20 0.20 0.10 0.00 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ 0.004 ⎥ ⎢0.00 0.30 0.25 0.20 0.25⎥ ⎢ ⎥ ⎢ ⎥ ⎣ 0.010 ⎦ ⎣0.80 0.20 0.00 0.00 0.00 ⎦ = (0.083, 0.103, 0.324, 0.395, 0.180)

a16W16 ⎤ a26W26 ⎥ ⎥ a36W36 ⎥ ⎥ a46W46 ⎥ a56W56 ⎥ ⎥ a66W66 ⎦⎥


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According to the principle of maximum membership degree, the maximum value is 0.395, showing this project is highly risky.

6 Conclusion Establish risk assessment model through comprehensive application of network analysis and fuzzy evaluation method; through combining qualitative analysis and quantitative calculation, tightly combine the decision makers’ subjective judgment and reasoning to carry out quantitative description of the decision maker’s reasoning process thus apply it in the decision-making issues with multi-criteria, complex structure and are difficult to quantify, providing scientific basis for decision-making. On the basis of the current e-commerce risk assessment method, propose ANP based fuzzy synthetic evaluation method in accordance with network analysis method and fuzzy synthetic judgment decision-making theory; try to seek a reasonable risk assessment method to solve risk management issues full of fuzzy information by applying such method in risk management.

References 1. Yang, Y., Feng, W.: Fuzzy AHP in the evaluation of construction projects. Construction Economics, special issue (2006) (in Chinese) 2. Fikset, J.: Risk Analysis in the 1990s. Risk Analysis 2 (1990) 3. Singh, M.P., Travis, C.C.: Environmental Risk Analysis: An Overview. Risk Analysis 3 (1991) 4. Jaafari, A.: Management of risk, uncertains and opportunities on projects:time for a fundanmental shift. International Joural of Project Management (1999)

Research and Application of Three Dimensional Visualization of Geological Objects Hua Li and Hao Wu Resource and Environmental Engineering Institute, Wuhan University of Technology, Wuhan, the People’s Republic of China [email protected]

Abstract. There are three modeling methods about the geological bodies, including the facial model, the volumetric model and the mixed model. This paper gives the reason why the facial modeling is still the main modeling method at the present stage. Also we presented a sort of three dimensional(3D) modeling approach which is suitable for the stratified geological bodies: first of all, we use DEM method to fit every stratum based on the stratum data of the bores. Then we show all DEM facial models and lastly construct entities through sewing the neighboring boundaries of the all layer. We also design and exploit a visualization system of the geological objects visualization system using the component technology. The system includes the data source management component, data dictionary management component, geological object core component, three dimensional control component. The system has the function to read the original data of the geological survey, display and query information about the stratums and also subdivide the section planes. The establishment of the system can provide reference to create the other similar system. Keywords: three dimension, visualization, component, geological objects, facial model.

1 Introduction Geological objects are composed of different kinds of data, such as borehole data, topography data, rock and soil data, geophysical and hydrological data[1]. With the development of computer technology, the techniques of interactive modeling and visualization about geological objects help overcome the shortcomings of the traditional method, such as tables and plots[2]. The research of 3D visualization has a wide scope, including the spatial modeling, 3D visualization and Three-dimensional topology. The spatial modeling method of the geological objects are the main topic in the 3D GIS domain. Over the past decade, researchers presented more than 20 kinds of spatial modeling, which can be generally classified into the facial model, the volumetric model and the mixed model[3]. Since the facial model has strong modeling capabilities and can realistically represent the outline of the geological body. And it is very suitable M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 380–386, 2011. © Springer-Verlag Berlin Heidelberg 2011

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for the human visual habit. While the technique about the volumetric model is not perfect, and the volumetric model has the poor interactivity. So the facial model is still the major modeling method nowadays[4]. The research domain is the geological survey. Through the data analysis about the research domain, we can draw the conclusion that the facial model can satisfy the geological modeling and visualization.

2 Methodology A. Data Model Research As the above narrated, the geological survey is the research domain, so the bore data and the stratum layer based on bores is the most direct data source of the geological body 3D modeling. We can use the data to simulate the 3D stratums, geological structures and the complex geological bodies. Figure 1 shows the three-dimensional database model diagram based on the bores. We can apply the database to store the raw data uniformly based on this model, then provide the data source to simulate, display and analyze the 3D geological body. The data model is mainly composed of four data tables, which are bore data table, stratum data table, segment data table about stratum, the stratum metadata table. Also, the data model diagram indicates the relationship between these tables.

Fig. 1. Three-dimensional database model diagram based on the bore

B. Modeling Study about the Geological Body Through the data analysis about the geological survey, the raw data are the 2.5, 2.75 dimensional data, also called quasi-three-dimensional data. And most of the geological bodies are Stratiform, so we can construct these geological bodies using the facial model. The following is the specific method: firstly we apply the layer data about the

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bores to fit each layer according to the digital elevation model method, and show the above every layer at the same time, then construct entities through sewing the neighboring boundaries of the all layer. The 3D modeling process is shown in figure 2.

Fig. 2. The 3D modeling process diagram

C. Algorithm Study 1) The single stratum modeling algorithm We use triangulated irregular network (TIN)[5] to build the single stratum of the geological body, and set up TINS to cover the entire area using the scattered bore points. It is the key technology to determine which of the three discrete data points form an optimization triangle, and insure that each discrete sampling point is the vertex of a triangle. 0

a

1

b ⊩

3

2

c

d

4

e

Fig. 3. The triangular surface reconstruction method

2) Algorithm about sewing the neighboring boundaries of the stratums Geological survey area involves mostly layered rocks, for each layer rock, it simply consists of front, back, left, right, top and bottom interface. Top and bottom interface are the neighboring stratum, so front, back, left, right interface can form through sewing the neighboring stratums.


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The sewing method is that any two neighboring stratums establish some triangleshaped surfaces. The basic idea is to connect the adjacent triangle mesh nodes of the stratums grid model border, and complete the triangular surface reconstruction between two neighboring stratums. The method is shown in figure 3. 3) Subdivision algorithm Based on the 3D geological model, we can clearly understand the geological model inside through subdividing the geological model to form the sections. Sections are subdivided by the following two steps: firstly section plane intersects every stratum and its segments to create lines, then the neighboring section lines can be sewed to generate the triangle meshes of the section plane. D. System Design and Implementation We design and implement a 3D geological objects visualization system(Geo3DModel System) based on the three-dimensional visualization data models and the above algorithm. The system stores data in a SQL Server database, reads the original data of the geological survey, uses the appropriate data model to build three-dimensional geological bodies which can visualize, display and operate. System is based on C/S structure and uses the component-based development techniques[6]. The system consists of four components (one control, three DLL, includes the data source management component, data dictionary management component, geological object core component, three dimensional control component) and a master calling program. The control(moSite3D.ocx) is written in C++ and the others in C#.Net[7]. The system component structure based on UML(Unified Modeling Language) is shown in Fig.4, the upper components depend on the underlying components.

Fig. 4. Three-dimensional visualization components diagram of the geological bodies

In the figure 4, the GeoCoreLib component((geological object core component)) is one of the most important components. The component implements the properties, methods of the core classes and their relationships, these classes include bore, stratum, segment about stratum, the stratum metadata. And the component also provides external interface for external application to access and operation. The class diagram of the GeoCoreLib component is shown in Figure 5.

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Fig. 5. The classes diagram of the GeoCoreLib component

The GeoCoreLib component was fulfilled by the collection classes and the single class based on the above class diagram. All bores compose a collection class(clsBores) and a single bore composes a single class(clsBore). Because of a bore can contain multiple stratum data records, so we can use a collection class(clsBoreLayers) to represent them. While a single stratum can be represented by clsBoreLayer. The segment about the bore also depends on the same principle.

3 Application Based on the above data model, algorithm, design thinking and process, we design and exploit a visualization system of the geological objects. The system can simulate the whole three-dimensional structure of the geological survey area, and display the every stratum information and the custom section planes. You can take a variety of display mode to build a three-dimensional view, and can freely zoom in, zoom out and rotate three-dimensional landscape field. Also you can query and analysis the arbitrary stratum, section plane. At the same time, you can fulfill the stratum color setting and texture setting using the system. The functionality of the system(The system is shown in figure 6) is described below: a) Display: The system displays the three-dimensional figure of the specified field in the geological survey area and can manipulate the three-dimensional figure, including zoom in, zoom out, rotate roaming, etc.


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b) Display mode: you can change the three-dimensional display mode according to the customer requirements, including the grids display, the 3D scatter points display, the survey points solid tubes display, the entities display and the section planes display. c) Any section plane subdivide: you can subdivide and display any custom section planes. d) Query: you can select and query information about the bores and the stratums.

Fig. 6. The classes diagram of the GeoCoreLib component

4 Conclusion As we known, there are three modeling methods about the geological bodies, including the facial model, the volumetric model and the mixed model. The facial modeling is still the main modeling means at the present stage, because the facial model has very strong modeling capability and is suitable for the human visual habits. We presented a sort of 3D modeling approach which is suitable for the stratified geological bodies: first of all, we use DEM method to fit every stratum based on the stratum data of the bores. Then we show all DEM facial models and lastly construct entities through sewing the neighboring boundaries of the all layer. We also design and exploit a visualization system of the geological objects visualization system using the component technology. The system includes the data source management component, data dictionary management component, geological object core component, three dimensional control component. The system has the function to read the original data of the geological survey, display and query information about the stratums and also subdivide the section planes. Although the system has the above function, but for the faults, folds and other more complex geological structures, the system’s modeling capacity is not very strong. So how to model these more complex geological structures is our next step research orientation[8].

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Acknowledgment. This research was supported by the Natural Science Foundation of China(Grant no. 40901214) and the Fundamental Research Funds for the Central Universities(Grant no.2010-IV-076).

References 1. Guo, Y., Li, L.: Structural Geology, simple tutorial. China University of Geosciences press, Wuhan (1995) 2. Zhang, L.Q., Tan, Y.M., Kang, Z.Z., et al.: A methodology for 3D modeling and visualization of geological objects. Sci. China Ser. D-Earth Sci. 52(7), 1022–1029 (2009) 3. Wu, L.-X., Shi, W.-Z.: Geographic Information Systems Theory and Algorithm. Science Press, Beijing (2003) 4. Brooks, S., Whalley, J.L.: Multilayer hybrid visualizations to support 3D GIS. Computers, Environment and Urban Systems 32, 278–292 (2008) 5. Yong, X., Sun, M., Ma, A.: On the reconstruction of three-dimensional complex geological objects using Delaunay triangulation. Future Generation Compute Systems 20(7), 1227–1234 (2004) 6. Takatsuka, M.: A component-oriented software authoring system for exploratory visualization. Future Generation Computer Systems 21(7), 1213–1222 (2005) 7. Wang, S.: Master Visual C# 2005—Language base, database and Web exploit. Posts & telecom press, Beijing (2007) 8. Wu, Q., Xu, H.: An approach to computer modeling and visualization of geological faults in 3D. Computers & Geosciences 29(4), 503–509 (2003)

The Control and Measure of Requirements Stability in Software Project Chen Ting Faculty of Mechanical & Electrical Engineering Kunming University of Science & Technology Kunming, P.R. China

Abstract. In the development of software project, requirements stability is an important factor which relates to success or failure of software project. This paper made a detailed analysis of the factors of affecting the requirements stability, proposed the control method of the requirements stability, constructed the control process of requirements change, and has conducted the research on the measure of the requirements stability for achieving the purpose to grasp the degree of the requirements change effectively, minimize the defects and risks caused by it, and ensure the successful completion of software project according to a predetermined cost, schedule, and quality. Keywords: Software engineering, Requirements stability, Control, Measure.

1 Introduction With the fast development of global economy & technology and the speed-up of the process of social informationization, computers are widely used in various industries, all kinds of application software come into being, and the management or production of various industries is becoming more specific, digitized, quickly. Then users' demand for computer software is getting more and more complex, the scale is getting bigger and bigger, the degree of requirements instability is increased along with it. In the development of software project, the quality and stability of requirements play a critical role regarding labor costs and deliverables quality of the project. Unstable requirements will inevitably cause extension delivery of the system, serious decline in quality, user dissatisfaction increasing, cost overruns and other issues. On the one hand the requirements change is inevitable, and it follows the entire software development lifecycle, on the other hand we must take effective measures and means to minimize the requirements change as far as possible, reduce influence caused by it. Therefore, through carrying on the control and the qualification to the requirements stability of software project can grasp the degree of requirements change of software project effectively, minimize the defects and risks caused by it, and ensure the successful completion of software project according to a predetermined cost, schedule, and quality.


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2 The Factors Affecting Requirements Stability Compared with traditional industrial production, software requirements are with the characteristics of fuzzy, implicit, uncertainty, variability and subjectivity, and so on. It makes requirements change become an inevitable problem which is most difficult to grasp in software project. There are many factors affecting requirement stability, summarized in the following four aspects: A. User-Side Factors Users are the proponent of project requirements. Determining users’ final requirement is a very difficult thing. This is because most users lack computer knowledge, or because of insufficient knowledge of information systems, not pay enough attention to the requirements, abstract level of their own business is not enough, and the coordination level with the developer is not enough. At the beginning of the project, users can not determine what the computer can do for themselves, can not do. So users often can not accurately express their requirements. However, it is unrealistic to require users to make all requirements clear one-time and do not allow any changes in requirements since then. With the continuous advance of the development progress for software projects, users gradually deepen understanding of the system, have the new understanding of requirements, and then put forward new requirements which are more meet their needs. B. Development-Side Factors Because of the existence of such problems for developing-side, such as they do not know users’ business processes, it is inadequate to communicate and exchange with users, the communication skills are not high, the knowledge reserve of requirements analysts is not enough, the technology of requirements engineering is not sophisticated, the requirements for research, analysis, definition and assessment is not enough detailed, clear and full, the requirements description exists ambiguity, lead to the questions are implied in the requirements specifications, failed to obtain the potential requirements of users accurately and comprehensively until it was discovered during the development process. Such requirements changes are the most common change reasons in the process of software development. It is also requirement change problems which requirement analysts and software developers are most concerned about. Moreover it will also result in the requirements change such as the project management is not standardized, the development method is not flexible, the contract binding on the user is not enough, the research range is uncertain, etc. C. System Factors With technology updating of hardware system, operating system and system software, there are requirements change in the security and compatibility aspects of the original design. For example, operating system changes from Windows 9X to Windows 2000/XP, IE upgrades from 5.0 to 6.0 or 7.0. D. Work Environment Factors It refers to requirements change related to software running, such as the changes of work systems, or regulations and policy, the continuous expansion of business scope, the continuous changes of business processes, the continuous innovation of management model, or business requirements changes. Such requirements changes often appear in

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the professional software. For example, the requirements change of financial software resulting from changes in accounting system, the requirements change of tax software resulting from changes in tax policy, etc. System factors and work environment factors are closer to a "force majeure" relative to the other two factors in these four factors. So the requirements analysts, system designers and developers should pay more attention to user-side factors and development-side factors, and reduce the requirements change outside of "force majeure" to a minimum as much as possible [1].

3 Control Methods and Measurement Since the requirements instability is an objective reality, then the correct treatment of requirements change, the courage to accept it, be proactive response to the changing requirements using new technologies, so-called "embrace change". Requirements change is not necessarily a bad thing, it could also be a good thing, because we can create and win the opportunity in the process of requirements change. A. Control Method •

•

•

In order to the developers can understand users’ requirements better, it is necessary to make a training of the developers on the related knowledge in the initial stages of doing requirements analysis. At the same time make a timely introduction of both sides recognized experts, and the experts feel the pulse for some key issues can also avoid some unnecessary requirements change. It must be emphasized the active participation of users in the development process of the system. Through collaboration and communication, development-side should get a common language with users, reach a consensus, and help users who are not familiar with computer to establish the common concept of software development. When users propose requirements change, the developers should carefully listen to the users' requirements, make a collation and analysis. Even if the users propose some "excessive" requirements, must carefully analyze the reasons and propose viable alternatives. Note to users that these requirements change will bring the adverse consequences to the development of the entire project. It allows users to realize that computers can not solve all the exist problems currently because of the constraints of technical, human and other resource. And the development of software product requires a certain period, too much requirements and too frequent changes will increase the development costs and duration extension to some extent. When developers sign the project contract with users, can increase some of the relevant terms about requirements change, clear the responsibility and obligation that both parties should bear, and reduce the friction between the two sides and random requirements change to some extent. Such as the establishment of a deadline for requirements change, the circumstances in which users can change the requirements, and what requirements change can be accepted by the development-side, etc.

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•

•

Requirements must be logged into the document and take good care of them, it is very important. The final result of requirements analysis is the specific document prepared by both sides when developers and users reach a consensus on the products to be developed. With this document, even if the changes for the role of the developer will not affect the preparatory work of requirements analysis. Each requirement change can be identified with a new version [2]. The version control of requirements document is an essential aspect of requirements management. It is likely to result in a variety of waste without good requirements document management. The version control must do the following: it needs to be unified to determine each version of requirements document, ensure that each member can get the current version of the requirements; the changes are written the documents clearly and timely notify the staff involved in project development; it should only allow the specified people to update requirements document in order to reduce confusion, conflict and misunderstanding. Simply put, the version control of requirements document is to ensure the relevant personnel have the latest version of requirements document and record history version of requirements. In addition, throughout the development process, it must carry on the requirement track, the aim is to establish and maintain the consistency and integrity from the beginning of users’ requirements to test, and ensure that all implementation is based on users’ requirements, while ensuring that all of the output is compliance with users’ requirements [3]. According to the experience of project management, carrying on the requirements change assessment is not only necessary but also essential. Generally, the project manager carries on first trial in order to improve working efficiency. As the project manager is more familiar with the project, his first trial can filter out unreasonable requirements change and some requirements change that are micro and easy to implement. The former will not be considered, the latter can enter the implementation process of requirements change directly. After first trial is passed, the review should be organized. Large projects or important requirements change should establish change control board of the project or similar organizations with related functions to be responsible for determining which changes to accept. CCB is composed together by multi-staff the project involved. It should include decision-makers of user-side and development-side. It needs to combine a variety of assessment methods in the assessment stage, fully listen to the views of all sides, allow different people to verify the requirements from different perspectives. The contents to be verified include requirements feasibility, integrity, consistency and accuracy, etc. As the authors of the requirements, users are one of the most authoritative spokesmen. In fact, in the assessment process of requirements, users often can provide many valuable advices. At the same time, this is the final opportunity that users confirm the requirements. It can effectively reduce the occurrence of requirements change. Ultimately, reach agreement among users, requirements analysts and R & D staff and form the final treatment views. It should determine requirements baseline after formal assessment and confirmation. The further requirements change based on the baseline will be carried on according to


•

391

change process of the project definition. Setting the requirements baseline can minimize trouble caused by requirements change. Most users do not like the control of requirements change. In fact, the standardized change control process is not a man-made obstacles, but a funnel and filter mechanism. It can ensure that the project includes the most appropriate requirements and reduces the number of random changes effectively, enables changes in a controlled implementation process, thus ensures requirements stability. The control process of requirements change must be drawn up before the first requirements change of the system occurs. The control process of requirements change, shown in Figure 1.

Fig. 1. The control process of requirements change

•

•

When the requirements change, in order to better adapt to requirements change, the requirements analysts can use technical countermeasures, such as rapid prototyping, agile software development and software reuse technology, etc. The requirements analysts can also use requirements management tool. The commonly used requirements management tool has CA Corporation's CA-Super Project & Project Software and Rational Corporation's Analyst Studio, etc [4]. From the perspective of analysis and design of software systems, through using rational analysis & design method, such as object-oriented technology, and good architecture can effectively reduce the risks and maintenance costs caused by requirements change [5].

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•

•

After the reexamination of requirements change passes, the project manager should implement requirements change as soon as possible, make reasonable, complete and clear division of labor, determine implementers and testers of requirements change. It should generally be considered that the original requirements implementers make a realization of requirements change directly. After the implementation of requirements change, the project team should organize to test requirements change. Regarding the test of requirements change, it should make the complete testing for related functions in order to avoid other problems caused by requirements change.

The above-mentioned control method seems simple, but it is difficult to implement the method truly. It needs to coordinate with the actual work of the project team based on theoretical knowledge, make concrete analysis of concrete and constantly explore and summarize in practice. B. The Measurement According to the project characteristics and requirements of business management, the requirements change often needs to be controlled below a certain threshold. For example, a company has the following requirements in the project until the end of the project: The total number of aggregate requirements ≤ number of initial requirements × 130%, namely, number of appended requirements is not more than 30%; The total number of aggregate requirements changes ≤ number of initial requirements × 60%, namely, aggregate requirements changes are not more than 60%. To meet these requirements, first, we need to make an entry and centralized management for the requirements. This is also a prerequisite for the measurement of requirements stability. Therefore, in the analysis of project requirements, the developer statistic number of initial requirements, number of appended requirements, number of removed requirements and number of modified requirements at regular intervals, such as one month. Then requirements stability and rate of change in requirements are determined by calculation. Table 1 is requirements statistics data first six months in 2009 that the company implements a software project: Table 1. Requirements statistics data Month

Number of Number of Number of Number of Number of initial appended removed modified unchanged requirements requirements requirements requirements requirements

The total The total Rate of number of number of Requirements change in current requirements stability requirements requirements change

1

25

1

1

0

24

25

2

96.00%

8.00%

2

25

3

0

1

24

28

4

85.71%

16.00%

3

28

2

1

0

27

29

3

93.10%

10.71%

4

29

1

0

0

29

30

1

96.67%

3.45%

5

30

1

1

1

28

30

3

93.33%

10.00%

6

30

0

0

1

29

30

1

96.67%

3.33%

Of which: Number of unchanged requirements = number of initial requirements - number of removed requirements - number of modified requirements


393

120. 00% 100. 00% 80. 00% changes

Requirements stability/Requirement rate of

The total number of current requirements = number of initial requirements + number of appended requirements - number of removed requirements The total number of requirements change = number of appended requirements + number of removed requirements + number of modified requirements Requirements stability + number of unchanged requirements / the total number of current requirements Rate of change in requirements = the total number of requirements change / number of initial requirements The total number of aggregate requirements = 30 ≤ number of initial requirements × 130% = 25 × 130% = 32.5 The total number of aggregate requirements change = 14 ≤ number of initial requirements × 60% = 25 × 60% = 15 Therefore, the requirement change met this project demands. Requirements stability & rate of change in requirements are shown in Figure 2.

Requirem en t s st abilit y

60. 00%

Requirem en t rat e o f ch an ges

40. 00% 20. 00% 0. 00% 1

2

3

4

5

6

Month

Fig. 2. Requirements stability & rate of change in requirements

Currently, there is no uniform standard about the calculation of requirements measure in the industry. For some special cases, the corresponding rules of data collection can be given combined with the specific characteristics of the project. For example: A requirement is broken down into two; two requirements gather are a requirement. It is not purpose to collect measurement data simply. It is the fundamental purpose to grasp the degree of requirements change, prevent and control requirements change, reduce the risks caused by requirements change through carrying on the qualification to the requirements stability and analyzing data.

4 Conclusions Currently, there are many problems to be studied about the control of requirements stability. It is impossible to stabilize requirements completely, only try to avoid and reduce the impact of requirements change, and actively respond from thinking, management and technology aspects. Thinking aspect refers to solve problems mainly

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from the subjective understanding; Management aspect refers to specify the control process of requirements change, enhance the training and exchange, etc. Technology aspect refers to control requirements change through the introduction of advanced technology. The ways to improve the stability of the requirements is not fixed. Although the different project teams use the different methods, the ultimate goal is to improve the requirements stability. The practice proved that requirements stability control the better, the success rate of software projects is higher.

References 1. Wang, Q.: The Management of Requirement Changes in Software Project. Computer Knowledge and Technology(Academic Exchange) 6, 1342–1343 (2007) 2. Meng, y.: Elementary Explanation of Requirements Analysis in the Development Process of Software Project. Science &Technology Information 11, 43–44 (2009) 3. Jiang, x., Wang, c.: Research on Management of Software Project Requirement. Computer and Modernization 2, 19–21 (2006) 4. Jiang, h.: Requirements Analysis and Requirements Change of Software Development. Fujian Computer 8, 65–66 (2009) 5. Zhang, x.: Research on Requirements Change Management of Software Project. China Science and Technology Information 01A, 107–108 (2006)

A Novel Initial Radius Selection with Simplify Sphere Decoding Algorithm in MIMO System Song Yang, Li Jianping, and Cai Chaoshi School of Information Engineering Communication University of China Beijing, China [email protected]

Abstract. Sphere decoding (SD) is an efficient algorithm which has been proposed in Multiple-input Multiple-output(MIMO) digital communications. Sphere decoding has been shown to achieve near-ML performance with low complexity which can avoid searching for the element. However, SD also has high complexity in some situations. The complexity of the algorithm is controlled by radius .Thus, it is important to choose a fit initial radius for SD which trade-off the performance and complexity. Chen-Lee sphere decoding algorithm can increase the size of the search region. In this paper, we propose a novel scheme to reduce the initial radius in Alamouti code decoding though combined with Chen-Lee sphere decoding algorithm and the average energy of qQAM constellation. The simulation results show when BER is below 10-4, the proposed scheme can achieve about 0~1 coding gains over Rayleigh fading channels. Keywords: MIMO, SD, STBC, ML, Alamouti code, initial radius.

1 Introduction Multiple-input Multiple-output(MIMO) wireless transmission systems have been intensively studied during the last decade. With MIMO system[1-2], the original one is transmitted on individual antennas. Space-time block code(STBC), is one of the key encoding techniques for MIMO system. Alamouti code [3], which increases the capacity of wireless systems with a relatively simple receiver structure and achieves the full diversity promised by the transmitter and receiver antennas, is an important space-time block code(STBC) of the STC family. Alamouti code has two transmit antennas and one receiver antenna, which can provide temporal diversity. STBC based on the ML detection can achieve the best bit error rate performance among all kinds of detection methods in MIMO system. However, the ML detection is its huge computational complexity. Sphere decoding(SD)[4], was introduced to perform ML detection, which achieves reduced complexity by searching over the lattice points. Sphere decoder based on Viterbo-Boutros scheme [5-6], and other algorithms for closest point search [7-9].The choice of method for solving the closest point problem depends on the structure of the lattice. Therefore, the method requires estimation of an M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 395–402, 2011. © Springer-Verlag Berlin Heidelberg 2011

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initial search radius. The radius is controlled by the complexity of the algorithm and plays a critical role in identifying the correct point in the lattice. However, the initial radius selection is still a problem in the decoding. If r too small, it leads to low probability of finding the ML solution and if too large, it results in a sphere containing more lattice point, named candidates . In[10-15] some of methods have been intruded to choose r and trade-off between the performance and complexity. The initial radius is mainly selected by the experience in this case, while any generally effective selection method for this spherical radius hasn’t been proposed yet. In this paper, a novel and effective method is proposed for initial radius selection with simple sphere decoding algorithm. As to qQAM, we propose a novel scheme to reduce the initial radius in Alamouti code decoding, though the average energy of qQAM constellation is combined with an improved algorithm based on Chan-Lee sphere decoder. This paper is organized as follows. In section 2 reviews multiple antenna system models with Alamouti code and Chen-Lee sphere decoder. Our proposed code scheme for choosing initial radius is presented in section 3. Simulation results are given in section 4, and finally conclusion is made in section 5.

2 System Model Consider a MIMO system with m transmit antennas and n receive antennas which can be modeled by the linear relationship: y=Hx+n

(1) T

Let H be the n×m channel gain matrix. n=[n0,n1,.....,nN-1] is the zero-mean additive white Gaussian noise(AWGN) complex vector which has i.i.d entries T ni~CN（ 0， N0/2） , x=[x1,x2,.....xN-1]T is the transmitted vector, y=[y0,y1,.....,yN-1] is the T received vector and (.) denotes transposition. The element hij of H is the complex path gain from transmit antenna j to receive antenna i. The receiver is assumed to have ideal channel estimates so it can separate and decode the symbols transmitted from each antenna. The ability to separate the symbols is due to the fact that in a scattering environment, the signals received at each receive antenna from each transmit antenna appear to be uncorrelated A. Alamouti Code The Alamouti Scheme[2], which includes two transmit antennas and one receive antenna, is one of the most elegant space-time codes for the transmit diversity system. And it can be extended to two receive antennas. The channel at time t can be modeled by a complex multiplicative distortion h0(t) for transmit antenna 0 and h1(t) for transmit antenna 1. Assuming that fading is constant across two consecutive symbols, these two complex multiplicative distortions can be written as follows:

h0 (t ) = h0 (t + T ) = h0 = α 0 e jθ0

(2)

h1 (t ) = h1 (t + T ) = h1 = α1e jθ1

(3)

A Novel Initial Radius Selection with Simplify Sphere Decoding Algorithm

397

where T is the symbol duration. The received signals can then be expressed as follows:

r0 = r (t ) = h0 c0 + h1c1 + n0

(4)

r1 = r (t + T ) = −h0c1∗ + h1c0* + n1

(5)

where r0 and r1 are the received signals at time t and t+T and n0 and n1 are complex random variables representing receiver noise and interference. The combiner shown in Fig. 4 builds the following two combined signals that are sent to the maximum likelihood detector:

c0 = h0*r0 + h1r1*

(6)

c1 = h1*r0 − h0 r1*

(7)

Substituting (2) ~ (5) into (6) and (7) we get:

c0 = (a02 + a12 )c0 + h0*n0 + h1n1*

(8)

c1 = (a02 + a12 )c1 − h0 n1* + h1*n0

(9)

After the signal combining, the combined signals are sent to the maximum likelihood detector which, for each of the signals c0 and c1, uses the decision rule expressed as follows: Choose ci if :

(a02 + a12 − 1) ci + d 2 (c0 , ci ) ≤ (a02 + a12 − 1) ck + d 2 (c0 , ck ), 2

2

∀i ≠ k

(10)

The Alamouti code with two transmit antennas and one receive antenna is used.

Fig. 1. The Alamouti coding system with 2 tx antennas and 1 rx antenna

398


B. Chan-Lee SD Our simplified algorithm can be summarized as follows: Step 1-Input r, C, H and S. Step 2-Compute Gram matrix G:=HTH, and find QR decomposition.{qij}:=QChol(G) Step 3-Compute ｐ :=H-1r Step 4-Initialize d2:=C, Tn=C, Sn=ｐ n ,i=n Step 5-Evaluate the followings: U

i

= Q − Up(

Ti

Li = Q − L o w (−

+ S i , S );

q ii Ti

q ii

+ S i , S );

N i := l e n ( L i , U i , S ) ; y i := f i n d ( L i , U i , S ) ; Z i := s o r t ( y i , U i , S ) Step 6-Output si=zi(1) Step 7-Next i

3 Proposed Scheme with Sd A. Initial Radius of Sphere Decoding The algorithm of Fincke and Pohst [4] does really address how to choose r and propose an efficient way to tell which lattice points are inside the sphere. When sphere radius is r, we have:

r 2 ≥ y −H x

2

(11)

In order to transform the problem into an easier form, it is useful to consider the Orthogonal-triangular(QR) factorization of the matrix H:

⎡R ⎤ H = Q⎢ ⎥ ⎣0 ( n − m )×m ⎦

(12)

Q=[Q1 Q2] is an n×n orthogonal matrix and R is an m×m upper triangular matrix. Now the (11) can be written as follows: ⎡R⎤ 2 r 2 ≥ y − [ Q1 Q 2 ] ⎢ ⎥ x ⎣0 ⎦

⎡Q T ⎤ ⎡R⎤ = ⎢ 1T ⎥ y − ⎢ ⎥ x ⎣0 ⎦ ⎣⎢ Q 2 ⎦⎥ = Q 1T y − R x

2

2

+ Q 2T y

2

(13)


Defining

2

rm2 = r 2 − y + H xˆ

2

so

rm2 ≥ rm2 , m ( xm − xˆ m ) 2 + rm2−1 , m−1 ×

（ xm−1 − xˆ m−1 +

399

rm −1,m rm −1,m −1

(14)

( xm − xˆ m )） 2 + ...,

And then:

⎢ ⎡ rm−1 ⎥ r m−1 ⎤ ⎥ ⎥ ≤ xm−1 ≤ ⎢xˆm−1 m + ⎢ xˆm−1 m − rm−1,m−1 ⎦⎥ rm−1,m−1 ⎥ ⎣⎢ ⎢

(15)

One can continue in a similar fashion for Sm-2 and so on, until all points inside the sphere are found. This essentially leads us to the sphere decoding algorithm. B. The Proposed Initial Radius Selection Method In this paper, we combine with Chan-Lee sphere decoding algorithm, and choose a fit initial radius to use the average energy of qQAM constellation. The conventional method chooses the initial radius r, that is: n

αn

∫

0

λ2

−1

⎛n⎞ Γ⎜ ⎟ ⎝2⎠

e − λ dλ = 1 − ξ

(16)

Where α is commonly based on experience. Γ ( ⋅ ) is he gamma function and the 1 − ξ is set as a value close to 1. Can we could increase the probability 1 − ξ by adjusting the radius r. We define average energy of qQAM constellation is E. and the Alamouti code transmit antenna m and definition coefficient ∂ , then we can get

E = ((q − 1)* 4 ) / 6

r = ∂*

1 m* E

(17) (18)

This new radius scheme defines the initial radius of SD to form average energy of qQAM which is combined with Chen-Lee sphere decoding algorithm.

4 Simulation Results In the improved scheme, we choose initial radius according to the average energy of QAM constellation in SD, combine with Chan-Lee sphere decode algorithm in Alamouti code with 2 transmit antennas and 2 receive antennas. Here we consider 16QAM and

400


Fig. 2. Chan-Lee sphere decoding algorithm, the reader is referred to [6]

Fig. 3. The performance comparison between the proposed and conventional SD with 16QAM


401

Fig. 4. The performance comparison between the proposed and conventional SD with 64QAM

4QAM modulation, Gary mapping .the proposed scheme r=1.6 and conventional r=3.2. We focus on the bit error rate(BER) performance over Rayleigh fading channels. Fig.3 shows the BER curves of the improved initial radius scheme and the conventional scheme of SD over fading channels. The improved scheme is kept about 1-2dB code gains when BER is below 10-3 with 16QAM modulation. The next shows that over Rayleigh fading channels when BER is below 10-5, it can achieve 0~1dB coding gains at the Fig.4. Simulation results show that our average energy of qQAM constellation to choose initial can get a better coding gain and ensures that at least one lattice point is inside a sphere.

5 Conclusion In this paper, a new initial radius selection scheme of the SD uses the average energy of qQAM constellation to combine with Chan-Lee sphere decoding algorithm which can get coding gains compared with the conventional one in Alamouti code. The proposed MIMO system defines the average energy of qQAM constellation algorithm formula with r. Simulation results demonstrate that when BER is below 10-4, it can get about 1~2 dB coding gains over Rayleigh fading channels with 16QAM. And with 64QAM can get about 0~1 dB coding gains. Acknowledgment. This paper is supported by the key project of Chinese Ministry of Education(No. 106042) and the project sponsored by the Scientific Research Foundation for the Returned Overeas Chinese Scholars, State Education Ministry(2007[24]).

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References 1. Foschini, G.J., Golden, G.D., Valenzuela, R.A., Woiniansky, P.W.: Simplified processing for high data spectral efficiency wireless communication employing multi-element arrays. IEEE Journal on Selected Areas in Comm. 17(8), 1841–1852 (1999) 2. Golden, G.D., Foschini, G.J., Valenzuela, R.A., Woiniansky, P.W.: Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture. Electron. Lett. 35, 14–16 (1999) 3. Alamouti, S.M.: A simple transmit diversity technique for wireless communications. IEEE J. Select. Areas Commun. 16(8), 1451–1458 (1998) 4. Fincke, U., Pohst, M.: Improved methods for calculating vectors of short length in a lattice, including a complexity analysis. Mathematics of Computation 44, 463–471 (1985) 5. Viterbo, E., Boutros, J.: A universal lattice code decoder for fadingchannel. IEEE Trans. on Inform. Theory 45(5), 1639–1642 (1999) 6. Chan, A.M., Lee, I.: A new reduced-complexity sphere decoder formultiple antenna system. In: IEEE Conference on Communications, ICC 2002, pp. 460–464 (2002) 7. Damen, M.O., Gamal, H.E., Caire, G.: On maximum-likelihood detection and the search for the closest lattice point. IEEE Trans. on Inform. Theory 49(10) (October 2003) 8. Damen, M.O., Gamal, H.E., Caire, G.: Low complexity ML Detection based on the search for the closest point. In: Damen, M.O., Gamal, H.E., Caire, G. (eds.) Intl Symp. on Inform. Theory, Japan, June 29-July 4, p. 135 (2003) 9. Agrell, E., Eriksson, T., Vardy, E., Zeger, K.: Closest point search in lattices. IEEE Trans. on Inform. Theory 48(8), 2201–2214 (2002) 10. Wang, Y., Roy, K.: Reduced-complexity sphere decoding via detection ordering for linear multi-input multi-output channels. In: SIPS IEEE 2004, pp. 30–35 (2004) 11. Liu, Q., Yang, L.: A novel method for initial radius selection of sphere decoding. In: IEEE VTC 2004-Fall, vol. 2, pp. 1280–1283. IEEE, Los Alamitos (2004) 12. Cheng, B., Liu, W., Yang, Z., Li, Y.: A new method for initial radius selection of sphere decoding. In: Proc. IEEE ISCC 2007, Aveiro, Portugal, pp. 19–24 (July 2007) 13. Shim, B., Kang, I.: On radius control of tree-pruned sphere decoding. In: Proc. IEEE ICASSP 2009, pp. 2469–2472 (2009) 14. Xia, X., Wang, H.: Reduced Initial Searching Radius for Sphere Decoder. IEEE Trans. Inform. Theory, PIMRC, 1–4 (2007) 15. Hosseini, F.E., Moghaddam, S.S.: Initial Radius Selection of Sphere Decoder for Practical Applications of MIMO Channels. IEEE Trans. Inform. Theory, COMPENG, 61–63 (2010)

The Research of Customer Relationship Management between China and Foreign Xinbao Guo Management school Henan University of Science and Technology Luoyang, P.R. China [email protected]

Abstract. The U.S. is the earliest initiator of Customer Relationship Management (CRM). In 1990s, it was introduced into China. The differences of economic background, technical resources, academic traditions, resources and methods result in different approaches to the CRM both at home and abroad. In this paper,a comprehensive discussion about the study on CRM background, theoretical foundation , the integration of CRM and the corporate culture in home and broard was conducted, and the research problem in our country was pointed out . At last, this study will provide some helps and suggestions to the research of CRM in CHINA. Keywords: Customer Relationship Management, Database Direct Marketing, Corporate Culture.

1 Introduction With the development of human society, the marketing concept had experienced the change from product-oriented to customer-oriented. Foreign research and application of customer relationship management (CRM) have got a great success. As the cultural background, economic background, technical resources and other factors, Chinese and foreign scholars studies have some differences in certain aspects of CRM. A small number of scholars compared theoretical study of Chinese and foreign CRM,such as Anshi reviewed and compared the domestic and foreign scholars study of the meaning of CRM; Liu Zhouping compared the research of Chinese and foreign scholars about customer satisfaction and customer loyalty; Yao Nanlin compared the study of consumer privacy of Chinese and foreign scholars. It is not difficult to see, these scholars are from a particular area to carry out comparison the CRM of Chinese and foreign. This paper attempts to compare the customer relationship management from following aspects such as background, theoretical basis, the integration of CRM and corporate culture, so that it will be useful to theoretical study of CRM in our country.

2 The Background of Customer Relationship Management In the west, it is the need of enterprise management and update core competitiveness of enterprises promote the generation of CRM, and it was drived by many aspects such as M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 403–408, 2011. © Springer-Verlag Berlin Heidelberg 2011

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X. Guo

the updation of management concepts and the support of electronic information technology. In China, with the development of economic and as the increasingly fierce competition in the market, more and more companies is looking for business development strategy. And this need to enhance the value of customers to a new level. Various functional departments of enterprises such as sales, marketing, customer service, technical support for all areas need to be able to achieve automation solutions, so that it can create a customer-facing platform. A. Economic Background It is the competition between producers and consumers that lead to the the change of enterprise management philosophy and consumers value choice, and this is the economic background of CRM generated. In China, it was divided into three stages. The first stage, a seller stage: product demand. Enterprises in a absolutly dominance of the market, do not care about the feelings of consumers, business management at this stage is the production control; consumers value choice is the product's prices and availability, customer satisfaction out of the question. The second stage, one-sided pursuit profit maximization stage: with the tremendous growth of products, consumers pay more attention to product brand and appearance of the image; while increased inventories and precipitation of funds threatens the enterprises interests, businesses began to pursue the sales maximization, using a variety of marketing methods and sales channels. Customer satisfaction is difficult to get a real in aspects such as brand integrity, product quality and so on, especially in after-sales services aspect. The third stage, customer satisfaction has been given sufficient attention. At this point, the improvement of living standards, technological advances and product greatly enriched made consumer value orientation is more personalized, more diversified. The brand of product, the degree of personalization, as well as its price and quality will affect customer choice. Compared with the previous, customer satisfaction has really begun to decide the fate of a product and a company's destiny. Therefore, the company began targeting their core management on achieving maximum customer satisfaction, Since then the philosophy of customer-focused management was formally established. B. Management Ideas Update After 20 years , the concept of business marketing has gone through a major shifting from the production concept, product concepts, promotional concepts, marketing concepts and then to the concept of integrated marketing. The latest marketing attempt including relationship marketing, database direct marketing and so on. Marketing theory evolues from the 4P (Product, Price,Place, Promotion) to 4C (Consumer wants and needs, Cost, Convenience, Communication) and then to 4R (Relevancy, Response, Relation, Return), accurately reflects the customer-centric trends. A large number of empirical studies have shown that close to the customer and customer-focused is one of the main features of good corporate. C. Technical Background With the improvement of office automation and staff computer skills and the level of enterprise information, business management are conducive to realize customer relationship management. With the global launch e-commerce, it is changing the way business operate: Enterprise launch marketing and sell products to customers, provide

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after-sales service, collect customer information through the Internet. Customer information is the basis of customer relationship management. The development of data warehousing , business intelligence, knowledge discovery techniques make the quality of collection, collation, processing and the use of customer information significantly improved. This will drive the Internet, telephone development, and then promot the development of call center. The combination of Internet and telephone allows enterprises to face the customers in a unified platform. A complete sales process is as follows: customers get the name of that company from advertising, browse the company's home page, then check the local distributors, and discuss sales discounts, delivery and service details with staff, place an order, inspect and test the product in the determining receipt , the final is payment. In this sales process, customers and business place a direct or indirect contact .Channels are varied: the telephone, interviews, e-mail, fax or mass media, etc. In the past, when any department dealing with the customers, any negative impact can make orders turn to competitors. As the customers know the company is a whole, the treatment that customers received in any part of the contact represent the company's style. As company has many departments, each department has different goals. It is difficult for inter-departmental to transfer information, resulting communication barriers. The whole process may be very long, and this potential customer may give up the association with the business in any link, and then turn to competitors. For internal staff, these problems are difficult to found.

3 A Review of the Oretical Foundation of CRM First, customer relationship management is based on the development of relationship marketing, then combine database marketing technology and methods, ultimately form customer relationship management. Thus, the theory of relationship marketing is theoretical foundation of CRM and the technology of database marketing is technical basis. Domestic and foreign scholars have done a lot of research on the relationship marketing and database marketing. As the cultural is different, Chinese and foreign research is not exactly the same. In the below, this paper will elaboratly describe the similarities and differences between domestic and foreign research about relationship marketing. A. CRM Theoretical Foundation - Relationship Marketing Customer relationship management is based on the development of relationship marketing, then combine technology and methods of database marketing, ultimately form customer relationship management. Thus, the theory of relationship marketing is theoretical foundation of CRM. Since 1982Bailey propose relationship marketing to 90's, many researchers have studied about it. Bailey think that "relationship marketing emphasis on the contact between buyers and sellers, through the maintenance of relationship among marketing, quality and customer service to win and retain customers." MeKerma summed up "the purpose of relationship marketing is to develop the close interaction among suppliers, customers or other members of value chain". Czepiel think that "long-term customer relationship is developed through a series of contacts at different stages". These stages include: the accumulation of satisfaction contact, active participation based on mutual

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X. Guo

understanding and trust, then produce dependence on partners and psychological integrity. For companies, the value that each customer can create is different, Thus, the company should adopt different strategies to treat different types of customers. The role of relationship marketing is to identify high value customers and develop longterm relationship with them, at the same time, give up the customers who is lack of loyalty and do not have the value of cultivating future. As cultural background is different, the study of relationship marketing focus has some differences between Chinese and Western scholars. Guo Zhiming has deeply studied the relationship marketing. He defines the characteristics of relationship marketing in China: In order to get the benefits of personal or business, close to the actual or potential interest groups. He also proposed the difference of relationship marketing between west and east: In the West, people pay more attention to the team participation, at the same time they try to limit the communication in the commercial level as much as possible; while in the background of eastern cultures, when people evaluate, measure, judge the strengths and the weaknesses of a business and products, they often make emotional exchanges and cultural integration of the two sides as the core. For example, in the east, business communication are often on the table, and it often involved some personal topics such as family, friends, experience and so on. These are avoided by the Western culture. He also stressed that "the performance is more important than the relationship for ever" and he developed relevant strategies for Chinese enterprises to conduct relationship marketing. Sun Qingyong, Zhang Yong and the other scholars propose the speciality of relationship content in Chinese culture --relationship privatization. they believe that because there are differences in culture between western and eastern, lead to understanding relationship and relationshiprelated behavior have differences. A high degree of customer relationship privatization is a sriking feature of the domestic CRM practice. It illustrates the relationship privatization has an impact on the CRM practice, and he also put forward some strategies to develop CRM in the case of relationship privatization. B. CRM Technical Foundation - Database Marketing Domestic and foreign scholars have the basically same definition of database marketing. Database marketing is based on accurate customer information, competitor information and internal information. This is an interactive marketing communication. Database Marketing mainly consists of three subsystems: the direct response marketing, computer-assisted sales and customer information services. 1) Direct response marketing -- Assisted with the database to communicate with existing customers or potential customers allow customers to respond quickly, such as direct mail, telemarketing and direct response advertising. 2) Computer- assisted sales -- Sales team direct access to the company's database through the computer, obtain information about customers or potential customers, competito's r information and company's information. 3) Customer Information Services -- To provide customers with information support as much as possible, such as billing inquiries, quality complaints, technical issues, products and services information, so that they can deep the understanding of this enterprise, better use of the company's products. From the above we can see that the study of relationship marketing focus has some differences between Chinese and Western scholars. Western scholars study focuses on

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how companies can maintain a close relationship with customers. Through constant contact with coustomer to win customer satisfaction and customer loyalty. However, our research is focused on the effective integration of Chinese-style "relationship" and marketing strategy. As the "relationship" have an important position in Chinese culture, Chinese scholars tend to study the relationship marketing under Chinese culture, they also stressed the relationship marketing through cultural integration and emotional exchange. On the contrary, because of cultural differences, " relationship " in Western culture is not at such an important position, therefore,there are very little relevant research.

4 Integration of CRM System and Corporate Culture The study of integration of CRM system and corporate culture is a key research area of CRM. CRM system will be integrated with the corporate culture is to ensure the CRM system successful implementation. Domestic and foreign scholars have done a lot of research about this area. Through the study, foreign scholars Delisi found the issues in the implementation process are all cultural problems. Only by building the "information culture", information System can play a role to solve these problems. Adler proposed the model of cultural influence. He thinks that people's behavior are influenced by culture and cultural through values influence their attitudes, and then indirectly affect human behaviors. Martinsons through the analysis of the characteristics of Western culture and information systems, found that Western culture is conducive to the use of information systems, while characteristics of Chinese cultural have a restricted impac on the implementation of enterprises information systems. He also suggested that to create a "customer-centric culture” is a prerequisite for the successful implementation of CRM in Western companies. In addition, in the study, scholars also found that information technology itself has culture. Some scholars have seen culture as one of important factors in technical implementation. Bowers think that information technology is not neutral in the culture. In fact the promotion of computer is to impose Western culture to other social cultural. In different cultural environment appliy the same technology will produce different results. From the above foreign scholars study, we can found that there have much more studies about relationship between information systems and corporate culture and integration of them. But in CRM systems, especially in the integration of CRM concept and corporate cultur,e there exists a great void. Here are the research results some Chinese scholars obtained in this area. Xie Lianan think that the building of enterprise culture is a key strategy to successfully implement CRM. He believes that in the initial stage of the implementation of CRM, change the traditional management philosophy and practice is the key link to the implementation of CRM. At the same time, we must do the training, make the customers at the center of business organizations, take steps to implement CRM etc. Weng Liang proposed one of the basic strategy for implementing CRM is training for CRM concepts of all employees,at the same time training for their values. Zhang Qinmin believes that when enterprises implement CRM, they must rebuild their corporate culture and implement the concept that customer is the

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enterprise strategic asset. Zhu Cuiping and the other scholars believe that the excellent corporate culture is the guarantee for successful implementation of CRM:(1) "Customer centric" is the concentrated expression of core corporate culture;(2) Established culture system to meet customers demand for personalized;(3) Create a corporate culture focus on the customer benefits and customer satisfaction. Zhong Qiuyan proposed corporate culture characteristics are those support the CRM and real play a role:(1) Customer-centric, focusing on maintaining existing customers; (2) Recognizing that customer is the permanent assets; (3) Management's primary objective is customer satisfaction; (4) Focus on the ability to use customers resources; (5) Recognizing customer's consumer demand for personalized. Throughout the scholars's Research in this field, we can draw up that: First, the foreign research has its cultural limitations. Foreign scholars research in information systems and corporate culture is rich, but the research about integration of CRM system and the corporate culture is lack, and studies abroad mostly are around the western companies. Therefore, the study does not fully applicable to our businesses. In contrast, domestic scholars have done a thorough study in the integration of CRM system and the corporate culture, thy have made great achievements, and the research also fully applicable to our businesses. However, many scholars of China are only brief summary, this can not establish some more convincing technology model to analyze and evaluate the relationship and performance between CRM system and corporate culture.Therefore, this aspect still needs further study.

5 Conclusion In the CRM area, the foreign has been nearly twenty years history, during this twemty years foreign scholars have done a lot of studies about CRM and achieved many results. Compared with foreign studies, our studies both have a lot of advantage and many shortcomings. Overall, our CRM research can against the situation in China and the status of Chinese enterprises to carry out, it also can make many valuable suggestions to successfully implementing CRM for our companies, which are foreign studies can not.

References 1. Churchill, G.A.J., Surprenant, G.: An investigation into the determ inant of customer satisfaction. Keting Research 11(9) (2007) 2. Wikstrom, S.: Value Creation by Company Consumer Interaction Journal Management. Journal Management 12, 359–374 (1996) 3. Stephanie, C.: An Extension on the Traditional Theory of Customer Discrimination. Customer Versus Customers 62(2), 319–343 (2003) 4. Gremler, D.D., Brown, S.W.: Service loyalty: its nature, inportance, and omp; implications. In: Edvardsson, B., et al. (eds.) Advancing Service Quality: A Global Perspective, International Service Quality Association, pp. 171–180 (2006) 5. Chiou, J.-S.: The antecedents of consumers loyalty toward Internet Service Providers. Information &Management 41, 685–695 (2004) 6. Bhatnagar, A., Ghose, S.: Segmenting. Consumers based on the benefits and risks of Internetshopping. Journal of Business Research 57, 1352–1360 (2004)

The Process Reengineering of Accounting Information System Xinbao Guo Management school Henan University of Science and Technology Luoyang, P.R. China [email protected]

Abstract. The needs of accounting information in different units will be different, the same will be the accounting procedure and interior data processing. Through the comparision between the traditional data processing and information-based process, this paper designs accounting treatment process based on information technology, which includes the flow of data transfer between sub-systems, the input data test, the output data sharing, and so on. Keywords: Accounting, Accounting system, Reengineering.

1 Introduction The independence of the accounting subsystem is characterized by the accounting functions of process control and reflection of results. Accounting is a process of recording, clarifying,summarizing and interpreting of those business activities that can be expresed in monetary terms. In the process, it produces large amounts of information flow. Due to the differences among various units in the size, production process, level of business complexity, and the requirement for accounting information, the function of accounting information system will be different,and the same is the accounting treatment process. I will do some research on these issues.

2 The Traditional Data Processing and Its Drawbacks In a traditional accounting system, the basic process should follow: source voucher→voucher records→bookkeeping→statement though there are different accounting processing procedures. That is because that compilation of statements should rely on sequential classification of bookkeeping instead of random businesses. Taking accounting process of voucher records as an example as follows.


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Fig. 1. Accounting process of voucher records

The above process has the following shortcomings: First,the process is extraordinary complex. Under manual system, although there are different accounting processing, the basic process is still in accordance with the process :original documents→posting documents →book →report. That is to say, the preparation of the report must rely on the general chronological books instead of the scattered businesses that happens because of the heavy workload . In the information technology environment, all these restrictions are swept aside ,so the report can be prepared by aggregating the amount of the documents directly no longer the general chronological books, and the accounting procedue accordingly changes into evidences → statements. Second, over-duplicated checking. Reconciliation is the core of manual accounting system. Under manual system, the different accounting books are recorded and taken in charge by different persons, with the view of verifying the correctness of accounting easily. When there is no data dislocation, omission, registering Into the wrong accounts, and duplicate registration account, the results should be correct. When the general ledger is not consistent with its subsidiary ledger ,there must be billing error occurs in one or both parties. So, regularly reconcile between different accounts is necessary and an effective way in detecting errors under the manual accounting system. Under the information technology environment, reconciliation between the accounts is no longer needed due to the same data source. Third, the massive data redundancy. Accounting documents are the data source of accounting processing subsystem, so, in a sense, the information that the documents contain nearly covers all kinds information contained in all kinds of subsidiary ledger,general ledger and statements.That is, from the information content point, what the latter can not provide more information than the forme. Under manual system, the account date on the certificates is copied repeatedly. This massive data duplication on the same date not only causes a waste of storage, but also easily leads to data inconsistencies between ducument and different books. Finally, lagging behind the information requirments. Accounting statements are the “end products” of accounting processing subsystem, which provide the impotant information for users,such as investors, creditors, managers, government agencies, workers ,trade unions ,and customers, to inquire the financial situations of an enterprise’,including its operating conditions at a certain day and operating results during a certain period. These information is necessary for the information users to

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make all kinds economic disicions. However, due to the massive wokeload and the slow pace of manual handling which combined with many reconciliation and account adustment events, manual accounting system has to take a long time to compile all financial statements, which inevitably leads to lag behind the information requirments .It will severely impaire the usefulness of accounting information.

3 Accounting Information Process Reengineering According to business process after business reengineering, information process of accounting information system can be obtained as fig.2. The system is consisting of five parts. The first part is various independent accounting subsystems, including human resource system marketing information system fixed assets, production information system accounting treatment, initialization; the second part is accounting process part, the main part is finishing initialization、 voucher inputting, checking, accounting, closing accounts, bank’s checking account, cross-year accounting and account current bookkeeping management, project management, department accounting, leader query etc.; the third part is automatic transfer accounting which solving control and data transfer between subsystems and accounting system; the fourth part is internal evaluation and monitoring, through value accounting to realize “control of process and conclusion of concept” and use value indexes to process data, predict future, assist Decision-making, it mainly include purchasing-sales-transporting and inventory management, contract management, labor statistics management etc.; the fifth part is financial report which provides financial report for stakeholders, including balance sheet, income statement, cash flow statement and receipt and payment statement of primary business、 statement of profit distribution, payable value added tax statement and financial analysis report etc. All the above parts are closely related, and the relationships between theme are not only data transfer, but control between systems, including calling control, sequential control etc. Above processes, (1)Deleting repeated data of bookkeeping in source system, mainly including subsidiary accounts, general account, journal, and various statements are directly made by balance sheet, voucher sheet； (2)Realizing automation of accounting data collection, mainly including various data collection from internal enterprise, automation transfer and producing mechanism vouchers and transferring into accounting process to process, certainly, including data transfer among internal subsystems, such as material, fixed assets etc. transferring data to cost subsystem, (3)self-making transfer voucher to record directly without checking by following design principle of “upstream checking data is unnecessary to be rechecked in downstream”. Therefore, the direction of data is not temporary voucher but voucher; (4)Increasing predicting future, assisting decision, and realizing sharing data resources, mainly including internal management, contract management, statistics management, break-even and target profit analysis, purchase-sale-transport-inventory management etc.; (5)Data transfer, and adjustment between subsystems should be realized by automatic control instead of manual control. For instance, accounting process of employees on salary in each period should be processed once only, and must be processed before settling accounts; therefore there will be a cycling control between “data transfer” and “closing accounts” so as to realize automatic control.

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Fig. 2. Computer information Process of accounting

References 1. Shiju, z., et al.: Computer Accounting. Petroleum Industry Press, Beijing (2001) 2. Wang, J.: On the Accounting Data-interface Methods of the Multi-function Card System. In: Chinese Control and Decision Conference, pp. 4009–4012 (2008) 3. Zhang, S.: Accounting information process reengineering based on ERP. In: Control and Decision Conference (CCDC), pp. 3818–3821 (2010)

The Model of Optimal Price and Leadtime in the Decentralized Setting Quan Jie School of Mathematics & Computer Science Jianghan University Wuhan, Hubei, China, 430056 [email protected]

Abstract. This paper investigates a firm with two independent functions, marketing and production, which serves customer demand that is sensitive to both price and leadtime. Price and leadtime decisions are made by marketing and production, respectively. We develop a new model that integrates pricing and delivery leadtime decisions constrained by capacity expansion cost, where substitution effect on competition is considered. In our model, we capture the optimal price and leadtime decisions in the decentralized setting. A numerical example is given to illustrate some helpful results. Keywords: price, leadtime, decentralized setting, capacity expansion cost, Substitution.

1 Introduction Price and leadtime are considered as two of the most important competitive priorities for success in today’s environment. So and Song (1998) study the impact of using delivery time guarantees as a competitive strategy in service industries where demands are sensitive to both price and delivery time. A mathematical framework is proposed to understand the interrelations among pricing, leadtime guarantee and capacity expansion decision [1]. So (2000) further illustrate how the different firm and market characteristics would affect the price and delivery time competition in the market [2]. However, they do not consider the effect of substitutability on the firm’s optimal decisions, where the products are differentiated in terms of prices and leadtimes in a competitive environment. Tsay and Agrawal (2000) study a distribution system in which a manufacturer supplies a common product to two independent retailers; they propose a demand model that reflects the substitutability of the products [3]. Draw inspiration from the demand model, Boyaci and Ray (2003) research a profitmaximizing firm selling two substitutable products in a price and leadtime sensitive market, but, they do not explicitly model competition in their study[4]. Pekgün et al. (2008) study a firm which serves customers that are sensitive to quoted price and leadtime, with pricing and leadtime decisions being made by the marketing and production departments, respectively [5]. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 413–420, 2011. © Springer-Verlag Berlin Heidelberg 2011

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Our purpose of this paper is to develop a new model that integrates pricing and delivery leadtime decisions constrained by capacity expansion cost, where substitution effect on competition is considered. Our analysis highlights the optimal price and leadtime in the decentralized setting. Through a numerical study, we illustrate how firms would choose their pricing and leadtime strategy to compete in a market.

2 Modol Formulation A. Description and Assumptions This paper investigates a firm whose product demand is sensitive to time and price and whose product competes with the alternative products in the market. The product is different from the regular one in that price is high and delivery leadtime is short. Subscript P and M denote the decentralized setting with production as the leader and marketing as the leader, respectively. Through the analysis of existence of the optimal solutions under model P and M, this paper studies the pricing and delivery time setting strategies for the firm under different competition market. For our analysis, we make some specific modeling assumption. We assume that the production facility forms an M/M/1 queueing system. The customers arrive to take delivery of the product according to a Poisson process. The mean rate for the product depends on the price and guaranteed leadtime of the product. The service time for the product is exponentially distributed and the customers are served on a first-come firstserved basis. The firm has a predetermined internal leadtime reliability target, which is the probability between zero and one and close to one. Similar to literature [1] and [4], we assume that capacity expansion cost is increasing and linear. Parameters

a = maximum attainable demand (market potential) corresponding to zero price and zero leadtime;

p = the firm’s product price; l = the firm’s guaranteed leadtime;

p0 = the regular product price in the market; l0 = the regular product leadtime in the market; bp = price sensitivity of demand;

bl = leadtime sensitivity of demand;

θp

= sensitivity of switchovers toward price difference;

θl

= sensitivity of switchovers toward leadtime difference;

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λ = mean demand for the product (units/time); μ = capacity for product facility (per time); m =unit operating cost (excluding capacity expansion cost); A = capacity expansion cost per unit time;

π

= profit per unit time for the firm;

s = internal leadtime reliability target, close to one B. The General Model Based on the above notation, the mean demand for the product is given by:

λ = a − bp ⋅ p − bl ⋅ l − θ p ⋅ ( p − p0 ) − θl ⋅ (l − l0 )

(1)

λ = a − (bp + θ p ) ⋅ p − (bl + θl ) ⋅ l + θ p ⋅ p0 + θl ⋅ l0

(2)

When decreased in price or leadtime per unit, the mean demand will increase bp + θ p or bl + θl units. The switching of the customers is governed by the difference between the prices and leadtimes (at a rate

θ p or θl

, respectively).

Our objective is to maximize the expected profit per unit time subject to the reliability requirement that the probability of meeting the delivery leadtime guarantee must be at least s . Then, the firm’s problem in its general form can be formulated as:

max π ( p, l ) = ( p − m) ⋅ λ − A ⋅ μ st

1 − e − ( μ − λ )⋅l ≥ s

(3) (4)

p ≥ m+ A≥0

(5)

μ ≥λ ≥0

(6)

l≥0

(7)

It is well known (see literature [1] and [4]) that at optimality, delivery leadtime reliability constraints must be binding, which implies that the capacity requirements of the product will be:

μ ( p, l ) = −

ln(1 − s ) + λ ( p, l ) l

(8)

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As a result, the firm’s problem reduces to maximizing Equation (3) with μ ‘s given as above. Note that Equation (8) enables us to explicitly model the impact of prices and leadtime (i.e., demand) on capacity requirements and costs.

3 Optimal Decisions Analysis In the decentralized setting, the pricing decision is made by the marketing department, while the leadtime decision is made by the production department. When production department as the leader, first the leadtime is determined by the production. Then, the marketing choose a price accordingly. We call such a model for P model. Correspondingly, when marketing as the leader, the price is determined. Then, the production chooses a leadtime accordingly. We call such a model for M model. A. Optimal P Model Under P model, leadtime is given, while price is decision variable. Replacing Equation (1) in Equation (3) and differentiating have:

π

twice wrt p , we

∂π = [a − bp ⋅ p − bl ⋅ l − θ p ( p − p0 ) − θl (l − l0 )] − ( p − m − A) ⋅ (b p + θ p ) ∂p

(9)

∂ 2π = −2(bp + θ p ) < 0 ∂2 p So, π is concave in p . Hence, we can determine the optimal price Equation (9) =0:

p* = −

a + θ p ⋅ p0 + θ l ⋅ l0 m + A bl + θ l ⋅l + + 2(b p + θ p ) 2(b p + θ p ) 2

by solving

(10)

Replacing Equation (10) in Equation (1), we have:

λ* = −

a + θ p ⋅ p0 + θl ⋅ l0 m + A bl + θl ⋅l + − ⋅ (bp + θ p ) 2 2 2

(11)

Replacing Equation (11) in Equation (8), then, Replacing Equation (8) and (10) in Equation (3), we obtain the optimal profit while production as the leader: π* =

a + θ p ⋅ p0 + θl ⋅ l0 m + A b +θ 1 ln(1 − s) ⋅[− l l ⋅ l + − ⋅ (bp + θ p )]2 + A bp + θ p l 2 2 2

(12)


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B. Optimal M Model Under M model, price is given, while leadtime is decision variable. Replacing Equation (1) in Equation (3) and differentiating π twice wrt l , we have:

∂π = −( p − m − A) ⋅ (bl + θ l ) − A ln(1 − s )l −2 ∂l

(13)

∂ 2π = 2 A ln(1 − s )l −3 < 0 2 ∂l So, π is concave in l . Hence, we can determine the optimal leadtime Equation (13) =0:

l* = −

A ln(1 − s ) ( p − m − A)(bl + θl )

by solving

(14)

Replacing Equation (14) in Equation (1), we have: λ * = −(bp + θ p ) ⋅ p − (bl + θl ) −

A ln(1 − s) + a + θ p ⋅ p0 + θl ⋅ l0 ( p − m − A)(bl + θl )

(15)

Replacing Equation (15) in Equation (8), then, Replacing Equation (8) and (14) in Equation (3), we obtain the optimal profit while marketing as the leader:

π * = ( p − m − A) ⋅[a +θ p ⋅ p0 +θl ⋅ l0 − (bp +θ p ) ⋅ p]

(16)

C. Numerical Example We present a numerical example to illustrate the behaviors of the optimal price and leadtime decisions, as predict by our model, when the firm compete in the different setting. We consider such example:

a = 400, m = 50, bp = 1, bl = 10, θ p = 2,

θl = 20, l0 = 3,

p0 = 250, s = 99% , A = 60 . We first studied how the leadtime would affect the price, mean demand and profit. The results are given in Figure 1. Figures 1 (a) and (b) show that the leadtime is inversely proportional to the price and to the mean demand. In Figure 1 (c), when the leadtime increases, the benefits first increased and then decreased. When the deviation of optimal leadtime, profits will reduce, but in the early period of the optimal leadtime profits drop more serious than in the late period.

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216 214

Price

212 210 208 206 204 202 200 198 0

0.5

1

1.5

2

2.5

3

2.5

3

3.5

Leadtime

Mean demand

(a) 320 315 310 305 300 295 290 285 280 275 270 265

0

0.5

1

1.5

2

3.5

Leadtime

(b) 35000 30000

Profit

25000 20000 15000 10000 5000 0 0

0.5

1

1.5

2

2.5

3

3.5

Leadtime

(c) Fig. 1. Optimal decisions under P model

Observation 1. Under P model, there is an optimal leadtime. To guarantee a too short leadtime will cause serious damage to the firm. We next studied how the leadtime would affect the price, mean demand and net profit. The results are given in Figure 2.


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Leadtime

1 0.8 0.6 0.4 0.2 0 100

150

200

250

300

350

250

300

350

250

300

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Price

(a) 600

Mean demand

500 400 300 200 100 0 100

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(b) 35000 30000

Profit

25000 20000 15000 10000 5000 0 100

150

200

Price

(c) Fig. 2. Optimal decisions under M model

Figure 2 (a) shows that the price is inversely proportional to the mean demand. In Figure 2 (c), when the price increases, the benefits first increased and then decreased. While the deviation of optimal price, profits will reduce at similar rate. Observation 2. Under M model, there is an optimal price. When price is much higher than the optimal price, the mean demand is very small. So, if the firm wants to keep market share, marketing department should avoid a too high price.

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4 Conclusions and Future Work Price and leadtime are two important factors for success for firms in today’s competitive markets. Using a new model, we studied a firm with two independent functions, marketing and production, which serves customer demand that is sensitive to both price and leadtime. Price and leadtime decisions are made by marketing and production, respectively. This paper developed a new model that integrates pricing and delivery time decisions constrained by capacity expansion cost, where substitution effect on competition is considered. In our model, we capture the optimal price and leadtime decisions in the decentralized setting. Through a numerical study, we illustrate how firms would choose their pricing and leadtime strategy to compete in a market. Our results help to identify the key market factors and have important implications on how firms should choose to compete under different market environments. Our model and results are based on linear cost structure. So, it would be interesting to see whether the results can be extended to more general cost structure. This question should be answered in future study.

References 1. So, K.C., Song, J.S.: Price, delivery time guarantees and capacity selection. European Journal of Operational Research 111, 28–49 (1998) 2. So, K.C.: Price and time competition for service delivery. Manufacturing and Service Operations Management 2(4), 392–409 (2000) 3. Tsay, A.A., Agrawal, N.: Channel dynamics under price and service competition. Manufacturing and Service Operations Management 2(4), 372–391 (2000) 4. Boyaci, T., Ray, S.: Product differentiation and capacity cost interaction in time and price sensitive markets. Manufacturing & Service Operations Management 5(1), 18–36 (2003) 5. Pekgün, P., Griffin, P.M., Keskinocak, P.: Coordination of marketing and production for price and leadtime decisions. IIE Transactions 40, 12–30 (2008)

Urban Residential Land Automatic Recognition from Remote Sensing Image Based on Combined Features Yunjun Zhan Department of Resources and Environment Engineering, Wuhan University of Technology, Wuhan 430070, P.R. China [email protected]

Abstract. Residential land is the main factors in the process of urbanization and for urban expansion, it is important for study the spatial structure of city, urban planning management and the development and monitoring of land use estate to auto-recognize residential land from remote sensing image. In This article, we regarded residential district as target object, analyzed spectral features, shape features and texture features. Then, we described these features by mathematics, and construct fuzzy discrimination rule. At last we integrated fuzzy rules base by combination of multiple features. As experiment the Wuchang local areas are recognized using QuickBird data. Keywords: Urban Remote Sensing, Residential Land, Feature Extraction, Automatic Recognition.

1 Introduction Urban residential land is the basic space for urban resident’s life, and is the main part of urban land use. With the rapid development of urbanization, particularly in recent years, the boom in real estate development, there is a serious contradiction in urban land use structure. Quickly mastering temporal and spatial distribution of residential land, especially commercial housing land has important significance for urban planning and urban management decision. Remote sensing has strong timeliness for getting urban spatial information. Currently, study on automatic acquisition of urban remote sensing object information is mainly habitation remote sensing and urban architecture remote sensing. Jianqing Zhang[1], Lorette[2], Jieli Chen[3], Wei Hou[4], Pan Li[5], Zhang He[6] extract residential information and dynamic monitoring of residential areas using remote sensing technology respectively. Residential land includes housing land, public service facilities land, road land and green space, in which public service facilities land includes primary school, middle school, kindergarten and others that postal station, savings office, police station in residential area. For studying housing land condition, semantic granularity that is too high is unable to investigate quantity and spatial structure of urban housing land, especially commercial housing. Haiyue Li [7], HouLei[8] have studied automatic recognition of building and recognition of main M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 421–427, 2011. © Springer-Verlag Berlin Heidelberg 2011

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contour of building from remote sensing image respectively and proposed concrete methods and algorithm .The results has referential significance for residential district as integral object, but the single building as object, the identification result can not meet the monitoring objective of housing land. This article , using the high resolution remote sensing image, analyzes image features of modern residential district, extracts the spectral features, shape feature and texture feature, which are combined into fuzzy discriminate rules of residential district and then the information of residential district can be automatically extracted.

2 Study on Automatic Extraction Model of Remote Sensing Information Based on Combination of Multiple Features A. Remote Sensing Image Features of Ground Objects Remote sensing process is an information transfer process. Ground information is multidimensional and infinite and it is simplified as two-Infinite and limited information throng remote sensing imaging. Consequently, the information included by remote sensing image space is comprehensive, time phase and mapping with geographical combination of multiple features. The information that provided by remote sensing image is mainly throng gray scale and color step scale spectral information, spatial information, temporal information ,comprehensive information and so on. Consequently, it is core and base of remote sensing application analysis to understand the characterization and rules of the object feature from remote sensing. Remote sensing image features of ground object mainly include spectral features, morphological features, spatial structure features, shadow characters, texture feature and activity features. Different objects have different identification features on image. Throng observing ground object and analyzing remote sensing image features， combination many characteristic can build semantic features and discriminatory features that indentify earth object . B. Image Features of Residential District Land Use Residential land is the main portion in the urban land, including residential building, public service facilities of district, road land and green space. Housing include pitched roof style apartment, pitched roof small house, flat roof style apartment and so on. Area of modern residential district relatively large, and its building has regular arrangement and good greening, some of them install open pit court. Because of different slope directions of roof, pitched roof style apartment have different hue on image, and there is certain spacing among buildings and it has regular arrangement. Pitched roof small house mainly lie in old city of urban, besides having different hue, the distance of building is density and has irregular arrangement and channel is narrow. Roof of flat roof style apartment has uniform hue on image. Generally, housing characteristic such as water tank and unit balcony can be seen. Because the age of flat roof style apartment is ….it is multi-layer or high rise and has regular arrangement and road around is regular and wide generally.

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C. Mathematical Expression of Combined Mult- features (1) Description of Spectral Features Spectral Features are the set of all the image object descried and related features of pixel gray value, which reflect spectral information of object. It mainly includes mean value, brightness and standard deviation of image objects. Formula of mean value is as follows:

μL =

1 n ⋅ ∑ v1 n i =1

(1)

μL mean value of single object Ui is pixel gray value n is total number of pixel in the object. Formula of standard deviation is as follows: nL 1 δ L= ⋅ ∑ (u i − μ L ) 2 n − 1 i =1

(2)

(2) Description of shape feature Shape feature are the set of all the shape feature of image object descried themselves, which reflect the shape information of object. It mainly includes area, length to width ratio and shape index of image object. Formula of area is as follows: n

A = ∑ ai i =1

(3)

A mean area of image object， ai mean true area of each pixel， n mean the number of pixel. The calculation of length to width ratio is according to rectangular of outsourcing. Formula is as follows:

γ=

l w

(4)

L mean the length of rectangular of outsourcing， w mean the width of rectangular of outsourcing. Shape index The shape are more smooth, the value are smaller. Formula is as follows:

si = Bl mean Boundary Length of object.

bl 4× A

(5)

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(3) Description of texture feature Description of texture feature based on grey level co-occurrence matrix. Grey level co-occurrence matrix method is a method that statistic all the pixel in the region of image object and describes the Spatial Distribution of gray. Characteristic Parameters that is common and formula is as follows: Homogeneity n −1

pi , j

∑ 1 + (i − j )

H=

i, j = 0

2

(6)

Probability after normalizing: It describes the uniformity of image, which is also the degree that concentrated on diagonal line of maximum element in grey level co-occurrence matrix. The more central, the homogeneity is larger, which suggests uniformity of image is higher. Dissimilarity:

D=

n −1

∑p

i, j =0

i, j

i− j

(7)

It is similar to contrast ratio, but it increases linearly. If local contrast ratio is higher, the similarity degree is higher too. Mean:

μi , j =

1 n −1 ∑ pi, j n 2 i, j =0

(8)

The mean which is described by the grey level co-occurrence matrix, is the probability that pixel combined with certain pixel that adjacent. Standard deviation

S=

n −1

∑( p

i, j =0

i, j

− μi , j )

(9)

The standard deviation The standard deviation that is described by grey level co-occurrence matrix is measurement of pixel and mean bias. It is similar to contrast ratio and non-similarity. Entropy

E=

n −1

∑p

i, j

(− ln pi , j )

(10)

i, j =0

It is an index that measure whether the texture feature is order. When the texture is inconsistent on image, element value of gray difference vector is small and the entropy is high. Entropy is uncorrelated to angular second moment height.


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It describes the uniformity and consistency of gray distribution, which is also called energy. When the image is uniform area or it has consistent texture, angular second moment is high.

3 The Example of Automatic Extraction of Residential Land Information Based on Combination of Multiple Features A. General Situation of Study Area and Interpretation of Data The study area that this article chooses lies in south lake of Hongshan area in Wuhan city Hubei province. It is in the south suburb of Wuhan. There is much commercial housing land and the residential land there has certain of typicality and universality. The data used includes QuickBird satellite-remote-sensing image data in 22nd. January. 2009. Spatial resolution is 0.6m. B. The Building of Recognition Fuzzy Rules Recognition rules of object are that build fuzzy rules using the method of application fuzzy discriminate, and then several fuzzy rules combine, forming a fuzzy rule base. Fuzzy rule use the form of “if-then”. If meeting the terms, it will perform an operation. In order to create an advanced fuzzy rule, fuzzy set can be combined. A logical operation can return to fuzzy value combined by fuzzy set, which depends on the operator of logical operation. The basic logical operation includes “logic and”, “logic or”, “logic not”. There are several methods to realize this operation. In the most case, the most simple practice is to realize fuzzy “logic and” through calculating minimum to fuzzy set, realize fuzzy “logic or” through calculating maximum to fuzzy set, realize fuzzy “logic not” through calculating negative number to fuzzy set. The expression formula and logic operation can be combined arbitrarily, which the description to categories is flexible and clear. An operation can combine expression formula and it also can combine the operation including expression formula. The result of logical combination of fuzzy set is independent of its order, A and B=B and A. In addition, the creating of priority structure is easy to the creating of general logic, A or ( B and C ) = ( A or B and A or C). For example, A, B, C represent one of or a few of spectral features, shape feature and texture feature respectively, and the combination form can be (A and B ) or ( A and C ) and A and ( B or C ). The discriminate eigenvalue can be obtained through statistical calculation to samples of designated object. C. Analysis of Extraction Result Input the remote sensing image data of experimental area and extract the information of residential district using the discrimination rule that have been built. Figs 4 is the

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identification result according to certain a residential district of combination of multiple features rules recognition. The experiment show that residential district, as a whole object, can be recognized easily using the recognition method of combination of multiple features, but the deficiency of the result is obvious too. Just as figs 1, it regards the road connected the district as the district, while it does not regard the central garden in the district as the district.

Fig. 1. One of the recognition results

4 Conclusion In this study, it is the beneficial and feasible exploration to recognize the residential district using the method of combination of multiple features such as spectral features, shape feature and texture feature, and it is the trend in the study of the intelligentized remote sensing image. The result also shows that, in order to improve recognition precision, it is necessary to improve the shortcomings of mathematical description. In addition, other mathematical methods, such as region-growing method, expansion operation method, should be used to improve the recognition results and eliminate the edge serrated of recognition result, which is the next research task. Acknowledgment. The work was supported by the Fundamental Research Funds for the Central Universities (No.2010-Ia-057), the Wihan University of Technology Scientific Research Found for Doctor (471-38650564), the Youth Chenguang Project of Science and Technology of Wuhan City of China (No.200950431203), the Natural Science Found of Hubei Province (No.2009CDA015), the National High Technology Research and Development Program of China (863 program, No.2009AA12Z201).


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References 1. Jianqing, Z., Qiong, S., Change, P.L.: Detection of Residential Area by Remote Sensing Image Based on LBP /C Texture. Geomatics and Information Science of Wuhan University 33(1), 7–11 (2008) 2. Lorette, A., Descombes, X., Zerubia, J.: Texture Analysis Through a Markovian Modeling and Fuzzy Classification: Application to Urban Area Extraction from Satellite Images. International Journal of Computer Vision 36(3), 221–236 (2000) 3. Jieli, C., Yongxue, L., Manchun, L., Chenglei, S., Dong, Z., Wenting, C.: Extracting remote sensing information of residential areas based on the analysis of normalized difference Index. Science of Surveying and Mapping 35(2), 204–206 (2010) 4. Wei, H., Xuejun, L., Chunxiao, Z., Jing, W.: Object-oriented Information Extraction from H igh Resolution Ima–A Case Study for Recognition of Residential Area in Lixian County Sichuan Province. Journal of Geo-Information Science 12(1), 119–125 (2010) 5. Mingsheng, L., Liming, J., Hui, L., Limin, Y.: Estimating Urban Impervious Surface Percent Using Boosting as a Refinement of CART Analysis. Geomatics and Information Science of Wuhan University 32(12), 1103–1106 (2007) 6. He, Z.: Automatic Abstraction Methods of Residential Area Information of Remote Sensing Image Based on Texture Features. Journal of Jianghan Petroleum University of Staff and Workers 20(4), 93–96 (2007) 7. Haiyue, L., Hongqi, W., Jianwei, L., Yin, L., Fusen, W.: Technique for automatic building recognition and mapping in remote sensing images. Electronic Measurement Technology 30(2) (2007) 8. Lei, H., Dong, Y., Xiaojian, Y.: An Automatic Building DetectionM ethod from Remote Sensing Images. Computer Simulation 23(4), 184–187, 224 (2006) 9. Dong, Z., Yun-cai, L.: Recognition of Building’s Principal Contour in High-Resolution Aerial Image. Journal of Shanghai Jiaotong University 37(11), 1723–1727 (2003)

Decision Support System for Emergency Response of Geological Hazards in Three Gorges Reservoir Area Haifeng Huang and Shimei Wang College of Civil Engineering and Architecture China Three Gorges University Yichang, China [email protected]

Abstract. China Three Gorges reservoir area (TGRA) has always been severe geological hazards, and it gets worse when reservoir water level rises greatly with the construction of dam, emergency response of geo-hazards is becoming a frequent and important work. To guarantee the order and high efficacy, it is necessary to establish decision support system to assist the decision makers to work out perfect emergency response plan. According to years of experience in TGRA, on the basis of summarizing emergency response framework that included emergency survey, risk assessment and emergency decision-making, a decision support system for emergency response of geo-hazards in TGRA, which consisted of database, model base, knowledge base, case base and inference machine was established, and three decision-making processes included emergency preplan decision-making, emergency plan decision-making and emergency measures decision-making were designed. The application effect indicated the DSS system had good practicability because it could not only meet the multi-level and multi-task requirement of geo-hazards emergency response decision-making, but also tally with the practical scenarios. Keywords: decision support system, emergency response, geological hazards, Three Gorges reservoir area.

1 Introduction It was the frequently occurrence area for geological hazard problems such as collapses, landslide and so on in Three Gorges reservoir area (TGRA) in history, with the construction of Three Gorges Project, the reservoir water level had been raised greatly, which induced and revived more geo-hazards. In order to minimized geo-hazards damage and effectively protected the lives and property of local people, the prevention and treatment work of geo-hazards in TGRA has been implemented since January 2002, and the emergency response of geo-hazards was an important part of the work. Usually, the emergency response of geo-hazards is a complex work that calls for a tight schedule, a close coordination of multi-department and multi-human to complete multi-task efficiently and methodically, so the quick and effective decision-making is an important prerequisite for success in this work. Decision Support System (DSS) for emergency response of geo-hazards can deduce pointed decision conclusions from M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 428–436, 2011. © Springer-Verlag Berlin Heidelberg 2011

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emergency survey information and effective method base, knowledge base and case base, to help managers and engineers in dealing with the emergency. This paper presented a decision support system for emergency response of geohazards in Three Gorges reservoir area (DSS-ERGH/TGRA). On the basis of analyzing geo-hazards emergency response framework in TGRA, in accordance with the technical requirements of DSS, we put forward and elaborated the system architecture, and then expounded three levels of decision processes in DSS-ERGH/TGRA. Finally, the system application effect was introduced and discussed.

2 Geo-hazards Emergency Response Framework In order to avoid or reduce casualties and property losses, when geological disaster is happening or about to happen, the emergency response of geo-hazards shall start at once. According to years of experience in TGRA, the geo-hazards emergency response framework consisted of three parts, which were emergency survey, risk assessment and emergency decision-making, as shown in Fig. 1. (1) Emergency survey. It was an important precondition and basis of geo-hazards emergency response that organized technical personnel to make a survey and write emergency survey report in the first time after the disaster or danger [1], because the firsthand information from emergency survey was an important foundation, sometimes to be the exclusive source of information to carry out all decision-making activities. Usually, from geo-hazards emergency survey reports, the decision-makers could know about at least the information included basic and deformation characteristics of hazard,

Fig. 1. Geo-hazards emergency response framework in TGRA

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statistics of losses and affected targets, preliminary analysis of formation mechanism, impact factors and development tendency of geo-hazards. (2) Risk assessment. Making decisions only based on emergency survey information was not enough, and it’s necessary to make comprehensive risk assessment by combining the basic information and establishing qualitative or quantitative assessment models. According to the contents of geo-hazards emergency response, in order to make professional identify and judgment of geo-hazard damage grade, stability, development tendency, trigger factors, warning criterion, etc., geohazards risk assessment should at least comprise loss estimation, vulnerability assessment, stability evaluation and so on. (3) Emergency decision-making. Based on the geo-hazard emergency survey information and risk assessment results, the pointed emergency decision-making conclusions could be reached by reasoning in accordance with all relevant national laws and regulations, technological standards, expert knowledge and practical experience, relevant cases and so on. Usually, according to the contents, levels and affected targets of emergency response, the geo-hazards emergency decision-making in TGRA could be divided into 3 parts, which were emergency preplan decision-making, emergency plan decision-making and emergency measures decision-making. Emergency preplan decision-making was identifying four-stage emergency response preplan of geo-hazards based on disaster levels; emergency plan decision-making was making the most appropriate choice among geo-hazards prevention and reduction plans, which are relocation project, monitoring and early warning project, and control project [2]; emergency measures decision-making was making decisions to choose the most appropriate methods and measures which corresponding to emergency plan decision-making conclusions. The above 3 parts of decision-making covered all emergency decisions task of geo-hazards in TGRA respectively from the macro, middle and micro levels, so it could meet the demands of geo-hazards emergency rescue and decision-making very well.

3 Design of DSS-ERGH/TGRA A. System Architecture Decision support system is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, professional knowledge, or business models to identify and solve semistructured or non-structured problems and make decisions[3]. Generally, DSS consists of four sub-systems[4, 5], which are human–computer interaction system (HCIS), database management system (DBMS), model base management system (MBMS) and knowledge base management system (KBMS). Because the spatial agglomeration of geo-hazards, it’s possible to refer to lots of similar cases in the same area when making decisions of emergency response, therefore, a case base management system (CBMS) was introduced into the system besides above four sub-systems. In addition, inference machine (IM) was designed as an independent functional component in DSSERGH/TGRA. So, the system architecture was shown in Fig. 2.


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HCIS DBMS

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Fig. 2. The system architecture of DSS-ERGH/TGRA

(1) HCIS, also called human-computer interface system, which mainly responsible for the management of user interface and supporting the interaction between user and DSS. In DSS-ERGH/TGRA, HCIS provided the interface of comprehensive information services (e.g. query, retrieval, and statistics), information management (e.g. input, read, modification, and save), reasoning and decision-making, and calling the DBMS, MBMS, KBMS and CBMS. (2) Database (DB) was the base of DSS and in which large amounts of data were stored. Taking into account the demand that some spatial data such as the geographic distribution of geo-hazards and so on was used in DSS-ERGH/TGRA, all data were divided into geographic information system (GIS) spatial data and non-spatial attribute data. GIS spatial data consisted of geographical background data of TGRA (remote sensing imagery, topographic map, etc.), and geo-hazards distribution data (location, boundary); non-spatial data consisted of geo-hazards attribute data (text/ table/picture/video/etc.) and geo-hazards emergency survey data. In addition, there were some important functions of DBMS include data management and maintenance, data query and retrieval, connection with other sub-systems, and so on. (3) Model base (MB) stored risk assessment models and methods of geo-hazards, mainly included loss estimation, vulnerability assessment, stability evaluation and some other auxiliary qualitative and quantitative evaluation models and methods. And by MBMS, user could maintain all models and methods, such as add, delete and modify. At the same time, MBMS provided model called interface so that user could make use of any model and method conveniently in decision-making process. (4) Knowledge base (KB) was the core of system, and various knowledge included facts, rules, and constraints which mainly came from expertise was saved. According to the geo-hazards emergency decision-making contents in decision framework (Fig. 1), the knowledge base also included 3 parts, which were emergency preplan decisionmaking knowledge, emergency plan decision-making knowledge and emergency measures decision-making knowledge. In the process of decision-making, KBMS could explain the input data and information by using knowledge, and simulated the method and process of decision maker’s thinking. So in the support of knowledge base and KBMS, DSS-ERGH/TGRA could fully exert the experience, judgment and deduction of experts and decision makers, and obtained satisfactory and creditable solutions to problems of geo-hazards emergency response in TGRA. (5) As mentioned earlier, each geo-hazard was not isolated, but usually appeared in the form of spatial agglomeration, for example, the landslides induced by rainfall or by the fluctuation of the reservoir water level was in the majority in TGRA. That was to say, when the decision makers faced an emergency response decision of geo-hazards,

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they might meet with the similar previous case frequently, so established case base (CB) and CBMS in DSS-ERGH/TGRA was absolute essential. In case base, all kinds of geo-hazard emergency response cases were stored, and each case included complete information of emergency survey, results of risk assessment, conclusions of emergency response decision-making and evaluation of applied effect. CBMS was responsible for case retrieval at first, and then adjusting or modifying the source case so as to get the results that conformed to the target case. Besides, CBMS could maintain case base such as add, delete and modify cases. (6) Usually, inference machine (IM) was not an independent subsystem, but the core part of KBMS. In DSS-ERGH/TGRA, there must be Case-Based Reasoning (CBR) mechanism to support the application of case base [6], and it was the same with Rule-Based Reasoning (RBR) mechanism to support knowledge base [7]. So IM in DSS-ERGH/TGRA was designed as an independent function module, which realized CBR and RBR and supported the interaction between IM and CBMS or KBMS effectively. Here was another point that above sub-systems was paratactic and could call each other, for example, the parameters of MB could extract from DB, and the calculated results of MB could be saved to DB, also could be joined to knowledge reasoning or case reasoning. B. Decision Process In order to achieve 3 levels of emergency decision-making, three corresponding decision processes must be designed in DSS-ERGH/TGRA, shown as Fig. 3: • Information acquisition of geo-hazards emergency survey. It’s the first step, also was the basic data source of decisions that establishing geo-hazard emergency survey data table in database according to the emergency survey report. • Process of emergency preplan decision-making. According to relevant laws and regulations, geo-hazard emergency preplan was corresponding to the disaster response levels, and which were classified by geo-hazards damage grade. So emergency preplan decision-making was a relatively simple process: first, decision makers could identify geo-hazards damage grade by adopting damage grade evaluation model based on losses data in emergency survey data table, then matched the damage grade with the premise in emergency preplan decision-making knowledge base, at last, used forward inference control strategies in RBR to get the emergency preplan decision-making conclusions. • Process of emergency plan decision-making. The geo-hazard emergency plan decision was based on emergency survey data table and a series of risk assessment conclusions including stability, vulnerability, and development tendency, et al. so an integrated and dynamic geo-hazard emergency response information table was built as the source of decision inference by classifying and filtering emergency survey data and risk assessment conclusions, then user could make emergency plan decisions based on CBR and RBR as follows: in CBR, searched and matched the emergency plan decision cases based on the data in geo-hazard emergency response information table at first, then extracted and output the most similar source case as emergency plan A; at the same time, in RBR, matched the data in geo-hazard emergency response


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Fig. 3. The decision process in DSS-ERGH/TGRA

•

information table with the premise in emergency plan decision-making knowledge base, used forward inference control strategies to get the emergency plan B; then compared and optimized emergency plan A and B to get the final decision-making conclusions. When the conclusions were saved, the process of emergency plan decision-making was over. Of course, in order to continue the emergency measures decision-making, the emergency plan decision-making conclusions could be saved to the dynamic geo-hazard emergency response information table. Process of emergency measures decision-making. It’s similar to the process of emergency plan decision-making, the only difference was the case base and knowledge base belonged to emergency measures.

4 Using the System According to the geo-hazards emergency response framework in TGRA, and the design of system architecture and decision process, DSS-ERGH/TGRA was built based on classic Browser/Server structure: the human-computer interaction interface was designed in web browser, and the decision inference function was developed on server side. Besides, WebGIS technologies was introduced into system: in browser side, map service function was integrated into human-computer interaction interface; in server side, centralized management of spatial and non-spatial data was realized in DBMS by mean of GIS spatial data engine technology [8].

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Fig. 4. The interface of acquiring emergency survey information

As the core function of DSS-ERGH/TGRA, the decision-making of geo-hazards emergency response began in the acquisition of emergency survey information (Fig. 4), users could search and modify the information that had been saved in database, also could input and save new information, and the map page would display or accept the input of geo-hazard point at the same time. After DSS-ERGH/TGRA got the emergency survey information, the system would infer and make decisions according to Fig. 3. To guarantee the automation of inference, the decision process minimized user intervention as much as possible, but in order to ensure the credibility of decision conclusions, users had to interact and confirm with system in these situations: decided to use the default or custom value of parameters and weights of models before risk assessment; decided the inference path among multi knowledge or cases that had same priority level when encountered the conflict in inference process; decided the break and continue running of inference and decision process. Fig. 5 showed the final integrated interface of geo-hazards emergency response decision conclusions, which included emergency preplan decision-making, emergency plan decision-making and emergency measures decision-making.

Fig. 5. The interface of displaying decision-making conclusions


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5 Discussion and Conclusions DSS-ERGH/TGRA was built on the framework and process of geo-hazards emergency response in TGRA, therefore, it conformed to the human mind and actual operation habits, which had more practicability. Especially the decision-making conclusions about emergency response of the common landslides induced by rainfall or by the fluctuation of the reservoir water level in TGRA had a good reliability, and which was closely related to lots of similar cases and knowledge stored in CB and KB. So, it’s important to keep perfecting CB and KB in order to improve the practicability of DSSERGH/TGRA, of course the improvement of IM and MB is necessary. On the other hand, we found that the geo-hazards emergency response decisionmaking involved enormous crucial qualitative analysis or assessment, such as formation mechanism, development tendency and so on, in which the traditional DSS was weak. Intelligent Decision Support System (IDSS) combined DSS with Expert System (ES), can solve the qualitative analysis problems easily [9], perhaps a better choice. At the same time, just like mentioned above, spatial data display and analysis was needed, so Spatial Decision Support System (SDSS) which has more tight integration between GIS and SDSS may be more suitable for geo-hazards emergency response decision-making [10]. In general, as an important technological means in support of the geo-hazards prevention and reduction of Three Gorges reservoir area, the DSS-ERGH/TGRA is necessary and effective. And on a long view, the intelligent spatial decision support system (ISDSS) that integrates DSS with ES and GIS may be the most suitable technical framework for assistant decision-making of geo-hazards emergency response. Acknowledgment. This project was funded by a China national science & technology support program (No. 2008BAC47B03-3).

References 1. Liu, C.Z.: Basic problem on emergency disposition of abrupt heavy geological disaster. Journal of Natural Disasters 15, 24–30 (2006) 2. Wang, S.Q.: Monitoring and prediction of landslide in the Three Gorges. Geological Publishing House, Beijing (2008) 3. Gorry, G.A., Morton, M.S.S.: A framework for management information systems. Sloan Management Review 12, 55–70 (1971) 4. Sprague Jr., R.H., Carlson, E.D.: Building effective decision support systems. Prentice Hall, Englewood Cliffs (1982) 5. Turban, E., Aronson, J.: Decision support systems and intelligent systems. Prentice Hall PTR, Upper Saddle River (1997) 6. Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Communications 7(1), 39–59 (1994) 7. Marling, C.R., Petot, G.J., Sterling, L.S.: Integrating case-based and rule-based reasoning to meet multiple design constraints. Computational Intelligence 15(3), 308–332 (1999)

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8. Charvat, K., Kafka, S., Holy, S., Horak, P., Cepicky, J., Kocáb, M., Cajthaml, T., Valdova, I., Konecny, M., Kubicek, P., Stanek, K.: Spatial data management. In: Computers in Agriculture and Natural Resources - Proceedings of the 4th World Congress, pp. 705–710 (July 2006) 9. Kuma, C.D., Sarma, V.V.S.: Towards building an intelligent decision support system for project management. Academy Proceedings in Engineering Sciences 21, 327–343 (1996) 10. Chang, N.B., Wei, Y.L., Tseng, C.C., Kao, C.-Y.J.: Design of a GIS-based decision support system for chemical emergency preparedness and response in an urban environment. Computers, Environment and Urban Systems 21, 67–94 (1997)

To Promote the Development of Retail E-Commerce in Depth with Regional E-Commerce Bo Zhang, Haijun Zhang, and Bingwu Liu School of information Beijing WuZi University Beijing, China [email protected]

Abstract. Compared with the traditional consumer-oriented E-Commerce, regional E-Commerce has many advantages such as customer base, types of goods, logistics and distribution, transaction security, reputation and etc. The developed areas in China, especially the central cities are all equipped with the conditions for developing regional E-Commerce. These conditions are the number of Internet users, distribution system, means of payment, and so on. These developed areas should pioneer the regional E-Commerce. Keywords: regional E-Commerce, conception, advantages, support conditions.

1 Introduction Consumer-oriented online retailing has two forms; one is B2C, or business to consumer E-Commerce, which representative is Dangdang and Joyo. The other is C2C, or consumer to consumer E-Commerce, which representative is Taobao (In order to have a convenient description, this article describes the E-Commerce models like Dangdang and Taobao as traditional consumer-oriented E-Commerce models, or traditional XTOC, X on behalf of B or C). These E-Commerce web sites have opened up a new world for the online retail market in China with a sharp rise turnover doubled each year (Figure 1). In 2009, online retail transaction volume has reached 263 billion Yuan, up 105.2% over 2008， online shopping transaction size accounting for the proportion of total social consumer goods retail sales climbed to 1.98%, while the scale of online shopping is expected to exceed 100 million users, and its penetration rate among Internet users has further increase, up to 28.2% [1]. The rapid development of online shopping not only stimulates domestic demand, contributes to the promotion of consumption, but also brings convenience and benefit for people's life. As online shopping has not restrictions in time and territory, so the traditional consumer-oriented E-Commerce (including B2C and C2C) has a common characteristic, that is they serve all netizens. In the early E-Commerce development stages, this model played a key role in nurturing consumer-oriented E-Commerce market, fostering consumer-oriented terminal distribution market, attracting netizens to understand online shopping and experiencing online shopping. However, this business model with no physical stores’ support serving for so many consumers by large-scale M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 437–445, 2011. © Springer-Verlag Berlin Heidelberg 2011

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distribution has some problems, such as high distribution costs, unscheduled distribution, seller’s bad faith, and etc. Therefore, this E-Commerce model is only a form of online retail E-Commerce. In order to make E-Commerce to develop in depth the consumer-oriented E-Commerce should go in the direction of regionalization, and substantiation.

VDOHVYROXPH

Fig. 1. 2004 to 2009, online retail transactions (unit: 100 million Yuan)

2 The Disadvantages of Traditional XTOC E-Commerce A. Users Dispersed The users of traditional XTOC E-Commerce spread over the whole China and even around the world, like a large market without borders, without fixed customer groups. B. The Low Rate of Repeat Purchase Commodities of the traditional XTOC web sites are more fashionable, novelty goods. Users often buy these goods only once. Their purchase will not be repeated. Although the traditional XTOC web sites have greatly increased the variety of goods, they do not change the basic characteristics of the goods. C. Only a Small Number of Firms Survive As the network has no distance, this makes the traditional XTOC E-Commerce has a typical characteristic which is "winner takes all". Chinese E-Commerce has already developed for 10 years, but the web sites can be remembered by users are only a few. Unless the business model has a change, or the subsequent enterprise is difficult to survive. D. High Distribution Costs and Low Distribution Efficiency Due to its fashionable, novelty merchandise, traditional XTOC E-Commerce’s every single sale is relatively low and the distribution scope is very broad, which will inevitably lead to high distribution costs and inefficiency. When the distribution amount does not meet the economy scale, the logistics costs is difficult to be reduced, and it is difficult to attract logistics companies to join in [2]. Therefore, the current distribution of XTOC E-Commerce depends on express companies.

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E. Restricted Goods Since there is no physical store, the products of traditional XTOC enterprise can not be experienced by customers, so, their commodities are largely restricted, which are often some products with no demand of users’ personal experience and touch, which are often some products with high degree of standardization and high-technology, such as computer-related products, books, audio and video products, creative unique products, collectable products, software, services, and etc. The products consumers need every day and the daily necessities are often not suitable for seller online. F. The Reputation Has No Guarantee China Consumer Association's latest survey shows that the growth rate of the complaints against the Internet services ranked first among all the complaints. Integrity has become the biggest bottleneck of online shopping. In the vast Internet, unless the website makes some fame, how can the credibility of the site make people believe? Even if the site has good reputation, how to ensure the credibility of the merchant signed in the site? I am afraid that some credit rating alone can not solve the consumer's fear.

3 Conception of Regional XTOC E-Commerce Regional XTOC E-Commerce means the trading parties are both in a small regional area, such as a city. The vendors and customers use E-Commerce tools to finish shopping, payment and complete the transaction. Regional XTOC E-Commerce and traditional XTOC E-Commerce have some fundamental differences in E-Commerce models, which follow as: A. They Have Different Service Providers The service providers of traditional XTOC E-Commerce usually are virtual enterprises, while in regional XTOC E-Commerce, traditional physical store-based retailers become major service providers, and allowing the multiple XTOC models coexist. B. Their Clients Differ in Territorial Scope Traditional XTOC E-Commerce serves all Internet population, and regional ECommerce provides services for local Internet users which are in local region or in the same city. C. They Provide Different Products The goods provided by traditional XTOC E-Commerce are restricted by delivery, integrity, and security, so, many products such as food, valuables, are not suitable for sale, while, the goods of regional E-Commerce have no restriction. D. They Have Different in Distribution In traditional XTOC E-Commerce condition, distribution has large range and distance, and is not timely; regional E-Commerce distribution occurs in the same city, which is small distance, even if there is, a need, it can provide instant delivery. Regional E-Commerce is to build a network platform which gathers all the sellers in the city and provides a virtual business life for citizens. This platform can provide

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efficient logistics and distribution services by safe and reliable means of payment, so that the people can take a stroll on all the city's shops staying at home, enjoy the efficient and convenient service brought by electronic commerce.

4 The Superiority of Regional XTOC E-Commerce Regional E-Commerce is mainly undertaken by traditional commercial enterprises, which is the traditional enterprise extending their business online. Compared with traditional XTOC E-Commerce, regional E-Commerce has the following advantages. A. Customer Flow's Stability and User's Trust In the long run of business, each physical store or physical enterprise has established a relatively stable customer groups and trusted relationship between buyers and sellers. To buy the goods on line of his familiar store, user will not have doubts. B. Goods Are Very Rich and Customers Repeat Purchase Traditional business enterprises provide more goods than pure XTOC web sites can provide. They can provide products daily used which are in great demand and will have repeat of purchase. C. Can Distribute Large Amount of Goods and Provide Timely Delivery We all have this experience, spending hundreds Yuan or several hundreds Yuan in once purchase in a supermarket is a common thing, and almost every week we will do this repeat purchase. In regional E-Commerce condition, sellers and buyers coexist in the same city; delivery distance is short which will reduce distribution costs. Buyers can get the desired goods just in time. D. Payment is Secure and a Variety of Payment Method Can Be Used Due to payment security, traditional E-Commerce can only use third party payment or cash on delivery or postal remittance and other payment methods. While, regional ECommerce’ s dependence on third-party payment will be reduced and more flexible payment can be adopted because the sellers in regional E-Commerce are most local physical stores or enterprises, the buyer’s worry about payment security will be greatly reduced. In addition to third-party payment, buyers can directly online pay by bank cards or credit cards, buyers can also apply for purchase card from sellers and pay(prepayment), they can also use cash on delivery(post- payment ). E. Conducive Competition and Inter-Enterprise Integration Developing regional E-Commerce, all sellers’ goods will be displayed online, consumers can shop around. In the past, the same product’s price in different shopping malls is very different, and this situation will greatly be solved. Users can buy most cost-effective goods from all sellers in the city. The market share of the sellers with high operating costs and poor service will be compressed, until they are eliminated from the market. And high-quality companies will be further expanded by integrating other enterprise.


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5 Support Conditions of Regional E-Commerce A. Online Shopping Population To develop regional X2C E-Commerce, the first prerequisite is sufficient concentration of the online population. Today, China has the world's largest number of Internet users. According to CNNIC statistics, as of December 2009, China's Internet population reached 384 million, ranking first in the world, coverage reached 28.9%, 28.1% of them do online shopping, the total number reached 108 million people, 24.5% of them use online banking, 24.5% of them use online payment, online payment users reached 96.04 million [3]. Since China's unbalanced regional economic development, these online populations concentrated in the economically developed areas and central cities, as shown in table 1 [3]. From the local perspective, in China's economically developed areas, especially in central cities the network population coverage is beyond Europe (52%) and other regions, just below the North America (74.2%); Internet population and Internet shopping population are very concentrated. Table 1. Top 6 Internet population coverage cities in China Province Beijing

Internet population 11.03 million

coverage 65.1%

coverage ranks 1

Shanghai

11.71 million

62%

2

Guangdong

48.60 million

50.9%

3

Tianjin

5.64 million

48%

4

Zhejiang

24.52 million

47.9

5

Fujian

16.29 million

45.2

6

Source: China Internet Network Information Center

B. Logistics Distribution System In recent years, the logistics industry has a rapid development in china; it is shown that logistics is the third source of profit. Beijing, Shanghai, Guangzhou and other central cities have thousands of logistics and distribution companies. Beijing Olympic Games and Shanghai World Exposition have greatly improved the logistics distribution network of the host city, and have provided valuable experience in the construction of china’s logistics distribution system. At the same time, after several years of development, E-Commerce cultivated a large number of express delivery companies whose main business is to serve consumers and provide logistics in the same city; it is not a dream to deliver the goods to customer within hours or even an hour. All these have provided a strong support for regional E-Commerce. C. Internet Bank Payment System As mentioned earlier, the regional E-Commerce can use a variety of payment methods; the popularity of bank card and Internet Bank usage will directly affect the scale of the regional E-Commerce. In the first, let we look at the use of bank cards, according to media reports, in Beijing, bank card penetration rate in 2008 had exceeded 80%, "2010, in Shanghai, the coverage of special merchants using Union Pay Card will

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exceed 80%; in Nanjing, Hangzhou, Ningbo, bank card penetration rate will exceed 60%” [4]. In Beijing, Shanghai and other central cities, the bank card coverage is beyond 70% which is the average level of developed countries. Secondly, let we see the Internet Bank usage, at present, all major commercial banks offer online banking business, in 2009, the utilization rate of online payment was 24.5% (the national’s average), having a growth rate of 80.9%; online payment is the fastest growing applications in all network applications, 75% of consumers online shopping use online payment [3]. Internet Bank users concentrated in central cities, according to 2007 survey of 10 economically developed cities; 37.8% of people use Internet Bank [3], after three years, this ratio will undoubtedly increase exponentially. In the end, from the seller’s perspective, in 2008, in Beijing, Shanghai and other central cities, more than 90% of the major commercial organization use credit card, debit card, and other bank card to complete the transaction, which is near 100%. The development of Internet Bank, bank cards provides regional XTOC E-Commerce with payment guarantee. D. Transaction Security Consumer in consumer-oriented E-Commerce has two main worry, one is payment security, and the other is the seller’s reputation and the merchandise quality assurance [5]. Currently, online payment security issue has a better solution, an increasing number of Internet Bank users hold a positive attitude towards this. As for seller integrity, in regional XTOC E-Commerce, the main sellers are physical shops and traditional enterprises, these sellers are around the consumers, after years of operation, they have established a good reputation and this greatly eased the worry of consumers. In summary, in economically developed areas, especially in central cities, to develop regional consumer-oriented E-Commerce is possible.

6 Several Proposals for Developing Regional E-Commerce A. Initiate Regional E-Commerce in Economically Developed Central Cities Because of the imbalance in regional economic development, business infrastructure, distribution system and payment system, regional E-Commerce can not be done overnight, it should be a gradual process; it can be initiated in the central cities of developed area, and then extended to second-tier cities and third-tier cities. B. Building Regional E-Commerce Platform Led by the Government Regional E-Commerce platform has two modes. One is setting up web sites by the commercial enterprises themselves; in this way, commercial enterprises will invest large money and undertake huge costs because logistics distribution issues, payment problems, safe certification issues had to be solved by themselves, and it is difficult to form a brand. Another is setting up a service platform led by the local government, constructing a regional online retail market, and providing the market with the necessary logistics, payment and security infrastructure; the market should be defined as integrated retail market; the platform mainly serve for local online sellers which have physical store (including department stores, supermarkets, restaurants, travel offices, and other business organizations or service groups), it also provides a trading


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platform for virtual business enterprises and individuals which have no physical store; in this way, it can reduce the seller’s investment, and avoid repeat investment, and it is conducive to the promotion of the web site and conducive to forming a brand. C. Overall Planning Urban Logistics Distribution System Due to a small distribution range, regional XTOC E-Commerce can use a variety of delivery methods, such as self-distribution, express company delivery, consumers going to specified distribution sites and picking up their own goods, and so on. But from the perspective of the healthy development of online retail, the city should build a unified distribution system, distribution standards, and standardizing company's distribution services. To do this, it should be led by industry associations; industry associations establish a long-term stable partnership with some logistic companies and express companies which have a certain size and reputation, use Internet and modern communication technology to realize information of shopping and delivery instant transmission and provide fast and efficient distribution services for customers. D. Actively Promote the Use of Online Banking Online payment is one of the important conditions to Regional E-Commerce, without online payment, E-Commerce’s advantage of rapid and convenient, advantages beyond the time and space limit will disappear. Local governments should make full use of their influence, and work with banks to actively promote the use of credit card and bank card, and guide the citizen to use online banking in payment, taxes, trade and other sectors, thus laying a solid foundation for regional E-Commerce. The good news is, Central Bank decided to set up online banking exchange platform, in June 2010, it will be completed and will be used on-line. The presence that Internet Bank connected each other but can not exchange each other will cease to exist [6], which will promote the use of bank card and Internet Bank.

7 The Significance of Regional E-Commerce Constructing regional E-Commerce platform has important significance, only a few reasons summarized below. A. Bring Innovation to E-Commerce Model Developing regional BTOC E-Commerce is an innovation to E-Commerce model [7], it will change the traditional concept that E-Commerce should win customers all over the world, it gives a better solution to the distribution and shopping security bottlenecks that traditional BTOC E-Commerce encountered, it can expand content and areas that BTOC E-Commerce serves. B. Enhance the City Status Economic strength, industrial structure, level of infrastructure, education and technology, urban environment, international level, technological innovation, the financial industry, the proportion of GDP created by tertiary industry, and so on are dominant measures of a city position in international as well in domestic. The

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development of regional BTOC E-Commerce needs the support provided by Network infrastructure, logistics and distribution infrastructure, scientific and cultural levels, the level of financial sector; The regional BTOC E-Commerce having successful development will highlight the city's comprehensive strength, and will promote the city’s status. C. Bring Convenience and Benefits to the Public With regional BTOC E-Commerce platform, people can stay at home shopping in the city and enjoy various services; the public life becomes much easier, and the costs of public travel will be reduced, traffic congestion will be reduced too, the logistics industry will be promoted. At the same time, in the regional E-Commerce platform, commodity prices becoming more transparent to consumers which effectively limits the merchant's windfall profits and will be conducive to competition among sellers and bring tangible benefits to the public. D. Promote Consumption Regional E-Commerce platform provides a place for merchants to promote products and services, in this platform, merchants can fully demonstrate their superior products and services, expand their sales area, pull the consumption.

8 Conclusion E-Commerce model innovation is a driving force for E-Commerce to develop in depth. Traditional enterprises pursue development online and virtual enterprises make development offline become the main tone of E-Commerce development. Traditional retail and online retail moving toward integration is an inevitable trend of ECommerce’s development. As the giant of online retail, Taobao also innovates in business model. Just the news was “January 16, 2010, the first 150 authorized Taobao shops opened for business in Hangzhou offline at the same time; nationwide, Taobao plan to authorize more than 30,000 stores to open business in universities and communities this year, offline authorized stores will use a unified brand "Yes! Tao"” [8]. Conditions for traditional enterprises to develop Internet marketing are also becoming more mature, it can be predicted that traditional enterprises making sales online will be also not far off. Acknowledgment. This paper is based on work supported by Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality under Grant No. PHR200906210, Funding Project for Base Construction of Scientific Research of Beijing Municipal Commission of Education under Grant No. WYJD200902, Beijing Philosophy and Social Science Planning Project under Grant No. 09BaJG258, and Funding Project for Science and Technology Program of Beijing Municipal Commission of Education under Grant No. KM200910037002.


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References 1. IResearch Consulting. 2009-2010 Report of China’s Internet shopping industry (April 2, 2010), http://report.iresearch.cn/Reports/Charge/1364.html 2. Chen, S., Ning, J.: Constraints on E-commerce in Less Developed Countries: The Case of China. Electronic Commerce Research 2, 31–42 (2002) 3. CNNIC. 25th Statistical Survey Report on Internet Development in China, p. 15, 31, 39 (January 15, 2010) 4. Huang, W.: Merchants using bank card in Shanghai over 80% penetration. Oriental Morning Post, 14 edn. (December 24, 2008) 5. Guo, Y., Salvendy, G.: Factor Structure of Content Preparation for E-Business Web Sites: A Survey Result of Industrial Employees in P.R. China, pp. 784–795. Springer, Heidelberg (2007) 6. Cheng, J., Cheng, Y.: Current Status of Online Banking in China. Managers, 138 (March 2009) 7. Jennex, M.E., Amoroso, D.L.: E-Business and Technology Issues for Developing Economies: A Ukraine Case Study. Electronic Journal on Information Systems in Developing Countries 10(5), 1–14 (2002) 8. Heart Rock. Is Taobao building physical stores contrary to the trend Mody?, http://column.iresearch.cn/u/panshizhixin/archives/2010/ 275408.shtml (January 18, 2010)

Research on Management Accounting for SMEs Innovation in China Min Pan Department of Accounting College of Economic and Management Wuhan University Wuhan, China

Abstract. This paper introduces the findings from an extensive postal survey conducted in Wuhan Optics Valley, which looks at the innovation process of small and medium enterprises (SMEs), both incorporated and unincorporated. The implications of management accounting practices on innovation decisions in these businesses, are considered. The results indicate that management accounting is very sophisticated and has an effect on innovation management in most SEMs. Especially for accounting planning practices are in a position to utilise fully all available innovation risk reduction mechanisms. Keywords: Management Accounting, SMEs, Innovation.

1 Introduction Small and medium-sized enterprises (SMEs) are of particular interest in the study of innovation. It has been argued that they are disproportionately responsible for significant innovations, and one estimate suggests they contribute more than twice as many innovations per employee as large organisations (Vossen,1998). Innovation processes need to build the internal and external R&D investment decisions mechanism,encourage investment in human resources, pay more attention to the management accounting report(Hatch, 2006). Although the literature on SMEs and innovation is large and diverse, and despite the existence of recognised centres of study with good linkages to policy makers, our knowledge of the place and operation of management accounting in small businesses innovation still contains significant gaps. In this paper, we hope to shed some light on the question of how managers in SMEs use management accounting to control innovation processes. We enter the subjective realities of individual managers, for these form the inner contexts in which management decisions are made, and accounting plan are evaluated. The paper is structured in three parts. First, we review the key literature which has sought to explain innovation in SMEs; secondly, we give more detail about our research study and its methods; and thirdly, we present our results and we conclude with a discussion of the link between our findings and the existing literature. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 446–450, 2011. © Springer-Verlag Berlin Heidelberg 2011

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2 Literature Review It has been said that SMEs do not necessarily innovate in formally recognised ways. It is likely that they seldom use management accounting to control innovation process as much as product innovation (Ho man et al.,1998). The literature (for example,Brush and Chaganti, 1996; Delmestri, 1997; Frybourg, 1997; Kerr and McDougall, 1999;Heunks etal., 2008) suggested that management accounting was being made in two main avenues: first, reflect the information of learning and development in SMEs, and secondly, control their key linkages in which small firms gain access to resources both internal and external. Small and medium-sized businesses face particular challenges with regard to innovation. The range of skills represented in-house tend to be limited, as is their bench depth, so that the loss of certain organisation members can entail a serious loss of tacit knowledge, sometimes suffcient to endanger organisational survival. Retention, therefore, is always a serious concern for small and medium-sized businesses, particularly in relation to skilled labour. Yet skilled labour is what has been seen as especially key to small firm innovation, the related individual intellectual capacity information can be obtained from management accounting report (SBRT et al., 2008). In new technology-based firms, innovation is dependent on individual or collective business intelligence (Hatch,2006). Vossen(1998) and Openshaw (2003) suggested that innovative SMEs seek resources through a complex array of interconnections with their environment. Management accounting is are helpful to explore of this linkage between SME and environment. The importance of customers as informational resources regarding new product development, customer information has been noted (Malecki and Nicole,2001). The most versatile information source, however, is said to be the network of other firms suppliers, neighbours, or trade association partners. Management accounting can be used to make an explicit and planned strategy of cooperation (Storey and Chaganti, 2009). The above literature is informed by the grand narrative of the relations between management accounting and SMEs Innovation. What has been less established by this growing stream of research is how the managers evaluate the importance of management accounting. In conducting empirical study, our purpose was to gain insight into how the practitioners perceived the nature of management accounting in SME innovation.

3 Method and Sample We located the SMEs for our study by asking innovation counsellors at a Wuhan Optics Valley Business Link to identify the 36 most innovative SMEs in their area. Some of these turned out to be part of a very much larger organisation and so our final sample consisted of the 25 SMEs which we report in this paper. For another, they were all medium-sized firms, which comprise less than 22 per cent of Wuhan Optics Valley businesses. Also, given that less than 69 per cent of SMEs survive longer than five years. The oldest dated from 1992 with a re-incarnation in 2004, and the youngest (by a considerable margin) from 2009. They were all manufacturers, whose businesses ranged from optical metal products through valves and ultrasonics to high-tech

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M. Pan

communications devices. The smallest employed 35 staff and the largest 212; although the latter fell above the Wuhan Optics Valley upper limit of 200 employees for a medium-sized enterprise, we nevertheless included it, as it certainly could not be described as a large enterprise (LE) and still was proud to consider itself an SME. Our method of enquiry was to use in-depth semi-structured interviews with individual managers in a variety of roles in each organisation. Within each organisation, we interviewed the CEO or CFO, and then we selected a purposive sample of managers to interview, on the basis of their involvement as key players in the innovation-implementation pathway. Our respondents totalled 57. Our content analysis focused particularly on ascertaining the value of management accounting, in so far as these could be derived from the narratives managers gave of their experience of innovation within their company. It allowed us to capture not only the technical detail of real-life innovation, but also its accounting level. We asked our respondents to tell the process of innovations as they had experienced them in their organisation. We wanted to understand how they use the tools of management accounting in innovation. The only aim which we investigated was wether the innovation process could be reflected and controled by management accounting.

4 Results and Discussion It can be concluded that managers spend time in accounting exercises in order to minimise their innovation risk. In an attempt to throw some light on the effectiveness of management accounting practices in these firms, respondents were asked to indicate at what stage of the financial year they have the first indication about their estimated innovation risk. The responses are summarised in Table 1. It is very interesting to note that only about one third (34.4 per cent) of the respondents know their innovation risk before the year end. A further 49.3 percent estimate their innovation risk after the year end, whilst 10.8 per cent only know their innovation risk when management accounting report is completed. Obviously estimating the innovation risk before the year end offers the opportunity to utilise available accounting control mechanisms effciently to help reduce the innovation risk. So why do all firms not try to estimate their innovation risk before the year end? Apparently, time and money are an issue. Perhaps the relationship of SMEs management with their accountants (the main port of outside finacial planning advice) and advisers is more tuned to the accounting cycle. Table 1. Estimation of innovation risk Question: When do you first know your estimated innovation risk? Timing of estimation

Before year end After year end When accounts are available When the products design are available When products prototype is completed Other

percentage

24.4 10.0 38.9 10.4 10.8 5.5

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In Table 2, it can be seen that these costs are regressive since the proportion of companies who do not estimate their innovation risk before the year end falls as the businesses grow in size. Although it would be expected that more profitable companies devote more time and effort to management accounting planning, results here suggest that this is not the case. Both profitable and unprofitable firms are equally likely (or unlikely) to estimate their innovation risk before the year end. It could be argued that although management accounting planning can be expected to be important in profitable firms where more profits are subject to innovation, planning is also important in less profitable firms, where innovation will be crucial in the struggle to improve cashflow. Table 2. Estimation by size of company Number of employees (%)

Timing of estimation 0-50

Before year end After year end When accounts are available When the products design are available When products prototype is completed Other

100-150

19.9 33.3 9.1 14.9 41.7 36.2 11.0 7.8 12.4 7.1 5.9 0.7

>150

40.7 9.9 31.9 4.4 4.4 8.8

chi-squared = 44.201, p = 0.000

Table 2 shows that management accounting planning practices become more sophisticated as the firm grows larger. However, since the majority of businesses are relatively small in size, accounting planning practices are generally unsophisticated. As a result small firms may fail to utilise available mechanisms effectively and eficiently to reduce their innovation risk which they do not know until after the year end, when it is too late to use most of these risk engineering. The primary accounting planning mechanism that such companies can use after the end of the financial year, in order to reduce their innovation risk, is investment in skilled labour/experts' pension schemes. Pensions are given favourable treatment in the legislation compared to other types of staffs, and as such they are an important aspect of innovation process. Pension scheme contributions not only reduce serious loss of tacit knowledge, but also accumulate intellectual capacity within the firm. However, contributions to pension schemes require money to be taken out of the business and so provide a disincentive to business growth, investment and employment. In fact, when respondents were asked to indicate which planning mechanisms they use to reduce their innovation risk, skilled labour/experts' pension schemes were rated as the most commonly used mechanism(73.9 per cent), followed by the purchase of fixed assets before year end (69.9 per cent). Other less important mechanisms are paying important members to use up their allowance (44.5 per cent) and increasing owner/directors' salaries to exhaust their allowances (42.7 per cent). The responses are summarised in Table 3.

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M. Pan Table 3. Management accounting to reduce I NNOVATION

RISK

Question: Do you use the following management accounting mechanisms to reduce your innovation risk? Yes (%)

1. skilled labour/experts' pension schemes 2. Buying of fixed assets 3. Pay other important members 4. Increase owners'/directors' salaries 5. Reduce management cost 6. Reduce operating expense 7. Reduce financial cost

73.9 69.9 44.5 42.7 36.4 23.2 21.1

No (%)

26.1 30.1 55.5 57.3 63.7 76.8 78.8

Reiterating the above, it is clear that SMEs are normally late in estimating their innovation risk, thus they cannot make effcient use of some available management accounting mechanisms to reduce their innovation risk, and (possibly) as a result they rely on planning mechanisms mechanisms that involve the extraction of money out of the business, such as pension fund contributions and salaries. On a macro-economic level, this may be efficient as such practices perfect investment in innovation with the potential to grow and to generate wealth and employment.

References 1. Acs, Z.J., Audretsch, D.B.: Innovation in Large and Small Firms: An Empirical Analysis. American Economic Review 78, 678–690 (1988) 2. Czarniawska, B.: Narrating the Organisation:Dramas of Institutional Identity. University of Chicago Press, Chicago (1997) 3. Hatch, M.J.: The Role of the Researcher: An Analysis of Narrative Position in Organisation Theory. Journal of Management Inquiry 5(4), 359–375 (2006) 4. Heunks, F.J.: Innovation, Creativity and Success. Small Business Economics 10, 263–272 (2008) 5. Nicole, A.: Local Partnerships for Economic Development: Business Links and the Restructuring of SME Support. Economic Development Quarterly 12(3), 266–279 (2001) 6. Openshaw, S.: Multivariate Analysis of CensusData: The Classification of Areas. In: Rhind, D. (ed.) Census User’s Handbook, Methuen, London, pp. 243–263 (2003) 7. SBRT, NatWest SBRT Quarterly Survey of Small Business in Britain 14(1) (2008), Small Business Resesarch Trust, London 8. Storey, J.: The Meanings of Innovation. Financial Times Mastering Management (26), 30–33 (2009) 9. Vossen, R.W.: Relative Strengths and Weaknesses of Small Firms in Innovation. International Small Business Journal 16(3), 88–94 (1998)

Web Services Technology and Its Application in Geophysical Data Processing Jianbo Lian1, Minghua Zhang2, and Chengxi Wang2 1 Information College, Zhongkai University of Agricultural and Engineering, Guangzhou, China 2 Data Process Unit, Development and Research Center of China Geological Survey, Beijing, China [email protected]

Abstract. Web services are the Application modules published on the web that internet users can easily find and use. Its characteristic is good encapsulation, loosen coupling, height integration and openness. This article describes technology and architecture of the development of a web service by using c # and Visual studio.Net platform for gravity and magnetic data processing in geophysical application. Good result and expect efficiency are obtained. Keywords: Web services, Geophysical data processing.

1 Introduction Web services is a kind of software technology with the development of distributed computing building a universal platform don't concerned with the difference in language and technology of various heterogeneous platform, it describes some operation interface, allows applications to use, is the XML standard messages through the network access these operating mechanism of the logic unit. Web services solve the defects of traditional middleware technology (platform dependencies, firewall and interoperability between components in different problem), and seamlessly integrate different hardware and software platforms [1].

2 Web Services 2.1 The Characteristics of Web Services (1) Good Encapsulation: Web services are objects deployed in the Web, these objects have a good encapsulation, users can only see the interface function and parameter name provided by Web services, and operation process and algorithm are encapsulated in Web services. (2) Loosely Coupling: For web service users, as long as the Web service interface functions do not change, Web services for any changes to the realization of internal Web services, and for users are transparent. And distributed application M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 451–456, 2011. © Springer-Verlag Berlin Heidelberg 2011

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logic need to use the distributed object model in sharp contrast, for example: distributed component object model (DCOM), common object request broker architecture (CORBA) program, the system can expand to the Internet, should they require service system to provide clients with services must be tight coupling between itself, which requires is a similar structure. (3) Highly Integrated: Web services using simple and easy to understand Web protocol, as components and collaborative description interface, completely blocked the difference of various software platform, CORBA, DCOM can through the EJB or a standard protocol interoperation SOAP, can highly integrated. Web services can be regarded as a group of programmable components, users can use them through the Web service application programming interface (API). They are integrated into the web applications such as Windows program, Web program and Web services [2]. Web service technology has been accepted by many manufacturers, it has become widely accepted open standards. Different manufacturers use these standard technologies, combining with their professional needs and development platform, to realize the unified Web service. These basal standard technologies include: (1) XML(Extensible Markup Language ) is a set of rules for encoding documents in machine-readable form. It is defined in the XML 1.0 Specification [3] produced by the W3C, and several other related specifications, all gratis open standards.[4] XML's design goals emphasize simplicity, generality, and usability over the Internet.[5] It is a textual data format with strong support via Unicode for the languages of the world. Although the design of XML focuses on documents, it is widely used for the representation of arbitrary data structures, for example in web services. Many application programming interfaces (APIs) have been developed that software developers use to process XML data, and several schema systems exist to aid in the definition of XML-based languages. (2) SOAP (Simple Object Access Protocol): It is a simple, universal, XML-based standard, the text transport protocol, which consists of three parts: the package structure, coding rules and the RPC mechanism. SOAP supports HTTP protocol and can pass through the firewall, using secure sockets layer encryption mechanism and the remote client services, exchange data, so that the client with TCP / IP network environment can access Web services around the world [6]. (3) WSDL (Web Services Description Language): It is a description of XML documents, and it provides access to Web services, Web services users need to know all the contents, such as location, parameter information and support protocols with language independence may be implementation of various languages to describe Web services interfaces for users to select and use. (4) UDDI (Universal Description, Discovery and Integration): It is an open standard and a structured way to help developers distribute their services created. UDDI manages Web services by classification and storage, and allow people or the systems anywhere in the world easily check the services and use them.

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2.2 Web Services Architecture Web service architecture is service-oriented architecture, a complete Web services architecture consists of three entities: service providers, service requester and service registry. Between the three involved bind, find, and publish operation [7], shown in Figure 1.

Fig. 1. Web services architecture

Service providers (Service Provider) is the creator and owner of the service, it creates Web services and generates WSDL documents, the created WSDL file and other information described by XML is registered in the registration center of Web Service, and issued to the Internet for public through the release operation. Service requester (Service Requestor) can find services at the Web service registry and understand its functions. Service requestor has to find and call another service, or start with the interactive services, Web service provider send the SOAP message access to Web services functionality. Service registry (Service Registry, UDDI server) is a searchable registry of service descriptions, where service providers can publish their services, their classification, and search services. Development in a static binding or dynamic binding during the implementation, the service requester finds services and obtains binding operation of information services, it does not store Web services, only provides links of Web services, service delivery functions and descriptions.

3 Geophysical Data Processing Web Services Most of the geological exploration data are geophysical data. Information extraction should undertake metallogenic need for geophysical data processing. Magnetic measurement method is the traditional geophysical exploration method. Gravity and magnetic measurements continuously improve the accuracy of the measurement results contained in the information is being continually expanded, in order to highlight the exception of the useful information must be processed and converted exception. Conventional gravity and magnetic data processing methods include upward continuation, downward continuation, regularization filter, the first order direction derivative, second derivative calculation of the vertical, gravity and magnetic separation of potential fields [8]. The following magnetic field separation of heavy computing services, for example gravity and magnetic data processing brief Web services development process.

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3.1 Web Services of Calculation of Gravity and Magnetic Potential Field Separation Web services development platform, such as Microsoft studio.net, Delphi, C++ Builder J2EE, etc. Asp.net platform, because the Web service simplified create, testing and deployment, easy to use and development, therefore, the paper selects the.net platform to develop magnetic data processing, develop language chooses c#. Separation of magnetic field calculation Web service function interface is as follows: public byte[] ApartField(byte[] DataS,int i_ExRows,int i_ExColumns,float m_fFactor) Input parameters: byte [] DataS: an array of binary data files. int i_ExRows: expanding rows, the data type is integer. int i_ExColumns: expanding columns, the data type is integer. m_fFactor: Regular Factor, the data type is float. Return values: It is an binary array. Web service will be pass the results to the Web service consumer with array. WSDL of input data in the XML Schema described as follows: - <s:element name="ApartField"> - <s:complexType> - <s:sequence> <s:element minOccurs="0" maxOccurs="1" name="DataS" type="s:base64Binary"/> <s:element minOccurs="1" maxOccurs="1" name="i_ExRows" type="s:int" /> <s:element minOccurs="1" maxOccurs="1" name="i_ExColumns" type="s:int" /> <s:element minOccurs="1" maxOccurs="1" name="m_fFactor" type="s:float" /> The return value in the WSDL XML Schema is described as follows: <s:element name="ApartFieldResponse"> - <s:complexType> - <s:sequence> <s:element minOccurs="0" maxOccurs="1" name="ApartFieldResult" type="s:base64Binary" /> 3.2 The Application of Gravity and Magnetic Data Processing Web Service For the convenience of the user processing gravity and magnetic data, this paper developed a network of gravity and magnetic data processing application, reference has been developed for registration of gravity and magnetic data-processing Web service to complete the core calculation.

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Using Visual Studio. NET to create applications, only to facilitate the use of. NET platform provides Internet search services and quoted on the Web service, which is found in the services by using the DISCO. Web reference name can be defined according to user's requirements, in the process of creating service agency, and application in the process of using the Web service, service agency after receiving the application, will send to the Web service request, and Web service accepts requests after treatment, the corresponding results in XML format will return to the service agent, application through the service agency for the need of complete Web services calling. Below is an example of gravity and magnetic anomaly separation calculation service: Gravity.ApartField test=new Gravity.ApartField( ); byte[] DataD; DataD=test. ApartField (DataS,i_ExRows,i_ExColumns,f_Factor); Users at the service page need to input/handle his data file and relevant parameters at local computer, the server-side will call the corresponding anomaly separation computing Web service. output document will be displayed after calculation to the user. The User can click on the "contour display" button also to observe the contour of calculated result, and change the parameter and re-computing till satisfied. Calculation service interface of anomaly separation is shown in figure 2.

Fig. 2. Calculation page of magnetic field separation

4 Conclusion Web services is an effective solution of distributed computing. This article work developed a geophysical data processing Web service for Internet user trying to meet the needs of daily data processing by geophysicists worldwide. Standards followed by are the Web services through Internet by UDDI. Users can find this service and integrated into their own geophysical data processing system for data processing. Research and application of this work using web services is a new field of geophysical data processing in the application of modern information technology for geo-exploration.

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References 1. Cai, X.R.: Web services architecture and open interoperability technology. Tsinghua University Press, Beijing (2002) 2. Tabora, R., Xu, J., Ying Yu, M.: Microsoft. NET XML Web Services. Mechanical Industry Press (2002) 3. XML 1.0 Specification. W3.org, http://www.w3.org/TR/REC-xml (retrieved 201008-22) 4. W3C DOCUMENT LICENSE, http://www.w3.org/Consortium/Legal/2002/ copyright-documents-20021231 5. XML 1.0 Origin and Goals, http://www.w3.org/TR/REC-xml/ #sec-origin-goals (retrieved July 2009) 6. Li, W.: C + + Builder SOAP / Web Service development. Huazhong University Press (2002) 7. Yan, X., Li, W., Chen, F.: Web services volume structure and application. Journal of Wuhan University of Technology 24 (June 2002) 8. Dong, H.: magnetic prospecting tutorial. Geological Publishing House, Beijing (1993)

The Analysis of Strengths and Weaknesses of Online-Shopping Li Milong International School Beijing University of Posts and Telecommunications Beijing, P.R. China [email protected]

Abstract. The development of E-commerce, accompanied by the wide usage of Internet technology in economic activities, has launched a global business revolution and economic revolution. As a part of E-commerce activity, onlineshopping has tremendous business opportunity and market potential. However, the problems of online-shopping at present have severely limited its development. This essay analyzed the strengths and weaknesses of online shopping from the aspects of consumers, merchants, and the whole market economy. Moreover, in order to promote the development, the essay also came up with solution for the existing issues of online-shopping from the four angles, which are legal policies, techniques, honesty and education. Keywords: online-shopping, strengths and weaknesses, solution.

1 Introduction Online-shopping, is the process whereby consumers directly buy goods or services from a seller in real-time, without an intermediary service, over the Internet. According to the “25th China Internet Development Statistics Report”, released by the China Internet Network Information Center (CNNIC), Up to Dec 2009, the scale of Chinese Internet users has reached 384 million. Compared with 2008, it rose by 86 million, and the annual growth rate is 28.9%. Among them, the scale of onlineshopping customers has reached 108 million; the annual growth rate is 45.9%. And the usage of online-shopping is rising continually, which reaches 28.1% now. Based on this statistic report, as a new way of shopping, online-shopping is showing the tendency of growth rapid. Online-shopping, with a huge potential, how can it develop healthily, become the tendency of shopping in the future, the need is to analyze the strengths and weaknesses of it firstly.

2 Strengths of Online-Shopping Compared with traditional shopping way, online-shopping is a product of our modern life. Amount of strengths as followed: M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 457–464, 2011. © Springer-Verlag Berlin Heidelberg 2011

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A. For Consumers: a) Unrestricted services. Online-shopping can be accomplish without the restrictions of the time and the place. Due to the application of the advanced internet technology, consumers can select and purchase goods at anytime in anywhere. One instance is iHush (www.ihush.com), it afford 24 hours services a day, which can ensure consumers achieve the process ‘choose-purchase-payment’ whenever and wherever possible. This idea solves the serious problems of traditional shopping in restrictions of the shop hours and the location of business efficiently and effectively. b) Comprehensive information. Current online-shopping platform, for example, Taobao, Dangdang, etc, have built their own search engine, which can help consumers finding the entire merchants that in the sale. Furthermore, this service helps consumers shop around to get a good buy quickly and easily. The survey data of the usage of search engine by the “2009 China online-shopping market research report” shows that the proportion of searching goods and commodities by using general search engines and local search engines are 27.1% and 20.6%, further highlighting the importance of searching in goods selection in online-shopping. Therefore, as the unique characteristics of online-shopping, comprehensive information has become one of the key advantages of it. c) Labor and time saving. Compared to traditional shopping, online-shopping should not be in the action during all of the shopping procedure, such as selecting, purchasing, and picking goods up. Consumers can save the cost and time which spend on the going to and form the shops, finding items, etc. Past five years, the survey comes from “Hots of China Internet Survey Report” shows that 35.7% of consumers believe that online-shopping can “save your energy and time”, while 53.9% of consumers believe that online-shopping is of “convenience due to home-delivery service”. d) Less cost. Thanks to the low requirement on the operating cost and few links of commodity channels, online store can save a lot of additional costs; while, the usage of Internet technology which built on the top of the online trading platform addresses the differences in the commodity prices led by the regional differences and business marketing strategies. Thus, based on this condition, the commodity prices sold online is cheaper than sold by traditional way. Moreover, for C2C shopping sites, such as PAT, provide a route for consumer make auction with businesses, which, likely, make consumer buying cheaper goods. B. For Merchants: a) Low operating costs and flexible operating form. Different from traditional shopping, the operating costs of online-shopping are relatively low. Merchants can save a lot of used in the purchasing of facilities or renovation, instead, just small amount of money will be taken for web design and maintenance. At the same time, the operation form is relatively flexible. As online store is a virtual network platform, the number of goods sold can be greatly increased due to no restrictions on business area. Merchant can allocate goods by using the time slot between the orders placed with the goods distributed. That is to say, deployment did after received the consumers’ orders. This way will help reduce the merchant’s inventory, thereby reducing the backlog of capital.

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b) Strong potential for market development and considerable economic returns. CNNIC pointed out that the scale of Chinese Internet users is considerable, while the corresponding policy environment is relaxed currently. While the increasingly growing purchasing power of market players and the gradual recovery in consumer confidence make the penetration of online-shopping which is relatively low before (at 2009 is 26%) have a tendency of growth clearly. Therefore, the number of potential consumers is considerable in China. For the merchants, great deal of opportunities in online trading is presented themselves. With the constant improvement of this market, related business strategies will be adjusted timely, which, indeed, will help improving the economic returns of merchants. C. For the Market Economy: a) Improve the efficiency of resource allocation. One of the outstanding performances of network economy is the flexibility when compared with other economic form. Against the background of global financial crisis, the major industry and market in China have got some impose. However, according to “China onlineshopping market monitoring statistics report of the second quarter of 2009” issued by iResearch Consulting shows that the transaction size in online-shopping market has reached 56.36 billion Yuan during the second quarter of 2009. This indicates that the network economy represented by network retail companies and small or medium B2B e-commerce enterprises has became the warm flow in economic winter. Deeply, as a industry, online trading is not exist in isolation, the following chart shows the relationship among the online trading and other industries.

Fig. 1. The map of Internet shopping business eco-system

Online-shopping is developing. This process will also bring out tremendous market opportunities for related industries such as advertising and other service providers. It is good for breaking the situation of industry’s malaise, restructuring the structure and upgrading the services of each level of industries. Thanks to the development of online-shopping, the efficiency of resource allocation will be improved fundamentally, and the resource will be better used.

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3 Weaknesses of Online-Shopping Currently, the distemperedness of online-shopping and the bottleneck of internet technology formed a number of weaknesses of online-shopping, which restricted the development of online-shopping. Analyzing these weaknesses will help find solutions of problems, thus promoting a virtuous cycle of development of online-shopping. A. For Consumers: a) Risks of online-shopping. According to the survey given by CNNIC, in 2009, Chinese consumers are not satisfied with online shopping for the following factors: Table 1. Statistics of factors of consumers dissatisfied with online-shopping Factors

Proportion

Goods does not match the pictures

52.3%

Merchandise is fake

25.0%

Shoddy or damaged goods

22.7%

Too long time of delivery

21.2%

Bad attitude of courier

15.7%

Goods damaged during shipping

11.3%

Shipping costs are too high

10.8%

The dissatisfaction of consumers is caused by the weaknesses of online-shopping. This survey indicates that one of the serious drawbacks of online-shopping is the risks in it, such as the risk of goods quality , risk of merchants’ reputation, etc. the following are the lists of each potential risks. • Risk of goods quality. Due to the complexity and virtual of Internet and Internet technology, consumers cannot shop like traditional way when shopping online. The “buyer experience” advocated by traditional shopping which namely means that test goods by seeing, touching and other related activities before purchasing is not suit for online-shopping. In this modern way, consumers cannot have any contact with the real foods before receive it, which, indeed, creates the risk of goods quality. • Risk of merchants’ reputation. During the whole process of online-shopping, consumers cannot see the entity store of the online store personally. Therefore, another risk existed about merchants’ reputation, for example, whether this store existed or whether it can provide good after-sales services, etc. • Risk of information leakage. Consumers will be asked to provide personal information such as email address, mobile number, etc. when shopping online. If the platform of online-shopping cannot provide adequate privacy assurance, it will cause information leakage, which may bring damage for consumers. Relevant information of consumer or credit card numbers may be stolen, even more, the phenomenon of false orders may happened, which may cause great economic losses for consumers.


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• Risk of logistics. Most of the online store cannot establish a national logistics system because of the limited operating power. They rely on courier companies or postal companies to deliver goods. Therefore, consumer have to wait a long time before receive goods, and the integrity of goods cannot be guaranteed in the distribution process. These discussed above are the main risks of online-shopping, based on this, a model of distribution of Risk severity- Satisfaction can be built, as followed:

Fig. 2. The distribution of Risk severity- Satisfaction

b) Issues of after-sales services. The process of shopping online is completed via the virtual medium. Traditional shopping process is that “selection - purchase payment - receipt – after-sales services”. The difference, however, is that the process of online-shopping has already ended after receiving goods because that the shopping platform built on the Internet and merchants set up shop in a virtual environment. When consumers ask for the after-sales services, or when consumer thinks that goods should be sent back for the quality problems, it is difficult for them to find a way to implement this activity, even if the after-sales service can be given, the efficient of it cannot satisfied with consumers as well. A typical case occurred in April 16, 2009, the flagship store of UNIQLO in Taobao, which is used to achieve online retail business system. According to follow-up investigation, the most things consumers dissatisfied is the after-sales services in the whole process of this system. On the BBS designed by UNIQLO online shop, the “rate of returned goods” is one of the problems consumers often complaint. Factors like transportation, verify and refund confirmation may impact the return rate. B. For Merchants: a) Difficult to enlarge the scale of online store. The characteristics of comprehensive information of online-shopping may make the accumulation of consumers becomes extremely difficult. Consumers can find many vendors who sell same commodity. Increased choice for consumers means that merchants should face a fierce competition which called “Red Sea”. Moreover, the quality of merchants online is uneven. Some merchant may use untrue or exaggerated way for sale in order to seek the interests of economic benefits, which, make the fierce competition

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increasingly lack of standardization and fairness. The “Chinese online-shopping market research report” in 2008 gives the survey about the single transaction of consumers as followed: Table 2. The data of single transaction of consumers Shopping amount

Proportion

Less than 100 RMB

24.7%

100-300 RMB

26.7%

300-500 RMB

27.5%

500-1000 RMB

9.3%

1000-2000 RMB

7.3%

More than 2000 RMB

4.6%

This survey indicates that the goods consumers have the willing to buy is whose price less than 500 Yuan. That is to say, the economic benefits of online-shopping that merchants can get are not enough. Therefore, for merchants who want to treat the online trading as long-term businesses and want a large-scale store online, it is of difficulty to accomplish this, only thing can be achieved is stay at a stage of relatively little profits at present. C. For the Market Economy: a) Regional differences may limit economic development. The development of online-shopping relies on the Internet technology. Thus, with the regional differences of development of modern society, the development of online-shopping has emerged in regional differences. It shows concretely as follows: the development of city is faster than that of rural, and the development of east is faster than that of west. According to the “Chinese online-shopping market research report” in 2009, 92.6% of Chinese online-shopping consumers are urban consumers, while only 7.4% of them are rural consumers. And according to the “Chinese online-shopping survey” in 2008, in 2007, the number of online-shopping consumers in Beijing, Shanghai, Guangzhou and Shenzhen which are major cities is over 10.5 million, the penetration rate of the online-shopping occupy 41.7% of total consumers. However, the number of onlineshopping consumers in Wuhan, Chengdu, Shenyang and Xi’an is only 2.53 million, the penetration rate is just 29.3%. This features of online-shopping which development regionally will make more serious of the differences between city and rural or east and west in their economic development, and may restrict the overall pace of Chinese economic development, obstruct the macro-control of market economy in China.

4 Effective Solutions Market structure includes consumption subject, purchasing power and desire to purchase. At present, the online-shopping market is far from satisfactory. Even through the penetration rate of online-shopping is growing; the total proportion of consumers who have the willing of shopping online is still in a low level. The


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weaknesses has restricted the consumption subject, purchasing power and desire to purchase, so amount of Internet users have a posture with online shopping as “wait and see”. This will impact the merchant and economic environment as well. Thus, it is of importance to proposed corresponding measures to improve the situation of onlineshopping currently. The following aspects should be considered: A. Laws, Regulations and Policies: Two aspects should be taken into account in order to perfect laws and regulations. One is aimed at consumers. The consumer protection system of online-shopping should be established as soon as possible. It is reported that Chinese SAIC will amend the “Consumer Protection Law” and other relevant laws and regulations so that give more clear regulations about the problems of online-shopping violations. At the same time, relevant departments should carry out uniform supervision for online stores and dispose the violations timely and correctly in order to protect the interests of consumers essentially. The other is aimed at merchants. Local governments should put the appropriate policies to support the development of local online retail market, provide the standardization of market which can give a environment of fair competition and freedom development for merchants. At present, Policies such as the “Regulations of promoting the development of E-commerce in Shanghai” promulgated in June 2009 and the “Notice for general college graduates to engage on E-commerce (online shop) for their own businesses” issued by Zhejiang’s Provincial Education Department are all aimed at afford opportunities for development of online retail market, but their efforts were to be enhanced. B. Technique: The improvement of technique is against the solutions of the problem of onlineshopping itself and other related technology. First is aimed at the information security. Network enterprise and Internet sectors should update the measures of information protection continually, focus on the security of website, use firewalls, encrypt technology or even electronic signature to protect the personal information and passwords of credit card from being stolen. Second is aimed at the delivery. Enterprise or logistics companies should pay attention to the built of logistics network in order to enhance the efficiency of logistics system and reduce the occurrence of bad situation such as goods damaged during the process of distribution, etc. final is aimed at the website design. Merchants should study the features of consumers such as consumers’ psychology, consumers’ decision etc deeply to redesign the website of online store, reduce the complexity of their page, add the detail description of their goods etc. Government is building a good technological environment for onlineshopping recently. Some measures, for example, optimize the third-party payment continuously, or promote the development of SMEs online. C. Honesty: Relevant departments should strengthen the level of supervision on the onlineshopping and advocate self-discipline. One is aimed at the monitoring of quality of goods in online-shopping. The merchant who did commercial fraud such as sell adulterated goods should be given seriously punish. Meanwhile, the merchant who have a good reputation should be rewarded and publicized. Second is aimed at the monitoring of the after-sales services. Government should punish the merchant who

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reject to afford after-sales services or provide “overlord clause” for consumers. Last but not the least, a fair environment for competition and a standardization of marketing strategy should be promoted so that the online-shopping market can develop soundly. D. Education: Government and relevant departments should strengthen the education of consumers, and create a good shopping environment for consumption constantly. First is to strengthen the awareness of consumers’ self-protection. This awareness includes the awareness of risk of possible information leakage, information theft and so on. Second is to educate consumers protect their legitimate rights and interests by using legal weapon and promote consumers handle the unlawful infringement during the process of online-shopping legally. Finally, government should promote a correct way to shop online. Standardize consumers’ behaviors and make them know that do not hanker after cheap when shopping online and request the purchase invoices when shopping ended in order to prevent the legal interests of consumers from being violated.

5 Conclusion In the future, the market will be domain by 80s retro and 90s retro. The features of this consumer group are skilled in Internet technology and willing to experience new things. It happens that this kind of demands and desires can be satisfied by onlineshopping. As the future development trend, the potential market and power are limitless. Faced with the strengths and weaknesses correctly, and improved the situation of online-shopping through the endeavor by consumers, merchants and the macro-control of market will promote a virtuous cycle of the development of onlineshopping. The boom of online-shopping is just around the corner.

References 1. 2. 3. 4.

Chen, L.: Shopping Online. China Social Press (2010), ISBN: 9787508728438 The 25th Chinese Internet Development Statistics Report, CNNIC (2009) The Chinese Online-shopping Market Research Report in 2009, CNNIC (2009) Ni, Q., Li, J.: Study of Demand Characteristics of Consumers in Online-shopping and Related Influencing Factors. Social Sciences Review (6) (2007) 5. Li, B., Li, Q.: Analysis on Consumers’ Perceived Risk in Internet Shopping: Its Components and Sources. Economic Management (2) (2006)

Confusion of Franchisor of Chain Business and Development Strategy Li Yuhong1, Lu Hong2, and Han Weixi³ 1

College of Applied Science and Technology, Beijing Union University, P.R. China, 102200 2 Beijing Information Technology College, P.R.China, 100070 3 College of Applied Science and Technology, Beijing Union University, P.R. China,102200 [email protected]

Abstract. The future chain business is bound to develop along the line of franchise chain which is bound to along the line of franchise business mode. However, presently a number of franchisors have never formed the franchise chain with standardized service, professionalized operation and informationalized management. With the rapid development and expansion of China’s business services, the franchise that relies on trademark or product now no longer suffices for the ongoing development of franchisees, so the road of connotation development has become the main stream for the chain business. The advanced stage of franchise chain development is the unified business model via high technology and advanced management philosophy, achieving unified accounting and management. Franchisors shall arrive at the purpose of quadruple-win of franchisors, franchisees, customers and society by the establishment and under the management of standardized service, professionalized operation, informationalized management and scientific decision-making. Keywords: Franchise chain business, franchisor, franchisee.

After the embryonic state of fully regular chain, the chain business has entered the initial stage of franchise business, that is, the franchisors achieve the purpose of chain business through franchisees by franchising trademarks and products to them. In developed countries, both the number of franchisees and the turnover of the franchise chain in this way have decreased obviously. For instance, the turnover in the United States shares less than 3% of the total turnover of chain business. With the rapid development and expansion of China’s business services, the franchise that relies on trademark or product now no longer suffices for the ongoing development of franchisees, so the road of connotation development has become the main stream for the chain business. The advanced stage of franchise chain development is the unified business model via high technology and advanced management philosophy, achieving unified accounting and management.


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1 Overview of Local Franchisee Chain’s franchise business has formed scale since the 1990s and almost all types of operation of chain business in the world have emerged in China. A number of chain groups of developed countries have entered China’s market, and became an important component of China’s franchise industry, greatly promoting and influencing the foundation of the organizational and management model of franchise business. Many of China’s local franchisees have the experience of working in foreign chain enterprises; imitating and learning from the successful model of foreign chain business, they have combined the law, technology and management of franchise business with China’s local environment, becoming the new force of the franchise chain business in China.

2 Confusion of Local Franchisors Presently, China’s chain industry is developing in an active stage. During 2005 to 2008, the number and sales of chain stores have grown with the rate of 20%, and in 2009 the financial crisis caused a decline in profits, leading a rather small increase largely in Beijing, Shanghai and other major cities and a higher increase in second-tier cities. In the light of franchise chain, both the number and turnover of franchisees are still in the high growth state. However, the date from China’s Chain Store & Franchise Association and other authoritative institutions show that on one hand, the franchisees increased rapidly with a number of nearly one thousand in peak months; on the other hand, the retreat or “disappearance” of them was quickly with a loss rate of above 40%, which can be described as “violently joining and hastily retreating”. It can be said simply franchising trademark or product now no longer suffices for the ongoing development of franchisees. The drawbacks lie in the followings: 1. Poor Sustainability of the Commercial Value Delivered to the Franchisees In the initial stage of the franchising relationship between the franchisors and franchisees, the former obtain the first franchise fee, and the latter get the trademark or products, rather than the operational way of them, of the former in exchange, and as a result, the franchisees generally get very little support in the operation from the franchisors. This kind of franchised intellectual property is very limited, so the franchisees fail to get increased turnover and profit from the purchase of franchise. To extend their business, many franchisees establish separate companies and operate other products and items or default on subsequent franchise fees, making the franchising relationship exist in name only and the franchising agreement a dead letter. 2. Weak Promoting Capacity of the Value of Franchisors Themselves The franchisors can only own a long-term stabile franchise in the fierce business competition by continuing to improve the intellectual property of their own, increasing the knowledge of their brands, products, business models and the connotation of management technology. They can only attract franchisees when they manage and exploit the intrinsic value attached to the brand and product. However, it is far from the attainment of this object set in the original agreement between the two sides due to the lack of long-term stable symbiotic and mutually reinforcing relationship with the

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franchisees as a result of franchisors’ weak capacities of maintaining their franchise and appreciation. The runaway state of the business in the first, middle and late stages after franchising has caused low knowledge and technology content of franchising, so that the franchisees can be independent of the franchisors or even regard them as a burden to strain at the leash to escape their control. 3. Lagged Franchise Philosophy and Method Franchise is a business model by which the chain enterprises expand market, increase market share, gather resources, reduce costs and form economies of scale. The purpose of franchise chain business is to form interest community through franchise and achieve the situation of quadruple benefit of franchisors, franchisees, customers and society by economies of scale. In the future, the chain business is bound to develop along the line of franchise chain which is bound to along the line of franchise business mode. However, presently a number of franchisors have never made efforts in creating the franchise chain system with standardized service, professionalized operation and informationalized management, but rather focused on trademarks and products promotion and charging franchise fee, because they believe that they can attract franchisees so long as the trademark and brand promotion is sufficient. This philosophy and practice, which are adopted by the United States one hundred years ago, still remain in the initial stages of franchise business and has distinctly fallen behind international franchise business philosophy, and the approach of simply franchising trademarks and products has reached a dead end in China.

3 Local Franchisee’s Countermeasure It is the key to the franchise business to build franchise chain business system, the aim of which is the quadruple-win of franchisors, franchisees, customers and society, and the source to achieve this goal lies in the franchisors. By creating and franchising standardized service, professionalized operation, informationalized management and scientific decision-making subsystem, franchisors enhance franchisee’s ability to quickly respond to market, accelerate the flow, reduce operating costs and make greater profits space, enabling them to offer more profit to customers and allowing customers to get satisfying goods or services at less costs. Meanwhile, franchisors shall integrate franchisee resources and the joint purchase and marketing will also reduces the social transportation costs and ease traffic pressure, which was one of the initial causes for Japanese government’s actively promoting the chain business. 1. Standardize Service by Providing Training System By organizing vocational institutions, vocational colleges, industry associations, etc, the franchisors can develop and gradually implement the training system, including training and selecting instructors, training, instruction manuals, training stuff development and management of training process and feedback. The training is designed to help franchisees standardize their operation and services, and therefore, the training should include: Establish the service ideology and code of conduct on service of the employees of franchisees;

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Train the ideology of unified service etiquette and enhancing customer satisfaction; train customer service skills; Understand the implication of company’s unified image, logo, brand, store layout, primary colors, etc; Service standardization is mainly to improve employees’ ideology of customer satisfaction, establish operating procedures and codes of conduct, and form combined internal force and consensus and set clear and consistent external corporate style and image. 2. Professionalize the Business by Designing Operating Procedures and Developing Codes of Conduct The value of franchise is to provide franchisees with mature procedures which are proven effective by practice and shall be perfected through constant improvements. （ 1） Franchisee manager manual, including Manager responsibilities, customer relationship management, project management, staff management, store management, sales management, financial management, marketing information management, administrative affair management, etc. （ 2） Franchisee operational management manual, including: Pre-, in- and after-business operating procedures, service procedures, after-sale service procedures, complaint handling procedures, emergency handling procedures, store sanitary standard, staff sanitary standard, staff instruction, operating hours, etc （ 3） Chain store commodity management manual, including: Procurement planning, order management, replenishment management, commodity receiving procedures, standard of goods placement, inventory management, stock-taking procedures, marketing statistics, etc

Only achieve the level of modern services when measure up to the standards of service maturity. “Service maturity” reflects the level of service and service management of a service enterprise which can be divided into five levels: Level 1, the “initial level”: chaotic service and management Level 2, “repeatable level”: repeatable service process and relatively orderly service, but no available service standards Level 3, “Standardized level”: The service procedures have been standardized, in which each action and each service has its standard, having available management document Level 4, “Manageable level”: This level has formed quantified management objectives in all procedures and links, so all the service actions can be measured and evaluated. It has achieved a quantitative management. Level 5, “Optimizable level”: This level has achieved continuous service improvement, and the service procedures are continuously optimized, service quality continuously improved, having the ability to prevent service defects. The service level and management level can be continuously improved by way of gradual progressions. Each progression is required to complete the “critical procedures” of this level and previous level. These “critical procedures” form a “critical procedures area”.

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3. Informationize Management by Establishing a Distribution Assurance Platform The distribution system includes three core business processing functions: integrated business management, warehousing operation management, distribution operation management, and two very important management functions: logistics cost management and logistics performance management. In addition to the above, it provides leadership decision-making with the functions of efficient inquiry and decision support, and basic information support maintenance and system management for the normal operation of the system.

◇

Available for a variety of business documents, such as distribution bills, transportation bills, warehousing management bills, transferring bills, lading bills, online orders; Reports of recorded, actual and expected inventory are available at any time Available for bar code and two-dimensional bar codes in inventory management Available for manual and automatic designation of storage spaces in stock in & out Inquiry for current and forecasted storage capacity, circulation and processing capacity and handling capacity are available at any time Dynamic tracking of distribution task helps enterprises and enterprise customers grasp the distribution status Arrangement of distribution tasks by various strategies such as owners, routes, goods, schedules, etc （ 1） Business document management, including The functions of online document; input, audit, decomposition, issue, feedback, reception and track of business document （ 2） Subsystem of storage operation Stock-in management The functions of forecasting the arrival of cargo, stock inspection and acceptance, stock difference processing, assignment of storage placement, making and refilling shelving bills; Inventory management The functions of consolidation of storage areas, shelf life management, inventory early warning, internal inventory replenishment, etc; Stock-out management The functions of making and refilling pick list, distribution record, stock-out inspection, stock-out record; Stock-taking management Setting stock-taking cycle, making and refilling stock-taking list, handling overage & shortage, etc; Distribution processing and packaging management Defining processing technology and packaging, making and refilling packaging list, making and refilling processing list, etc; （ 3） Subsystem of distribution business management

◇ ◇ ◇ ◇ ◇ ◇

· · · · ·

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Dynamic vehicle management The functions of setting and inquiry of available vehicle, dynamic report and inquiry of vehicle; Dispatching plan management Arranging vehicle for certain cargo distribution in defined path and order according to vehicles state, distribution cargo and requirements; Log book management Recording the processes and costs of the distribution; Distribution accident management The functions of providing distribution accident and direct losses records, record and inquiry of compensation processing and record and inquiry of responsibility handling; Cargo transfer management Cargo transfer record, arrangement of rejected or undelivered cargo; Cargo transit management Managing the operating procedures which need transit in temporary storages before transport and distribution, including the functions of temporary stockpiling management, temporary discharge record, cargo sorting and loading, etc.

· · · · ·

4. Achieve Scientific Decision-Making by Information Data Analysis System The computer information data analysis provided by franchisors is of great significance for the decision-making of franchisees. The automatically recorded name, number, quantity and other data of the cargo of franchisors can be provided for franchisees after information aggregation, calculation and analysis statistics. This date can provide franchisees with sales information of different types of goods, such as salability state, margin, etc, forecasting the information as passenger flow, purchase volume, sales of single product, commodity wastage, etc in a certain time period to help franchisees make accurate business decisions.

References 1. Liu, w.: China Franchise Directory. Publishor of China Finance Economic (2002) 2. The Future of Franchising: Looking Twenty-Five Years ahead to the year 2010, a study for the International Franchise Association by The Naisbitt Group, p. 1. International Franchise Association, Washington, DC (1986) 3. Schmitt, B.H., Pan, Y.: In Asia, the Supermarket Means Sales. The Newyork Times 3(11), 2 (1995)

On Early Warning Evaluation Index System of Enterprise Purchasing Risk Based on the Balanced Scorecard Yongsheng Liu and Chunlei Ma School of Logistics Beijing Wuzi University Beijing, P.R. China [email protected]

Abstract. This research aims to seek a better early warning evaluation index system of enterprise purchasing risk. Based on the basic principle of the Balanced Scorecard (BSC), a feasibility of applying the BSC in early warning evaluation of enterprise purchasing risk is analyzed first. Secondly, risks in enterprise procurement and their respective influencing factors are proposed from the perspectives of finance of purchasing, purchasing performance, internal operation of purchasing and purchasing future development. Also, an early warning evaluation index system of enterprise purchasing risk is constructed. And finally, the Fuzzy Analytical Hierarchy Process (FAHP) is introduced in the early warning evaluation index system of enterprise purchasing risk, which thus helps to strengthen the enterprise purchasing risk management. Keywords: balanced scorecard, enterprise purchasing, early warning evaluation of risk, index system, fuzzy analytical hierarchy process.

1 Introduction With an accelerated process of economic globalization and an increasing importance of purchasing in enterprises, the scope of enterprise purchasing has been extended from mere domestic market to a global market. Also, the risks for purchasing are correspondingly increased. This requires enterprises to find out an effective way to prevent purchasing risks from the aspect of internal management. Therefore, it is necessary to establish and perfect an early warning mechanism of enterprise purchasing risk. To achieve this, however, it is essential to construct the early warning evaluation index system of enterprise purchasing risk. As yet, in terms of enterprise purchasing risk, much of the literature focuses on identification, cause analysis, risk prevention and control[1-3] or specific risk measurement[4-5]. Little is researched on a comprehensive evaluation of enterprise purchasing risk, and there is still no research in the respect of the early warning evaluation of enterprise purchasing risk. As such, the paper seeks to apply the Balanced Scorecard (BSC) in early warning evaluation of enterprise purchasing risk, M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 471–477, 2011. © Springer-Verlag Berlin Heidelberg 2011

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and then the early warning evaluation index system of enterprise purchasing risk is established. It is noted that the Fuzzy Analytical Hierarchy Process (FAHP) is applied to early warning evaluation of enterprise purchasing risk.

2 Feasibility Analysis of the Balanced Scorecard in Early Warning Evaluation of Enterprise Purchasing Risk[6] Firstly, based on the balance idea, the Balanced Scorecard (BSC) emphasizes that the level of organization performance does not directly depend on its financial standing, and more attention should be given to the capabilities of sustainable development and value creation. As for early warning evaluation of enterprise purchasing risk, the concept of balance and overall planning should also be emphasized when building up the early warning evaluation index system. Specifically, it is of great concern to strike a balance between cost and benefit, short-term goal and long-term goal , development and stability, among past risk condition, current risk condition and possible risk condition in the future and so on. Secondly, the BSC, which puts the development at its centre, converts strategic goals of organization into performance evaluation indexes, and associates the behaviors of organization and its members with such goals. It is therefore beneficial to achieve strategic goals of organization and enhance organization performance. Taking purchasing as its central task, the purchasing department is required to translate its objectives into specific purchasing activities. Moreover, enterprise purchasing refers to continuous and developing activities, and it is unfavorable for sustainable development of enterprise purchasing if enterprises only focus on the current risk evaluation. Therefore, paying more attention to development factor is essential for the early warning evaluation of enterprise purchasing risk. Thirdly, the BSC presents qualitative and quantitative analysis method. Quantitative analysis should be a major method in the early warning evaluation of enterprise purchasing risk, and at the same time the combination of two methods is used when needed. Thus, the BSC provides a practical and reliable technical tool for the early warning evaluation of enterprise purchasing risk in a scientific and an accurate way.

3 Early Warning Evaluation Index System of Enterprise Purchasing Risk Based on the Balanced Scorecard Early warning evaluation index system of enterprise purchasing risk refers to a series of index sets that reflect enterprise purchasing risk condition, and a basic idea for setting up the early warning evaluation index system of enterprise purchasing risk is offered by means of starting with analyzing and predicting basic risk factors of enterprise purchasing[7]. Depending on enterprise controlled resources in procurement, obtaining the very products that enterprise needs at the cheapest possible price is a critical element in enterprise operation and is also an important source of profits. Through purchasing, the normal production process can be ensured. Particularly by improving the quality of raw materials and controlling and reducing the costs related to purchasing, product quality and economic benefit can be improved. However, due to the complexity of the environment and operation process regarding purchasing, enterprises will certainly face many kinds of risks in activities including purchasing planning, supplier selection,

On Early Warning Evaluation Index System of Enterprise Purchasing Risk

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purchasing decision, order processing, transportation, receiving and until the use of these materials. Meanwhile, the risks are caused by a number of factors, such as natural factors, economic policy, technological progress, price fluctuation, behaviors of the supplier and so on. To conduct an effective early warning evaluation of enterprise purchasing risk in a comprehensive and specific way, classifying these risk factors is needed to make their relationships clear. So the degree the influence of risk factors on the evaluation objectives can be distinguished. To analyze what factors lead to these purchasing risks, both external environment and internal operation should be taken into consideration. But these risk factors, whether from external environment or from internal operation, are complicated and correlated. Thus, it is impossible and also not necessarily to design early warning evaluation index system for each enterprise purchasing risk. The objective should be set before integrating related factors and indexes. Clearly, the BSC lays a foundation for integrating related factors of enterprise purchasing and the early warning evaluation index system. Firstly, according to the basic idea of the BSC, both financial factors of procurement and the potential factors for future development should be considered. Secondly, it is essential to consider risk conditions of procurement from the perspectives of performance and internal operation, and have close linkage between long-run strategic risk factors and short-run operational risk factors. Borrowing from research results of purchasing performance evaluation[6,8,9], risk factor analysis of the enterprise purchasing is proposed from four perspectives, that is, financial Risk of purchasing, internal operation risk, purchasing performance risk and future development risk. These four perspectives are corresponding to finance, performance, internal operation, future development. It is obvious that this risk analysis combines financial indexes with non-financial indexes and lays a foundation for establishing the early warning evaluation index system of enterprise purchasing risk. A. Financial Risk of Purchasing Financial risk of purchasing refers to a state of deviation from expected financial expected goals resulting from the unforeseen circumstances in purchasing by purchasing agencies. If financial risk indexes of purchasing are worsen in a low level, it indicates low performance of Purchasing input, while worsen in a high level, it means enterprise financial burden will be increased. The factors influencing purchasing financial Risk include purchasing cost risk, purchasing rate risk, purchasing capitalsaving risk and cost-saving risk of bulk commodity purchase. B. Internal Operation Risk Internal operation risk involves the possibilities and losses caused by operation failure or failing to achieve the expected goal due to limitation of cognitive ability and adaptability in procurement. The factors that affect internal operation risk of procurement include turnover risk, risk of an honest of purchasing staff, information management risk, open and transparency risk of purchasing, operating efficiency risk, standardized operation risk, risks of operating system construction, etc. C. Purchasing Performance Risk The right quality, the right price, the right quantity, the right time and the right place have been constant pursuit objectives of enterprise purchasing. Purchasing performance risk refers to the possibility and the degree purchasing activities and their results do not achieve the goals. The factors that affect performance risk of procurement include price

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risk, commodity coincidence rate associated with quantity, specification and quality, the risk of the purchasing department response to demand, environment risk, etc. D. Future Development Risk Future development risk refers to the possibility and its extent that enterprise can not adapt to new economic situation and new requirements. The factors that affect enterprise future development include risk of the expenditure on business improvement of purchasing staff, self-improving risk of purchasing staff, business exchange risk of purchasing agencies, risk of out-of-date purchasing model, risk of development strategy, etc. To maintain the significant momentum, enterprise should improve the quality of purchasing personnel, purchasing institutional self-adaptability and innovation when facing the fierce market competition. Based on the above risk factors, the early warning evaluation index system of enterprise purchasing risk is designed in accordance with mentality and principle of designing of early warning evaluation index system of risk. It centers on the objectives of early warning evaluation of enterprise purchasing risk and includes various factors that affect the operation of enterprise purchasing. The index system is showed in table 1. It should also be clearly noticed that early warning evaluation index system of enterprise purchasing risk designed here is of generality. These early warning evaluation indexes are required to be adjusted according to purchasing tasks of different enterprises. Furthermore, the calculations of early warning evaluation indexes of risk are also needed to be changed in the light of actual situations of different enterprise purchasing. Table 1. The early warning evaluation index system of enterprise purchasing risk

Early warning evaluation of enterprise purchasing risk

Target Layer

Rule Layer

Index Layer

Early warning evaluation indexes of purchasing financial risk

Purchasing cost

Early warning evaluation indexes of purchasing internal operation risk

Early warning evaluation indexes of purchasing performance risk Early warning evaluation indexes of future development risk

Purchasing rate Capital-saving rate Cost-saving rate of bulk commodity purchase Turnover rate Honest index The level of information management Open and transparency Standardized Operation Operating efficiency Operating system construction Price rationality Commodity coincidence rate service efficiency Environmental protection effect The ratio of business improvement to its cost Time for vocational study Business exchange rate A model innovation index The clearness of development strategy


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4 Early Warning Comprehensive Evaluation of Enterprise Purchasing Risk Each early warning evaluation index can only reflect one aspect of risk condition of enterprise purchasing. The entire risk condition of enterprise purchasing can be effectively reflected only when there is a comprehensive evaluation of the early warning evaluation index system. On this basis, the Fuzzy Analytical Hierarchy Process (FAHP) [10] is applied in the domain of the early warning comprehensive evaluation of purchasing risk. The Analytic Hierarchy Process (AHP) provides a framework for acquiring the weight of each risk factor by integrating expert evaluation, constructing the judgment matrix, and avoiding the errors in the logical reasoning in terms of complicated risks. Through simulating the property of making the judgment by human, fuzzy mathematics can be used for effectively dealing with imprecise and ambiguous information. The FAHP, however, is a model that combines the AHP and the Fuzzy Evaluation Method and makes them complement each other, thereby ensuring the early warning evaluation index system of enterprise purchasing risk more effective. A. The Construction of Factor set, Evaluation Set and Set of Decision Values Factor set refers to a set whose elements are various factors associated with the evaluation object. As illustrated in table 1,the factors under the objective of the early warning evaluation of enterprise purchasing risk can be classified into two grades: the first-grade factor set is X={X1, X2, X3, X4}={early warning evaluation index of purchasing financial risk, early warning evaluation index of internal operation risk, early warning evaluation of purchasing performance risk, early warning evaluation of future development risk};the second-grade factor is subordinate to the first-grade factor, and its factor set respectively is X1={X11, X12, X13, X14}, X2={X21, X22, X23, X24, X25, X26, X27}, X3={X31, X32, X33, X34}, X4={X41, X42, X43, X44, X45}. Evaluation set involves a set that is composed of any possible evaluation results about the evaluation object made by the evaluator. Evaluation set includes four levels: V={v1, v2, v3, v4}, representing {safe, basically safe, risk, major risk}. Set of decision values is a set that corresponds to the evaluation level and the set is B={b1, b2, b3, b4}, where bi stands for the decision value associated with the evaluation level of the (ith). B. Determination of the Weight of Each Index by the AHP The importance of factors in factor set is compared one another two at a time by expert. As to the second-grade factor set, the judgment matrix Cs(s=1， 2， 3， 4) can be respectively constructed with 1-9 methods of scale, and the largest eigenvalue λ s,max and the corresponding eigenvectors are solved by the matrix. Thus the weight of each factor is obtained as follows: Ws=(ws1， ws2， ⋯， wsm) Then consistency checking of these weights is carried out according to C.I.=( λ s,max m)/(m-1)≤0.1, that is, logical consistency checking of these weights is given. Likewise, the weight vector of factor set that is composed of the first-grade factors can be obtained as follows:

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W=(w1, w2, w3, w4) C. The First-Grade Comprehensive Judgement on Sub-factor Set Single-factor judgment matrix, that is, fuzzy relational matrices from U to V, is first constructed. It is generally obtained by using the method of random sampling. For U1:

⎛ r11 ⎜ r R1 = ⎜ 21 ⎜ r23 ⎜⎜ ⎝ r41

r12 r22 r32 r42

... r1m ⎞ ⎟ ... r2 m ⎟ ... r3 m ⎟ ⎟ ... r4 m ⎟⎠

where rij stands for the degree the index (ith) is defined as the level j. Similarly, R2, R3, R4 can be obtained by using the above matrix. Then the model of Fuzzy transformation from Ui to V is as follows: Bi=Ai·Ri=(bi1, bi2, …bin), i=1, 2, 3, 4 where n stands for the index of the (nth) in Ui . D. Second-Grade Comprehensive Judgement Single-factor judgment matrix R is established with R1, R2, R3 and R4, whose elements are made up of U1, U2, U3 and U4. Then it is followed by Fuzzy transformation from U to V: B=A·R=(b1, b2, b3, b4). By unitary processing, the model is as follows:

B' = (b1 ' , b2 ' , b3 ' , b4 ' ) . In this case, according to maximum membership principle, the level of enterprise purchasing risk can be judged to realize comprehensive judgement. If B≤[0.9, 1.0],it means safe and is defined as no warning area. At this level, the warning light is green. If B≤[0.7, 0.9） ,it means basically safe and is defined as a low-level warning area, where the warning light is blue; If B≤[0.5, 0.7） ,it represents risk and is defined as a medium-level warning area. Correspondingly, the warning light is yellow. If B≤[0, 0.5）， it stands for major risk and is defined as a high-level warning area, thus the warning light is red. The purpose of using lights of different colors is to warn managers involved in Enterprise Purchasing Risk to adjust strategies in good time to reduce the losses and the occurrence of the risks. It will also enhance the ability of risk resistance in enterprise purchasing. Meanwhile, a comprehensive, systematic and preventive management is required. The countermeasures regarding early warning management should be formulated and implemented according to the warning sign when a forecast or a warning has been given. In doing so, the risks and the losses can be reduced or avoided, thereby ensuring enterprise purchasing go on smoothly.


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5 Conclusions The goal of the paper is to provide a reference for enterprises to perform the early warning evaluation of purchasing risk and theoretically for further study on the early warning evaluation of purchasing risk. The early warning evaluation index system of enterprise purchasing risk is a basic part of enterprise purchasing risk management. It is noted that early warning and control of risk in advance can be realized by designing a scientific early warning index system of risks. The theory on early warning of risk is applied to the risk management. Also, the design idea of early warning evaluation index system of enterprise purchasing risk is proposed. On this basis, according to the basic principles of the BSC, the early warning evaluation index system of enterprise purchasing risk is constructed. And in the end, the FAHP is applied to a comprehensive early warning evaluation of enterprise purchasing risk. Acknowledgment. The research is supported by the Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality (PHR (IHLB)) under Grant PHR200907134.

References 1. Zsidisin, G.A.: Managerial Perceptions of Supply Risk. Journal of Supply Chain Management 39, 14–25 (2003) 2. Liu, B., Wan, W.W.: Risk Countermeasures and Strategies for Power Construction Company Purchase. Electric Power Construction 28, 61–62 (2007), doi:CNKI:SUN:DLJS.0.200702-022 3. Deng, Y.G.: Research on the Risk of Enterprise Material Purchase. China Logistics & Purchasing, 72–73 (2008), doi:CNKI:SUN:ZWZJ.0.2008-12-025 4. Jiang, W.D.: A New Way for Purchasing Risk Management. Technoeconomics & Management Research, 74–75 (2007), doi: CNKI:SUN:JXJG.0.2007-02-032 5. Wan, X., Yan, L.: Procurement Risk Management Model Based on VaR. Logistics Technology 26, 54–57 (2007), doi:CNKI:SUN:WLJS.0.2007-01-015 6. Zhang, X.Y., Liu, W.Y., Xue, R.: Equipment Procurement Performance Measurement Structure Design Based on BSC. Journal of Academy of Armored Force Engineering 20, 25–27 (2006), doi:CNKI:SUN:ZJBX.0.2006-06-006 7. Liu, Y.S., Tang, B., Yang, L.: Research on Early-Warning Index System of Logistics Enterprise Risk. Railway Transport and Economy, 74–76 (2010), doi:CNKI:SUN:TDYS.0.2010-02-024 8. Shang, C.B.: A Study on Performance Evaluation of the Military Material Purchase. China Logistics & Purchasing, 62–63 (2004), doi:CNKI:SUN:ZWZJ.0.2004-09-028 9. Zhang, M., Liu, W.Y.: Research on Construction of Equipment Procurement Performance Evaluation Index System. Military Economic Research, 36–37 (2007), doi:CNKI:SUN:JSYP.0.2007-09-011 10. Zhang, J.J.: The Fuzzy Analytical Hierarchy Process. Fuzzy Systems and Mathematics 14, 80–88 (2000)

Investment Value Analysis for Listed Companies of China Communications Industry Hua Han and Fei Tang Science College Wuhan University of Technology Wuhan, Hubei, PR China [email protected]

Abstract. In this paper, it studies 42 communication industry listed corporation companies in China. By constructing the evaluation index system, selecting the 13 financial indicators, using principal component analysis to extract six principal components so as to calculate the integrated value, thus the 42 companies were sorted. On that basis, through cluster analysis, the stocks which have similar performance are classified. Result shows that in the first quarter of 2010, about 50 percent of China's communications industry companies behave well and implicate enormous investment value, these companies are distinct on different aspects. It also gives the corresponding policy recommendations from the angle of both managers and investors. Keywords: communication industry, cluster analysis, investment value, principal component analysis.

1 Introduction With social development, communication technology and people's daily life are increasingly linked. Communications industry has become the national economy progress and basic industry. On the background of the global financial crisis, China telecommunications industry remained stable growth while global communications industry is generally depressed. The industry has gradually become one of the fastest growing and the most effective in China. With the coming of 3G mobile media era, the telecommunications industry has added new vitality. With a greatly increased scale of investment, communications section will continue to strengthen. Communications sector will definitely become the new focus in the future stock market. In view of the situation, how to objectively measure the communications industry investment value of listed companies to control market risk is the common problem facing by investment institutions and investors. With the deepening of the study for investment analysis, investors are increasingly concerning about the listed companies’ inherent investment value as well as communications industry. Through a forward-looking grasp to the regular pattern and trend of the stock’s intrinsic value, it can provide a scientific basis for investors to have a rational investment decision. M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 478–483, 2011. © Springer-Verlag Berlin Heidelberg 2011

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This article analysis the stocks’ investment value of 42 China's communications industry listed companies to examine the impact factor and establish an integrated investment value system. According to the 2010 first quarter financial indices, it establishes the investment value evaluation model which based on the principal component analysis and cluster analysis: Firstly, using the method of principal component analysis combines together with various indicators to form the main component, determine the correlation between principal components and investment value, calculate the principal component values, integrated values and rankings so as to find stocks with investment prospects. Furthermore, based on the extracting principal components, similar stocks are classified by cluster analysis in order to make comparative analysis of different category company.

2 Model Constructed A. Selection of Indicators For the analysis of the investment value of listed companies, many scholars construct the investment value index system. Financial dates obtained from the consolidation of listed companies can reflect the value of their investment to some extent. However there are many factors which affect the investment value of the listed company, such as profitability, solvency, asset management, capacity development and capital structure and so on. On one hand, including all indicators is impossible when we establish the investment value evaluation model. It not only lacks of maneuverability but also leads to distortion of evaluation results easily. If some selection has little effect on investment value or includes a greater amount of repeated information, the correlation among each factor is strong. On the other hand, it easily leads to miss some important indicators if we choose subjectively. Therefore, the proper choice of evaluation indicators is the key to evaluate the investment value of listed company correctly. For the communications industry, the research objects are selected from the same field, so the profession characteristic difference is not obvious. It can be ignored. According to the general theory of company's value, firm value is primarily decided by profitability, growth, liquidity, asset management and other various factors. Taking into account data availability and comparability between indexes, the paper selected the following 13 indicators to constitute the evaluation index system of listed company’s investment value: Main Business Profit Margins, Earnings Per Share, Net Asset Per Share, ROE, Current Ratio, Quick Ratio, Asset Liability Ratio, Fixed Asset Turnover, Total Assets Turnover, Total Assets Growth Rate, Net Profit Growth Ratio, Main Business Revenue Growth, Net Assets Per Share Growth Rate. B

．Selection of Evaluation Methods

Index system of the investment value of listed companies is constituted by a number of indicators. These indicators reflect listed company's operating conditions from different angles. It easily leads to wrong evaluation results if depending on only one indicator to assess the value of the company's investment evaluation. So it should be

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avoided. Judging the investment value of listed company by evaluation index system belongs to the problem of evaluating the integrated evaluation index system in the nature. Comprehensive evaluation methods are used commonly include principal component analysis, hierarchical analysis, expert consulting and so on. In this paper, it adopts the method of principal component analysis. The nature of this method is to seek less unrelated indicators instead of the original ones by seeking simplify indicators which unrelated to each other, so as to reduce dimension. The principal components can reflect not only the original information but also the similar indicators’ common sense and features after the combination of the principal component which chooses from the similar indicators. The integrated effect is greater than the actual interpretation of each one. In this way, it not only rules out the subjective factors when choosing and determining indicators but also reduces the influence of repeated information. It reduces variables which the quantitative analysis involved in and obtains more information. It is easier to grasp main contradictions. So the result of comprehensive evaluation is objective and reasonable. Cluster analysis is a method of studying “Birds of a feather flock together". Its basic idea is to provide a value about the certain samples or the degree of similarity according to a given measure of similarity or indicators. Thus we can classify the objects into several categories. For communication industry listed companies, the similar performance of companies can be classified through cluster analysis, then it provide a measure to make a contrast among different types and structure a reasonable and effective portfolios.

3 Analysis A. Sample Selection and Data Sources In this paper, it studies 42 listed companies of China’s communications industry, using the 42 companies’ basic financial data and key financial indicator on research. Raw date comes from Tong Huashun software. SPSS13.0 statistical analysis software is used for data processing. Under the cumulative variance in the required contribution rate, extracting the principal components to calculate each principal components’ value and the comprehensive ranking of investment value analysis. Furthermore, principal component values and integrated values are used as the experimental data to make further cluster analysis. B. Principal Component Analysis Process After input the dates into SPSS, in the cumulated variance contribution of 89.208% circumstances it can extract six main composition. Through the reasonable explanation about six main components combining with the individual scores and composite scores, it can evaluate the overall level of investment value for the 42 companies, the main component of each corresponding Eigen value characteristic vector is shown in Table 1, and the integrated values and sorting results are shown in Table 2.


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Table 1. Component matrix Component Name Main Business Profit Margin Earnings per share Net assets per share ROE Current Ratio Quick Ratio Gearing ratio Fixed asset turnover Total assets turnover Growth rate of total assets Net profit growth rate Main business revenue growth Net assets per share growth rate

1

2

3

4

5

6

0.441 0.680 0.290 0.697 0.238 0.204 -0.300 0.702 0.633 0.214 0.726 0.231 0.703

0.272 0.490 0.606 0.353 0.479 0.476 -0.422 -0.595 -0.690 0.439 -0.070 -0.608 -0.370

0.089 -0.297 -0.176 -0.277 0.831 0.841 0.015 0.105 0.102 -0.416 -0.047 0.287 -0.055

0.506 0.287 -0.420 0.445 0.019 0.039 0.734 0.036 0.098 -0.271 -.0378 -0.413 -0.084

0.432 -0.113 0.210 -0.240 -0.002 0.016 0.209 -0.065 -0.077 0.473 -0.437 0.336 0.404

-0.341 -0.049 -0.334 0.017 0.134 0.131 0.050 0.093 0.084 0.479 -0.046 -0.259 0.139

Table 2. Companies ranked Stock Code 002148 600658 002281 600522 002115 002194 002089 002093 600487 002231 600289 002151 600485 600498

Integrated value 3.1734 1.0773 0.9982 0.6512 0.6204 0.4995 0.4604 0.4516 0.4390 0.3674 0.3532 0.3352 0.2614 0.2276

Rank

Stock Code

1 2 3 4 5 6 7 8 9 10 11 12 13 14

000063 600345 000829 600105 002017 600050 000547 600640 000016 002188 600776 000733 000070 600260

Integrated value 0.2012 0.1935 0.1883 0.1841 0.0895 0.0645 -0.0587 -0.1376 -0.1400 -0.1623 -0.1963 -0.1992 -0.2607 -0.2625

Rank

Stock Code

15 16 17 18 19 20 21 22 23 24 25 26 27 28

000100 000062 000851 600130 000555 000890 600680 600775 600198 000586 000034 600677 002052 000766

Integrated value -0.3294 -0.3459 -0.4370 -0.4716 -0.5080 -0.5103 -0.5152 -0.5629 -0.6179 -0.6226 -0.7015 -0.7438 -0.7783 -2.2751

Rank 29 30 31 32 33 34 35 36 37 38 39 40 41 42

As TABLE 1 show, through principal component analysis it can reduce the 13 indicators to 6 main components. According to the contribution rate of the principal component and the Eigen value load quality of every principal component, the ability that each component represents can be easily got. It’s convenient for investors to construct investment portfolios. From the point view of integrated value in TABLE 2, there are 20 enterprises whose investment value are positive, accounts for 47.2 percent of the industry. The other 22 enterprises’ integrated values are negative, accounting for 52.8 percent of the statistical listed companies. It can be said that the percentage which the companies possessing investment value and investment potency is not small. Communications industry is still a potential investment stock in the future. The ranking can provide certain reference for investors.

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C. Cluster Analysis Process The evaluation in TABLE 2 largely meet investors’ need for the investment value analysis of listed companies, but the investors’ idea tend to vary and the focus of attention is always different. To analysis various factors more detailed, the paper will further make cluster analysis about the above companies depending on the already received six major components, in order to get more useful conclusions. Hierarchical Cluster which is belonged to the system of cluster analysis is used in the paper. The measurement adopts absolute value of distance scale, and clustering algorithms method is Wards’ Method, the classified conclusion is as follows in TABLE 3: Table 3. Company classification

Class

Stock Code

Number

000016ˈ000586ˈ000070ˈ000100ˈ000733ˈ000851ˈ002017ˈ000890ˈ

18

List 1

002194ˈ002188ˈ002231ˈ600260ˈ600198ˈ600640ˈ600677ˈ600680ˈ 600775ˈ600776

2

000063ˈ000062ˈ000547ˈ000829ˈ002052ˈ002089ˈ002093ˈ002151ˈ

16

600105ˈ600130ˈ600289ˈ600345ˈ600487ˈ600485ˈ600522ˈ600498

3

002115ˈ002281ˈ600050

3

4

000034ˈ000555ˈ000766

3

5

002148ˈ600658

2

The classification results suggest that the fifth class companies represent best, the integrated value are of the top two rows. The ranking of every principal component is on the top. Their comprehensive values are on the first two rows; the main business profit margins and net profit growth rate are higher. The companies have lower debt ratio, their outstanding competitive advantages and other indicators are better than the overall level of listed companies in communications industry. They belong to the leading in the same industry and are the first choice for investors to have a long-term investment. By contrast, the first class companies lag behind the overall ranking. The principal component values and integrated values are mostly below zero and lower than the overall industry average (expected value is zero). Net profit growth and main business revenue growth is negative. The companies are losing money whose shares are low income, low-growing. Although there is some main business profit, in general, prudent investors should not be too much involved in such stocks. The other three categories companies belong to the middle and upper ranks, investors can make reasonable and effective portfolio according to characteristics of class.


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4 Conclusion Through the above analysis, it can be found that in the first quarter of 2010, about 50 percent of China's communications industry companies behave well and implicate enormous investment value, and these companies are distinct on different aspects. Investors can choose the most advantages company into their investment choice scope. So, it provides a rational investment advice for investors to some extent. On the opposite, as for the management of the company, through the comparison with other companies in communications industry, they shall cause enough attention to the disadvantage factors, dedicate to improve corresponding skills so as to promote companies’ comprehensive value.

References 1. Han, Z., Xie, M.: Listed companies’ investment value evaluation model and empirical analysis. Journal of the central university of finance and economics (11), 71–75 (2004) 2. Johnson, D.A., Wachern, D.W.: Multivariate statistical analysis. Tsinghua University press, Beijing (2008) 3. Li, J., Guo, Y.: The principal component analysis method of evaluation indexes for more. Journal of engineering management (1), 39–43 (2002) 4. Wall, A.: Ratio Analysis of Financial Statements. The Accounting Review 3(4), 415–417 (1998) 5. Kiviluoto, K.: Predicting bankruptcies with Self-organizing map. Neurocomputing 1, 191–201 (1998) 6. Zhang, Y.: 3G mobile communication of China’s development present situation analysis. Hua Zhang 15, 153–159 (2009)

E-Commerce Extension Multi-factor Assessment Sunxu and Wan Haixia Jilin Technology college of Electronic Information Jilin, China [email protected]

Abstract. With the development and application of computer technology, internet and innovation of related technology, China’s enterprises invested considerable human and material resources to construct e-commerce systems, but the construction and application effects are not perfect because of many factors. In view of this, many researchers began to pay attention to comprehensive evaluation of enterprise e-business. In order to provide method reference to China’s enterprises, the author put forward a comprehensive evaluation method of e-business in this paper combining extension theory on the basis of previous studies. Keywords: E-commerce, enterprise, extension theory, determination model.

1 Problem Statement All Along with the amazing development of computer technology and the rising and popularization of Internet, with the innovation of correlation technique, human civilization gets into information era. In the meantime, the more and more enterprises start constructing and using information technology to construct their e-busines system. E-commerce evaluation understand the value of development e-commerce business.A scientific assessment method can promote the whole level and quality of e-commerce and improve the business regulation of e-commerce,while it promotes the healthy development of e-commerce and increases the corporate competitiveness [1]. In present years,e-commerce performance evaluation theory became one of a frontier problem and it was generally concerned by the enterprise and the academia circles.

2 Evaluation Index System and Method A. Establishment Evaluation Index System Evaluation index is objective vector and external styles of evaluation content,and the concrete expression of evaluation method. While it makes comment thinking and evaluation thinking ways carryin out through setup measures. The design of evaluation index needs to construct system analysis and to follow a couple of basic principles. Firstly, enterprise has to follow the combination scientifis and mainly principles.In terms of grasping the correctness of e-commerce assessment, the completeness of evaluation index design and the logical tightness of quantitative treatment method, it M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 484–491, 2011. © Springer-Verlag Berlin Heidelberg 2011

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has to reflece scientific priciples and construct performance evaluation index system to outburst the main index priciples.Scondly, enterprise has to follow the combination of quantitative and qualitative priciples. Quantitative index is more specific and intuitive. When evaluate it we can calculate actual numerical value. Evaluation results can make the directness and clear impression through quantification present. Therefore, the choice of evaluation index need to follow the combination of quantitative and qualitative priciples. Thirdly, enterprise has to follow combination of comparability and operability priciples. Evaluation index needs to have the rounded comparability, including compared wih othe e-commerce and compared with profession average level, mainly Enterprise has to select diffent enterprise indexes which can get them generally to ensure the comparability of index. Finally, enterprise has to follow comparability and systemic priciples of index. The quantitative index of e-commerce evaluation index system use relative index to evaluate. According to importance of carrying out evaluation objective of index, and the logical relation and the logical relations degree in diffent indexes, enterprises setup and select index to stick out the key point of evaluation index, to keep the relative unity and to carry out the optimization of system[2]. According to above priciples and combining to the related e-commerce evaluation index system[3], this essay construct the enterpise e-commerce evaluation index system. According to Figure 1:

Fig. 1. Evaluation index system of enterprise e-business plan

B. Evaluation Method In the present age, enterprise e-commerce evaluation methods include of the method of fuzzy cluster analysis and fuzzy comprehensive evaluation method, mainly. Althouth these methods is widely used, there is no other compared method to confirm the reliability of evaluation. Therefore, this essay construct the enterprise e-commerce evaluation methods basised of extension theory.

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a) Define cassical domain and joint domain When N j represents evaluating enterprise e-commerce and

ci represents enterprise

ci ’s value range is v ji =< a ji , b ji > ( i = 1, 2, " , n; j = 1, 2, " , m : n represents numbers of article feature； m represents grade

e-commerce feature, while the

number), the evaluating equipment classical domain can represents that:

R

j

⎡N ⎢ ⎢ ⎢ = ( N j , c, v) = ⎢ ⎢ ⎢ ⎢ ⎢⎣

j

c1 c2 # ci # cn

< a j1 , b j1 > ⎤ < a j 2 , b j 2 > ⎥⎥ ⎥ # ⎥ < a ji , b j i > ⎥ ⎥ # ⎥ < a jn , b j n > ⎥⎦

(1)

The whole of evaluating enterprise e-commerce plus the whole of enterprise ecommerce index which consist of matter-element is joint domain matter-element. While v pi =< a pi , bpi > is the ci feature ratio about joint domain matter-element. It expands the value range. Joint domain matter-element can represent that:

Rp

⎡N ⎢ ⎢ ⎢ = (N p , c, v) = ⎢ ⎢ ⎢ ⎢ ⎣⎢

< a p1 , b p1 > ⎤ < a p 2 , b p 2 > ⎥⎥ ⎥ # ⎥ < a pi , b pi > ⎥ ⎥ # ⎥ < a p n , b p n > ⎦⎥

c1

j

c2 # ci # cn

(2)

N p represents the whole of enterprise e-commerce. Obviously, it has that < a ji , b ji >⊂< a pi , bpi > (i = 1, 2, " , n ) .

b) Define evaluating matter-element N represents enterprise e-commerce and R represents enterprise e-commerce evaluation system index. Therefore,we can see that:

R

=

⎡ N ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢⎣

c

1

v

1

c

2

v

2

# c i # c n

# v i # v n

⎤ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥⎦

(3)

R repersents enterprise e-commerce evaluating matter-elementa. N represents enterprise e-commerce. vi represents ci ’s value about N or ci ’s concrete value about evaluating enterprise e-commerce feature index. c) Calculation of weight coefficient Weight coefficient can use system analysis method, elementary association function methods and analytic hierarchy process to define, from up to down. This eaaay use analytic hierarchy process to define every feature weight.


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We use AHP to process analysis. Firstly, we put the inclusion factors in every group and make every group as every level. Let the highest level, several middle levels and the lowest level in a row. The whole of levels must be in a row. We can assume that the whole of factors, A1 , A2 , " , Am , is finished. Therefore, the weight is

a1, a 2 ,", am , respectiively. The result of local level B1 , B2 , " , Bn is i b1i , b2i ,..., bni . We can assume that Bi and Ai have on relation, and b j = 0 ,

therefore the result of total taxis of hierarchy can represent by table 1. Obviously, n

m

∑∑ a b i

i j

=1

(4)

j =1 i =1

Total taxis of hierarchy is also a normalization normal form of vector. To evaluate the uniformity of Total taxis of hierarchy result, we have to calculate the detection observables as same as single sequencing. As same as the uniformity of single hierarchical arrangement, this step carries out from up to down. CI represents uniformity total taxis of hierarchy index. RI represents mean consistency index of total taxis of hierarchy. CR represents random index of total taxis of hierarchy index. Table 1. Hierarchy of the table

Level A

A1

A2 …… Am

a1

a2 …… am

Global weight level B

of

m

B1

b11 b12 …… b1m

B2

b 21

b 22

…

…

……

Bn

bn1

bn2 ……

∑ab i

i =1

i 1

m

∑ab

…… b 2m

i =1

…

m

∑

bnm

i =1

m

∑ a CI i =1

Ai

and

judgment

i 2

…

They can respectively present that: CI = about

i

matrix

in

i

level

i

a i b mi

( CI i is the consensus index

B),

and

CIi =

λ max − n n −1

.

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Sunxu and H. Wan m

RI = ∑ ai RI i ( RI i is mean consistency index about about Ai and judgment matrix i =1

in level B).Therefore, m

CI CR = = RI

∑

a i CI

i

∑

a i RI

i

i =1 m

(5)

i =1

λmax

is the energy of judgment matrix. n is the order of judgment

matrix. RI is mean consistency index. Usually, it can selected from table 2. Table 2. Different values of the order of the standard comparison matrix RI judgment matrix numbers

1

2

3

4

5

6

7

8

9

10

RI

0

0

0.58

0.9

1.12

1.24

1.32

1.41

1.45

1.49

Only when CR < 0.1 , we can say that the result of global weight has great uniformity. Otherwise we have to rebalance the value selection of matrix factors[5]. d)Calculation of correlation function and correlation degree When the correlation function represents value selection of matter-element on real axis, matter-element fits the requested degree. As a result of extension set of correlation function can represent by algebraic expression, we can resolve questions through quantification. According to extension theory, we can define the evaluating working state of quipment of about every standard of correlation function: the number of i index belongs the number of j standard about correlation function: ⎧ ρ ( xi , x ji ) ⎪ ⎪⎪ ρ ( xi , x pi ) − ρ ( xi , x ji ) K j ( xi ) = ⎨ ⎪ ρ ( xi , x ji ) ⎪− x ji ⎪⎩

xi ∈ x ji ; xi ∉ x ji

a ji + b ji

⎫ 1 − (b ji − a ji ) ⎪ 2 ⎪ ⎬ a pi + b pi 1 ρ ( xi , x pi ) = xi − − (bpi − a pi ) ⎪⎪ 2 2 ⎭

ρ ( xi , x ji ) = xi −

(6)

2

(7)

e) Comprehensive correlative degree and comprehensive evaluation in matter. Toward multi-index evaluation, to compare simply, we have to design general evaluating value to evaluate matter N about level j’s comprehensive correlative degree k j ( N x ) .


489

n

∑α

k j(Nx) =

i =1

ij

k j ( xi )

(8)

k j ( N x ) is evaluating mater about level j’s comprehensive correlative degree. k j ( x i ) is evaluating mater about every level of correlative degree (i = 1, 2," , n) .

α ij

is

every evaluation index of weight coefficient. As: k j 0 = m ax [ k j ( N x )] ( j = 1 , 2 , " , m )

Evaluation matter

(9)

N x belongs level k j 0 .We also can define eigenvalues’level

through calculating variable grade eigenvalues. As below calculation formula: k k

j

=

j

− m in k

j

j

m a x k j − m in k j

m

j* =

(10) j

j

∑

j× k

j

j =1

(11)

m

∑

k

j

j =1

Evaluation matter N belongs level

j* [4].

3 Empirical Analysis In this essay, active data indexes involved come from one of every associated department of a ralated electric power Co. Ltd. The selection of indicators standard value can acccord to these priciple: indicators standard value of enterprise index mainly use of index value of model enterprise. About unlocatde index of model enterprise evaluation system and designde index of enterprise indicators standard value, we can consult our historical data, industry standard and profession scoring method to study out. Inside every index weight should be calculated by AHP. We can refer active data index, standard value and value from table 3. According to table 3, the evaluating classical domain R j of defined enterprise ecommerce is : ⎡N1 ⎢ ⎢ ⎢ R1 =(N1,c,v) =⎢ ⎢ ⎢ ⎢ ⎢⎣

c1 ⎤ ⎡N1 ⎥ ⎢ c2 ⎥ ⎢ ⎥ ⎢ # # ⎥ R = (N1, c,v) = ⎢ ci ⎥ 1 ⎢ ⎥ ⎢ # # ⎥ ⎢ c15 ⎥⎦ ⎢⎣

c1 < 0.85,0.70 >⎤ c2 < 0.75,0.60 >⎥⎥ ⎥ # # ⎥ ci < a1i ,b1i > ⎥ ⎥ # # ⎥ c15 < 0.75,0.65 >⎥⎦

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Sunxu and H. Wan Table 3. Evaluation of a Power Company E-commerce and data

Establishme nt hardware facilityk1 Resource input k2 Network security k3

Trade sizek4 Socialbenft k5 Economic benefit k6

0.20 0.15

c31

0.15 0.25

classical domain

0.06 0.05 0.04 0.10 0.05 0.05 0.05

c32 c33 c41 c42 c51 c52 c61 c62

0.10

⎡N1 ⎢ ⎢ ⎢ R1 =(N1,c,v) =⎢ ⎢ ⎢ ⎢ ⎣⎢

Rp

c11 c12 c13 c21 c22 c23

0.15

0.03 0.07 0.04 0.06 0.70 0.80 0.15 0.10

Very good

Good

Normal

Bad

measured data

Two Three grade grade index weight index weight evaluation evaluation

0.88 0.58 0.56 0.48 0.26 0.48

0.02

0.28 0.78 95 750 0.80 0.56 0.85 0.78

c1 ⎤ ⎡N1 ⎢ c2 ⎥⎥ ⎢ ⎥ ⎢ # # ⎥ R = (N1, c,v) = ⎢ ci ⎥ 1 ⎢ ⎥ ⎢ # # ⎥ ⎢ c15 ⎦⎥ ⎣⎢

c1 < 0.65,0.10 >⎤ c2 < 0.55,0.35 >⎥⎥ ⎥ # # ⎥ ci < a1i ,b1i > ⎥ ⎥ # # ⎥ c15 < 0.55,0.35 >⎦⎥

Rj :

⎡N ⎢ ⎢ ⎢ = (N p , c, v) = ⎢ ⎢ ⎢ ⎢ ⎣⎢

j

c1 c2 # ci # c1 5

< 0 .9 0 , 0 .1 0 > ⎤ < 0 .8 0 , 0 .3 5 > ⎥ ⎥ ⎥ # ⎥ < a pi , b pi > ⎥ ⎥ # ⎥ < 0 .8 0 , 0 .3 5 > ⎦⎥

According to calculation (6,7), we can calculate every factors included level 2 index investigation value abou their correlation function of classical domain. We can get these evaluation matrices: k1 =[ −0.1106 0.0128 0.0208 0.0708] k2 = [ −0.015 0 0.015 0.04] k3 = [ −0.0128 0.0007 0.0142 0.0332] k 4 = [ 3.2

9.6

25.4

41.2 ]

k5 =[ −0.0027 0.0123 0.0273 0.0573] k6 = [0.0105 0.028 0.053 0.103]

According to (8), we can calcuiate comprehensive correlative degree of this evaluatin n

a : Kj (a) = ∑αi Kij (a) =[0.3007 0.9709 2.5656 3.7977] .If we let these 4 evaluation i=1

level(“very good”, “good”, “normal” and “bad”) as 1, 2, 3, 4, respectively, we can get


the result that,

491

K2 (a) = max K j (a) = 3.7977 . Therefore, we can evaluate that j∈{1,2,",5}

evaluating enterprise e-commerce is “very good”, Preliminary. To get basis for decision making more precise, according to (10) (11), we can calculate that

j* =3.6732. According to this result, this enterprise e-commerce multi-factor level is “very good” , but it not arrives at “very good” totally. It is in the middle of “very good” and “good”, in favor of “very good” [6].

4 Conclusion Extensive comprehensive evaluation approach is combined with qualitative analysis and quantitative calculation. According to these above analysis, we can get these result as below: (1) It can be made out that extension theory construct evaluation measure model enterprise e-commerce multi-factor level. (2) The expandable evaluation model not only evaluate enterprise e-commerce multi-factor level through association degree score, but also it can evaluate superiority and inferiority of enterprise e-commerce multi-factor level. The expandable evaluation model has obvious superiority compared with other methods. The key to enhance correctness of evaluation result is consructing evaluation index system, correctly and resonably. And we have to distribute every weight of index, correctly. Besides, grade interval of classical matterelement can make a tremendous influence to evaluation result.

References 1. Mou, D.: E-Commerce Performance Analysis. Enterprise Economy 6, 26 (2003) 2. Yao, Y.: Study on E-business Performance Evaluation Systems Based on the AHP. Science & Technology Progress And Policy 10, 129–133 (2009) 3. Liu, M., Chen, Z.: Research on Indicator System for Measuring E-commerce. Statistics & Information Forum 7, 20–27 (2008) 4. Cai, W.: Matter Element Model and Its Application. Science Press, Beijing (1994) 5. Zhao, H.: AHP. Science Press, Beijing (1986) 6. Liang, H., et al.: Extenics theory in evaluation of water quality in the application. Pollution control Technology and Equipment 7, 25–29 (2004)

SWOT Analysis of E-Commerce Development in Yunnan Province Sun Liangtao and Chen Gang Business College Honghe University Mengzi, China

Abstract. This paper applies the SWOT analysis method to analyze the strengths, weaknesses, opportunities and threats for the development of the ecommerce in Yunnan Province, makes a concrete foundation for the following exploiting local advantages according to the local conditions to develop ebusiness development strategy, thus provides referred advices for getting rid of the development dilemma and opening the way for e-commerce development in Yunnan. Keywords: Yunnan, E-commerce, SWOT analysis.

1 Introduction SWOT analysis is a method commonly used in strategic analysis method, is an analysis on the advantages, disadvantages, opportunities and threats. The basic principle of SWOT is that through a systematic analysis of the internal conditions and external environments of the studied objects like organizations, individuals, industries or regions, the internal strengths and weakness of the studied objects can be learned, the external opportunities and threats of the studied objects can be analyzed, and on this basis, the optimal action strategy can be selected to mobilize resources and strengths at a maximum level, exploit opportunities and avoid risks, realize the possibilities for sustainable development. Through a helpful SWOT analysis, the weaknesses can be transformed, the strengths can be developed, the opportunities can be grasped, and the development of electronic commerce in Yunnan Province can be accelerated in consequence.

2 The Strengths Analysis of the E-Commerce Development in Yunnan Province A. A Broad Market Prospect •

Agricultural Development Speed Is Fast and Agricultural Products Has Great Market Potential. Yunnan climate resources are very rich with unique location, a variety of agricultural products such as tea, sugar cane, oil plants, vegetables, flowers, pomegranates, tangerine and other agricultural products play


SWOT Analysis of E-Commerce Development in Yunnan Province

•

•

•

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important roles in the country. Although the agricultural products are rich in Yunnan province, but the market is comparatively dispersed with slow circulation and higher transaction costs. E-commerce can be applied to agricultural markets to link scattered markets together through the Internet to enhance the market competitiveness of agricultural products in Yunnan province, to create a brand of Yunnan province's agricultural products. It is also very helpful to improve the agricultural value chain and enhance the competitiveness of agriculture. Tourism will release a new vitality. Yunnan’s special geographical and climatic environment, numerous nations, long history and splendid culture created a unique tourism resource in Yunnan. Within its border, there is a magnificent landscape of mountains, forests, peaks; caves, rivers, lakes, spectacular waterfalls, Yunnan Stone Forest, Dali, Xishuangbanna, the Three Parallel Rivers, Dianchi Lake in Kunming, Lijiang, Yulong Snow Mountain, etc are all scenic areas of national priority. More than 100 nature reserves at or above the county level with the total area of 1.926 million hectares has been established in Yunnan province, 22 national and provincial forest parks with a total area of 85,500 hectares are also established here. Tourism industry needs the cooperation of many other sectors such as the traffic sector, the business sector, and e-commerce can link scenic spots, travel agencies, hotels, inns and other related industries together, attract more tourists with the help of web sites. Viewed from this point, tourism e-commerce is a new opportunity for developing e-commerce in Yunnan. Mineral Resources: Mineral Reserves Are Numerous in Both Quantity and Categories in Yunnan, Known as China's "Non-ferrous Metals Kingdom." 142 categories of minerals have been found, there are 92 categories with proven reserves, 1274 mineral deposits are identified. The maintained reserves of 54 categories of minerals rank the top 10 in China. The largest mineral advantage in Yunnan is non-ferrous mineral, the reserve of aluminum, zinc, tin ranks first in the country, the maintained reserves of copper, nickel metal rank third. Among precious metals and rare element minerals, the reserves of indium, thallium, cadmium metal rank first in the country, silver, germanium, platinum group metals rank second; among chemical raw materials minerals, the reserves of 8 kinds of minerals including phosphorus, salt, Glauber's salt, arsenic, sylvite, pyrite, calcium carbide with limestone, serpentine mineral for fertilizer use, ranking on the top 10 list. Yunnan has formed a group of mineral resources mining, dressing, and smelting industries with a certain scale mainly consisting of non-ferrous metals industries, it is the country's important production base of tin, copper, phosphate fertilizer. The field of geology and mineral resources is an important industry in Yunnan, the development of its ecommerce with integrated production, supply, and sales and the e-commerce integrating demand, and supply forms a large electronic market, so as to achieve the goals of raising greater efficiency, increasing sales, reducing inventory and lowering cost. The Development Space for the Logistics Industry Is Huge. Yunnan is located in the southwestern border of China, connecting with Sichuan and Tibet in the north, connecting with Guizhou, Guangxi in the east, is adjacent to Myanmar,

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Laos, Vietnam in the Southwest, connecting Pacific Ocean, Indian Ocean, Southeast Asia, South Asia, is an important channel open to South-East Asia. Now, "Kunming-Bangkok Highway" (from Kunming to Bangkok, Thailand) has opened, "Trans-Asian Railway" (Kunming, China through Vietnam, Cambodia, Malaysia, Singapore) has been under construction, the development of the logistics industry has a unique geographical advantage. Yunnan is in the center of the "China - ASEAN Free Trade Area,", with the opening the "China - ASEAN Free Trade Area”, the geographic advantage of Yunnan will be given full play, Yunnan Province has the potential and opportunities of becoming an important node of the international regional trade logistics chain, possesses the objective conditions of developing into a logistics center where the great Southwest facing the Southeast Asia. Yunnan possesses the basis for the development of modern logistics industry, and with the quickened economic and social development and the increase of the overall strength in the whole province, the development of the logistics industry has also made the corresponding achievements. Transport enterprises can integrate the existing vehicles, routes and stop sites, and changes into the logistics businesses as far as possible. Therefore, logistics and e-commerce has a promising development in Yunnan. B. Government Gives Strong Support and Encouragement to the Development of the e-Commerce Yunnan provincial commission of the CCP and the provincial government formulated 2 documents titled "The Implementation Opinions of Accelerating the Development of e-business in Yunnan Province "and "The “Eleventh Five-Year "development goals of E-Commerce in Yunnan Province". It is the requirement to realize "the Eleventh Five" economic and social development objectives to accelerate the advancement of ecommerce development in Yunnan province, during the "Eleventh Five-Year Plan" period, the main objective of e-business development in Yunnan province are: by 2010, over 70% enterprises in the province realize the primary internal information transformation; provincial key enterprises fully realize the internal information transformation and B to B e-commerce transactions; e-commerce applications will basically be realized in provincial tobacco, tourism, medicine, metallurgy, information, electricity, flowers, transportation, petrochemicals, commerce and other key industries and large agricultural trades; to strive to have more than 40% of large enterprises that apply e-commerce to procure raw materials or parts and sell products. SMEs with good conditions realize the e-business applications; the government procurement will have a full realization of e-commerce transactions between business and government. This laid a solid foundation for the development of e-commerce in Yunnan and creates a favorable environment for development.

3 The Analysis of Disadvantages of e-Business Development in Yunnan Province A. Network Infrastructure Lags Behind Network infrastructure is one of the biggest bottlenecks restricting the rapid development of e-commerce. The realization of real-time online transactions requires a


495

very fast network response speed and higher bandwidth, which must be provided by the hardware support for high-speed networks. , Although Yunnan has made certain achievements in the network infrastructure after the development in recent years, however, due to insufficient investment and lack of technology and human resources, etc, there is still a big gap between the construction of the network infrastructure and the requirements of the development of e-commerce. Meanwhile, areas with developed Internet in Yunnan are confined to a handful of main cities; some areas are yet to solve the internet access problem, some areas with internet access need to raise the speed of surfing on the internet. Many factors such as lagged telecommunications infrastructure, the serious shortage of internet access among the whole population, unreasonable prices seriously hinder the development of e-commerce in Yunnan. B. The Internet Development Lags, Network Coverage Rate Is below the National Average The Building and wider application of Internet is the base of the e-commerce. The development of electronic commerce needs rapid, safe, stable network system, and a large number of Internet users. According to the 25th China Internet Development Statistics Report issued in January 2010 by the China Internet Network Information Center, ended December 31, 2009, the number of Internet users has reached 384 million people, the coverage rate reached 28.9%, an annual growth rate 28.9%, of which the number of internet users in Yunnan Province is 8.44 million, the internet coverage rate is 18.6%, ranking No.27 among all provinces in the country, the network coverage rate is below the national average. C. Insufficient Internet Applications, the Low Percentage of Online Transactions As of December 2009, the national rate of net applications ranked online music (83.5%), network news (80.1%), and search engines (73.3%) as the top three. By the end of June 2009, the proportion of Chinese Internet users doing online shopping is 28.1%, the number of online shopper reached 87.88 million, online shopping penetration rate among Internet users is not high, only 26%. Online shopping penetration rate in Beijing, Guangzhou and Shanghai is 51.3%, 52.6% and 35.2% respectively Internet users in Beijing, Shanghai and Guangzhou, represents only 8.4% of the country, but online shoppers account for 15.6% of all online shoppers in the country. Among them, the number of online shoppers in Shanghai reached 6.13 million, ranking first in the three cities. The proportion of online shopping in Yunnan has not yet reached the national average, compared with the figures in economically developed regions; the Yunnan e-commerce market still needs more breeding. D. Weak Awareness of e-Commerce Yunnan Province is located in the border areas with mostly minorities and relatively backward economy, people's thinking is also relatively closed, and lack a clear understanding and understanding on the importance and necessity of the development of e-business. On the one hand, governments in some prefectures and cities do not recognize the important role the government can play on the development of ecommerce, did not take positive and effective policies to promote e-commerce development; on the other hand, enterprises are the main body of e-commerce, but some enterprises have only a weak sense to develop e-commerce, focusing only on short-term interests, leading to backward management, lacking stamina for enterprise

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development; furthermore the general public lacks sufficient enthusiasm for the participation in electronic commerce, it is difficult to for the general public to change the traditional shopping habits of "See with eyes, touch with hands, listen with ears, tastes with tongue", which restrict the rapid development of consumption patterns of online shopping. E. Information Technology and E-Commerce Personnel Shortage E-commerce is the organic combination of information modernization and business, so the development of e-commerce needs multi-level and complex talents who understand not only technology and management skills, but also business and law talent. To achieve the integration and upgrading of e-commerce and traditional industries, talents are the key. Due to a number of disadvantages like natural, social and economic factors, Yunnan lack enough attractiveness for talents, which will inevitably lead to deprivation and loss of talents. This is very bad to the development of electronic commerce. F. Logistics Distribution System Is Not Perfect An easy, fast and efficient E-commerce depends partially on a fast logistics system. As logistics companies in Yunnan do not have a strong economic strength, resulting in high logistics costs, limited coverage area. The professional and technical levels of the logistics system in Yunnan are relatively low and are unable to adapt to rapid ecommerce information flow and cash flow needs. Currently a number of third-party logistics companies have formed in Yunnan province, but these companies have not achieved the scale of economy and lack efficiency on the distribution of goods, which limits the further development of electronic commerce in Yunnan province.

4 The Analysis of Opportunities for E-Commerce Development in Yunnan Province A. The Influences of the Financial Crisis The financial crisis triggered a global economic recession, many companies are in the layoff or a pay cut, quite a number of businesses went bankrupt. E-commerce can save costs for businesses, improves efficiency, expands market, open a new development path for enterprises. The development of electronic commerce can be accelerated greatly by e-commerce by integrating electronic commerce with related businesses such as IT, communications, logistics and other industries; meanwhile the state can adopt various measures to expand domestic demand, accelerating the flow of material merchants and personnel, provide the perfect opportunities for the rapid development of e-commerce. B. "Late Development Advantages" and the Great Environment for Development Because of the existence of late development advantage, less developed regions can learn from the successful experience of developed areas, conduct technical imitation and innovation, the system reference and remolding, the optimization and upgrading of structure, make up own deficiencies with others’ advantages. Yunnan can use information technology and electronic commerce to influence and change methods of


497

the allocation of resources, make the development of the region no longer depend entirely on local resources and conditions; transform traditional industries, change systems change concepts through direct use of new technology, new thinking, new management approach in order to shorten the gap, to realize the goals of the leapfrog socio-economic development in Yunnan. As e-commerce possesses the characteristics of low transaction costs, high efficiency, and huge market, many companies actively develop e-commerce market. In addition, the state is also increasing funding for the construction of related infrastructure investment. This has accumulated some experiences and also laid some material foundation for the development of ecommerce in Yunnan province, also provided the guarantees of many aspects such as human resources and technology. C. Great Potential Benefits E-commerce can push forward the economic development of a region or country from multi-levels and around all directions. E-commerce can lower the operational costs, improve efficiency for enterprises and to provide enterprises with a broad market space, enhance the overall competitiveness of enterprises; to break through time and space constraints of traditional transactions, providing personalized products and services and provide great convenience for people’s work and lives. Yunnan must tap the huge potential e-commerce benefits to achieve the rise and economic leap-forward development. D. Resource Allocation Level Is Improved Yunnan is a great resource province with rich tourism resources and human resources, and has established the multi- category industrial system consisting of tobacco, tourism, medicine, flowers, metallurgy, construction materials, etc. The development of e-commerce can take full advantages of various advantages of Yunnan province, rising continuously the application level of e-commerce technology in the relevant industry , and take the path of low-cost, high-quality, cost-effective development to enhance the overall resources allocation level, which will be conducive to rapid and healthy economic development in Yunnan province. E. China - ASEAN Free Trade Area Was Officially Launched On January 1, 2010, China - ASEAN Free Trade Area was officially launched, and Yunnan is located in the China - Southeast Asia two regional economy convergence zone, is the forefront of regional economic cooperation, is a important windows and bridges, through which, China and neighboring countries strengthen neighborly friendship and the economic and trade exchanges. The launch of China-ASEAN Free Trade Area brings great opportunities to Yunnan's foreign trade and e-commerce.

5 The Threat of e-Business Development in Yunnan Province A. There Is a Risk for E-Commerce Security System Network security is the key issue of e-commerce development, any organization conducting business on the Internet must take active measures to ensure adequate safety system to prevent the illegal invasion and loss of information leaks. Viruses, fraud, hackers and other factors continue to threaten the security of online transactions,

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L. Sun and G. Chen

China's encryption technology, and digital signature technology is relatively backward, and these factors become safety hazards for the development of electronic commerce in Yunnan Province. Due to technical factors, Yunnan lags behind in the construction of the e-commerce security system, coupled with the lack of a sound credit system; there are some inevitable risks on the electronic trading. B. E-commerce Related Laws and Policies Is Still Not Perfect Besides security system and support system, business-related laws, regulations and policy support are also needed for the e-commerce. E-commerce transactions are completed through the computer and network, involving a number of legal issues, how to use legal means to ensure the security of online transactions, binding laws and regulations are needed to deal with the main e-commerce legal issues such as evidence problems, clearing certification and contract certification, the validity of making electronic contracts and the time and place of the contract validity, , legal regulations on the transaction behaviors of buyers, sellers and intermediaries, transaction risk and liability issues, etc. But e-commerce transactions is a relatively new transaction approach, at present, e-commerce legislation and the corresponding standard is not perfect, it is difficult to effectively guarantee the legitimate interests of parties in the network transactions. C. Inter-departmental and Inter-regional Coordination E-commerce is a huge and complex social engineering involved not only the two sides of the transaction, but also the industrial and commercial administration, taxation, banking, insurance, customs, and many other sectors and different regions, different countries. It also involves cooperation among a number of links and multiple industries on information resources, electronic payment, security certification, trade flows, taxation at different levels. This requires unified laws and policies to regulate, restrict and coordinate related issues and sectors. At present, a unified, coordinated, and orderly e-commerce system in China has not yet been built, which, restricts to some extent the development of e-commerce in Yunnan.

Summary Through SWOT analysis, we have recognized the strength, weaknesses, opportunities and threats of e-commerce development in Yunnan Province, laid a concrete foundation for making the following specific e-business development strategies by exploiting local advantages according to local conditions; enable Yunnan to get rid of e-commerce development dilemma, and go ahead on a development path with an overall planning, focused key points, continuous improvement, less investment, fast achievements. Acknowledgment. Many thanks to the support of Honghe College Scientific Research Foundation for Masters and Doctors on this project titled: "A Study of the Influences of E-commerce on the Economic Development in Yunnan", Project Number: XSS08023.


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References 1. Li, Q.: E-Commerce Introduction. Higher Education Press, Beijing (2006) 2. Wang, J., E-commerce, A.: Business Perspective. Higher Education Press, Beijing (2007) 3. Du, Y.: Take Full Advantages of the Functions of Information Modernization in the Changes of Economic Development Methods in Yunnan. Economic Problems Exploration, 190 (July 2008) 4. Jiang, F.: An Analysis of the Current Situation of E-Commerce in Yunnan. The Academic Journal of Liaoning Engineering & Technical University, 153–155 (March 2004) 5. China Internet Information Center. China’s Online Shopping Market Research Reports (November 2009) 6. China Internet Information Center. China Internet Development Statistics Report (January 2010)

Application of Analytic Network Process in Agricultural Products Logistics Performance Evaluation Xiaolin Zhang1,2 and Chunhui Wang1 1.

Department of Economy and Management, Tianjin Agricultural University, Tianjin, China 2 Business School, Tianjin University of Finance & Economics, Tianjin, China [email protected]

Abstract. Besides the technology advancement and political support, an important factor in the development of agriculture is the circulation of agricultural materials and products, which is agricultural products logistics. This paper analyzed the meaning of agricultural products logistics and characteristics of its development. This paper established an agricultural products logistics performance evaluation indices system based on analytic network process (ANP) performance evaluation methodology. Then it discussed the theoretical foundations and application process of ANP and analyzed dependence and feedback among indices. Super Decisions software was used to obtain the result of ANP model for the indices system. The case study in this paper proves that the ANP method can solve problems with dependent indices effectively. Keywords: agricultural products logistics, performance evaluation, analytic network process (ANP).

1 Introduction Agriculture is the basis of national economy and it has been attached much importance by the government with the rapid development of our national economy. In the new century, China has entered a new stage of agricultural development, which is at a high speed. As the foundation of national economy, the development of agriculture is emphasized more and more. An important factor in the development of agriculture is the circulation of agricultural materials and products, namely, agriculture logistics, besides the technology advancement and political support. Agricultural Products Logistics has formed a potentially huge market demand for logistics because of large quantities and varieties. It has become an important part of agricultural industry. Nevertheless, the level of Chinese agricultural products logistics is still in a primitive stage for several reasons, such as high costs and low efficiency. The delayed construction of modern logistics system of agricultural products has seriously affected the process of agricultural industrialization in China. Agricultural Products Logistics is one important part of economic behavior, which is to create value and surplus value with the purpose of the act. Modern agricultural products logistics is to use modern science and technology to service in modern M. Dai et al. (Eds.): ICCIC 2011, Part I, CCIS 231, pp. 500–506, 2011. © Springer-Verlag Berlin Heidelberg 2011

Application of ANP in Agricultural Products Logistics Performance Evaluation

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society. It is a profit-oriented economic behavior. Modern agricultural products logistics is a global agricultural market. The production and consumption has become a worldwide behavior. Through high-tech, high intelligence and modern marketing, agricultural products have entered into the international circulation of the track. Agricultural products logistics is throughout the entire process. With the agricultural production process and the increasing integration of the circulation process, the labor in agriculture and trade have integrated. Now agricultural production is the production of circulation, and the consumer is the circulation of agricultural products consumption. In modern times, how to meet the current consumer’s demand for agricultural products, how to develop the potential demand for agricultural products, and how to create new demand, are running the development of durable agricultural products logistics. A successful agricultural products logistics management, which is an important tool to improve the organizational competitive power and to drive the development of social economy, will obviously provide sustainable competitive advantage. There are many researches on the literature on evaluation methods. It is necessary to make an evaluation for the reality of some of the management decision-making. Through the evaluation, we can identify strengths and weaknesses in order to improve the system. Evaluation is an important decision-making tool. The significance of the study about evaluation is to provide the basis for decision making of complex economic system according to results of the evaluation. Today, agricultural products logistics has been given more and more attention, including evaluation on agricultural products logistics performance. Zhao Yingxia [1] constructed for the evaluation of agricultural products logistics from three angles, which are the external environment of agricultural products, internal processes and overall effectiveness; Du Xiaofang [2] from Huazhong University of Science and Technology established a fresh agricultural product such as JIT delivery logistics effectiveness evaluation model, whose evaluation results showed that access to fresh farm produce more benefits than the traditional distribution system; ZHAO Zhen and Wang Wenbin [3] made the logistics of the evaluation index system of agricultural products, and established a multi-index comprehensive evaluation of nonlinear decision-making model based on network analysis (ANP ); Gong Dickson [4] impacted from four areas of logistics and distribution of fresh factors, and established three levels of the 25 indicators the evaluation index system, using multi-level fuzzy comprehensive evaluation model to evaluate.

2 Constructing Evaluation Indicator System of Agricultural Products Logistics It is significant to establish a logistics system performance evaluation of agricultural products to judge and evaluate the performance of logistics activities, which means to improve the existing system of agricultural products logistics services by providing a reference. To ensure the effectiveness of the system, some principles should be followed in establishing the system: systematic principle, scientific principles, and operational principles, qualitative and quantitative principles.

502

X. Zhang and C. Wang

According to the paper [5], an ANP model for agricultural products logistics performance evaluation indices system is shown in Table 1. The influential factors are derived through widespread investigation and consultation with several experts. Table 1. Agricultural Products Logistics evaluation indices system criteria logistics infrastructure

human resource

logistics information management and customer service levels

Sub-criteria transportation distribution network storage preservation proportion of highly educated employees proportion of employees obtained logistician certification employee training information level logistics standardization investment in hardware investment in software feedback quality management management fees

3 Analytic Network Process Method The AHP is a relatively popular tool for multi-criteria decision-making and has successfully been applied to many practical decision-making problems. The basic assumption of the AHP is that the decision-making problem can be decomposed in a linear top-to-bottom form as a hierarchy, where the upper levels are functionally independent from all lower levels, and the elements in each level are also independent. But many decision-making problems cannot be structured hierarchically, or there would be strong interactions and dependencies between inter-level and intra-level elements. There are many ways to determine the index weight. AHP and ANP are all used to solve unstructured and semi-structured decision problems. As the application of AHP method is on the premise that index system is a separate hierarchical structure, while the index of agricultural products within the logistics system is not independent, the logistics of the evaluation of agricultural products should adopt the ANP method [3]. ANP has the advantage that the process can be considered in the analysis of various indicators of the interaction between the inevitable and conditionality. Saaty proposes a “supermatrix” approach and extends the AHP to problems with dependencies and feedback. The resulting ANP generalizes the AHP and provides a framework for dealing with decision-making problems within which assumptions about dependencies between criteria and alternatives are unnecessary. The ANP has been applied to a large variety of evaluations: marketing, medical, political, social, forecasting, prediction and many others. For example, V. Ravi, Ravi Shankar and M. K. Tiwari [6] use ANP model, for end-of-life computers in reverse logistics; Wu Weiwen and Li Yuting [7], for knowledge management strategies selection; Eddie W. L. Cheng and Heng Li [8], for strategic collaborating. In


503

agricultural products logistics performance evaluation problem, decision-makers might intuitively feel that some factors are more important that others in affecting their final preference among alternatives. If there is some feedback and interdependency among the factors, an unimportant factor may turn out to be far more important than even the most intuitively important one. Therefore, ANP is preferred over other approaches to handle agricultural products logistics performance evaluation problems. The establishment of a logistics system performance evaluation of agricultural products to judge the performance of logistics activities, evaluation, thereby improving the existing system of agricultural products logistics services provide a reference of great significance. Evaluation system o ensure the effectiveness of the system should be followed in establishing the following principles: the principle of systematic, scientific principles, operational principles, qualitative and quantitative principles, financial indicators combined with the principle of non-financial indicators. An ANP model on agricultural products logistics performance evaluation system will be constructed in Super Decision (SD) software here, which is a simple easy-touse package for constructing decision models with dependence and feedback and computing results using the supermatrix of the ANP. A typical network structure is as below[9].

Fig. 1. A typical network structure

A. Supermatrix First, the first step of ANP is to compare the criteria in whole system to build up the supermatrix. The relative importance value can be determined using a scale of 1-9 to stand for equal importance to extreme importance. We postulate network structure is composed of hierarchy C k (h = 1,2, "" , m) . For each hierarchy, Ck assume there exist elements ek1 , ek 2 ,"" , ekm , so the influence of C k (h = 1,2, "" , m) can be denoted as below:

504


Which is the general form of the supermatrix. Wij shows the influence of each element of the i hierarchy on j the hierarchy, which is called a block of a supermatrix, whose form is as follows

⎡Wi1 j1 ⎢ ⎢Wi2 j1 Wij = ⎢ ⎢ # ⎢W ⎣⎢ in1 j1

Wi1 j2 " Wi1 jn ⎤ j ⎥ " Wi2 j2 Wi2 jn ⎥ j ⎥ # " # ⎥ Win j2 " Win jn ⎥⎥ 2 i j ⎦

B. Weighted Supermatrix The priorities of elements in one hierarchy according to a certain criterion can be denoted with a supermatrix, which means every column of every hierarchy in the supermatrix is column stochastic. However, the influence that other hierarchy according to this criterion is not concerned. As a result, each column of the supermatrix is not column stochastic. It is essential to consider the influence between every two hierarchy. The method is: regarding each hierarchy as an element, and pairwise comparing according a certain hierarchy, then computing corresponding priorities. Assume aij is the influence weight of the i hierarchy on the j hierarchy, let W ij = aijWij

(1)

W is a weighted supermatrix. In a weighted supermatrix, addition of elements in each column is 1. Matrix has this trait is called column stochastic. This step is much similar to the concept of Markov chain for ensuring the sum of these probabilities of all states equals to 1.

C. Limited Supermatrix What we want to obtain is the priorities along each possible path in a supermatrix, on the other word the final influence an element on the highest goal. This kind of result ∞

can be acquired by solving W , W

∞

= lim W k →∞

k

(2)

The weighted supermatrix is raised to limiting powers like in (2) to get the global priority vector or called weights[10]. For compute the weight of factors, index system in Table I is used to establish the model. Agricultural Products Logistics Performance model has been constructed in Figure 2 based on analyzing theories and consulting experts.


505

Fig. 2. Super Decision model for the Evaluation index system

With the help of Super Decision software, it become more easy to calculate the supermatrix, weighted supermatrix and limited supermatrix. The elements have been sorted by priority, which help decision-makers focus on certain factors. We can see the priorities of alternatives in Figure 3.

Fig. 3. Priorities of alternatives in evaluation system of Agricultural Products Logistics

The priorities were shown in Figure 3 , it can help decision makers to make decision more easily. It is clearly which factors have a greater influence in the Agricultural Products Logistics. The green number were normalized by cluster, the last column means the priorities of every index, people can make decision according to the priorities directly.

506


4 Conclusion Agricultural products logistics system is a very complicated system. For such a system, how to evaluate the performance? How to optimize the system? These problems are of practical significance. From the development process of agricultural products logistics, the logistics of agricultural products are at the initial stage of development. It is significant to research on agricultural products logistics performance evaluation. In this study, agricultural products logistics performance evaluation was considered as a multi-criteria decision problem and a model was proposed by using ANP. The ANP approach proposed in this study offers a more effective method for problems with dependence and feedback, with which decision-makers can evaluate more exactly and more rationally. But the model developed in this paper has a limitation as well: the evaluation result is based on the opinion of experts in agricultural products logistics field, whose preference to some criterion might have influenced the result. Although Delphi method is used in pairwise comparison phase, some subjective factors are still inevitable. Further research should be carried out on the usage of triangular numbers, which can revise human vague and imprecise judgments.

References 1. Zhao, Y.: China’s agricultural products logistics evaluation index system. Business Research, 211 – 213 (2007) 2. Du, X., Zhang, J., Zhang, S.: Agricultural Products Logistics Assessment Model for JIT delivery efficiency, 103- 106. Huazhong University (Social Science) (2004) 3. Zhao, Z., Wang, W.: Agricultural Products Logistics Performance Evaluation of ANP method. Agricultural system science and comprehensive study, 237–240 (2005) 4. Gong, D.: Perishable goods logistics performance of the fuzzy comprehensive evaluation. China Transportation, 104–106 (2007) 5. Yang, J., Qi, Y., Tang, C.: The Construction of the Performance Evaluation Index System of Sichuan Agricultural Products Marketing Logistics. Journal of Sichuan Agricultural University 26(3), 301–304 6. Ravi, Ravi Shankar, Tiwari, M.K.: Analyzing alternatives in reverse logistics for end-oflife computers: ANP and balanced scorecard approach. Computer & Industrial Engineering 48(1), 327–356 7. Wu, W., Li, Y.: Selecting knowledge management strategies by using the analytic network process. Expert Systems with Applications 32(1), 841–847 8. Cheng, E.W.L., Li, H.: Application of ANP in process models: An example of strategic partnering. Building and Environment 42(7), 278–287 9. Xu, S.: Practical Decision-making Method——Theory of Analytic Hierarchy Process. Tianjin University Publisher, Tianjin (1998) 10. Wang, C.-h., Wei, J.-y.: Research on the Dry Port Location of Tianjin Port Based on Analytic Network Process. In: 2008 Internationl Seminar on Business and Information Management, vol. I, p. 77 (2009)

SMEs Contest between Asymmetric Rivals in Financial Market from an Evolutionary Viewpoint Zheng Zhou and Fanzhao Zhou Center for Economic Research Harbin Commercial University Harbin, China [email protected]

Abstract. This paper mainly discusses the contest between two types of businesses in the financial markets, one is intense innovation geared but of smaller size and the other being just the opposite. From an evolutionary viewpoint, a model is established from references to the hawk-and-dove game theory in an attempt to illustrate the process of competition so that we can find how a new institution is to be formalized. And it can also demonstrate which roles both parties act in the game. It sheds light on the appropriate way which will facilitate the formalization and promotion of a newer and better institution. Keywords: Logistic Innovation, Following Cost, Fitness, SSE.

1 Introduction1 Since logistic theory was introduced into China in 1990s, past financial enterprises in planned economy system had transformed into new ones in succession. But it was just a simple change of a name. And it brought financials the first valley on the developing road in China. We found in financial market that actually innovation happened every now and then, but there were a little which could have key effect on the companies. Especially there are many small and medium enterprises (SMEs). To a turn, these key innovations change the status of financial company and improving the operational benefit. Thus, to study the development of financial innovation has become a important theme. Innovation was brought forward by Joseph Alois Schumpeter in 1911, and soon became a best-known core conception. As the explanation of Schumpeter, innovation is not only a new technical discovery, but also a economic conception. It means “enterpriser carries out new combination of production factors”, introducing a new productive function, so that the company can produce more than ever. In his eyes, the reason why the economic system can go from a kind of equilibrium to another kind of equilibrium is the continuous innovation activity. Modern financial is a process including management, control and execution, dominated by information, using present financial technology, target on satisfying 1

This thesis is supported by the funds project under the Ministry of Education of the PRC for young people, named "Analysis of Evolutionary Game and Research on Related Factors about Innovation of Financial System"(09YJC790062).


508

Z. Zhou and F. Zhou

customer’s need, to improve the efficiency and benefit of flowage and deposit of raw materials, products in process, finished products and correlative information from supply to consume. Compared with the traditional financial system, modern financial system improves qualitatively whether on the advance of technology or on the social and economic benefit. Entering into the 21th century, there appears a new trend of development of financial technology, including four sides: 1, accelerating the research and practice of integrated financial system technology; 2, financial establishment and facilities growing to be reconfigurable, reusable and extensible; 3, virtual financial system coming into appliance; 4, financial system growing to be environmental (Du Xiaojun, 2001). These leads to three new targets: response ability, agility or elasticity, Condense. The realization of these three targets depends on financial company’s possession and use of information. That is to say, a modern financial company should also be a intellectualized company. From three views of the form and approach of financial innovation, innovation can be divided into two types: 1, product innovation and procedure innovation; 2, technology-push innovation and market-traction innovation; 3, radical innovation and gradually innovation (Hans Christian Pfohl, 2004). Different innovation types depend on different innovative elements. And companies with different structures face different innovations. Because companies with different scale have different drive to take innovative strategy, we analyze mostly whether a innovation developed by a company with little scale can be recognized by the market.

2 Evolutionary Game of Asymmetric Financial Rivals Consider two financial company groups, one is small, as be player A, the other is big, as be player B. assumed that big companies have market leadership, and small companies have market vigor and elasticity comparatively. In order to occupy market, small companies have to take innovative competition strategy on his own-take supplying innovative product or service as a example, continuously developing new product. Because the financial market is competitive, we might as well suppose that one’s market influence is in the direct ratio to its market capacity. Assumed that big companies’ market influence is μ, and small companies’ market influence is λ. Because big companies have bigger market than small ones, we can obtain that μ>λ, and μ+λ=1. Because the market of innovative product is uncertain, small companies may supply common product instead of innovative product. Thus A companies have two options: strategy 1 is to supply innovative product, strategy 0 is to supply common product instead of innovative product. Because of considering the factors such as market preference and cost, B companies also have two options. Strategy 1 is to follow the innovation, supposed the following cost is i. If so, A companies will gain the following cost entirely. Strategy 0 is to supply common product instead of to follow the innovation. This following cost is mainly made up of patent transfer fee or management technology transfer fee, including staff training expense and equipment updating expense, etc. When A companies and B companies choose option 1 at the same time, the innovation is realized and recognized by the whole market. B companies’ fitness defines as b11, but they have to pay the following cost i. Thus their fitness turns to be

SMEs Contest between Asymmetric Rivals in Financial Market

509

b11-i. And A companies’ fitness is a11+i correspondingly. Because B companies have bigger market, we find b11>a11. And because they adopt the same innovation, we can suppose a11/a00=b11/b00=θ. Θ describes the changing rate of fitness brought by innovation, θ>1. When A and B choose 0 at the same time, they can both gain some fitness by common product. Because inferior innovation will be washed out in competitive market by all appearance, we just take innovations superior to common product in this paper. Because of the brand effect, big companies’ fitness is bigger than small ones, 0

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