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The valuation of technology in buy-cooperate-sell decisions

Valuation of technology

Vittorio Chiesa and Elena Gilardoni Politecnico di Milano, Milano, Italy, and

Raffaella Manzini

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Universita` Carlo Cattaneo – LIUC, Castellanza (VA), Italy Abstract Purpose – This paper is aimed at studying the technology in buy-cooperate-sell decisions process in order to identify and analyse the logical steps that should characterise a complete and reliable appraisal process. Design/methodology/approach – The paper develops a framework to support the whole process, based on literature analysis and an empirical study. A case study is presented in order to discuss some of the theoretical and practical problems affecting the appraiser during a technology valuation. Findings – It is found that the use of the proposed framework: forces the appraiser to perform a systematic and rational analysis, coherent with the internal and external context of the valuation; points out the most critical elements that could lead to a misleading and/or unusable and/or biased valuation; forces the appraiser to solve some critical trade-offs and to deal with contrasting elements; imposes coherence throughout the process and consistency among the various hypotheses and assumptions needed to finally identify a (range of) final value(s); gives the appraiser a communication tool, as different people are involved during the process; allows people (even if not directly involved in the process) to understand how the value of the asset has been determined and the validity, reliability and precision of the results obtained; and increases the bargaining power of the appraiser during the negotiation with a potential counterpart, allowing a clear and complete understanding of the value of the asset. Originality/value – This paper analyses the entire process and gives emphasis to the critical aspects of each phase, suggesting some solutions. Keywords Asset valuation, Intangible assets, Technology led strategy, Decision making, Italy Paper type Case study

Introduction In the last few years the importance of external technology acquisition has greatly increased and this is critical for the success of the innovation process within firms (Chatterji, 1996). In fact, in the area of technology, firms much more frequently contract-out their own technology to third parties or contract-in technology from external sources than they did in the past (Escher, 2001). In the literature this topic is widely analysed and discussed, especially from the perspective of companies that access external sources of knowledge and technology (Roberts and Liu, 2001). The following topics have already been given significant attention: the motivation that pushes companies towards external sources of knowledge and technology (Atuahene-Gima and Patterson, 1993); the organisational forms for accessing This paper is the result of the joint work of the authors. Vittorio Chiesa wrote the “Introduction”, Elena Gilardoni “The valuation of intangible assets in literature”, “Techniques for valuing technological assets” and “The appraisal process: a reference framework” and Raffaella Manzini “The empirical study” and “Concluding remarks”.

European Journal of Innovation Management Vol. 8 No. 1, 2005 pp. 5-30 q Emerald Group Publishing Limited 1460-1060 DOI 10.1108/14601060510578556

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external sources (Chatterji, 1996; Chiesa and Manzini, 1998); and the management of technological collaborations (Chiesa, 2001). These studies reveal a significant problem, which affects the definition, organisation and management of collaborations aimed at exchanging technology and technical know-how. This problem is related to the valuation of technology-based assets, such as patent, process and technical know-how. The aim of this paper is to analyse the process of appraisal for technological assets involved in a buy-cooperate-sell decision, in order to develop a framework to support managers in dealing with this type of process. The valuation of intangible assets in the literature In the literature as well as corporate practices, great attention is given to intangible assets. An intangible asset is defined as a resource that does not have a physical embodiment and whose industrial and economic exploitation gives a claim to a future benefit (Bouteiller, 2000; Smith and Parr, 2000; Lev, 2001). There are several intangible assets’ classifications (Brugger, 1989; Anson, 1998, 2001; Gotro, 2002); one illustrative, although not comprehensive clarification has been put forward by the Financial Accounting Standards Board (Holzmann, 2001) (see Table I). As shown in Table I, the term “intangible asset” covers a wide range of resources; in fact it could be: . part of an integrated group of other business assets: such as trained staff, mailing lists, customer lists, agreements; or . an independent economic unit: such as patents, copyrights, trademarks, technological know-how, technical drawings. This paper focuses on assets belonging to the second group, i.e. on separable and identifiable assets (Brugger, 1989; Guatri, 1989). In particular the paper considers technology-based assets such as patents, process and technical know-how, engineering drawings, computer software and databases. These technology-based assets[1] can generate income (and therefore value) separately from the business enterprise and can be bought, sold or licensed-in/out as independent assets. This phenomenon is becoming increasingly relevant, and it is highlighted by the fact that firms are increasingly relying on external sources of technology to support their innovation Intangible assets

Examples

Customer-based or market-based assets

Customer base, mailing list, distribution channels, presence in geographic location or markets Technical expertise, assembled workforce, trained staff Favourable government relations, outstanding credit rating Consulting agreements, advertising contracts, rights (water, gas allocation, lease) Patents, copyrights, trademarks Computer software and programs, technical drawings, database

Workforce-based assets Corporate organizational-based and financial-based assets Contract-based assets Statutory-based assets Technology-based assets Table I. Intangible assets

Source: Holzmann (2001)

process (Roberts, 2001, Jones et al., 2000, Howells, 2000, Chatterji, 1996, Chatterji and Manuel, 1993). The nature of technological innovation – the need for technology fusion, the increasing specialisation in knowledge production, the pressure on time and costs – forces companies to search for partners able to support their innovation process, particularly those that serve their need for technological assets (Kodama 1992, Chiesa and Manzini, 1998, Chiesa, 2001). In this context, a “market for technology” is emerging (Arora et al., 2001), in which technology is exchanged among different companies through buy/sell transactions or within several forms of co-operative agreements (such as joint ventures, alliances, consortium etc.). Whatever the form of transaction, the commercialisation of technology calls for a definition of the “value” of the subject technology. In the existing literature there are several articles dedicated to the importance of these technological assets and to the problem of their valorisation. The importance and the value of technological assets have increased consistently in the past two decades. In fact, today the value of intangibles exceeds the value of tangibles by six-seven times (Lev, 2001); whilst at the beginning of the 1980s the value of tangible assets was twice that of intangibles. A great deal of research concentrates on this first aspect (Morris, 2001; Korniczky and Stuart, 2002). In the past, companies derived a significant part of their own value from hard assets and manufacturing processes (Gotro, 2002) investing heavily in the use of tangible assets to gain a competitive advantage. Today, technological assets play a key role in determining the value of the company (Daum, 2001). This is consistent with the changes affecting the competitive context. In recent years the competitive context has become more and more dynamic and turbulent. In other words, there is not only competition among tangible assets, that either change very rapidly or are not able to sustain the competitive advantage over the long run, but also (and even more) with intangible ones. This is particularly emphasised in the area of technological assets. Hence these intangible assets are becoming a powerful tool in facing competitive market forces alongside the traditional assets (WIPO, 1998). The second theme analysed in the literature is the valorisation of intangible assets. The valuation of these types of assets is critical for company shareholders. It is critical in assessing the true value of shareholder companies. It is also an important tool for the management of the firm in supporting the decision-making process. The literature contributions are focused on different aspects of the valuation. A number of authors have analysed the methods and techniques applied to perform a proper economic analysis. These methodologies can be classified into two main groups (Mun, 2002): (1) traditional methods (among them, the most important are the cost, market and income method); and (2) innovative methods (among them the most important is the real option method). These methodologies are diffused not only in the academic literature (Anson, 1998; Mard, 2001), but also in corporate practice (Mullen, 1999). As regards these contributions, the valuation techniques will be presented in the next section. Other authors have frequently discussed different problems, such as: . the coherence between the techniques and the type of intangible asset (Smith and Parr, 2000);


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the coherence between the techniques and the objective of leveraging technology (Khoury, 1998); and the linkage between the appraisal method and a specific form of transaction (e.g. licensing) (Berkman, 2002).

Little literature has been written on the valuation process and in particular about: the most important principles of the appraisal process; the specific activities to be conducted; and how the process should be organised and managed. Some contributions derived from available consulting literature, which draws on some guidelines from the direct experience of companies. There are, in fact, different international valuation firms that provide independent valuation services to the business, financial and legal communities (such as Appraisal Economics Inc., The Patent & License Exchange, Inc. or Willamette Management Associates). They define the main steps making up the process as: (1) Definition of the problem. This implies the identification of the intangible assets to be valued, the description of the scope of analysis, and the identification of some limiting conditions such as the assumed accuracy of data used in the appraisal. (2) Preliminary analysis and data selection and collection. The appraiser must analyse and understand the forces, which guide and influence the entire valuation process, such as, the relative bargaining power and the relationship existing between the buyer and the seller. (3) Application of the three traditional methods. The practice focuses strongly on the cost, market and income method. (4) Reconciliation of values. When an analyst uses several valuation methods, he or she rarely obtains the same value indications. In this case he or she has to define a range of “significant” values so as to understand why a method is producing outlier value indications. The consulting literature shows the appraisal process is composed of different and critical activities. The overall weakness of these contributions is that although a set of activities is described, a systematic view of the whole process (of the links among activities and of the relative managerial problems) is not discussed in detail. In view of what is expressed in the academic and consulting literature, the attempt here is: (1) to study in depth the entire appraisal process and activities, thus presenting a systematic vision of the entire process; (2) to understand how the management of different activities influences the effectiveness of the valuation, identifying the critical problems to be solved during the appraisal; and (3) to suggest some guidelines by ascertaining some solutions to the identified problems. Techniques for valuing technological assets Appraisal methods and techniques are broadly classified into: . cost method; . market method;

. .

income method; and real option method.

These valuation methods are well documented in an extensive bibliography: Gilardoni, 1990; Anson, 1996; Khoury, 1998; Stiroh and Rapp, 1998; WIPO, 1998; Martin, 1999; Razgaitis, 1999; Reilly and Schweihs, 1999; Mard, 2000; Mard et al., 2000; Smith and Parr, 2000; Anson, 2001; Anson and Serrano, 2001; Damodaran, 2001; Khoury et al., 2001, King, 2001; Mard, 2001; Spadea and Donohue, 2001; Benninga, and Tolkowsky, 2002; Hoffman and Smith, 2002; Khoury, 2002; Mun, 2002; Tenenbaum, 2002; Khoury, 2003; Park and Park, 2004. In this paper, the methods and techniques are presented for an illustrative purpose and are not intended to reflect a comprehensive review of valuation issues. The cost method The cost method appraises the value of technology assets by measuring the expenditure necessary to create and develop the technology asset. This method is based on the economic principle of substitution in which a prudent investor would pay no more for a technological asset than it would cost to create or acquire a similar asset. The technology asset value is related to its cost structure. The structure of cost to be considered during the valuation process can vary. In the literature, there are several definitions of cost which include: . Cost of avoidance (or cost savings) quantifies either historical or prospective costs that are not incurred by the owner of the technology due to the ownership of the subject technology. . Trending historical costs. Current historical asset development costs are identified and quantified and then “trended” to the valuation data by an appropriate inflation-based index factor. . Re-creation cost (or reproduction cost) is the total cost, at current price, to develop an exact duplicate or replica of the subject technology. This duplicate asset would be created using the same materials, standards, design, layout and quality used to create the original technology. . Replacement cost is the total cost to create, at current price, an asset having equal utility[2] to the technology subject to be appraised. However, the replacement technology would be created with modern methods and developed according to current standards, state of the art design and layout and the highest possible quality. Accordingly, the replacement technology may have greater utility than the subject technology. Among these, the most common types adopted in practice are reproduction and replacement costs. However, many authors consider the structure of cost irrelevant to establish the value of a technological asset. At most, it could be used as a benchmark value. In fact the cost-based method has too many weaknesses. It does not take into consideration the amount of economic benefits related to the ownership and exploitation of assets, whereas it includes the sunk R&D costs. The second main weakness is the implicit assumption that expenditure should always create value, as a matter of fact not all costs lead to successful assets. Another weakness is related to the efficiency of


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investments. The cost method assumes that the level of past investment-effectiveness will be the same in the future. This is a false assumption as there are several situations in which an investment can be characterised by different levels of efficiency. This method is usually used when the application is at such an early stage of development that its market application is still unclear. In this case, in fact, the level of uncertainty is higher and the knowledge of the future business is very limited. In conclusion, the cost-based method appears inappropriate to establish the value of the technology, as it is applicable only when the extent of uncertainty is very high. Even then only a benchmark value is provided.

The market method The market method measures the present value of future benefits by obtaining a consensus of what others in the marketplace have judged it to be. This provides an indication of value by comparing the price at which similar intangibles have been exchanged between willing buyers and sellers. In other words, when the market approach is used, an indication of the value of the specific item of intangibles can be gained from looking at the price paid for comparable asset. This appraisal method is based on the economic principle of competition and equilibrium; in a free and open market the supply and demand factors will drive the price of all goods to a point of equilibrium. This method is largely intuitive and easily understood, for this reason it is widely adopted. The application of the market method can be summarised as follows: (1) Identifying the units of comparison (comparables). In order to do this, the selected units have to be comparable each other. Elements commonly looked at to select the appropriate comparables are: industry, market share, capital investments required for the exploitation. (2) Identifying the appropriate information. For each comparable, the appraiser has to collect data about: the transaction, i.e. the value at which the transaction has been concluded; and an economic measure, such as revenue, or margin or net profit associated to the technology-based asset, or, alternatively, an operative measure such as, for example, the number of users of the technology. (3) Calculating the ratio between the value of transaction and the economic or operative measure. This ratio is called “multiple”. (4) Applying the “multiple” to determine the value of the technology. Requirements for successful use of this approach include the following: . the market has to be active: having a few number of exchanges does not make a real market; and . the market has to be public: the information of exchanges have to be available. The main weakness concerns the point that transactions are unique (referring, for example, to the specific characteristics of the buyer and/or of the seller), in fact this is not considered by the market method as it assumes that the value of the transaction is similar to that of comparables.

The income method The value of any asset can be expressed as the present value of the future stream of financial benefits that can be obtained from the exploitation of the specific technology considered. This method is based on the principle of expectation. For the application of this technique, the calculation of the future cash flows, related to the specific asset, the time horizon considered, i.e. time in which the above cash flows can be generated and reliably estimated, and the actualisation rate, which reflects the business risk and is usually estimated with the Capital Asset Pricing Model, is needed. The expression of the value of the asset is shown below:

VT ¼

T X NCFðtÞ t t¼1 ð1 þ kb Þ

where: VT

¼ technological asset value.

NCF(t) ¼ net cash flow. kb

¼ actualisation rate reflecting business risk.

T

¼ time horizon.

This method is the most accurate to value technology as it considers the specific operating environment (market size, pricing, cost structure, risk) in which the technology is exploited. However, its practical application may present problems, as the required data can be difficult to estimate.

The real option method The cost, market and income methods all have significant limitations because they consider given technological assets without considering the opportunity (but also the risk) embedded in them. In particular the income method assumes that the projection will meet the expected cash flow and it handles the risk in the actualisation rate. However, cash flow is usually stochastic and risky by nature, the risk has different characteristics and can change across project time. A method that overcomes this limitation is the real option method; it, in fact, is considered an extension of income analysis. The real option is an instrument to respond to uncertain events. The theory behind option pricing was originally developed for use in financial development. It has recently received growing attention in R&D and in new technology development because it can support the decision process. In fact, not all decisions are made in the present but are deferred to examine the future. The real option is also applied to establish the value of technological assets during a transaction process: when information is incomplete and, in particular, unknown the appraiser can (has to) use the option theory in order to make risk and uncertainty explicit.


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This new method is tailored to deal with uncertainty and flexibility. The adoption of this method requires the identification of factors such as: . present value of project cash flows; . standard deviation of the project value; . investment cost of project; . time left to invest in; and . risk-free interest value These factors are used to calculate the value of intangibles using a specific formula; the most famous is The Black-Scholes Model. The real option method represents a new way of thinking; uncertainty is considered an opportunity to create economic value. These methods have not been presented in order to give a comprehensive review of valuing issues related to valuation methods, but to underline their strengths and weaknesses (Table II). As shown in Table II, each valuation method requires specific data and information and different resources in terms of the appraiser’s competencies and skills and is suitable only in specific situations and contexts. In addition after balancing advantages and drawbacks for each valuation method, the appraiser could choose to use more than one method simultaneously.

The appraisal process: a reference framework According to the current literature presented in the above sections, a framework has been developed aiming to give a systematic vision of the appraisal process and to identify the most critical problems. This framework is described in Figure 1. Within the framework, three different elements should be distinguished: activities, constraints and links. The activities represent the logical phases of the appraisal process: (1) identifying the unit of analysis; (2) identifying the aim and scope of analysis; (3) identifying the most appropriate valuation method(s); (4) comparing available and necessary data; (5) collecting data; and (6) determining the value of the asset. The process is affected by constraints such as: . available data; . necessary data and resources/time required to apply a method; and . available time and allocated resources. The links represent the relationship between two or more logical phases. Obviously such links do not indicate a sequential relationship, but a logical one. As a consequence, in some case, different phases can be conducted contemporarily, and/or there could be feedbacks throughout the process.

Real option method – find the value of the asset starting from the appraisal of the future benefits associated to the asset and considering uncertainty and variability in future outcomes

Option calculation required to use a complex formula. The project value uncertainty is difficult to estimate. The underlying has to be estimated

Most technological assets are not traded frequently enough to be able to establish a comparison. The intangible assets are commonly traded within a business and it is difficult to dissociate them from the business. Get enough details on similar transactions is difficult. The market is characterised by the buyer’s interest and this may bring in distortions The projection of the future net cash flows is difficult. The estimation of the actualisation rate is complicated. It has to consider not only the cost of capital but also the risk associated to the intangible asset. The required data and information need to be estimated

A practical and logical method applicable to all type of intangible assets. Most direct method

Some elements that in the other methods are considered implicitly, such as the income generating capacity, the appropriate cost of capital and the risk associated with the asset, are made explicit. Adaptable and flexible method. Well know and widely recognized method Most complete method. Uncertainty and variability are considered

The future earnings of the asset is not reflected. The efficiency of past investments is not considered. There is the implicit assumption that expenditures should always create value

The idea of the minimum value is given. The information and data are available and highly reliable (reproduction cost)

Cost method – reproduction cost: find the value of the asset starting from its recreation cost. Replacement cost: find the value of the asset starting from the recreation of its own utility Market method – find the value of the asset starting from sales comparison

Income method – find the value of the asset starting from the appraisal of the future benefits associated to the asset

Major disadvantages

Major advantages

Methods and scope


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Table II. The major appraisal methods

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Figure 1. The appraisal process framework

The activities of the appraisal process Identifying the unit of analysis. A correct appraisal process starts by identifying the unit of analysis. Problems can emerge during the appraisal process of the technological asset. Even though an asset is an independent economic unit, it can be a part of a product, system or service. In a number of cases, there is a difference between the technological asset and the product, which embeds the technology and is available on the market. Electrical products representative of the industrial sector present such a case, where the technological asset is a component of a system. For example, the microchip is a component of several products such as PCs and mobile telephones. If the technological asset is a component of a system, it is important to recognize that not all the income (or value) generated by the system is related to it. In some cases, indicators measuring the technological asset’s value compared to the value of the system can be identified. But it is not possible to suggest a general method to identify such indicators at this point. In fact it is due to the technological asset and the system. For example, a possible solution can be identified considering the incidence of the reproduction cost of the technological asset on the system. The same incidence could be used to estimate the value of future cash flows generated by the technological asset analysed. At some point it would be interesting to understand the exact contribution of the technological asset to the functioning of the entire system. The higher the contribution, the higher the value generated by the technology. Another aspect of the problem arises when the technological asset has different uses, i.e. when it can represent, in different situations, an end product, a component or a work in progress. For example a company can use a pharmaceutical molecule as an end product and can sell it on the market; the same pharmaceutical molecule can be used as a catalyst in a chemical process. This implies that different values can correspond to various uses, i.e. that the unit of analysis is not the single molecule, but the “molecule plus its relative use”. As pointed out in these examples, recognizing the right unit of analysis can be difficult. But it is important for the appraisal process because it allows for making a correct definition of the context and borders of analysis. Thus, it is fundamental because it defines the unit of reference for all the other activities. The proposed framework aims at putting into evidence these issues and, in synthesis, at alerting the appraiser to pay attention to these problems: . an intangible asset can be a part of a product or system, even if it is considered as an independent economic unit; in this case, it is necessary to separate the value generated by the intangible from the value of the product/system; and . the same intangible asset can have different uses, in this case it is important to identify a specific use, to which a specific value is associated. Identifying the aim and scope of analysis. The valuation of technological assets can be performed in different contexts and, hence, may have many different aims (Rabe and Reilly, 1996; KPMG, 1999). The context of the valuation can be: . The accounting process: due to the rising interest and relevance of intangible assets, a correct accounting of intangible assets is necessary. This, in fact, allows managers and stakeholders to increase their own knowledge of the dynamics of value creation and to define the value to be considered within the accounting reports and the external financial reports.


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.

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The decision-making process: valuing technological intangibles is critical for managers that are required to make decisions on: technology acquisition versus internal development; direct versus indirect technology exploitation; technology selling versus technology licensing. The transaction process: an intangible asset analysis and valuation is often required to define the terms of the contract related to the transaction process (e.g. the negotiated price). The main commercial transaction forms are: the transfer of ownership – this category includes all business transactions, in which there is a complete shift of the ownership title of the asset that a part grants to another without restriction; and the transfer of the right of use – it is the right that the owner of a technological asset grants to a third part, under the payment of an earning (Brooke and Skilbeck, 1994). The infringement process: sometimes the intellectual property rights on intangibles can be infringed and in these situations a valuation of damage is required. The bankruptcy process: in dividing and distributing the debtors’ assets, the value of intangible assets has to be established to identify, for example, any cancellation of debt income.

The comprehension of the aim and scope of the analysis affects the appraisal process since it influences the available data and the identification of the most appropriate valuation method(s) (see Figure 1). These links will be analysed later. Identifying the aim and scope of the analysis often requires a specification of the set of actors potentially involved in the use of the intangible valued. For example, in a transaction or in case of bankruptcy, the identification of the potential buyer/seller or licensee/licenser or creditor is required. The specific characteristics of the counterpart (its competence, marketing strategy, cost structure etc.) affect the valuation, since they determine the specific data to be used when the valuation method is actually implemented. It is critical to underline: . The correct identification of the context of analysis influences the identification of the most appropriate method(s) for the valuation and the relative application. . The identification of the aim and scope of the valuation defines the context in which the valuation takes place. It allows for the improvement of the accuracy of data used and the quality of the valuation itself. Identifying the most appropriate method(s). The appraiser has to identify a method (or methods) to be used to determine the intangible’s value. As shown in Figure 1, this activity is influenced by several factors: . The availability of time and resources. A first selection of the method is made considering the level of resources allocated to the process. In fact, the appraiser has to select a suitable method, according to the resources (in terms of quantity, but, first of all, competence) that are actually available. Some sophisticated method, such as the income or the real options method, can be used only by expert and trained analysts.

.

The identification of the aim and scope of analysis. For example, consider an appraiser who has to support the accounting process. In this case, the accounting rules must comply with the historically sustained costs that have to be considered and, hence, the cost method is required. Instead, if the analysis is conducted in order to support a transaction process, the appraiser has to value the future potential benefits generated by the asset and the cost for exploiting it. Hence, a method able to take into account the future benefits associated with the intangible asset is necessary, such as the income or the real options methods.

In synthesis, it is important to observe that the choice of the valuation method is not trivial, and that several elements are to be considered. In particular, the advantages and disadvantages of the various methods (shown in Table II) should be evaluated in the light of the specific aim, scope and resources identified for the analysis. Comparing necessary and available data. As mentioned previously, in the literature review the major appraisal methods are widely explained and discussed. The main characteristics of the methods are described in Table III, in terms of necessary data, time horizon and resource required. These must be considered to correctly use the techniques. In particular, matching necessary data with available data is critical. As a matter of fact, beyond theoretical considerations about the coherence of the method with the specific context, aim and scope of the valuation, a definite set of data is necessary to adopt each method. As a consequence, if the necessary data is not available (due to a lack of time, resources or competence etc.) the (theoretically) selected method cannot be adopted. In other words, comparing necessary data with available data allows for the identification of the “usable” method(s), among those previously selected as appropriate for the specific case. In several cases the available data is not coherent with the context and bundles of valuation and/or with the necessary data. Sometimes, in fact, the specific context requires the use of a particular valuation technique (e.g. the income method), but the necessary data is not available (e.g. the projection of future net cash flow). However, the analyst has to resolve the problem and come to a valuation. In this case, the appraiser may decide to accept a lower level of accuracy of the valuation, using “proxies” or fuzzy estimations for the unavailable data. The value indication will be less precise, but will be obtained with a method, which has the right “perspective”. The result obtained can be improved, in the future, with greater resources, time, etc. As pointed out above, defining the usable method is a critical step that implies for coherence with the other steps previously described. In some cases, this step forces the appraiser to accept compromises or to select the “best solution” when the “optimal solution” (in terms of accuracy, precision, overall coherence etc.) cannot be identified. Collecting data. In order to determine the value of the technological asset, it is important to access and collect data concerning different aspects (financial, operational and market oriented) and different time (historical, contemporaneous and future). The unit of analysis, the aim and scope of the valuation and the usable method identified, determine the types of data that have to be collected (Figure 1). During this activity the main problems are related to: . The identification of data sources. The necessary data, in general, has to be partially collected outside the appraiser’s company. This means that data


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Table III. Characteristics of major appraisal methods

Replacement cost

Cost Reproduction cost

Methods Material: it includes expenditures related to the tangible elements of the intangible asset development process Labour: it includes expenditures related to the human capital efforts associated with intangible asset development process Entrepreneurial incentive: it is the amount of expenditures required to motivate the owner of the intangible asset to enter into the development process or to produce a new patent, trademark, chemical formulation, etc. The previous types of cost should be adjusted in order to express the historical costs to current price (a capitalisation rate has to be considered); and take into consideration the obsolescence, i.e. the reduction in the value of the intangible asset due to improvements in technology or its inability to perform its originally function (e.g. the remaining useful life) Material: it includes expenditures related to the tangible elements used during the intangible asset development process Labour: it includes expenditures related to the human capital efforts associated with intangible asset development process

Necessary data

Present-Future

Past

Time horizon

18 (continued)

#

Resources required for a correct applicationa

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Entrepreneurial incentive: it is the amount of expenditures required to motivate the owner of the intangible asset to enter into the development process or to produce a new patent, trademark, chemical formulation, etc Similar transactions: the comparison is made with reference to transactions involving similar assets that have occurred recently in similar markets Future net cash flows: incremental revenues; decremental expenses; additional investments Time horizon: the period during which the intangible is expected to generate net cash flows Actualisation rate: the future net cash flows will be actualised Underlying: it is the current value of asset, that is the present value of expected cash flows Exercise price: it is the present value of investment cost Time of expiration: time until opportunity disappears Risk: project value uncertainty Interest rate: risk-less interest rate

Necessary data

Future

Future

Present

#

Resources required for a correct applicationa

Note: aThe amount of resources (time) required to apply the method increases following the arrow; in fact the methods are listed in increasing order of sophistication (Pitkethly, 1997). For example, the cost method (e.g. reproduction cost method) could require a lower amount of time and resources than income method. This is justifiable because the income approach involves some element of forecasting the future cashflows. Moreover, the higher the level of sophistication, the higher is the amount of time required for a correct application and the higher is the level of competences and skills needed

Real option

Income

Market

Methods

Time horizon


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Table III.

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.

sources are both internal and external, with respect to the appraiser’s intangible[3]. Obviously, data that has to be collected from external sources can create several problems, due to the confidentiality and “secrecy” of some information. Some public sources can be used, such as legal and trade publications, databases, newspapers. Even if the source of information is internal, the data is not always easily accessible, for example, when data is “dispersed” among databases and systems that are not integrated. The identification of the “right” data and information to be collected, according to the aim, scope and context of the valuation. Particularly when a great deal of data is available, selecting what is really necessary can be difficult. The completeness and accuracy of data. The same information, obviously, can be collected with a different level of accuracy. This affects the final result: a valuation is more reliable as the accuracy of data and information increases. But as previously explained, the accuracy of data is influenced by time and resources allocated to the process. In fact, increasing time and resources available usually means availability of a more complete, detailed and precise set of data and information.

Determining the value of the asset. This is the phase in which the selected valuation technique(s) is (are) actually applied in order to come to the final value of the technological asset. This activity can present different problems concerning: (1) The method. Each valuation method presents some specific criticalities (as shown in Table II) that make the application difficult; and (2) Its correct application. Sometimes there are difficulties related to the correct analysis and use of data previously collected. This challenge is influenced not only by the appraiser’s capability and experience, but also by the time and resources allocated to the process. (3) The management of the different values obtained when more than a single method is applied. Generally, different valuation methods produce different results. This is coherent with the fact that the technological asset cannot have a definite, precise, “universally” valid value. Different methods and results allow us to define a range of significant values. The single results are valid in the specific context and hypothesis under which they have been calculated and in relation to the level of accuracy of data and information.

The constraints of the appraisal process The constraints can be classified into: . necessary data and resources (time) required to apply a method; . available time and allocated resources; and . available data. Necessary data. This is the information needed for a correct application of a definite method. It is determined by the characteristics of each method and, in this sense,

cannot be modified. Hence, it represents a critical constraint within the process. The appraiser has to analyse in depth the information needed to apply to a specific method for implementing it in the correct manner. Resources (time) required. These represent the resources needed to properly apply the usable method and to establish the value of the technology with a high level of accuracy. Techniques, such as the real options method, undoubtedly require a complex data elaboration, a sophisticated analysis and, hence, a vast amount of time and competent resources. Available time and resources. These are usually determined by decisions taken at top management level, depending on the relevance assigned to the valuation. These variables affect the level of precision of expected results, influencing first of all the identification of the usable method, the collection of data (and the relative completeness and reliability) and the implementation of the method (and the relative theoretical coherence). Available data. This is the information that can be accessed during the appraisal process and that is identified by the specific context of analysis. In more detail, the available data is influenced by: . The unit of analysis. For example, in the case of very innovative technological assets, data on the future cash flows is usually unavailable. . The aim and scope of the valuation. For example in the context of the accounting process, data and information is generally accessible and can be obtained in a short time and with little cost. In the case of transactions, another element is the identification and knowledge of the potential buyers. As previously explained, this information is necessary in order to quantify particular data. Also the appraiser’s position, with respect to the valued asset, is important. In fact if the company possesses the asset, undoubtedly more data and information will be available than for an external appraiser. . The available time and the level of allocated resources. These elements impact on the quality and the degree of accuracy and completeness of available data. The links within the appraisal process As shown in Figure 1 there are several links within the framework. A careful management of the entire valuation process is assured by links; in fact activities and constraints are consistent due to the links. The importance of same links and their meaning have already been discussed above, in particular: . “unit of analysis – aim and scope of analysis” link was analysed during the definition of activity related to the identification of the unit of analysis; . “aim and scope of analysis – available data” and “aim and scope of analysis – most appropriate method” links are presented within the description of “identifying the aim and scope of analysis” activity; . “time and resource allocated – most appropriate method” link is illustrated throughout the discussion of “identifying the most appropriate method” activity; . the links related to the activity “compared available and necessary data” have just been examined during the presentation of this activity.


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In the framework, the appraisal process presents feedback. Feedback is required to assure the coherence of the entire valuation process with respect to constraints. Sometimes a loop is required if it is unable to identify a usable method during the comparison between necessary and available data. In this case, the appraiser has to repeat certain activities (the identification of available time and resources, the identification of the appropriate method etc.), modifying the relative conclusions.

22 The empirical study The described framework has been based upon the most recent theoretical state-of-the-art literature and the empirical cases illustrated in this literature. An empirical research was necessary to enrich the framework and improve its completeness, clarifying: . the factors considered by companies during the valuation process; . how the management of different elements that compose the framework, has an effect on the process; and . the main issues and the critical problems faced by the appraiser during the whole process. The empirical research comprises qualitative interviews and a case study. The research has been conducted by interviewing five managers of private and public institutions, directly involved in the problem of valuing technology-based assets (Table IV). The case study concerns the Technology Transfer Office (TTO) of Politecnico di Milano (an Italian University). The TTO has been appointed to manage the economic and industrial exploitation of patents belonging to the University. The case study has been conducted to: (1) apply the framework to show the meaning of activities, constraints and links in a real and specific context; (2) enrich and complete the framework; and (3) highlight and discuss the problems faced by the appraiser during the whole process.

Firm

Brief firm’s description

Italtel

Supplier of telecommunications devices Group operating in energy cables, telecom and tires businesses Technical University

Pirelli Politecnico di Milano

Table IV. Institutions involved in the research

Snamprogetti

Engineering company of the ENI Group (petrochemicals)

STMicroelectronics

Global semiconductor company

Role of interviewed people Industrial Property Manager Industrial Property Manager Director of Technology Transfer Office Licensing and Technology Planning Department Manager Industrial Property Manager

Identifying the unit of analysis The case study concerns the licensing of a patent applied for in the surgical field. The patent concerns a specific aortic cannula that will be used during surgical open-heart operations. In these particular operations the heart is stopped and a machine is used to pump blood into the patient’s aorta through a cannula. The new device differs from the traditional cannula mainly in its terminal section that enters the patient’s body. The traditional cannula has a pre-established and rigid final section, whilst the new device has a flexible final section folding in on itself and, therefore, with a variable area. This new device could bring about many advantages that are briefly described below: . The new device is less invasive. Having a flexible terminal section, the surgical cut is smaller than with the traditional devices. . The terminal section is flexible. For this reason it can be larger than in the traditional cannula. Moreover, the speed of blood flow, pumped from the machine, is lower and does not damage the walls of the blood vessel (this problem often arises with the traditional cannulae). . The flexible final section folds in on itself, when the heart starts working again, limiting the clogging of the aorta. Examining the object of analysis, it is evident that the technological asset corresponds to the product to be sold. Therefore, establishing the value of the surgical device means appraising the technological asset. In this case the identification of the unit of analysis does not present any trouble. Identifying the aim and scope of analysis The University first identified and then exploited the patent. Licensing out is preferred, as an indirect form in the exploitation of patents. The main reasons underlying this policy are: . maintaining a wide patent portfolio gives a positive image; and . the selling of patents can create problems with the further researches of the University. An analysis was carried out to support the transaction process and the TTO had to quantify the value of the patent in order to define the economic benefits arising from the licensing out of the patent. The identification of the potential licensee was required to improve the understanding of the context of analysis and consequently the accuracy of data. Also in relation to this aspect, the TTO analysed the potential buyers of the license briefly described in Table V (letters used for confidentiality). The TTO selected two licensees, firms A and F, among the different firms operating in the market for aortic cannulae. Firms D and E were not considered due to unavailable data (e.g. US market share). Among the firms, the TTO selected: . firm A, because it is a world-wide leader in the sector of producers of pump machines for surgical open-heart operations and has recently acquired a small firm that produces traditional cannulae; and . firm F, because it is a small company, specialising in the production of cannulae.


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The first (A) has 38 per cent of the global market share, while the second (F) covered 6.5 per cent of the cannulae producing market (Table V). This case study shows that: .

.

24

The TTO had to identify the potential licensees in order to clarify the context of the valuation, and to define correctly and accurately the boundaries of analysis. The TTO has introduced subjectivity into the appraisal process (two specific potential licensees have been selected). This choice dramatically affects the following steps of the valuation.

Identifying the most appropriate method(s) After the identification of the context in terms of unit of analysis and aim and scope of analysis, the analyst has to select the most appropriate method(s). As explained in Figure 1, this activity is influenced by the aim and scope of analysis. Due to the transaction process, the appraiser, very likely, will adopt a method able to consider the future benefits associated with the patent. So the cost method does not seem adequate to the aim of this valuation. This method does not take into account incremental profits that are critical for an external buyer[4]. On the contrary, the income and the real options methods seem to be the best option, according to the aim and scope of the analysis. The market method can be considered adequate as well, even if it is less precise and complete. Beyond the aim and scope, the available resources have to be considered. From this point of view, traditional techniques are preferred, because the competencies needed to apply the innovative techniques are lacking. For this reason, the income method and the market method are the most appropriate methods. Comparing necessary and available data) Table VI and Table VII illustrate the situation of available and necessary data in the case of the valuation of the cannula according to the two most appropriate methods identified: income and market methods. The following considerations emerge from the analysis of these elements: . Critical information allowing for the application of the income method is the quantification for future net cash flows sprung from the use of the new device (see Tables III and VI). The advantages related to the use of the new cannula Firm

Table V. Potential buyers of the licence and their relative market share

A B C D E F Note: na ¼ not available

UE (%)

USA (%)

Average (%)

40 22 10 8 7 5

36 33 12 na na 8

38 27.5 27.5 na na 6.5

.

cannot be easily expressed in terms of increases in revenues and/or decreases in expenses except in the case of claims for assurance related to surgical problems. Data needed for the market method is available, since it is possible to find out the current price of similar devices and the dimension of the market (see Table VII).

The above analysis points to the use of the market method. The selection of the appraisal method is linked not only to the comparison of available and necessary data, but also to the identification of the most appropriate method(s) (Figure 1). In particular the previous analysis has shown that the income method is not coherent with the data available, even if, from the point of view of the aim of the valuation, this seems to be the most desirable method. Therefore the choice of the method falls on the market method, as the necessary data is available. The market method is also coherent with the aim and scope of the valuation, (i.e. the transaction), since it considers the future economic benefits related to an economic exploitation of the asset. As a consequence, the market method has been selected; the application of this method is quite easy and requires the only quantification of the selling price and the potential market. The case study underlines that this step is influenced not only by the comparison between available data and necessary data, but also by the specific context of valuation.


25

Collecting data To implement the selected method the TTO had to know the market size and the market price of similar devices. The TTO decided to use only external data sources. In fact it examined several market analyses and interviewed many companies working in the field of surgical instruments. Thanks to external data sources the TTO was able to estimate the worldwide market for aortic cannulae: as 1.100.000 surgical open-heart operations during year 2000 in 3,000 heart-surgical centres located in 80 countries. In order to estimate the applicable price of the cannula, the price of similar existing products have been analysed. The price applied to the final users (that are the heart-surgical centres) is around e 50 per unit.

Necessary data Future net cash flows (incremental revenues; decremental expenses; additional investments) Time horizon Actualisation rate

Not available Available Available

Table VI. Necessary data vs available data (income method)

Necessary data Units of comparison Find the parameters on which carrying out the comparison

Available Available

Table VII. Necessary data vs. available data (market method)

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Determining the value of the asset In order to establish the value of the patent the appraiser has to draw up some hypotheses. In this case, the hypotheses are related to the success of the experimentation of the new cannula, the doctor’s ability to pick the advantages related to the new cannula, and the strategic and marketing actions carried out by the manufacturer versus the medical class for promoting the new medical device. On the basis of previous elements the TTO has estimated a 10 per cent penetration rate for both the firms (even if the TTO for firm F could assume a higher rate than firm A’s because F mainly concentrates on the cannulae market (Table VIII). Table VIII presents the served market in terms of the number of cannulae that could be sold. To establish the potential value of the patent, the TTO has to consider not only the size of the potential market, but also the price of the new cannula (Table IX). As shown in Table IX, the value ascribed to the patent will be e 2,090,000 if the patent is licensed to the worldwide leader (firm A), or e 357,500 if the licensee is a smaller company (firm F). As we can see the value is strongly dependent not only on the formulated hypotheses, but also on the characteristics of the licensee. This underlines the importance of the right identification of the context of analysis and especially of the licensee. The appraisal process The case study showed how the process should be characterised by contrasting elements. In particular during the identification of valuation method, some contrasting elements emerged. Examining the unit, the aim and scope of analysis, the income method would have been better, but the necessary information and data was not available. This problem was solved by selecting a method that represented a “second best” solution, from the point of view of the aim and scope of the analysis, but one that was also coherent with the data, resources and time available. An interesting and more complete analysis could be conducted to discuss the valuation of the patent. In fact, it would be interesting to understand how the value of the patent can change considering other transaction forms, such as the transfer of ownership or a solution in order to take direct advantage of the patent.

Table VIII. The served market of the patent

Table IX. The value of the patent

Market share Potential market Penetration rate Served market

Firm A

Firm F

38 per cent 418,000 units 10 per cent 41,800 units

6.5 per cent 71,500 units 10 per cent 7,150 units

Note: World-wide market – 1.100.000 u

Served market Price Patent’s value

Firm A

Firm F

41,800 units e 50 per unit e 2,090,000

7,150 units e 50 per unit e 357,500

Concluding remarks In the literature as well as corporate practice great attention is paid to the problems of the valuation of the technological assets, however an in-depth analysis of the whole appraisal process is lacking. In view of this, this paper aims at taking some steps to amend this situation. The paper hopefully presents the complexity of the appraisal process. The first part of the process (from the identification of the unit of analysis to the identification of the usable method) is directed at contextualizing and defining the valuation problem. This part of the valuation process leads to the correct definition of the appraisal problem (in terms of unit of valuation, aim and scope, valuation method(s)) and it does not necessarily need, a real time sequence among the activities. The second part of the process (concerning the collection of data and the actual determination of the asset value), however, has to be executed in a sequenced way (even if some feedbacks are presented (see Figure 1)) and represents the operative phase of the appraisal process. Even if each valuation of the technological asset is unique, this paper aims at providing an analytical framework for estimating the value of a technological asset. As explained in the paper, it is possible to understand that the appraisal process is not simple, but quite multifaceted and that it is not systematic either in the literature or corporate practice. This paper analyses the entire process and gives emphasis to the critical aspects of each phase, suggesting some solutions. In brief synthesis, it can be argued that the use of the proposed framework: . forces the appraiser to perform a systematic and rational analysis, coherent with the internal and external context of the valuation; .

points out the most critical elements that could lead to a misleading and/or unusable and/or biased valuation;

.

forces the appraiser to solve some critical trade-offs and to deal with contrasting elements;

.

imposes coherence throughout the process and consistency among the various hypotheses and assumptions needed to finally identify a (range of) final value(s);

.

gives the appraiser a communication tool, as different people are involved during the process;

.

allows people (even if not directly involved in the process) to understand how the value of the asset has been determined and the validity, reliability and precision of the results obtained; and

.

increases the bargaining power of the appraiser during the negotiation with a potential counterpart, allowing a clear and complete understanding of the value of the asset.

Notes 1. These type of resources will be called “technological assets”. 2. Utility is an economic concept and it means the ability to provide satisfaction.


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3. It is assumed that the appraiser is the owner’s intangible. 4. TTO learned, by experience, that licensees are not interested in licensor’s costs. References Anson, W. (1996), “Establish market value for brands, trademarks and marketing intangibles”, Business Valuation Review, June, pp. 47-56. Anson, W. (1998), “Identify, value, leverage your intellectual assets”, les Nouvelles, March. Anson, W. (2001), “Traditional valuation methodologies of intellectual Property”, The Licensing Journal, September, pp. 30-2. Anson, W. and Serrano, M. (2001), “Intangible asset valuation techniques”, The Licensing Journal, January, pp. 37-8. Arora, A., Fosfuri, A. and Gambardella, A. (2001), “Markets for technology and their implication for corporate strategy”, Industrial and Corporate Change, Vol. 10 No. 2, pp. 416-51. Atuahene-Gima, K. and Patterson, P. (1993), “Managerial perceptions of technology licensing a san alternative to internal R&D in new product development: an empirical investigation”, R&D Management, Vol. 23 No. 4, pp. 327-36. Benninga, S. and Tolkowsky, E. (2002), “Real options: an introduction and an application to R&D Valuation”, Engineering Economist, Vol. 47 No. 2, pp. 151-68. Berkman, M. (2002), “Valuing intellectual property assets for licensing transactions”, The Licensing Journal, Vol. 22 No. 4, pp. 16-23. Bouteiller, C. (2000), “The evaluation of intangibles: advocating for an option based approach”, paper presented at the Alternative Perspectives on Finance and Accounting Conference, Hamburg, 4-6 August. Brooke, M.Z. and Skilbeck, J.M. (1994), Licensing: the International Sale of Patents and Technical Know How, Gower, Aldershot. Brugger, G. (1989), “La valutazione dei beni immateriali legati al marketing e alla tecnologia”, Finanza Marketing Produzione, Vol. 1, pp. 33-52. Chatterji, D. (1996), “Accessing external sources of technology”, Research and Technology Management, Vol. 39 No. 2, pp. 48-56. Chatterji, D. and Manuel, T. (1993), “Benefiting from external sources of technology”, Research and Technology Management, Vol. 36 No. 6, pp. 21-6. Chiesa, V. (2001), R&D strategy and Organisation (Managing Technical Change in Dynamic Contexts, Imperial College Press, London. Chiesa, V. and Manzini, R. (1998), “Organising for technological collaborations: a managerial perspective”, R&D Management, Vol. 28 No. 3, pp. 199-212. Damodaran, A. (2001), The Dark Side of Valuation: Valuing Old Tech, and New Economy Companies, Pearson Education, Inc, Upper Saddle River, NJ. Daum, J. (2001), “How to better exploit intangible asset to create value”, The New Economy Analyst Report, available at: www.juergendaum.com/news/07_06_2001.htm Escher, J.P. (2001), “Process of external technology exploitation as a part of technology marketing: a conceptual framework”, paper presented at the EHT – Center for Enterprise Science, Picmet 2001 Conference, available at: www.tim.ethz.ch/research/conferences/ picmet01/escher/picmet8.pdf Gilardoni, A. (1990), “Il valore del patrimonio tecnologico aziendale nelle prospettive economico-finanziarie e strategico-organizzativa”, Finanza Marketing Produzione, Vol. 3, pp. 93-110.

Gotro, J. (2002), “Unleash your intellectual property potential: in the ‘knowledge economy’, intangible assets such as intellectual property and brand strategies play a key role in determining company value”, CircuiTree, Vol. 15 No. 8, pp. 70-3.


Guatri, L. (1989), “Il differenziale fantasma: I beni immateriali nella determinazione del reddito e nella valutazione delle imprese”, Finanza Marketing Produzione, Vol. 1, pp. 53-62. Hoffman, R. and Smith, R. (2002), “An introduction to valuing intellectual property”, The RMA Journal, Vol. 84 No. 8, p. 44. Holzmann, O.J. (2001), Update: Mergers and Intangible Assets, John Wiley & Sons, New York, NY. Howells, J. (2000), “Research and technology outsourcing and systems of innovation”, in Metcalfe, J.S. and Miles, I. (Eds), Innovation Systems in the Service Economy, Kluwer Academic Publishers, Boston, MA. Jones, G., Lanctot, A. and Teegen, H. (2000), “Determinants and performance impacts of external technology acquisition”, Journal of Business Venturing, Vol. 16 No. 3, pp. 255-83. Khoury, S. (1998), “Valuing intellectual properties”, in Sullivan, P.H. (Ed.), Profiting From Intellectual Capital, John Wiley & Sons, Inc, New York, NY. Khoury, S. (2002), “Valuation of BioPharm intellectual property: focus on research tools and platform technology”, les Nouvelles, June, pp. 48-53. Khoury, S. (2003), “Valuing of technology, technology assessment and valuation of intellectual properties”, seminar, Milan, 1 April. Khoury, S., Daniele, J. and Germeraad, P. (2001), “Selection and application of intellectual property valuation methods in portfolio management and value extraction”, les Nouvelles, September, pp. 77-86. King, K. (2001), The Value of Intellectual Property, Intangible Assets and Goodwill, Thomson Derwent, available at: http://thomsonscientific.com/ipmatters/acctecon/8199544/ Kodama, F. (1992), “Technology fusion and the new R&D”, Harvard Business Review, Vol. 70 No. 4, pp. 70-9. Korniczky, S.S. and Stuart, C. III (2002), “IP gains importance in the valuation of company assets”, San Diego Business Journal, Vol. 23 No. 23, pp. A6-A8. KPMG (1999), “A core competency approach to valuing intangible assets”, paper presented at the Measuring and Reporting Intellectual Capital: Experience, Issues and Prospects technical meeting, June, available at: www.oecd.org/dataoecd/16/17/1947847.pdf Lev, B. (2001), Intangibles, Management, Measurement, and Reporting, Brookings Institution Press, Washington, DC. Mard, M.J. (2000), “Cost approach to valuing intellectual property”, The Licensing Journal, August, pp. 27-8. Mard, M.J. (2001), “Intellectual property valuation challenges”, The Licensing Journal, May, pp. 26-30. Mard, M.J., Hyden, S. and Rigby, J.S. (2000), Intellectual Property Valuation, The Financial Group, April, available at: www.fvginternational.com/library/library_ip.html Martin, M. (1999), “Financial valuation of intellectual property”, excerpted from “Marketing of advanced materials intellectual property”, paper presented at the 12th International Conference on Composite Materials, Paris, 8 July. Morris, M.R. (2001), Intangible Assets and Their Role in Corporate Value, Value Incorporated, available at: www.valueinc.com/press/Intangible per cent20Assets.PDF

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Mullen, M. (1999), “The art of managing intellectual assets”, Financial Focus, October, available at: www.pwcglobal.com/uk/eng/about/svcs/cvc/LECTURE2.doc Mun, J. (2002), Real Options Analysis, John Wiley & Sons, Inc, Hoboken, NJ. Park, Y. and Park, G. (2004), “A new method for technology valuation in monetary value: procedure and application”, Technovation, Vol. 24, pp. 387-94. Pitkethly, R. (1997), “The valuation of patents: a review of patent valuation methods with consideration of option based methods and the potential for further research”, available at: www.oiprc.ox.ac.uk/EJWP0599.html Rabe, J.G. and Reilly, R.F. (1996), “Looking beneath the surface: valuing health care intangible assets”, The National Public Accountant, Vol. 41 No. 3, pp. 14-24. Razgaitis, R. (1999), Early-Stage Technologies. Valuation and Pricing, John Wiley & Sons, Inc, New York, NY. Reilly, R.F. and Schweihs, R.P. (1999), Valuing Intangible Assets, McGraw-Hill, New York, NY. Roberts, E.B. (2001), “Benchmarking global strategic management of technology”, Research Technology Management, Vol. 44 No. 2, pp. 25-36. Roberts, E.B. and Liu, W.K. (2001), “Ally or Acquire? How Technology Leaders Decide”, MIT Sloan Management Review, Vol. 43 No. 1, pp. 25-36. Smith, G.V. and Parr, R.L. (2000), Valuation of Intellectual Property and Intangible Assets, 3rd ed., John Wiley & Sons, Inc, New York, NY. Spadea, C. and Donohue, J.J. (2001), “Business valuation approaches in intellectual property”, Philadelphia Business Journal, Vol. 20 No. 31, p. 11. Stiroh, L.J. and Rapp, R.T. (1998), Modern Methods for the Valuation of Intellectual Property, Nera Consulting Economists, available at: www.nera.com/Publication.asp?p_ID ¼ 793 Tenenbaum, D. (2002), “Valuing intellectual property assets”, The Computer and Internet Lawyer, Vol. 19 No. 2, pp. 1-7. WIPO (1998), WIPO Regional Seminar on Support Services for Inventors, Valuation and Commercialization of Inventions and Research Results, World Intellectual Property Organization and Technology Application and Promotion Institute, Manila, 19-21 November, available at: www.wipo.int/innovation/en/meetings/1998/inv_mnl/



New knowledge creation through dialectical leadership

Dialectical leadership

A case of IT and multimedia business in Japan Mitsuru Kodama

31

Department of Management, College of Commerce and Graduate School of Business Administration, Nihon University, Tokyo, Japan Abstract Purpose – Aims to provide new practical viewpoints regarding the knowledge management and leadership theory of project management through an in-depth case study Design/methodology/approach – Argues that community leaders can develop a concept of a business community comprised of diverse types of business and processes to achieve business innovation. Studies a regional initiative in Japan towards electronic networking that illustrates the use of information and multimedia technologies as an instance of the latest business case of strategic community management. Findings – Community leaders serve an important function in creating networked strategic communities. The case study shows how community leaders have created networked strategic communities in which the central government, regional governments, universities, hospitals, private businesses and non-profit organizations take part in the advancement of regional electronic networking. Originality/value – Provides new practical viewpoints regarding the knowledge management and leadership theory of project management. Keywords Innovation, Knowledge management, Multimedia, Intelligent networks, Communication technologies, Japan Paper type Case study

Networks of strategic communities Rapid progress in information and multimedia technologies is leading the way for gradual renovation in diverse areas including society, economy and industry. Ever widening acceptance of the internet, intranet and extranet is spawning the flattening of corporations on novel communications platforms as well as the creation of a new-business model for inter-corporate transactions as championed by e-commerce. The internet platform is poised to dramatically change the way new jobs are handled by people in corporate settings and even the lifestyle of individuals in their day-to-day living; it is furthermore stimulating the proliferation of small offices and home offices. New business styles based on such concepts as virtual teams and virtual communities are representative of such a trend (see Bechard et al., 1996; Lipnack and Stamps, 1997). Amid such changes in the times, the advent of new twenty-first century networking generations will usher in major changes in individual people’s value systems, especially as they relate to living and working. At the same time, increasing importance is expected to accrue in the years to come in the manner of existence of, and new ways of thinking about, the “communities” represented by corporate entities and non-profit organizations (NPOs), which constitute massive aggregates of individuals (Hesselbein et al., 1998). In corporate settings particularly, the knowledge management


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method, refined through rapid information technology sophistication, is being adopted to address internal particulars, bringing on structural renewals in affected areas. However, the important point here is that no matter how information technology is utilized in business-handling renovation, a corporation’s strategic behavior most importantly depends upon innovation of the value systems of the individuals concerned and of the knowledge accumulated by them. Leadership generative of business innovation on a continuous basis that strategically taps the knowledge of extra-corporate human resources including customers will become important. To this end, it is most important for leaders of corporations to aggressively create strategic communities (SCs) tapping their own organizations as well as outside contacts, including customers, in leading positions for staff toward innovating their own in-house core knowledge while simultaneously creating new values and offering them to their customers (Kodama, 1999). The SC is based on the concept of “ba” as a shared space for emerging relationships that serves as a foundation for knowledge creation (Nonaka and Konno, 1998). Participating in a “ba” means transcending one’s own limited perspective or boundary and contributing to a dynamic process of knowledge creation. In a SC, members including customers who possess different values and knowledge consciously and strategically create a “ba” in a shared context that is always changing. They continually create new knowledge and competencies as a new “ba” by merging and integrating a single “ba” or multiple numbers of “ba” both organically and from multiple points of view. In this paper, SC is defined as both emergent and strategic, a collaborative, inter-organizational relationship that is negotiated and associated with creative yet strategic thinking and action in an ongoing communicative and collaborative process, in the case of several arrangements such as strategic alliances, joint ventures, consortia, associations, and roundtables, and which depends on neither market nor hierarchical mechanisms of control (Heide, 1994; Lawrence et al., 1999). From the practical aspect, the SC is seen as an informal strategic organization possessing qualities with both a resource-based (or knowledge-based) view and a strategic view. The resource-based view is an emergent, learning view of the community in a shared context, while the strategic view is a planning view that aims to establish a desired position in the target market. The SC is applied, for instance, in cases where enterprises are in a management environment beset by numerous uncertainties, where predictions are difficult, and management is searching for valid strategies. The task of the SC is to emergently and strategically form and implement concrete business concepts and ideas. Trial and error such as incubation is necessary, however, and the SC takes the stance that a strategy will emerge from among the collaborative actions. For the most part, middle management is at the center of the SC. They form informal and virtual teams both inside and outside the company, including customers, and actively generate emergent entrepreneurial strategies and create new knowledge. They then produce new demand that did not exist before which in turn results in the emergence of a new technology and market (Kodama, 2001a, b). On the other hand, the acquisition of resources and transfer of knowledge between strategic partners is different from the creation of new knowledge. Knowledge creation occurs in the context of a community that is fluid and evolving rather than tightly

bound or static. The canonical formal organization, with its bureaucratic rigidities, is a poor vehicle for learning. Sources of innovation do not reside exclusively inside firms but between them. Accordingly, knowledge creation is an extremely important issue that sees knowledge as a property of communities of practice (Brown and Duguid, 1991), “ba” (Nonaka and Konno, 1998), communities of creation (Sawhney and Prandelli, 2000), the SC (Kodama, 2001a, b); Storck and Patricia, 2000), and networks of collaborating organizations (Powell and Brantley, 1992), rather than as a resource that can be generated and possessed by individuals. When the knowledge base of an industry is both complex and expanding, and the sources of expertise are broadly dispersed, the locus of innovation will be found in networks of inter-organizational learning rather than in individual organizations (Powell et al., 1996). Connection through the networks of SCs based on the inter-organizational collaborative relationships is thus an important origin of knowledge creation, and new knowledge grows out of the sort of ongoing social interaction that occurs in ongoing collaboration between SCs. This paper describes the development process in an ambitious project in Japan that occurred over the past five years. This paper will focus on new knowledge creation process by synthesizing capability (Nonaka and Toyama, 2002) through dialectical leadership in the networked SCs. An example of the establishment of networked SCs will be the business case involving the promotion of a regionally based electronic networking in Japan that makes use of information and multimedia technologies. The case will examine how the network of SCs involving the central government, the regional government, public agencies, the private sector, NPOs and other parties promoted electronic networking in a regional setting in Japan to create the world’s first-ever multimedia village project, and the impact on such areas as education, medical care, social welfare and regional administration will be considered from the standpoint of a new knowledge creation process through the synthesis of various knowledge within the networked SCs. In this in-depth case study, our analysis of knowledge creation focuses on the degree and process to which the networks of the SCs created new knowledge based on new technologies, social and customer needs, and various contents that were diffused beyond the boundaries of the SCs. The case is then analyzed from two angles described below. The first angle analyzes the characteristics of SC networks that became the trigger causing the synthesis of knowledge diffused from the boundaries of individual SCs that were distributed from the three elements of their involvement in collaboration (DiMaggio and Powell, 1983), embeddedness in collaboration (Granovetter, 1985; Dacin et al., 1999) and resonance of values (Kodama, 2001a, b) at which the SCs were formed. The second angle discusses the synthesizing capability through dialectical leadership that the leadership-based strategic community comprising community leaders within networked SCs uses to dialectically synthesize the different knowledge of SCs that is distributed in the new knowledge creation process in a big project. Finally, this paper touches on the managerial implications as organizations make use of their dialectical leadership and innovations in their efforts to achieve new knowledge creation and innovation.


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Research methodology and data collection In the methodological approach for this study, the author adopted a qualitative research design due to my need for rich data that could facilitate the generation of theoretical categories that could not derive satisfactorily from existing theory. In particular, due to the exploratory nature of this research and the author’s interest in identifying the main people, events, activities and influences that affect the progress of innovation, he selected the grounded theory style of data interpretation, which was blended with the case study design and with ethnographic approaches (Locke, 2001). Data used in this paper comes from a longitudinal study during a five-year period (1996-2000) examining new knowledge creation processes with respect to new products and services development at a large company in the field of competitive IT and multimedia business fields. This research paradigm, which was based on an in-depth qualitative study, has some similarity to ethnography (Atkinson and Hammersley, 1994) and other forms of research (Lalle, 2003) that derive their theoretical insights from naturally occurring data including interviews or questionnaires (Marshall and Rossman, 1989). Especially, the researcher should intervene in the organizations studied and work with organization members as a project manager on a matter of genuine concern to them on which they have a genuine need to take action. Research data and insight are gained alongside or on the back of the intervention. The data collected over the five years of the intervention have derived from work with practitioners involved in a large number and variety of customers and outside partners as well as internal organization members. During these interventions, the expressed experiences, views, action-centered dilemmas, and actual actions of participants have been recorded as research data in a variety of ways, including notes and internal and external rich documents. The theory that has emerged from this research centers around the concepts of new knowledge creation process collaborated with outside partners and customers. The data analysis for the research consists of three stages: (1) developing an in-depth case history of a big project’s activities from the raw data that provided all the information; (2) open coding and subsequent selective coding the in-depth case history for the characteristics and origin of knowledge creation process: and (3) analyzing the pattern of relationships among the conceptual categories. In the first stage of the data analysis, chronological descriptions of the project’s activities were constructed with respect to knowledge creation process, describing how it came about, when it happened, who was involved, and major outcomes. Through this work, an in-depth case history of the project was completed. The second stage of analysis involved coding the in-depth case history with respect to its characteristics, origin and effects. This was a highly iterative procedure that involved moving between the in-depth case history, existing theory, and the raw data (Glaser and Strauss, 1967). The data was subjected to continuous, cyclical, evolving interpretation and reinterpretation that allows patterns to emerge. The grounded theory approach is based upon the researchers’ interpretation and description of phenomena based on the actors’ subjective descriptions and interpretations of their experiences in a setting (Locke, 2001). This “interpretation of an interpretation” strives to provide contextual relevance (Silvermann, 2000). From the in-depth case history, I initially advanced

first-order descriptions based on broad categories that were developed from the existing theory, and then refined these categories by tracing patterns and consistencies (Strauss, 1987). The analysis continued with this interplay between the data and the emerging patterns until the patterns were refined into conceptual categories (Eisenhardt, 1989). The third stage of data analysis was to examine the empirical in-depth case results across the selected categories and drawing on the theoretical literature, and to identify distinctive dynamics, generalize patterns of the case, and develop the emerging constructs and logic of the conceptual framework, which could be designed to develop rich descriptions of social phenomena and allow the discovery of categories and the generation of new theory. The author was particularly interested in the origin and dynamics of the new knowledge creation process within networked SCs. Therefore, on the basis of the patterns evident in stage 2 analysis, the various categories describing the origin and characteristics of new knowledge creation process were studied, and six aggregate broader concepts were identified. These six concepts are a conceptual framework that would determine the structure of this article: involvement (DiMaggio and Powell, 1983), embeddedness (Granovetter, 1985; Dacin et al., 1999), resonance of value (Kodama, 2001a, b), and leadership-based strategic community, dialectical leadership, synthesizing capability (Nonaka and Toyama, 2002), which are described in detail in the discussion section.

Case study: promotion of diffusion of IT in regions of Japan – world’s first multimedia village project The importance of promoting regional IT diffusion Regional governments throughout the world, seeking to realize a regional society characterized by abundance and a high quality of life, are actively taking steps, listening to various requests and complaints brought to them daily by residents, and developing various measures in order to solve regional problems in fields such as education, medical care, social welfare, the environment, industry, tourism, city planning, and disaster prevention. Recently, particularly with individual problems in fields such as education, medical care, and social welfare, finding transverse solutions has been considered a matter of some urgency. On the other hand, over the past few years, the words, “diffusion of information technology,” “multimedia,” and, “the advent of the advanced info-com society” have come to be used frequently by newspapers, television, and other mass media outlets. It would be difficult to say, however, that there has been sufficient discussion of the fundamental issues of the kind of influence and constructive effects the diffusion of information technology would exert outside of business fields, on the lives of ordinary people, and regional residents in particular. The essence of information technology lies in overcoming distance and time in various human endeavors, from daily life to business, and broadening the range and possibilities of human activity. Having various fields of application, the most prominent example of which is the internet, affordable, increasingly easy-to-use info-com technology holds many possibilities for addressing the needs of residents and for solving regional problems in order to realize regional societies characterized by greater abundance and a higher quality of life.


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Background and aims of the measure Multimedia-based enrichment of regional communities is becoming an important topic as we approach the twenty-first century. As the population declines due to a falling birth rate and society continues to age, progress is being made in the social structure with regard to internationalization and the decentralization of authority to the local level. For village residents in various regions to lead secure, healthy, and enjoyable lives, we must work to enrich local, intra-village community, encourage active extra-village intercourse, and improve the environment for lifelong learning, beginning our efforts with enrichment in fields such as health insurance, social welfare, medical care, and education, and the improvement of regional government services. The Multimedia Village Project is a measure in which the government and private sector (the Ministry of Posts and Telecommunications (MPT), regional governments, Japan’s largest telecommunications carrier, Nippon Telegraph and Telephone Corporation (NTT), and others) are collaborating and coordinating their efforts. It is based upon a special project concerned with working to overcome the depopulation problem, to improve the living environment in mountain villages, and to revitalize them, while investigating the question, “What kind of multimedia would village residents be glad to use?”

Formation of networked strategic communities Mission and challenges. In September, 1997, NTT, Japan’s largest telecommunications company, launched the marketing throughout Japan of a new-generation videophone. Though business and virtual classroom communications was its initially targeted sales market, its use in household circles began to gradually catch on, helped by features that allowed the enjoyment of a high-quality two-way video communication at the world’s lowest price of ¥198,000 a pair. The vision and concept under which the NTT project leader pursued the popularization of the videophone called for offering a helping hand in the areas of medical care, insurance, social welfare and education for the aged populations, including bed-ridden people, in remote regions. This vision and concept was furthermore intended to bring on an impact to society by selecting one remote village in Japan and connecting all the households in it by videophone to the rest of the country. A larger frame of the project concept, called the Multimedia Village Project, envisioned the creation, and provision to large numbers of elderly people, of new values through a number of applications in the areas of medical care, health insurance, social welfare, and education. The vision and concept of the project leader was to realize such a multimedia village in some village in Japan and to create a new template as a model project – the first of its kind in the world. The project, however, faced some obstacles that stood in the way of its launch: . Financial difficulty with the installation of equipment to support the videophone and associated systems. The problem of how to secure government subsidies such as from the MPT and other sources. . Selection of one village from among many. Consensus-building among the villagers concerning the introduction of the videophone to each household of the village.

.

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Problem of how to diffuse an extensive application of the videophone to the areas of medical care, insurance, social welfare, and education. The videophone, when it was developed, made a debut flashing the catch phrase, “So easy to use, anyone can use it.” It was not certain, however, whether elderly not familiar with such equipment would be able to learn how to use it. A host of other problems also needed to be addressed.

Decision making based on past accomplishments. For the project leader, selecting a village posed a major challenge. It was additionally important to secure the consensus and cooperation of those concerned at the level of the local prefectural government under whose jurisdiction the village hosting such a large-scale project, if it were to be started, was. NTT did have a track record of working with Fukushima Prefecture in the institution of a multimedia-supported, virtual-format life-long learning program. For example, Koriyama Women’s University, which celebrated the 50th Anniversary of its foundation as an educational corporation in 1996, launched a “Multimedia Telecommunications-based Life-Long Continuing Education Service” as one of its commemorative projects (Fukushima Minpo Shimbun, 1997). Under this program were put in place a PC-based teleconferencing system, a multi-room teleconference system that enables participation with a regular TV set or by simple monitor hook-up, and an interactive life-long continuing education course accessible to subscribers through multiple-point-of-access teleconference hook-up. Specifically, multimedia-based two-way classes were inaugurated in the framework of a network linking the “Life-Long Learning Center” with a plurality of citizens’ centers in farming communities. Under the slogan of “Attend college courses near your home” the program promoted life-long learning while contributing importantly to putting an end to the dwindling number of educational opportunities. A course linking the Center to three citizens’ centers in the prefecture in real time offered a total of five lectures centering around the general theme of “Respecting regional needs” and focusing on such specific topics as “Real-life problems in day-to-day living,” “Themes that make our lives worth living,” and “Events of topical social interest.” The participants took part with enthusiasm, and lively debates unfolded. Satisfying exchanges of information and knowledge took place between participants and lecturers and among the participants themselves. Coordinated by NTT, a linkup between Fukushima Prefecture and faraway Brazil was realized using the teleconferencing system in August 1997, providing an opportunity for, among other things, an exchange of opinions between the Fukushima Governor and Fukushima-born residents of Brazil. In view of that background, the first thought on the project leader’s mind was to target a village in Fukushima. I believed there was in Fukushima Prefecture a sufficiently deep-rooted culture receptive to the teleconferencing system and the videophone. The telecommunications-based life-long continuing education course had won acclaim from housewives and the elderly, and we had successfully made the Fukushima Governor, the highest-ranking official of the prefecture, sufficiently cognizant of the value of video communications. We were thus to choose a village in Fukushima as the primary candidate. Of the several villages in the prefecture, we chose Katsurao-mura where Katsurao Middle School, known for its emphasis on internet utilization in its curricular program, was located. Katsurao-mura became the site of the Multimedia


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Figure 1. Formation of strategic community and networked SCs

Village Project. We believed that the leadership of the Governor would be key to the startup of this large-scale project. Our first, most important task, then, was to make a presentation of the vision and concept for the project before the Governor and secure his consent.

Formation of a strategic community and networked strategic communities In January 1998, the NTT project leader made a presentation of the vision and concept for the project before a panel of executive-level core leaders including the Fukushima Prefectural Governor and Katsurao Village Mayor. Following an exhaustive discussion, the sympathy and positive response of the core leaders was obtained in support of the project, and a SC (SC-a) could be formed (see Figure 1). On the other hand, keeping pace with the formation of SC-a, the NTT project leader made a presentation of the vision and concept for the project to the executive director and senior officials of the MPT, and tried to gain financial support for this project. Then the strategic community (SC-b) between NTT and MPT could be formed, and several problems and issues regarding the allotment of a fund and the effect of the project on the social welfare were discussed within the SC-b (see Figure 2, Phase 1). In the process of pursuing political and financial issues in greater detail and solving a number of problems in Katsurao Village’s households, NTT actively collected data on the Katsurao Village’s needs for the videophone and other related multimedia systems, and discussed with MPT including the Fukushima Prefectural Governor and Katsurao Village toward the realization of this project. Through this process, SC networks linking SC-a and SC-b were formed in this phase (Figure 2, Phase 2). In connection with these negotiations and consensus with MPT, for the sake of the realization of the project, the Fukushima Governor and Katsurao Village officials tried to finalize the completion of the proposal in which the implementation of the


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Figure 2. Networking strategic communities at the big project

experiments of e-Learning, remote health care and telemedicine were planned through extensive collaboration with universities and hospitals. They therefore made presentations of the vision and concept for the project to several universities and hospitals. In this process, they formed new SCs with the universities (Koriyama Women’s University and Fukusima University) (SC-c) and hospitals outside the village (SC-d) for the collaborations in the project (see Figure 1). The NTT project team, on the other hand, formed a SC with system vendors (Mitsubishi Electric Corp. and NEC) (SC-e) to realize the concept of the multimedia village from the standpoint of the technology using IT and multimedia. A variety of technical issues related to video communications and transmission of educational and medical content were thoroughly discussed (see Figure 2, Phase 3). Accordingly, an umbrella networked project centered on Katsurao-mura in SC-a, which was linked to SC-a through SC-e, was formed that would coordinate the inter-workings of different entities toward the realization of the Multimedia Village Project, and a decision was made to work out the details (see Figure 2, Phase 4). A proposal based on a vision and concept developed by an NTT project leader triggered the realization of a community as an executive-created project, which in turn provided a vehicle for the mutual sharing of values held by the core leaders. In April 1998, an organization named the Katsurao-mura Multimedia Village Promotion Council (the MV Council) was formed to work across various organizations, including hospitals and schools, the Ministry of Posts and Telecommunications, the Ministry of Education, the Fukushima Prefecture, the Katsurao Village, Fukushima University, Koriyama Women’s University, medical associations, villagers’ livelihood cooperatives, and NTT (see Figure 1). The purpose was to take further steps toward the accomplishment of the project. The MV Council was established among the core leaders in each of the various organizations. (In this paper, the MV Council will hereafter be referred to as the Leadership-based Strategic Community (LSC).) The LSC was formed to aggressively promote and verify the experiment, promote the introduction of the videophone-based multimedia system to remote village

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communities across the nation. From this initiative it was hoped that the Multimedia Village Project idea would be accepted throughout the country. The core leaders of the various organizations (government agencies, Fukushima Prefecture, Katsurao Village, universities, hospitals, medical associations, NPOs, and others) will hereafter be referred to as “community leaders.” As part of the particulars of the implementation of the experiment, a Health Maintenance and Well-Being Subcommittee and an Education Subcommittee were formed. The Health Maintenance and Well-Being Subcommittee was to provide care, medical consultation, health counseling and other services for the aged while verifying through the experience the possibility of realizing in the future a videophone-based remote medical care and consultation of diverse sorts. It was decided furthermore that the Education Subcommittee would organize videophone-aided remote classrooms, seminars and inter-school student exchanges and provide support for life-long learning in farming communities so as to create an educational environment that would eliminate regional disparities. In this way, a community was created by the systematic institution of the MV Council from an initially core leadership-led approach to a strategically organized one. With a view to bringing the Multimedia Village Project ever closer to inauguration, the MV Council studied every minute detail relating to the conceptual foundation of the Multimedia Village Project, such as the design of the system structure, matters pertaining to medical care, insurance, social welfare and education, presentations to the villagers toward building a consensus, and the test run schedule. Thanks to swift action of the community, the village residents, customers to the project, were able to deepen their understanding. Equipment installation was completed by June 1998, and under a three-year plan ending in March 2001, a test run of the videophone-aided Multimedia Village Project got under way[1]. (Figure 3 shows a conceptual drawing of the video-net established in Katsurao-mura.) (Nihon Keizai Shimbun, 1998; Nihon Kogyo Shimbun, 1998; The New York Times, 1999)[2]. By laying digital access lines in all 473 of the households in Katsurao-mura, in the schools, the town hall and other public facilities, organizers prepared an environment in which videophones could be used freely under a Multimedia Village System (MV System) that would be put in place. The equipment that was installed consisted of a multipoint connection unit (MCU) (Kodama, 1999), which permitted a maximum of 94 locations to be simultaneously connected to the multimedia center in the town hall to make arrangements and hold meetings, and a video-on-demand (VOD) based video server (Kodama, 1999), from which various graphical information could be searched and retrieved using a videophone. Residents took the initiative in expressing numerous opinions, such as “I’d like them to put a lot of information closely related to daily life on the video server,” “Aren’t there any applications that let children play and have a good time?” and, “I want to use my videophone to talk to family and friends outside the village.” In the experiment, as a measure to revitalize mountain village regions, multimedia that can be easily, cheaply, and readily used by anyone was put to practical use, and methods were examined for applying multimedia in various fields, starting with medical care, social welfare, education, and government services, with the objective of promoting the diffusion of information technology. Specifically, the experiment verified how efforts can be made to put to practical use bi-directional communication


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Figure 3. Video-net in Katsurao-mura Village, Fukushima Prefecture (conceptual diagram)

through easy-to-understand, videophone-based graphical information in order to improve the depopulation situation, improve the living environment in mountain villages, and revitalize them. The information and knowledge levels of individual residents in various fields were successfully raised by using a video-net between public facilities and each home to provide various services that met the individual needs of village residents, and demonstrating their effect, in order to form a society for village residents in which everyone from children to the elderly could feel secure and lead a life worth living. In Katsurao-mura, amid a rapidly shrinking and aging population, and in an effort to form a regional society in which village residents could live healthy, secure lives, a multimedia center was installed in the town hall, public facilities were networked to each home using digital access lines, and health preservation, social welfare, education services, and government information were made available. Thus, with the vision and concept proposed by an NTT project leader serving to trigger a sympathetic resonance of the value systems of core leaders, community creation on a grand scale and on an organized basis was harvested out of a group-level, community-creating effort, resulting in the provision of services to the village population, the customers. Innovation in new knowledge creation The biggest challenge for the MV Council, an LSC, was how to provide truly worthwhile content and applications for the village residents, the customers, using a completed MV system as the platform. In other words, this was a major challenge that

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addressed the human side of the proposition that was to look at inspiring life (software) into the vessel we called the MV system (hardware). The challenges faced by the LSC at the time of startup were the consolidation of the Multimedia Village Project, conceptualization of the MV system, and the designing and building of the system. In the stages following start-up, the content and applications of services in the fields of medical care, insurance, social welfare and education, all services already realized, were made available to villagers as virtual knowledge-based services (Kodama, 1999) offered on the MV system platform, the new task being, then, to work out a way to make the system accepted throughout the community. Services such as the following were provided in the fields of medical care, insurance, and education: Virtual knowledge-based services in the medical fields. It became possible to provide videophone health consultations, in which videophones are used to remotely provide home medical care and health consultations, lightening for patients and their families the physical burden of commuting to a hospital, and improving for doctors the efficiency of making house calls. In an elderly care-related aspect of a comprehensive social welfare and medical care support initiative, it became possible for a home helper to check the appearance of his or her elderly charges via videophone screen at any time, permitting early detection of emergencies and detailed care giving. It also became possible to receive at-home calisthenics instruction from the social welfare center. Furthermore, a mechanism was established whereby hearing-impaired residents could use VOD to retrieve videophone-based sign language assistance and graphical information related to insurance and social welfare on demand. Furthermore, as the search continued for applications in various fields that contribute to new medical care innovations such as remote medical care using vital-sign sensors and home delivery of medicine to chronic patients based on videophone medical examinations, it became possible for a new era of resident-centered multimedia to find its beginnings in this village of Katsurao-mura[3] (Nikkei Sangyo Shimbun, 1999; Asahi Shimbun, 1999). Under the provisions of the existing Japanese Medical Act, in particular, a face-to-face meeting between the diagnosing physician and his patient is required for drug prescriptions. However, this would make it necessary for residents of doctor-deprived villages such as Katsurao-mura afflicted with chronic ailments (patients with relatively stable symptoms such as diabetics or hypertension) to undertake, because of geographical circumstances, trips of several hours expressly to visit doctors for drug prescriptions, an onerous burden, indeed, for aged people. For a break away from such a situation, the community producer engaged in aggressive negotiations with the Ministry of Public Health and Welfare, the governmental organ regulating medical care. The result was a legalization of medicine home delivery on the basis of videophone-aided remote diagnoses (Medicine Pack Service). The creation of the Medicine Pack Service was a major boon for aged sufferers of chronic disorders. Thus, toward an innovative creation of a new virtual knowledge-based services, a sharing and inspiring of new and never before acquired knowledge occurred while new know-how and skills were accumulated through the creation and practice of new services. Virtual knowledge-based services in the educational fields. Services provided in the area of education included the following: To enable village residents to avail

themselves of various educational opportunities from home, Koriyama Women’s University village residents and other institutions offered them a variety of lifelong learning programs via videophone. In addition, to offer children in depopulated areas an educational environment in which regional differences were irrelevant, participation in nationwide seminars, cooperative learning, and inter-school exchanges via videophone and in real time was made possible. School-centered videophone uses continued to be established, among them joint research announcements with elementary and middle schools outside the village, debates and student exchanges with other schools, videophone-based inspection of classes by parents and guardians, and remote English conversation classes taught by non-Japanese English teachers. Applications for administrative and other services of various kinds were test-run by way of a pioneering effort into a new field outside medical care, insurance, social welfare, and education. Experiment organizers, for example, produced various informational video content, including a government guide and data-related shopping, recreation and various services, and stored it on the VOD server. This allowed users to search and retrieve this various graphical information, and to readily utilize and enjoy everything from governmental information to window shopping and karaoke. Moreover, a multipoint video connection service was used to allow multiple individuals to simultaneously and interactively engage in such activities as making appointments and participating in seminars. In this way, village residents were able to easily participate in videoconferences held in their own village or anywhere in Japan, from the comfort of their own homes. The whole community itself strove for self-improvement under the slogan of providing quality services to its customers, the villagers, making the innovation of new knowledge creation. It was this innovation that abidingly created new values for the community’s customers. Results and discussion In this section, six dimensions derived from the research method will be used to consider the sort of impact that the SC networks and the synthesizing capability through dialectical leadership of the community leaders had on new knowledge creation, the output of MV Council. As a first angle, the characteristics of SC networks that became the trigger causing the synthesis of knowledge diffused from the boundaries of individual SCs that were distributed from the three dimensions of their involvement in collaboration, embeddedness in collaboration and resonance of values at which the SCs were formed are analyzed. As a second angle, the synthesizing capability through dialectical leadership that the leadership-based strategic community comprising community leaders within networked SCs used to dialectically synthesize the different knowledge of SCs that was distributed in the new knowledge creation process in this project is discussed. Characteristics of networked SCs Information and knowledge within communities is both sticky and leaky. It is important, however, that the networked SCs makes the leaky aspect of knowledge in communities work in a positive manner and that community leaders of all SCs promote the sharing and inspiration of knowledge beyond the SCs’ boundaries. The act of transcending boundaries stimulates deep, meaningful learning, which in turn opens


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Figure 4. Evaluations of knowledge creation in the case study

possibilities for the generation of new knowledge and creativity. Radically new insights and developments, such as the project in this case, often arise at the boundaries between SCs (Grant and Baden-Fuller, 1995; Grant, 1996). In particular, the dilemma faced by organizations is the need to reconcile rapid access and synthesis of relevant new knowledge, with the long time frames needed for knowledge creation and synthesis. Networked SCs based on extensive inter-organization collaboration can offer a possible solution. The need for businesses and society to transcend the boundaries of SCs has been increasing in recent years as markets in their industry become more uncertain and technology as well as customers’ needs change more rapidly. One practical experience and the knowledge of a single organization need not be embraced in order to solve the complex problem of synthesizing technology as well as social needs shown in this case. The community leaders of organizations need to actively build SCs inside and outside the organization, including with customers, and then to transcend the boundaries of the SCs and network them in a speedy manner. One important element in the formation of networked SCs is collaboration. The presence of deep interaction among community members, the presence of a strategic partnership among organizations that form networked SCs, and interactive information sharing within networked SCs are not the only conditions required for extensive collaboration as defined by DiMaggio and Powell (1983), as high levels of involvement in the collaborative process, i.e. the development of a strong mutual awareness that SC members are involved in a common enterprise, are also essential. Figure 4 shows the results when this author evaluated the networked SCs of the MV Council with weight given to the factor of high involvement. The second important element in the formation of networked SCs – embeddedness – describes the degree to which a collaboration between SCs is enmeshed in inter-organizational relationships. This element highlights the connection between the collaboration and the broader inter-organizational network. Highly embedded collaborations between SCs were observed as an expanded network of SCs centered on Katsurao-mura came into being. The third important element in the formation of networked SCs is the resonance process of values in the community. This is the process whereby all community members, in their effort to fulfill the networked SCs mission and goals, share and

resonate values aimed at achieving the business. This idea of the resonance of values is also the same as the hidden value, espoused by O’Reilly and Pfeffer (2000), that enables the shared values within the formal organization or community to produce new knowledge or competencies (O’Reilly and Pfeffer, 2000). The resonance of values in networked SCs with partners inside and outside the organization and in networked SCs with partners (Kodama, 2001b) leads to dialectical ideas and strength to act among community leaders and turns into a capability for generating new knowledge that forms the new core for the networked SCs. High levels of resonance value were observed in the networked SCs of the MV Council, which had succeeded in the project (see Figure 4). Next follows a supplementary explanation of the three factors of the networked SCs obtained from the field study mentioned above. High involvement, the first element of networked SCs, refers to the condition in which specialized engineers and professionals in the networked SCs are thoroughly understanding and sharing each other’s knowledge in the various core technologies and content that were created in each SC through concerted dialog and collaboration among members of the networked SCs. The specific knowledge of core technologies and content that was created in each SC is as follows (see Figure 5). SC-a, comprising Katsurao Village, Fukushima Prefecture, and NTT, created knowledge that formed concepts aimed at realizing the future Multimedia Village Project that resulted from merging the social and technological contexts. SC-b, comprising NTT and the MPT, the overseeing body, created a road map for bringing outlying regions into the information age in order to realize SC-a’s new concepts from the standpoint of national policies and financial resources. In SC-c, Katsurao Village, Fukushima Prefecture, and local universities collaborated to develop a new e-Learning


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Figure 5. Core technologies and contents of SCs and new knowledge creation of networked SCs

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system. In SC-d, Katsurao Village, Fukushima Prefecture, and local hospitals collaborated to develop a new e-healthcare system. And in SC-e, NTT, Mitsubishi Electric, and NEC collaborated to develop a total system that could realize the Multimedia Village concept from the technological standpoint. The development results (core technologies and content) that were created by these SCs became knowledge that was deeply shared through close dialog and collaboration within the networked SCs in the case. Much of the data from interviews and other sources confirm that a condition of high involvement had been attained. An NTT manager, for instance, commented: To make this project a success, we not only needed to tackle tangible issues such as developing technology and finding finances, we also needed to address intangible issues such as developing support for residents’ education, medical care, and welfare services and to integrate these with the tangible resources. If we could not achieve a deep and thorough understanding of specialized knowledge among the various organizations involved, it would not have been possible to produce a system that residents would truly enjoy using. Our first mission was therefore to ensure that members of all these organizations were able to share this knowledge at a deep level.

High embeddedness, the second element, refers to the condition in which knowledge created in each SC transcends the SCs’ boundaries and is deeply shared among them, and is then generated as new knowledge by integrating the various bodies of knowledge from the networked SCs. The main feature in the networked SCs of each case is that the element of high embeddedness facilitates the integration of the core technologies and contents of each SC and creates concrete new knowledge as development results (see Figure 5). High resonance of value, the third element, refers to the condition in which networked SC members deeply share and sympathize with a vision for development that the members of networked SC aim to achieve through close dialog and collaboration. This observation was obtained by the author from discussions with many community members. An NTT director, for example, commented: It was important for us to develop a system that appealed to the human heart and sensitivities, so we had to devote considerable thought to devising a system that residents found easy to use and enjoyable at the same time. We therefore had many debates on what sort of IT would be meaningful to the lives of village residents. The extensive dialog among members of all organizations that enabled us to sympathize and share uniform values was extremely important.

For the analysis mentioned above, community members including community leaders needed to build a platform for resonating values and creating relationships of mutual trust while also engaging in ongoing mutual exchanges, deep collaboration, high involvement and high embeddness at the boundaries of multiple, different SCs. An evaluation of networked SCs can be found in the representative pattern of the project which quickly networked their SCs and realized high involvement, high embeddness, and high resonance value within these SCs. These effects can establish the leadership-based strategic community between community leaders and produce the synthesizing capability based on their dialectical leadership (see Figure 4).

Synthesizing capability through dialectical leadership of community leaders Struggles and conflicts are a common occurrence among networked SCs. These elements are harmful factors in the effort to synthesize the knowledge possessed by the SCs. This synthesis is thus promoted by the LSC, described below. The role of the LSC is to synthesize the knowledge of all SCs on the network that were formed by community leaders (made up of personnel from various levels of participating organizations including top management and middle management) and to generate synthesizing capability through dialectical leadership, the combined network power of all SCs (see Figure 6). The ability of community leaders in the SCs to unite comes from a solid LSC. A solid LSC possesses the elements of high involvement, high embeddedness, high resonance of value, and trust building. In order to achieve knowledge creation, the ultimate aim of the networked SCs, community leaders need to thoroughly understand and share each other’s knowledge through the SCs that they formed. This engagement among community leaders is the element of high involvement. The solid LSC then integrates all the different knowledge that was shared among the SCs and creates new knowledge as networked SCs. This comes as a result of the LSC’s element of high embeddedness. In order to produce the elements of high involvement and high embeddedness within the LSC, the author has been able to confirm through dialogs with many community leaders that it is particularly important for community leaders to build high resonance of value and trust among each other. For instance, a Katsurao Village leader comments:


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To bring a project of this scale to a successful conclusion, it was important for leaders in the various organizations to build relationships of trust. This project required a diverse range of specialized knowledge. Experienced leaders in such fields as government policy, finance, education, medical care, welfare, technology development, and politics needed to build

Figure 6. Synthesizing capability through dialectical leadership of community leaders

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relationships of trust and to exercise their own expertise to the greatest extent of their ability. To achieve this trust, it was vital that they shared and sympathized the visions and values that would bring the project to fruition. This trust enabled them to share specialized knowledge in various fields and then to integrate this knowledge to give substance to the new concepts that represented the ultimate aim of the project.

The above four elements of the solid LSC thus produce the synthesizing capability that leads to knowledge creation. The LSC also needs to balance the various paradoxical elements and issues within SCs on the network in order to realize this synthesizing capability. The LSC needs to enable community leaders to consciously conduct dialectical management based on dialectical leadership and engage in dialectical dialog to solve the various differences and issues that result from learning among the community leaders. As a result, the LSC actively analyzes problems and resolves issues, forms an arena for the resonance of new values, and creates a higher level of knowledge. Dialectical management is based on the Hegelian approach, which is a practical method of resolving conflict within an organization (Benson, 1977; Peng and Nisbett, 1999; Seo and Douglas Creed, 2002). The balancing of paradoxical elements and issues involves the synthesis of mutually divergent views among organization members coming from different corporate cultures on the one hand, and the synthesis of a variety of divergent business as well as social issues,such as the procedures of different management, technologies, or customers’ needs. In the case of the MV Council, for example, synthesis was required in three areas: (1) the values of many employees possessing a broad diversity of viewpoints and knowledge shaped by the different organizational cultures to which they belong; (2) balancing customers’ needs and high technology presented by firms; and (3) balancing political aspects and social needs. The LSC plays a central role in synthesizing the paradoxical elements and issues in the specific areas of human resources, elements among seeds and needs, and political issues. The dialectical leadership with the new ideas and approaches of the community leaders who have adopted the methods of dialectical management based on dialectical leadership in their efforts to synthesize paradoxical elements and issues make new knowledge creation and innovation possible. The LSC promotes dialectical dialog and discussion among community leaders in order to cultivate a thorough understanding of problems and issues. By communicating and collaborating with each other, community leaders become aware of the roles and values of each other’s work. As a result, community leaders are able to transform the various conflicts that have arisen among them into constructive conflicts (Robbins, 1974). This process requires community leaders to follow a pattern of dialectical thought and action in which they ask themselves what sorts of actions they themselves would take, what sorts of strategies or tactics they would adopt, and what they could contribute toward achieving the project and the innovation of a new knowledge creation. In achieving new knowledge creation and innovation, the LSC promotes the sympathy and resonance of the community leaders’ values, and the combined synergy and dialectical leadership among the community leaders have resulted in the high levels of synthesizing capability that has enabled the MV Council

to realize this big project and form new virtual knowledge-based services in the medical and educational fields. In another sense, it can be seen that the MV Council has used the resonance of values among community leaders in their SCs and their leadership synergy based on dialectical leadership to form the LSC and high levels of synthesizing capability, which in turn generated a solid network of SCs (see Figure 4).


Managerial implications: toward the realization of SC-based organizations Through the analysis of this in-depth case study, this author would like to emphasize that innovative organizations in the twenty-first century need to be strategic community-based organizations. In other words, it is important for innovative organizations to create ongoing innovation through business as well as non-profit activities that involve the formation of SCs based on creative knowledge assets and the networking of these SCs. Knowledge, or management resources, aimed at innovation is created from SCs; a wide range of knowledge both inside and outside the company, including customers and strategic partners, is synthesized via the network; and new knowledge that never existed before is created to become a new source of competitive advantage. To that end, it is important for community leaders who form the LSC to find a new value aimed at innovation with customers and leaders of strategic partners inside and outside the organization as the organization endeavors to achieve its desired vision and mission. The newly created value is then shared, sympathized, and resonated by all community members through dialectical dialog and discussion within the LSC. The philosophy of an interactive learning-based strategic community, where members teach each other and learn from each other, is an important part of this process. This approach promotes further dialectical leadership based on dialectical consideration and becomes the driving force for producing high levels of synthesizing capability.

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Dialectical leadership of community leaders Dialectical leadership refers to the sort of leadership that is required of community leaders that make up the LSC. The LSC is an informal SC made up of community leaders from the various SCs, and they are positioned above the layer of networked SCs (see Figure 1). The LSC gives greater strength to the cross-functional or inter-corporate integration characteristics that the SCs and networked SCs have. The LSC’s role is to boost the performance of knowledge sharing and integration, and to fulfill this role, community leaders in the LSC need to have the element of dialectical leadership. In other words, dialectical leadership embodies the leadership of community leaders that promotes a management (referred to as “dialectical management” in this paper) capable of integrating a variety of knowledge in the different SCs. As mentioned earlier, the community leaders must exercise a leadership that balances the various paradoxes in the areas of human resources, technology, and political considerations in order to successfully integrate the knowledge of these SCs. They need to have not just the elements of the participative leadership style and a flexible approach discussed thus far in the literature on new product development (NPD), they will also need to balance creativity and efficiency or participative control and directive. This sort of issue on thinking or behavior by individual leaders or among a number of leaders has not been discussed in the past in research on the cross-functional team (CFT) or project management in NPD. More recently, however,

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Lewis et al. (2002) have been maintaining that a balance of a number of paradoxes is required for successful product development. They clarify the frequent but ambiguous calls for subtle control: Effective managers provide strong leadership to keep teams focused and on schedule while empowering team members to foster motivation and creativity. In addition, O’Reilly and Tushman (2004) maintain that a leadership role that is both authoritative and top down as well as visionary and involved is necessary in order to balance exploitative business and exploratory business in corporations. They call this style of leadership “ambidextrous leadership”. In our own field studies as well, we were able to glean some rich data from dialogs and discussions with community leaders concerning their dialectical considerations and actions. An NTT community leader, for example, remarked: While it is important for specialists in the various fields to take advantage of their experience thus far to fulfill tasks for which they are responsible, at the same time they also need to provide support for the tasks of members from other organizations so that the project as a whole progresses well. Business models that focus not just on the hard area of IT but on soft areas such as education, medical care, and welfare where people are used must also be considered.

A community leader from Mitsubishi Electric commented: Since this project involves new business models in a variety of technical fields, we need to maintain communication and ties with engineers and other people both inside and outside the company. Though leadership and management capable of providing strong guidance to development team members of our own organization is naturally important, it is also important each day to empower young members of our own team at the same time, enhance their motivation, and to build cooperative relationships and a support system with engineers and leaders from other divisions or outside the company.

Similar issues and views that leaders and other members faced each day as they struggled to develop new technologies, build business models, or cultivate unknown markets resulting from the merging of the hard areas of IT and the soft areas involving human beings were received from 13 other community leaders, engineers, and other players. The demand for community leaders in SCs and networked SCs to exercise dialectical thinking and behavior is growing stronger than before. The sort of leadership required, gleaned from much of the data we obtained, can also be expressed as follows: As a first important element regarding the dialectical leadership which synthesize the different leadership behaviors of leadership’s dominant dualities, the community leaders in the LSC, who use synthesizing capabilities, do not only exhibit their “strategic leadership” as directors based on integrated, centralized leadership which can produce short- and long-term strategies, focus on the big picture and perform efficiency, but also exhibit their “creative leadership” based on autonomous, decentralized leadership which can produce creative thinking and behaviors of community members. As a second important element, community leaders do not only exhibit their “forceful leadership” as directors who can take charge and control community members, but also become listeners, recipients and collaborators based on collaborative leadership (Chrislip and Larson, 1994; Bryson and Crosby, 1992), empowering community members through enabling leadership and enhancing

intrinsic motivation (Osterlof and Frey, 2000) among community members in their knowledge creation activities. Their role as supporters and followers providing ongoing collaboration and support for the community so that it can pursue dreams and a sense of accomplishment for the business and its vision requires the element of “servant leadership” (Greanleaf, 1979; Spears, 1995). In this way, community members are themselves able to participate in decision-making in the SC and to enhance mutual understanding and strengthen links within the SC. As a result of synthesizing capabilities through dialectical leadership, community leaders including community members can create new knowledge creation of strategic, creative big projects, business concepts, and reforms in business processes (see Figure 7). This image of leadership at strategic community-based organizations is not the old type that was buttressed by a rigid hierarchy but a new model of leadership aimed at achieving innovation. This new type of leadership, that is the dialectical leadership, is oriented toward the growth of not only individuals but of groups or organizations in the form of SCs and networked SCs at the same time. From the viewpoint of leadership and organizational development, the key issue for companies of the twenty-first century aiming to achieve innovation is how to nurture and produce many community leaders who possess the dialectical leadership based on the concepts of being creative and strategic, and the ability to act. And the formation of SCs that can continuously generate innovation via the capabilities of individual community leaders, the number of community leaders from each level of management, and the abilities of these leaders to exercise their skills, along with the networking of these SCs, determine whether or not a company is able to build synthesizing capabilities through dialectical leadership.


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Figure 7. New knowledge creation through dialectical leadership

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Conclusion Through an in-depth case study, the author presented one view on the proposition of what the capabilities of leading organizations in the knowledge-based society are for strategic community-based organizations that form dynamic innovative processes in SCs and network these SCs. In other words, one of the keys to producing innovation in a knowledge-based society is how organizations can organically and innovatively network different knowledge created from the formation of a variety of SCs inside and outside the organization, and acquire synthesizing capabilities through the dialectical leadership they need to generate new knowledge. As community leaders, managers in the organization who play important roles in producing dialectical leadership for the organization use dialectical thinking and power to act to synthesize knowledge of good quality that was unevenly distributed inside and outside the organization. To this end, it is important for community leaders to promote the speedy formation of quality SCs networked inside and outside the organization, including customers, and to form an LSC made up of community leaders as soon as possible. Superior core technology in the leading-edge high-tech fields of IT and e-commerce continues to spread throughout the world and undergo dramatic changes. Innovative organizations that need to establish competitive advantage in the network economy must not retain full control over innovative processes under the conditions of conventional hierarchical mechanisms and closed autonomous systems. In other words, organizations will from now on probably increasingly require a management that can, from a multiple variety of viewpoints, use networked SCs to synthesize superior knowledge that is open and spread out both inside and outside the organization, including customers. Notes 1. Government (MPT) subsidies, made available under the heading of regional electronic networking promotion (Networking Facilities Upgrade Project Grants-in-Aid), include a facilities-building costs component, one-third of which is shouldered by the Government and the remaining two-thirds by regional governments (prefectures, cities, towns, villages). In the case of the Katsurao-mura project, the total construction cost came to ¥75 million, an amount that was covered in equal parts by the MPT, Fukushima Prefecture, and Katsurao-mura. This total construction cost was incurred by the VOD, MCU (Multipoint Connection Unit), networking equipment and other multimedia center-related construction components. NTT agreed to undertake alone the building of the multimedia center, proceeding to lease videophones free of charge to all the households in the village, which numbered 500, and putting the Video-Nets system in place. For the Video-Nets concept and virtual knowledge-based services applications, see Kodama, 1999. 2. Many television stations, newspapers and other media produced stories on the world’s first videophone-aided multimedia village project realized in Katsurao-mura. Some of them were TV Tokyo (World Business Satellite, aired May 18, 1998), TBS (Wide Show, aired May 11, 1998) and NHK (news). 3. A patient receives a diagnosis via videophone, then the doctor writes a prescription if needed, faxes it to a pharmacy outside the hospital, and mails it to the patient. The pharmacy prepares the medicine according to the prescription facsimile, and an employee then takes it directly to the patient’s home, and compares the original prescription with the facsimile. If they match, the employee exchanges the medicine for the original prescription and payment

(including a delivery fee). Patients eligible for home delivery include those with chronic illnesses, such as high blood pressure and rheumatism, who are in stable condition. (Home delivery of medicine on the basis of videophone diagnosis was approved by the Ministry of Health and Welfare in April, 1999.) The “Medicine Pack Service” was the first of its kind in Japan in the area of medical care, and the event was reported by Japan Broadcasting Corporation (NHK) in nationally broadcast television programs, such as Ohayo Nippon (Good Morning, Japan) (December 9, 1999) and News at Nine (December 1, 1999).

References Asahi Shimbun (1999), “Your home to double as clinic: diagnosis by videophone, drugs delivered to your door”, Asahi Shimbun, Vol. 19 December 25. Atkinson, P. and Hammersley, M. (1994), “Ethnography and participant observation”, in Denzin, N.K. and Lincoln, Y.S. (Eds), Handbook of Qualitative Research, Sage Publications, Thousand Oaks, CA, pp. 105-7. Bechard, R., Goldsmith, M. and Fesselbein, F. (1996), The Leader of the Future, Jossey-Bass, San Francisco, CA. Benson, J. (1977), “Organization: a dialectical view”, Administrative Science Quarterly, Vol. 22, pp. 221-42. Bryson, J. and Crosby, B.C. (1992), Leadership for the Common Good: Tackling Public Problems in a Shared-Power World, Jossey-Bass, San Francisco, CA. Brown, J. and Duguid, P. (1991), “Organizational learning and communities-of-practice: toward a unified view of working, learning, and innovation”, Organization Science, Vol. 2, pp. 40-57. Chrislip, D. and Larson, C. (1994), Collaborating leadership: How Citizens and Civic Leaders Can Make a Difference, Jossey-Bass, San Francisco, CA. Dacin, M.T., Ventresca, M.J. and Beal, B.D. (1999), “The embeddedness of organizations: dialogue and directions”, Journal of Management, Vol. 25 No. 3, pp. 317-56. DiMaggio, P. and Powell, W. (1983), “The iron cage revisited: institutional isomorphism and collective rationality in institutional fields”, American Sociological Review, Vol. 48 April, pp. 147-60. Eisenhardt, K. (1989), “Building theories from case study research”, Academy of Management Review, Vol. 14 No. 4, pp. 532-50. Fukushima Minpo Shimbun (1997), “Kooriyama Women’s University offers distance/lifelong learning courses featuring university lectures over television monitors”, Fukushima Minpo Shimbun, Vol. 11 June, p. 3. Granovetter, M. (1985), “Economic action and social structure: the problem of embeddedness”, American Journal of Sociology, Vol. 91 No. 30, pp. 481-510. Grant, R. (1996), “Prospering in dynamically competitive environments: organizational capability as knowledge integration”, Organization Science, Vol. 7, pp. 375-8. Grant, R. and Baden-Fuller, C. (1995), “A knowledge-based theory of inter-firm collaboration”, Academy of Management Best Paper Proceedings, Vol. 38, pp. 17-21. Glaser, B. and Strauss, A. (1967), The Discovery Of Grounded Theory: Strategies for Qualitative Research, Aldine, Chicago, IL. Greanleaf, R. (1979), Servant Leadership, Paulist Press, New York, NY. Heide, J. (1994), “Inter-organizational Governance in marketing channels”, Journal of Marketing, Vol. 58 January, pp. 40-51.


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Hesselbein, F., Goldsmith, M., Beckhard, R. and Schbert, R.F. (1998), The Community of the Future, Jossey-Bass, San Francisco, CA. Kodama, M. (1999), “Strategic business applications and new virtual knowledge-based business through community-based information network”, Information Management and Computer Security, Vol. 7 No. 4, pp. 186-99. Kodama, M. (2001a), “Innovation through creation of strategic communities in traditional big business: a case study of digital telecommunications services in Japan”, European Journal of Innovation Management, Vol. 4 No. 4, pp. 194-215. Kodama, M. (2001b), “New business through strategic community management: case study of multimedia business field”, International Journal of Human Resource Management, Vol. 11, pp. 1062-84. Lawrence, T., Phillips, N. and Hardy, N. (1999), “Watching whale-watching: a relational theory of organizational collaboration”, Journal of Applied Behavioral Science, Vol. 35, pp. 479-502. Lalle, B. (2003), “The management science researcher between theory and practice”, Organization Studies, Vol. 24 No. 7, pp. 1097-114. Lipnack, J. and Stamps, J. (1997), Virtual Teams, John Wiley & Sons, New York, NY. Locke, K. (2001), Grounded Theory in Management Research, Sage, Thousand Oaks, CA. Lewis, M., Dehler, G. and Green, S. (2002), “Product development tensions: exploring contrasting styles of project management”, Academy of Management Journal, Vol. 45 No. 3, pp. 546-64. Marshall, C. and Rossman, G. (1989), Designing Qualitative Research, Sage, London. Nihon Keizai Shimbun (1998), “Government services by videophone: installation in every household in Katsuraomura, Fukushima Prefecture”, Nihon Keizai Shimbun, Vol. 12, February 12, p. 38. Nihon Kogyo Shimbun (1998), “Vitalizing mountain villages by videophone: a response to the aging of depopulated areas”, Nihon Kogyo Shimbun, Vol. 25, p. 8. Nikkei Sangyo Shimbun (1999), “Home delivery of medicine via videophone: doctors in Katsuraomura, Fukushima Prefecture making remote diagnoses”, Nikkei Sangyo Shimbun, April 14, p. 8. (The) New York Times (1999), “Japan bets on a wired world to win back its global niche”, The New York Times, August 30. Nonaka, I. and Konno, N. (1998), “The concept of ‘Ba’: building a foundation for knowledge creation”, California Management Review, Vol. 40 No. 3, pp. 40-54. Nonaka, I. and Toyama, R. (2002), “A firm as a dialectical being: towards a dynamic theory of a firm”, Industrial and Corporate Change, Vol. 11 No. 5, pp. 995-1009. O’Reilly, C. III and Pfeffer, J. (2000), Hidden Value: How Great Companies Achieve Extraordinary Results with Ordinary People, Harvard Business School, Boston, MA. O’Reilly, C. III and Tushman, M. (2004), “The ambidextrous organization”, Harvard Business Review, April, pp. 74-81. Osterlof, M. and Frey, B. (2000), “Motivation, knowledge transfer, and organizational forms”, Organization Science, Vol. 11, pp. 538-50. Peng, K. and Nisbett, R. (1999), “Culture dialectics, and reasoning about contradiction”, American Psychologist, Vol. 54, pp. 741-54. Powell, W. and Brantley, P. (1992), “Competitive cooperation in biotechnology: learning through networks”, in Noria, R.G. and Eccles, R.G. (Eds), Network and Organizations: Structure, Form and Action, Harvard Business School, Boston, MA.

Powell, W., Koput, K. and Smith-Doerr, L. (1996), “Inter-organizational collaboration and the locus of innovation: networks of learning in biotechnology”, Administrative Science Quarterly, Vol. 41, pp. 116-46. Robbins, S. (1974), Managing Organizational Conflict: A Nontraditional Approach, Prentice-Hall, Englewood Cliffs, NJ. Strauss, A. (1987), Qualitative Analysis for Social Scientists, Cambridge University Press, New York, NY. Silvermann, D. (2000), Doing Qualitative Research, Sage, Thousand Oaks, CA. Sawhney, M. and Prandelli, E. (2000), “Communities of creation: managing distributed innovation in turbulent markets”, California Management Review, Vol. 42, pp. 24-54. Storck, J. and Patricia, A. (2000), “Knowledge diffusion through strategic communities”, Sloan Management Review, Vol. 41, pp. 63-74. Seo, M. and Douglas Creed, W. (2002), “Institutional contradictions, praxis, and institutional change: a dialectical perspective”, Academy of Management Review, Vol. 27, pp. 222-47. Spears, L. (1995), Reflections on Leadership, Wiley, New York, NY. Further reading Davenport, T.H., Ge Long, D.W. and Beers, M.C. (1998), “Successful knowledge management project”, Sloan Management Review, Winter, pp. 43-57. Leonard-Barton, D. (1995), Wellsprings of Knowledge, Harvard Business School Press, Boston, MA. Nonaka, I. and Takeuchi, H. (1995), The Knowledge Creating Company, Oxford University Press, Oxford. Peng, K. and Akutsu, S. (2001), “A mentality theory of knowledge creation and transfer: why some smart people resist new ideas and some don’t”, in Nonaka, I. and Teece, D. (Eds), Managing Industrial Knowledge-Creation, Transfer and Utilization, Sage, London, pp. 105-23. Van Maanen, J.V. (1979), “The fact of fiction in organizational ethnography”, Administrative Science Quarterly, Vol. 24, pp. 539-50. Van de Ven, A.H. and Poole, M.S. (1995), “Explaining development and change in organizations”, Academy of Management Review, Vol. 20, pp. 510-40.


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Adoption of behaviour: predicting success for major innovations David J. Langley and Nico Pals TNO Telecom, Groningen, The Netherlands, and

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J. Roland Ortt Delft University of Technology, Delft, The Netherlands Abstract Purpose – The goal of this article is to show that memetics is particularly useful to predict the adoption of major innovations. Design/methodology/approach – Describes how TNO Telecom, an applied research institute in The Netherlands, adopted the theory of memetics to develop an instrument that predicts the adoption of major innovations. Explains and defines relevant aspects of this focus. Findings – Initial results are encouraging and suggest that the approach may provide qualitatively better results than the existing methods when applied to major innovations. Originality/value – Describes for the first time how the theory of memetics can be used to gain a real insight into the market adoption of major innovations as well as to focus and optimise product development. Keywords Product innovation, Forecasting, Behaviour, The Netherlands Paper type Case study


Introduction Predicting whether an innovation will be adopted in a market has always formed a major scientific challenge. Generations of scientists have pursued this challenge, by studying the subject from different disciplinary angles and for different kinds of innovations. Sociologists and psychologists have tried to pinpoint the unique characteristics of the first groups of consumers that adopt an innovation (the innovators and the early adopters). After studying these characteristics, they tried to predict the likelihood that an innovation would be adopted by these types of people, leading to a critical mass of users in the market. An overview of the results of this line of research is provided by Robertson (1971), Engel et al. (1990), Foxall and Goldsmith (1994) and Rogers (2003). Macro economists have studied the specific conditions on the supply and the demand side of the market that foster innovation (Shumpeter, 1942; Galbraith, 1956; Schmookler 1967; Mansfield, 1968; Kamien and Schwartz, 1975). Consumer researchers have focused on measuring potential consumers’ reactions to, or perceptions of, product concepts and thereby estimated future demand for the final product (Greenhalgh, 1985; Moore, 1982; Page and Rosenbaum, 1992). As well as these approaches, diverse methods of using expert opinions have been applied (Armstrong, 2001a; Rowe and Wright, 2001). For example, the Delphi technique can lead to a consensus between a range of experts on the likely success of an innovation. Furthermore, several methods of data-analysis and curve fitting have been applied to predict the adoption of innovations (Armstrong, 2001a). Finally, econometric models have been developed to predict the sales and market shares of product variants (Lilien et al., 1992; Leeflang and Naert, 1978; Allen and Fildes, 2001). Although widely

different in scientific approach and orientation, these studies have clearly indicated that there are a number of difficulties in predicting whether an innovation will be adopted in a market. We will focus on one of these difficulties, namely: how can we validly predict the adoption of major innovations that change the patterns of product usage. Prevailing methods of market analysis, data analysis and expert analysis fall short in this case. This article introduces a new approach, based on memetics, to predict the adoption of major innovations. Relevant aspects of this focus will be explained and defined. Memetics Memetics is a theory that proposes a mechanism for the evolution of ideas and their associated behaviours. Memetics postulates that ideas and their associated behaviours survive in a population by being copied between people. The theory describes the conditions under which this copying of behaviour is likely (see also the section, “Description of memetics”). This article considers adoption and use of an innovation as a type of behaviour that can be copied. Insights from the theory of memetics are applied to indicate how likely certain types of people are to copy certain types of product-related behaviour. Major innovations Although innovation is sometimes defined, rather broadly, as a new product, service, process, or type of organization (Trott, 2002; Tidd et al., 2001), this article will focus on product innovations. Various typologies have been proposed to distinguish the degree of newness of product innovations (Veryzer, 1998; Garcia and Calantone, 2002). We will focus on major product innovations because for these innovations new approaches are required to predict adoption. Major product innovations comprise a completely new set of attributes and form a new product category, as opposed to minor innovations comprising small-scale alterations to existing products. Major innovations induce behavioural changes on behalf of the users (demand side of the market). As well as this, the production and marketing of new product categories typically requires new market actors, and thereby induces new patterns of interaction in the market (supply side of the market). The focus in this article will be on the demand side of the market since it describes an approach to predict the adoption of human behaviour. Adoption of an innovation The adoption of innovations in many cases just seems to refer to the act of buying an innovation (Tornatzky and Klein, 1982). Following Tauber (1977) and Tornatzky and Klein (1982), adoption in this article refers to buying and using a product innovation. Buying and using a product innovation are important since both behaviours are inextricably linked and can be copied by potential consumers. Relevance of predicting the adoption of major innovations Methods to predict the rate of adoption of major innovations have a large practical relevance. Major innovations have been the source of new markets and industries (Christensen, 1997; Olleros, 1986; Abernathy and Clark, 1985; Henderson and Clark, 1990; Tushman and Rosenkopf, 1992). For some companies, the introduction of major innovations has been a keystone of their long-term viability. The history of the

Adoption of behaviour

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American company Ratheon, for example, is intimately connected with the radar, a major product innovation. Similar examples of companies that are closely related with one or more major innovations are: Xerox (photocopying machines) and The Bell company (e.g., the fax and the transistor). Yet, for many other companies, the introduction of major innovations has caused their demise (Olleros, 1986; Pech, 2003). When a high level of investment is combined with a high level of risk, it is clear that the ability to predict the adoption of major innovations is of crucial importance. Goal of the article The goal of this article is to show that memetics is particularly useful to predict the adoption of major innovations. The following section, “Current approaches,” describes why these predictions are difficult to make for major innovations. It will also show what types of questions have to be addressed by any new approaches. The next section, “Description of memetics,” will introduce the scientific field of memetics and will show that this field offers a new perspective on the topic. This is followed by “Instrument development,” describing an instrument based on memetics to predict the adoption of major innovations. Preliminary results of this method will be described. Finally, conclusions are stated and discussion issues are addressed. Current approaches Many methods are suggested to predict the adoption of innovations (Armstrong, 2001a). Taschner (1999), in a simple categorization, distinguishes three categories of methods: consumer, expert, and data analysis. Each category includes a range of different methods. Expert analysis, for example, includes methods like Delphi approaches and expert interviews. Table I describes and compares these categories. The first row lists some of the methods in each category. The second row summarizes the type of conclusions that can be expected when applying each category. The next rows describe the source of the data, what data are required, the assumptions and requirements for valid conclusions, and the kind of situations in which the category of methods cannot be applied, respectively. Table I shows that consumer analysis techniques gather data about (potential) consumers and therefore focus on conclusions with regard to the demand-side of the market. On the other hand, methods of expert and data analysis can be applied to analyse data from the supply and the demand side of the market. The fifth row in Table I summarizes the assumptions and requirements for valid conclusions for each category of methods. This row implies that the three approaches do not deliver valid results for major innovations. The distinction between minor and major is important here. A minor innovation has a combination of attributes that is similar to the attributes of products that are already on the market. The set of competitive products as well the majority of the market actors involved in production and marketing of these products remain essentially the same. The basic attributes and the working of these products are known by most potential consumers. Although the minor innovation may contain some new features that distinguish it from similar products in the market, its adoption will not require major behavioural changes on the behalf of its users. The usage situations are mostly known for these products. So, relatively valid consumer evaluations regarding their future adoption behaviour, or relatively valid expert opinions regarding the market developments are possible prior to the introduction of a

Future behaviour of consumers

Type of data requested from source

Data source

Type of conclusions possible on the basis of techniques

Consumer survey, concept test, conjoint measurement, focus group, consumer interviews, test markets, simulations with consumers, experiments Problems of consumers with current products, analysis of required versus actual characteristics of products, description of user segments for a product category, description of potential consumers for a product category, preferences for specific product, actual behaviour of consumers in usage situations, effect of marketing-mix changes on consumers’preferences Consumer evaluations and opinions

Consumer analysis

Examples of techniques in each category

Categories ! Characteristics # of category Data analysis

Extrapolation of long-term trends in the industry, long-term developments in diffusion of a product category, analysis of short-term sales of product variants when marketing-mix of another product changes, effects of these changes upon the entire market and the market shares of product variants of various companies

(continued)

Long-term data about past (weekly) sales of existing products in a category Future developments on the demand Data about prices, specific actions, and supply side of the market, future type and intensity of distribution and communication for all products behaviour of consumers variants in a category

Expert evaluations and opinions

Technological developments in the industry, comparison of price/performance-ratios of alternative products, assessment of the effect of long-term trends in the market on the actors in the market, prediction of future demand of consumers

Trend extrapolation, curve fitting Delphi technique, focus group, analogy marketing models electronic group discussion techniques, expert interviews, expert econometric models surveys

Expert analysis


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Table I. Characteristics of three categories of methods to predict the adoption of innovations

Table I.

Assumptions and requirements for valid conclusions about market adoption

Consumers understand the product, its main attributes, its consequences in use and are aware of alternative products. Consumer researchers can validly deduce future consumer adoption behaviour if evaluations, attitudes and intentions are strongly related to this future adoption behaviour Situation in which techniques cannot When an innovation requires significant behavioural changes and be applied to predict market when consumers cannot understand adoption the product or its likely impact on their daily lives. This is because it comprises a new set of attributes, or when evaluation requires a long term learning process

Consumer analysis

The product category and marketing approaches for this category will essentially remain the same. Similar numbers and types of products will remain in the product category

Experts understand the market and its main actors on the supply and demand sides. Experts know the (future) competitive products. Experts understand how long-term trends will impact on the industry. Experts understand how changes in market patterns will affect adoption and usage behaviour When the industry changes radically, i.e. when new product categories emerge, and when usage patterns in the market change radically

When sales of an innovation cannot be derived from past data of prevailing products, i.e. when new product categories emerge, and when usage patterns in the market change radically

Data analysis

Expert analysis

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Categories ! Characteristics # of category

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minor innovation in the market. Moreover, since the product category to which the minor innovation belongs remains essentially the same, data about the diffusion of the product category can still be extrapolated. In practice, a major innovation comprises a new combination of attributes, and requires considerable changes in behaviour. As a result, it is more difficult for potential consumers to infer the benefits of this product (consumers can not evaluate the benefits of products that they will use as part of a completely different behavioural pattern). That means that they have more difficulties in validly indicating whether this product will fulfil their needs and wants. The difficulties in consumer research for major innovations have been recognized by many authors (Hills, 1981; Von Hippel, 1986; Moriarty and Kosnik, 1989; Ortt, 1998; Shanklin and Ryans, 1987; Taschner, 1999; Tauber, 1974; Tauber, 1977). Similarly, the validity of experts’ opinions with regard to market developments becomes much more questionable since major innovations cause a discontinuous shift in relevant market actors on both the demand and the supply side of the market. Experts tend to be prone to bias and inconsistency, both of which damage forecasting accuracy (Harvey, 2001; Hogarth, 1987), they tend to place too much trust in their own predictions (Brenner et al., 1996; Arkes, 2001) and they have a bad record in predicting the adoption of major innovations (Schnaars, 1989; Wheeler and Shelley, 1987). Finally, data analysis is also not recommended for major innovations (Armstrong, 2001b). A major innovation in many cases causes a new product category. The invention of video communication in 1930, and its subsequent development into the product television, created an entirely new product category, for example. Along with an entirely new combination of core attributes, new suppliers, new producers and new competitors of the product may emerge in the market, causing a shift in the relevant market structure. Because of this shift, past data regarding the diffusion of predecessors of the innovation can no longer be extrapolated to indicate the future adoption of such a major innovation. So, current approaches to predict the adoption of innovations, i.e. consumer analysis, expert analysis and data analysis, seem inapplicable in case of major innovations. What type of approaches are required for major product innovations? Several adaptations of the current research methods have been proposed to help improve this situation. One of these adaptations concerns the selection of experts and consumers on the basis of their expertise and experience. It has been shown that consumers with high levels of expertise and experience are more able to understand early concepts of major innovations (Loosschilder and Ortt, 1994). A second adaptation concerns checking the consistency of experts’ opinions or consumers’ evaluations. It has been shown that higher levels of expertise and experience are related to more consistent evaluations (Ortt, 1998). A third approach, based on the structuring of judgmental techniques, attempts to formalize the steps taken when posing questions, collecting opinions and analysing the responses, in order to reduce bias and inconsistency (Stewart, 2001). A fourth adaptation attempts to increase the validity of consumer evaluations by checking whether consumers actually understand the concept of the major innovation before they start evaluating it. More adaptations are possible in consumer, expert and data analysis but all of them somehow assume that


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adoption can be predicted either by human opinion about the future or by the analysis of past data. This assumption of predictability of adoption seems highly unlikely if one looks at the pattern of diffusion of major innovations. Major innovations change existing markets and create new markets. A closer look at this market creation shows a trial-and-error process. Even the most successful major innovations, like television, fax, telephone, laser, CTI scans and so on were confronted with dubious results after their first introduction into the market (Lynn et al., 1996; Ortt, 1998). During the process of creating a new market, we think that approaches should focus on the following issues: (1) Create alternative product variants or designs for the major innovation. (2) Distinguish alternative customer groups. (3) Carefully match the product variants with the characteristics of the customer groups. (4) Select the (logical order of) segments or niches that may establish a critical mass of users. Especially during the erratic pattern of diffusion just after the market introduction of a major innovation, prevailing methods of consumer, expert and data analysis are not applicable. Clearly, something new is needed in this case. Description of memetics Memetics is a theory that proposes a mechanism for the evolution of ideas and their associated behaviours and material artefacts. For example, the use of children’s nursery rhymes can be seen to evolve over time. Each new generation of parents introduces their children to the nursery rhymes from their own youth. The least popular or least memorable rhymes are discarded or forgotten and their place is taken by new rhymes. Small changes in some rhymes, for example an alteration in a couple of words or an adaptation of the tune, may be adopted by subsequent generations. Some nursery rhymes remain in use for hundreds of years, whilst many others fail to be adopted by more than one generation. Long-lived nursery rhymes often have particular mechanisms which aid their chances of survival. A rhyme may be sung with an easily remembered tune and may be accompanied by a group dance on the school playground. Another may contain a message which increases the chance that parents will want to sing it to their children, such as an encouragement to the children that they go quietly to sleep. There are many other commonly used examples used to describe memetics, such as ideologies, languages and clothing styles. The theory took shape in the 1970s when Cloak (1973, 1975) proposed two forms of culture: the instructions in our minds he termed “i-culture” and the material expression of these instructions (including behaviours) he termed “m-culture”. The proposal was that m-culture functions to maintain and propagate i-culture within a population. It does this, according to Cloak, through a process of natural selection of the cultural elements most suited to the human environment. The evolutionary geneticist, Dawkins, coined the term “meme”, pronounced to rhyme with “beam”, as a unit of cultural inheritance (Dawkins, 1976). Memes evolve in much the same way as genes. Genes are carried by biological organisms, and affect the physical and behavioural characteristics of those organisms. These characteristics determine the likelihood that each organism will

survive and reproduce in a particular environment. And this in turn determines which genes are passed on to the next generation. Genes that have survived for many generations have proven themselves to be highly capable of getting themselves passed on in this way. Memetics proposes an analogous (although not identical) mechanism for memes. Memes, in the form of ideas, or their associated behaviours and material artefacts, are held by people. For example, some parents know and remember the song, “Rock-a-bye baby” (the idea, or i-culture). They may sing it to their children (the behaviour). They may own a book with the words and music in written form (the material artefact, which together with the behaviour are the m-culture). The characteristics of this meme (how easy it is to remember, how appealing it is for parents to sing, how much children like to hear it, etc.) determine the likelihood that it will survive and be passed on to subsequent generations. Memes that are better suited to a particular environmental niche (for example, rhymes with catchy tunes and pacifying lyrics) will out compete other memes and be expressed more often and by more people. Memes that have survived for many generations have proven themselves to be highly capable of getting themselves passed on in this way. It is important to note that memes, unlike genes, are not only passed on from parents to children. They can be passed on within a generation, such as children learning a dance from each other, and can even be passed from younger to older generations, such as when a teenager shows her grandfather how to use an internet browser. This opens the possibility for memes to spread rapidly through an entire population in a fraction of a biological generation. In this way i-culture can be seen as analogous to the information coded by genes and m-culture can be compared to the biological phenotype, or physical expression of those genes (see Table II). Organisms reproduce, whereby their genetic material is replicated, occasionally with mutations giving rise to novel adaptations. During the “struggle for survival” (Darwin, 1859) the organisms most suited to their environment will generally prosper better and bear more offspring. In much the same way as Rogers’ theory of the diffusion of innovations (Rogers, 2003), memetics takes an “idea-eye-view” of the world and postulates that behaviours and ideas compete for attention and expression by their human carriers and replicate themselves through imitation or copying behaviour (Dawkins, 1976; Blackmore, 1999). This implies that for a meme to be suitable for a particular group of people, it must combine well with the other memes already resident in their minds (c.f. Blackmore, 1999).


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Memetics applied to the adoption of innovations Memetics has the potential to provide an insight into which behaviours or ideas become successful. A plain, non-memetic, viewpoint may hold that the behaviours most likely to become widespread will simply be those offering the most benefit to people. In contrast, a memetic viewpoint would propose that the behaviours which will Replicator

Physical form

Genetics

Gene

Memetics

Meme, ideas, i-culture

Physical characteristics and instinctive behavioural characteristics of organism Copied behaviours, material artefacts, m-culture

Table II. Comparison of two forms of replicator: genes and memes

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be expressed the most will be those which are best suited to being copied. The theory proposes that for a behaviour to be successful it must achieve three things: There must be many copies made of it (fecundity). For example, imagine a new type of dance which is intended for any type of situation; at parties, in the disco, etc. Such a dance may spread more rapidly through a population than a new dance which is only intended for infrequent occasions; such as weddings or royal coronations. The copies must be quite accurate (fidelity). If the dance steps are altered too much each time a new person copies them, then the original dance will not survive long. On the other hand if the fidelity is 100 per cent, then the dance cannot adapt, for example to changing social styles, and will eventually become old-fashioned and obsolete. The copies should be long-lived (longevity). If each person that learns the new dance remembers it and performs it over a long period, then many others will come into contact with it. If the dance conforms to prevalent social attitudes, for example of individuality and personal expression, then it is more likely to remain a stable part of one’s behavioural habits. We believe that the behavioural component of the use of products and services could also be analysed in this manner. If we are to do this, we will need to assess the capacity a behaviour has to get itself copied in a particular population. As such, this approach is different to all the existing methods for assessing the adoption of innovations. Existing methods make use of one of three sources: the opinions of people about the future behaviour of themselves; the opinions of people about the future behaviour of others; or they make use of data obtained from existing products. The more radical an innovation, the less human experience or past data can be validly applied. In these cases, this new approach may offer an advantage. Existing research applying memetics to innovations Despite the commercial investments made in understanding customer behaviour, for example through market research, usability studies and market forecasting, little work has been published in which the new perspective offered by memetics is applied to product-related behaviours. More than twenty years ago, developments in the field of cultural evolutionary theory led researchers to adapt mathematical models from population genetics and apply them to cultural traits (e.g. Feldman and Cavalli-Sforza, 1976). Although most traits studied were “vertically transmitted”, i.e. passed from parents to children, such as religion or the use of salt, some were “horizontally transmitted”, i.e. within peer groups and were unrelated to reproductive or biological fitness, such as a preference for a particular soft drink (Cavalli-Sforza and Feldman, 1981; Boyd and Richerson, 1985). We have only been able to identify two studies since then linking memetics to products or innovation processes. Pech (2003) claims that management strategies can be seen as memes which can be copied between or within organizations. Some such memes may be highly stable, resisting challenge from other memes, even when this is not in the best interests of the company. For example, the belief that a proven and successful technology will remain successful may become so powerful that the threat posed by a new technology may be ignored. More directly relevant to the products themselves, is the work of Marsden (2002) who has developed a method he calls “meme mapping.” This method appears to have

much in common with another method, known as “laddering” (Reynolds and Gutman, 1988). When applied to the brand image of a commercial product, Marsden starts with the central value of the product (his example is the value of healthy living). Consumers are then questioned in order to distil out the component values and their relative positive or negative connotation. In this way he produces a hierarchical analysis (the meme map) of the values embodied within a product brand.


65 Controversies surrounding memetics The theory of memetics, sometimes referred to as an emerging science, is not without its controversies. Although this is not the place for a rigorous discussion of all the detailed issues surrounding memetics, if we are to propose a new method based on the theory then it is essential to believe that any serious reservations others have concerning the theory do not undermine the relevance or validity of our method. Therefore, a few of the most important controversies and those most relevant to this paper are briefly described below. What exactly is a meme? An idea can be very narrow (e.g. relating to a single word) or very broad (e.g. an entire language). How necessary is it to have a strict definition? On the one side of this debate are those who believe that such a vaguely defined term is meaningless (e.g. Plotkin, 2000; Williams, 2002). They argue that such diverse things as ideas, behaviour, artefacts, mental states, information and culturally transmitted instructions cannot all be described by the single term, meme. On the other side of the debate are those who believe that the theory in its current state already offers a useful perspective and that a tight definition will come as a matter of course. In much the same way as the Darwinian theory of evolution through natural selection (the non-random selection of random mutations) had to wait for Mendel to show that it was particulate and for Watson and Crick to identify the specific molecules involved. Some authors (e.g. Auger, 2002) believe that recent advances in neurology already allow us to describe a meme as a neuronal state and a specific configuration of neurotransmitters. Rose (1998) suggests that much of the controversy has originated through carelessness in distinguishing between the ideas residing in minds and the physical or behavioural expression of those ideas. Cloak’s definition of replicating and competing ideas (i-culture) and that being expressed (m-culture) seems clear enough to be used in our case. For example, the idea of sending messages to a friend using a mobile phone has become propagated with the help of the copyable behaviour of actually sending a text message. People see others sending and receiving messages and hear about text messaging from friends or through the media. This has been enough to stimulate many people to adopt the idea that text messaging is a good thing to do. A second controversy surrounds the explanatory power of memetics (e.g. Williams, R., 2002). Some authors believe it to be, at best, an intriguing perspective on the world, unable to provide insight into why one meme becomes widespread whilst another dies out? Rose (1998) suggests that other theories, in particular socio-biology (the use of biological theories, including population genetics, to explain social phenomena such as altruism, kinship, etc.), are sufficient to understand human cultural evolution and that, therefore, memetics is unnecessary. Other authors see the application of “universal Darwinism” to fields other than biology as providing a rich and powerful insight (e.g.

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Dennett, 1995). The instrument we propose in this paper, based on memetics, goes some way in testing precisely this explanatory power. Another issue relevant to this paper is the question regarding how we choose new memes to adopt. If our minds are composed of memes, who is it then who does the choosing (c.f. Rose, 1998)? Some (e.g. Rose, 1998; Williams, R., 2002) ask if memetics requires the existence of a mind which is distinct from one’s memes. Others (e.g. Blackmore, 1999; Lynch, 1996) suggest that we have a complex of memes of which our minds are composed, which is capable of providing a coherent self image and at the same time selecting new memes. In terms of our needs for this paper, the instrument which we propose includes an assumption that the personality traits of a person play an important role in their (conscious or sub-conscious) processes of selecting new memes. This will be described further in the next section. Whether those personality traits are formed by existing memes or in other ways (such as being genetically programmed) is then, for our current purposes, less relevant. The following paragraph describes how the theory of memetics has been used as the basis for a new type of instrument for assessing the likely adoption of new behaviours. Specifically, behaviours relating to the use of new products or services. Instrument development As stated in the introduction, the very “newness” of major innovations brings the validity of the current approaches into question. The end-user, for instance, cannot say he is going to use something he cannot yet imagine. Considering this from a memetics point of view, we may be able to bypass opinions about what will happen in the market and simply address the question of whether or not a new behaviour is suited to being adopted (copied) by a certain type of person. We take this “type of person” to be reflected in the basic personality traits and therefore that one’s make up in terms of those traits will determine (consciously or subconsciously) which new ideas or behaviours one is likely to adopt. If we succeed in decomposing innovative concepts into a number of behavioural elements (memes) it should be possible to estimate the probability that a person with certain personality traits will copy these behavioural elements and, as a consequence, will adopt the new product. Based on these principles an instrument was developed which is described below. Basically it analyses the match between a number of product characteristics and a number of target group characteristics. This instrument, called SUMI (Service-User Matching Instrument), calculates the likelihood that a target group with certain characteristics will copy the behaviour associated with certain product characteristics (see Figure 1). The process of developing the instrument was started with a literature search looking for product characteristics that can be related to copying behaviour and also for personality traits that might influence the copying behaviour of an individual. This resulted in two “long lists” of characteristics. Both lists were reduced in size during a number of discussion sessions with experts. To determine the match between product characteristics and personality traits an “expert model” was developed in which for each characteristic – trait combination the likelihood of copying is estimated on a generic level. The process was completed with the development of a software application into which specific information about product and target group must be fed. The application then calculates the likelihood that a specific target group will

adopt a specific new product. The phases of the development process are now described in more detail. Product characteristics Several authors described sets of product characteristics which are important for the adoption of a product (including Tholke et al., 1997; Heylighen, 2001; Rogers, 2003). From these sets of characteristics the ones which possibly related to copying behaviour, in a positive or negative sense were selected. For instance the characteristic “complexity” (Rogers, 2003) is supposed to have a negative impact on the possibility that behaviour is copied, while “tryability” (Rogers, 2003) has a positive effect. This resulted in a list of 26 product characteristics affecting copying behaviour. These characteristics can be clustered into Dawkins’ (1976) categories: fidelity, fecundity and longevity (see “Description of memetics”) whereby the most successful behaviours are those that make many accurate and long-lived copies of themselves (Blackmore, 2000). Some characteristics fit into more than one cluster. The characteristic “visibility”, for instance, affects fecundity (more visibility leads to more copies) as well as fidelity


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Figure 1. Basic model of the SUMI instrument

Fecundity

Fidelity

Longevity

Product combines well with existing behaviour: the extent to which the behaviour is reinforced because it is part of (or complementary to) other behaviour Inherent sociability: the extent to which the behaviour is social or forms part of a social event, etc. Ease of use: the extent to which the product is easy or difficult to operate Visibility: the extent to which the behaviour can be perceived in full detail, etc. Stability: the extent to which the behaviour remains constant over time Long-term effect on the individual: the long-term positive effects the behaviour has for individuals (money, time, status, appreciation), etc.

Table III. Examples of product characteristics in the three categories

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(better visibility leads to better copies). Table III shows a number of examples of product characteristics. Target group traits The Jungian approach to personality psychology embodied by the Myers-Briggs Type Indicator (Myers, 1962, Hirsh and Kummerow, 1990) has evolved into a new approach focussed on traits rather than types. The standard personality model in this trait theory consists of five personality dimensions, known as the big five (Ewen, 1998; Norman 1963; Tupes and Christal, 1961). Many researchers agree on the basic influence of these dimensions, although there are a number of different labels in use, including a version based on the acronym, OCEAN, which stands for Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism (Digman, 1997). A number of similar approaches have been combined to produce the Abridged Big Five Dimensional Circumplex (Hofstee et al., 1992; Johnson and Ostendorf, 1993). Some dispute the accuracy of these models which use such a broad-brush approach to something clearly so complex as human personality (e.g. Paunonen, 2001). However, for our purposes these approaches, although not perfect, do appear applicable, having stood up to rigorous testing over a number of decades. SUMI is based on a combination of seven pairs of these traits (Table IV).

Match between traits and characteristics The match between personality traits and product characteristics is determined by the influence of the behaviour associated with a certain product characteristic on the likelihood that the person will copy that behaviour. Table V gives some examples of Big Five dimensions (e.g. Hofstee et al., 1992)

SUMI

Table IV. Personality traits used by SUMI and other authors

Table V. Examples of how the personality traits match with product characteristics to influence the likelihood that the behaviour will be copied

Innovative – Conservative Organised – Spontaneous Introvert – Extrovert Altruistic – Egoistic Conformist – Non-conformist Rational – Emotional Driven stoical

Openness (O) Conscientiousness (C) Extroversion (E) Agreeableness (A) Neuroticism (N)

Myers-Briggs Type Indicator (Myers, 1962) Judging – Perceiving Introvert – Extravert Thinking – Feeling Sensing intuition

Personality trait Openness Extroversion Conscientiousness Conscientiousness Openness Agreeableness

Influence on likelihood of copying

Product characteristic Innovative Extrovert Spontaneous Organised Conservative Egoistic

Distinctiveness Inherent sociability Ease of use Visibility Stability Effect on individual

High High Low Low Low Positive

High High Low High Low High

the proposed influence of product features on the chance that a person with a particular personality trait will copy the behaviour associated with that feature. For example the first row in the table means that if the product related behaviour is highly “distinct from existing behaviour”, the likelihood that an “innovative” person (who is more than average open to new experiences) will copy that behaviour is higher than for a person who is average with respect to new experiences. The heart of the SUMI instrument is an “expert model” in which generic estimations are made of all possible combinations of which Table V gives examples, i.e. the effect that a certain product characteristic has on the chance that an individual possessing certain traits will copy the behaviour associated with the product. For each of the possible combinations of characteristics and traits (26 £ 14) experts were asked the following question: “What is in general the effect of characteristic x, on the chance that a person with trait y, will copy the behaviour associated with the use of the product”. This expert model is generic and can be applied to a broad range of combinations of products and target groups. To apply the instrument to a specific product – target group combination, the characteristics of both product and target group have to be assessed by people with sufficient knowledge of these characteristics. The characteristics are scored on Likert type scales. Based on these scores the expert model calculates a total “match score” for the product – target group combination, which is a measure for the expected adoption of the product by this target group. The instrument also generates match scores for every individual product characteristic (see Figure 2). Figure 2 can be understood best by starting with characteristic 1 (first bar). The match score for this characteristic is about 3, the “target group sensitivity” is 5 (dotted line), so the match is reasonable but not perfect. So in Figure 2 the dotted line represents the target group. It is a measure of the “sensitivity” of the target group for each product characteristic. The bars are the match scores for the product characteristic – target group combinations. The distance between the top of a bar and the target group sensitivity line represents the possibility for improvement of the product. This kind of output can be used for detailed analysis of the product – target group combination. It is important to focus on the product characteristics where target


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Figure 2. Example of the output generated by a SUMI analysis

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group sensitivity is high and the match is low (circled areas). These characteristics represent the best possibilities for improvement. The process of using SUMI The process of a SUMI analysis is illustrated using the adoption of SMS by trendy adolescents. (1) By means of a series of interviews, as much information as possible is gathered about the service and about the envisaged target group. The people to talk with at this stage are, for instance, product developers, product managers, marketing directors and marketers. During these interviews the emphasis is on factual information (e.g. the market segmentation methods which are used, target group descriptions, etc.). The SUMI variables are not directly mentioned at this stage. (2) During the next phase the researchers translate this information into the characteristics and traits used by the SUMI instrument and quantify it. Typically, one or two variants of a product are analysed for three or four target groups. SMS gets high scores on, for example: visibility, reach, inherent sociability, combines with other behaviour and frequency. It scores low on: financial attractiveness and ease of use. A few traits of the target group, trendy adolescents, are: innovative, spontaneous, egoistic and emotional. (3) In the next phase the product and target group scores are fed into the instrument and the results are calculated and analysed. (4) The process is concluded with a workshop with stakeholders in where the results are presented and discussed. Discussion is specifically focussed on those product characteristics that are important to the target group(s) and on how to improve the product offering when results exhibit a poor match for those characteristics. Case study The following example is an illustration of applying SUMI in the telecommunications sector. It was in an assignment for a European mobile telecommunications operator, who was considering the introduction of a number of mobile services. Ten mobile services were analysed for their likely adoption by one broad target group, self-employed entrepreneurs working from home or from a small office. Five of the services had already been launched and the operator wanted to decide which of the other five to introduce. The mobile telecom services were: . Text messaging (SMS (Short Message Service). . SMS group. . SMS info. . Voicemail. . Voicemail call back. . Voicemail direct. . Voicemail group. . Fax mail.

. .


Internet-connectivity via WAP. Internet-connectivity via GPRS.

During a number of workshops with marketing and product experts information about the target group and about the services was collected. Based upon this information the SUMI experts determined the input scores for the product characteristics and the target group traits. The results were calculated and analysed. During a final workshop with the most important stakeholders the results were presented and discussed. In Table VI the total SUMI scores for the ten services are summarised and compared to the market penetration in The Netherlands where the ten services were already on the market. The match scores, which provide a relative indication of likely adoption, vary between 1 and 52. It is clear that the two highest SUMI scores match precisely with the two services that did in fact achieve the highest penetration. For the moderately successful and failed services there is also agreement between SUMI scores and market adoption, although the exact match is less clear. Only one service, which scored “5” in the SUMI analysis, performed clearly better in the Dutch market than the SUMI score would have predicted.

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Managerial applicability The results of a SUMI analysis can be used in a number of ways: . The overall match score compared to other products from previous analyses. This overall match score is an indication of the probability of adoption by the target group. Managerially it can be used to decide whether or not to launch the product. . A comparison of a number of variants of the same product. Especially in the early stages of development a lot of decisions have to be made about which product variant to offer to which market segment. SUMI can assist in this decision making process, by showing which variants show the highest potential for the chosen target groups. . Identifying the strong points of a product for a certain target group. From the detailed results, like Figure 2, it is possible to asses the elements that are important for the target group and that have a high match (high bar and high SUMI scores for the ten services 1 9 14 17 5 16 22 23 50 52

Market adoption by target group in The Netherlands Failure

Moderate

Success

Note: Services are displayed anonymously. The target group was self-employed entrepreneurs working from home or from a small office

Table VI. SUMI scores for the ten analysed services, compared to the penetration level in The Netherlands

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.

target group sensitivity in Figure 2). This can be used, for example, in the design of marketing campaigns. The aspects of a product that can be improved. From the same results the characteristics that need improvement can be derived (circles in Figure 2). This can be used for changes in the design of the product, making it better suited to being adopted by the target group. A comparison of target groups. Finally it is possible to analyse a product for a number of different target groups. The results of these analyses can be used to select the launching target group and / or to focus the marketing of the product.

So the SUMI results can be applied in a number of ways. In some cases it can lead to a decision to stop the development of a product and not put it on the market. Other decisions can lead to changes in the product design, or to a shift of focus regarding the target group. The analysis can also result in recommendations for the marketing of a product, for example, by using the advertising message to emphasizing its strong points or to paint the important but weak point in a positive light. Another possible application is to use the instrument to choose (or prioritise) from a range of products, which are in competition for a limited development budget. It is important to note in this respect that SUMI can be applied in very early stages of the development process. Discussion Just after the introduction of a major innovation, in many cases a so-called trial-and-error process occurs in which companies introduce different product forms in different applications and for different target consumer groups. Especially in this phase, a market research instrument is needed by which companies can quickly establish the match between alternative product forms and customer groups. Such an instrument is invaluable since it focuses and shortens this trial-and-error process. This article shows that current approaches to predict the adoption of innovations, shortly categorized as consumer analysis, expert analysis and data analysis, seem inapplicable in the case of a major product innovation. A method is needed which does not rely on the opinions of people about the future behaviour of themselves or of others related to the adoption of major innovations, or past data of the adoption of other products in other situations being applied to estimate the future adoption of major innovations. This paper shows that memetics, a theory of how behaviour is copied and therefore spread throughout a population, appears to lend itself to filling this need. This is the first time, as far as we can tell, that this theory has been applied to predicting the adoption of behaviour relating to innovations. It allows us to assess how well a certain behaviour is suited to people with certain personality traits. It does this without resorting to peoples’ judgements about the future and without relying on past data about other (product related) behaviours. The first attempt to validate an instrument, SUMI, based on this theory, compared adoption predictions for services in one country with market data from the same services in a different (but similar) country. The results are encouraging and suggest that SUMI predictions are reasonably accurate indicators of market potential. The initial results described in this paper are a first step in the development of a valid and reliable instrument for providing insight into the likely adoption of major

innovations. Ideally, we would already have carried out a series of longitudinal studies across a wide range of sectors and we would have compared the results of SUMI to the predictions made by other methods and instruments as well as to the eventual market data. For such a new instrument this has not yet been possible. The best validation method available at this point is the type of backwards prediction described in this paper. Actual diffusion requires a focus on more market actors than consumers only. SUMI primarily predicts the acceptance of innovations by looking at the match between (potential) consumers and the characteristics of the innovation. However, more market actors and more market factors have to be taken into consideration to explain whether an innovation will actually be introduced in the market. The acceptance, by 10-20 per cent of the population of people buying and using a car, of electrical vehicles, for example, has been consistently assessed in extensive market research projects in the 1960s, 1980s and 1990s (Ortt, 1998). Yet, the vehicle has only marginally diffused. The reason for this disappointing degree of diffusion is that multiple actors involved in the supply of the product and the complementary services, had convincing reasons to practically block the introduction of the vehicle. SUMI focuses on the consumers only. If a company is willing and capable of introducing an innovation (e.g. infrastructures, service arrangements, outlets and so on are all available) only then can SUMI validly indicate whether this innovation will become a success. It is important to consider when SUMI can or cannot be applied. Four issues seem worthy of attention: stage of development, level of innovation, product type and industry sector. SUMI requires input in the form of information about the proposed target group and information relating to the characteristics of the product. This information can be gained early in the development process, long before time and money has been spent developing prototypes or carrying out market trials. In this way, SUMI can have a significant positive effect on the development of major innovations by making the trial and error process quicker, more focussed and therefore cheaper. In the case described in this paper SUMI was applied to major innovations. There is no reason to believe that SUMI would not be applicable to minor innovations. However, as most existing methods for assessing the likely adoption of products are ideally suited to minor innovations, the added benefit of applying SUMI in these cases appears small. For SUMI to work, something must be copied by one person from another. For innovations that are invisible to end users, such as cost-efficient chemical processes in the production of materials, the use of SUMI is inappropriate. Which sectors produce the type of innovation that can be evaluated with SUMI? The case described in this paper comes from the Telecom industry and it appears that SUMI is broadly applicable in this sector. We speculate that SUMI will also be applicable in the closely related industry of consumer electronics, as well as other sectors with a high pace of innovation that directly induces novel consumer behaviour, such as the financial, employment services and fast-moving consumer goods sectors. This is, as yet, speculation and validating case studies in a range of sectors is a priority for further research.


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SUMI may be of interest to researchers in the emerging field of memetics. As stated above, some have questioned the explanatory power of the theory and Edmonds (2002) has gone so far as to propose three challenges to memetics if it is to prove itself as a theory worthy of continuing research effort: A conclusive case study, a theory for when it is appropriate and a simulation of the emergence of a memetic process. This paper may have contributed to this debate to a certain degree by offering a practical application of the theory coupled to encouraging early results. This explanatory power has additional relevance to the development of innovations, due to the reduced reliance on opinion and data relating to old or existing products. Our approach is based on the assumption that for a new idea or behaviour related to a new product to be adopted by consumers, it must match with their personality characteristics. For example, extravert people are more likely than non-extravert people to adopt behaviour that is inherently social. In this way we bypass the discussion about whether an individual is distinct from his or her memes. In whatever way our personalities have developed, with or without the help of our memes, we have more chance of adopting any new behaviour that fits well with our personalities. This paper describes for the first time how the theory of memetics can be used to gain a real insight into the market adoption of major innovations as well as to focus and optimise product development. But it is just a start. Much further research is needed. In developing SUMI we have selected a range of personality traits and product characteristics. In order to improve SUMI the selection, relative importance and interactions between these variables need to be further researched. As stated above, longitudinal and comparative studies need to be carried out across a range of sectors to clearly assess the validity and reliability of SUMI results. Added to this, the business relevance of improving the process of innovation development as well as the new insights SUMI can provide for marketing communication and target group segmentation have yet to be fully qualified. The results described in this paper would suggest that further investigation of this area is justified.

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Market-oriented new product development How can a means-end chain approach affect the process?

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Helle Alsted Søndergaard The MAPP Centre, Aarhus School of Business, Aarhus, Denmark Abstract Purpose – Aims to ascertain whether a well-known theory within consumer research – a means-end chain (MEC) – can be used as a catalyst to achieve market oriented product development. Design/methodology/approach – Describes a case study, involving a Danish food manufacturer, where a MEC approach was introduced to a cross-functional development team at two different stages of the development process. Findings – Results show that MEC data is perceived as a good way of gaining knowledge about consumers; that the information serves well as the basis of discussions and for keeping project goals fixed. The results also indicate that MEC data are most valuable to the team in the early stages of the development process and that lack of a learning orientation may inhibit the effects of a MEC approach. Originality/value – The MEC approach shows clear advantages for market oriented product development. Keywords Product development, Market orientation, Consumer research Paper type Case study

Introduction The means-end chain (MEC) theory is widely used in consumer research and for the development of advertising strategies (Gutman, 1982; Reynolds and Whitlark, 1995). This paper shows an attempt to apply a MEC approach to the development of new products. The aim is to investigate how the introduction of means-end chain data to the new product development (NPD) process influences some of the critical factors that support successful product development. When looking into the vast literature on success and failure in new product development, it is clear that certain groups of factors are crucial for the success of new product development (Henard and Szymanski, 2001; Montoya-Weiss and Calantone, 1994). Two of the central themes are market orientation and inter-functional integration between functions in the development process. Due to the way means-end chain data are collected and to the nature of the data, it seems an adequate instrument for influencing these two vital areas in new product development. A MEC approach to NPD The MEC theory of consumer behaviour is based on the assumption that consumers demand products because of the expected positive consequences of using the products (Grunert and Valli, 2001; Gutman, 1982; (Walker and Olson, 1991). Products are usually described in terms of their attributes, even though the consequences of using them are more important, since these may be related to the realisation of life values. A


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means-end chain illustrates the links between product attributes, consequences and values, where the means is the product and the end is the desired value state. The purpose of the MEC theory is to explain how product preference and choice is related to the achievement of central life values (Gutman, 1982). Figure 1 illustrates a means-end chain for apples. It can illustrate that we buy apples not only for the sake of the apples but because they give us energy so that we can lead an active life, which may enhance our wellbeing. The most important practical application of the MEC approach has been in the development of advertising strategies and for this purpose, the “Means-Ends Conceptualisation of the Components of Advertising Strategy” (MECCAS) model has been constructed. It builds on product positioning according to relevance to the consumer (Reynolds and Craddock, 1988; Reynolds and Whitlark, 1995). According to Gutman (1982) and Olson and Reynolds (1983) the means-end chain approach is also applicable in product development although it has been sparsely used in this area (Grunert and Valli, 2001; Valli et al., 1999). Information about consumers’ high-priority means-end chains for a product category may give companies the necessary knowledge to develop products that offer consumers the desired consequences and which help them obtain central life values. A means-end chain approach to product development is therefore expected to affect areas central to successful market oriented product development. These areas are identified in the following paragraph. Succesful market-oriented NPD The understanding of customer needs with the purpose of supplying superior customer value is central both to market orientation (Jaworski and Kohli, 1996; Narver et al., 1998) and to new product development (Cooper and Kleinschmidt, 1995; Griffin and Hauser, 1993; Zirger and Maidique, 1990). Most definitions of market orientation include reference to both the use of market information and inter-functional coordination. Market oriented new product development can, with inspiration from Kohli and Jaworski (1990) be defined as: “The development of new products, which is based on the generation of market information, the dissemination of the information across departments and responsiveness of various departments to it”(Biemans and Harmsen, 1995). The use of market information in NPD One of the primary goals of the collection and use of market information in NPD is the identification of customer preferences (Moore, 1987). Empirical studies show that within market orientation customer focus is central to the success of innovation (Han et al., 1998; Lukas and Ferrell, 2000). However, there is still much to learn about the role of market information in product development (Hart et al., 1999). In their study, Ottum and Moore (1997) show that the use of market information has a direct positive effect

Figure 1. MEC for apples

on new product success, and they stress the importance of using the information effectively. Market information may be used in different ways in connection with product development: either instrumentally (the use of information for decision-making, implementation and evaluation of decisions), or conceptually (the information is valued and the company has processes for converting information to knowledge) (Moorman, 1995). The barriers inhibiting market orientation are many and complex (Bisp, 2000). In their study, Adams et al. (1998) find that some of the barriers can be overcome by broadening the functional participation in acquiring, interpreting and using market data. Furthermore, the collected data should be vivid and in a language that users can understand (Adams et al., 1998).

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Inter-functional integration in NPD The relationship between functions, especially R&D and marketing, in product development has been the interest of a large body of literature in NPD (Dougherty, 1992; Griffin and Hauser, 1992; Griffin and Hauser, 1996; Gupta and Wilemon, 1988; Gupta and Wilemon, 1990; Moenaert and Souder, 1996; Souder, 1981, 1988). Although the literature agrees that integration is a question of both communication and cooperation, there has been no uniform way of analysing the concept. This is criticised by Kahn (1996, 2001) who shows that, although communication is essential to integration, it is collaboration, which correlates with success. Integration between R&D and marketing is primarily important in the early stages of the development process (Olson et al., 2001). The barriers to integration identified by Gupta et al. (1985) can be overcome by promoting mutual understanding, encouraging teamwork, by being more responsive to market needs and by improving marketing research (Gupta and Wilemon, 1990). The two areas, the use of market information and inter-functional integration, may be interconnected since the use of market information is seen as a way of overcoming the barriers of integration and vice versa. The way in which the factors are expected to be influenced by a means-end approach and in turn affect successful new product development is illustrated in Figure 2.

Figure 2. How the MEC approach is expected to influence NPD

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Due to the way MEC data is collected and to the nature of the data, it seems an adequate instrument for influencing the use of market information and inter-functional integration. MEC data supplies information about consumer attitudes on three levels of abstraction: attributes, consequences and values. In order to develop products with superior value for customers, it is important for the NPD team to be aware of the motivations that lie behind consumer preferences (Griffin and Hauser, 1993; Gutman, 1982; Moore, 1987). Furthermore, since MEC data are presented in the words of the consumers they are easily understood by all members of the development team, which is essential for the cross-functional communication and integration of activities in the development process (Adams et al., 1998; Gupta et al., 1985). Research method The research method for the project is a case study approach with an element of action research where I as a researcher participate in the initiation of a change process or intervention (Grønhaug and Olson, 1999). The “means-end chain-intervention” in the project involves the collection of MEC data, which are made available to the product development team in the case company. Prior to the development task, team members are interviewed about NPD routines in the company. When the project has been concluded they are interviewed again about their experience with using MEC data in the development process. The action research process is illustrated in Figure 3. In the MEC-intervention, MEC data are made available to the product development team for a specific NPD project. First, the team was introduced to the means-end chain theory and how this theory allegedly conveys links between attributes, consequences and values in the consumers mind. Concurrently, MEC data were collected for the chosen NPD project. Then the data were introduced to the development team for the development of product concepts. After the MEC-intervention, team members were interviewed about their experiences with the MEC approach in the process of developing product concepts for the specific project. The interview guide for the final interviews was developed on the basis of a literature review focusing on market information and inter-functional integration in product development. The guide is shown in Table I. This paper draws on empirical evidence from one case study in which MEC data was collected and made available to a new product development team, which represented both marketing and technical development. The study is part of a project conducted in cooperation with a Danish food manufacturer with the purpose of developing nutritious frozen products for children based on organic vegetables. The collection of MEC data took place in two different phases of the development process. The first round of MEC data collection was carried out during the early stages of the development process in order to give the development team initial material to work

Figure 3. The phases of the action research process

Market-oriented NPD

The use of market information Attitudes to market information: What do you think of the information in the hierarchical value maps (commitment, recognise the value)? Are they understandable (relevance, credibility, comprehensibility)? Did you feel like using it? The use of market information: How did you use the information? Directly/instrumental use (in connection with decision making, implementation and evaluation of decisions)? Indirectly/conceptual use (by conversion of information into knowledge and understanding)

Moenaert and Souder (1996); Adams et al. (1998); Moorman (1995)

83 Moorman (1995)

Inter-functional integration Communication between functions: Has the information been used in the communication between R&D and marketing (how)? What effect has the information had? What type of information has been exchanged? Cooperation between functions: How did the cooperation between R&D and marketing take place during the project (the role of the information)? Teamwork, shared vision, mutual understanding, shared knowledge and resources? Co-ordination of tasks: How has the co-ordination been between the development of the product, advertising, packaging etc.?

Kahn (1996); Griffin and Hauser (1992)

Gupta et al. (1985); Kahn (1996, 2001)

Griffin and Hauser (1992)

with. The second round of MEC data collection was designed as a test of the product concepts, developed by the team. The MEC data was achieved by conducting laddering interviews, which is the most common way of collecting MEC data (Grunert and Grunert, 1995; Reynolds and Gutman, 1988). A total of 30 respondents participated in each round of data collection. The software programme Ladder Map was used to develop the hierarchical value maps (HVM) from the coded interviews. Design and results of the MEC data collection in the case company Drawing on initial focus group interviews with children and parents, six broad meal categories were identified for the first round of MEC data collection. Respondents, who were parents of children aged 2-14, were first asked to rank and then generate ladders for the following six descriptions of food categories, all based on organic vegetables:

Table I. Guide for the post-intervention interviews

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(1) (2) (3) (4) (5) (6)

frozen side dish for the family; fresh side dish for the family; frozen side dish for children; frozen ready-made dish for children; frozen snack for children; and fresh snack for children

One of the meal categories that the respondents ranked highest in the first round of data collection was “frozen side dish for the family” (see Figure 4 for the hierarchical value map for this category). As can be seen from the HVM, parents perceive this type of product in a positive manner due to the fact that it is a side dish for the whole of the family and not just the children. Furthermore, it is easy to prepare and it is possible to serve the same food product for the whole family instead of having to prepare separate food for the children. This is important for the manner in which parents wish to bring up their children regarding food and meals. After data collection and analysis, the six hierarchical value maps from the collected MEC data were introduced to the development team, which were to develop new product ideas. The team came up with seven different product concepts; one of these was “Indian mix”, a product based on frozen rice with peas, corn and carrots. The seven concepts were used in the second round of MEC data collection where the respondents were asked to rank a number of products showed to them as pictures (see Figure 5 for an example). The HVM showing parents’ perceptions of “Indian mix” is shown in Figure 6. The HVM shows that parents perceived it as a negative attribute that the product was frozen. At the same time, the perception of the ingredients was positive, which is important for good taste and for the desire to eat. The central consequences are good

Figure 4. Hierarchical value map for “frozen side dish for family”

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Figure 5. Indian mix

Figure 6. Hierarchical value map for Indian mix

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health and healthy eating habits, which give energy, make one able to do well in life and are important for one’s quality of life. After considerations about economic feasibility and strategic fit of the “Indian mix” with the company’s other products, the participating company decided not to launch the product. However, other product concepts, which received better evaluations, are still in the refining process and will be launched within a year. The “Indian mix” product serves as an example of the HVMs and their use in the development process. Results and implications The final interviews with members of the development team show that the MEC intervention clearly led the team to use the available information on consumer motivations as inspiration for the development of product concepts. Furthermore, the instrument gave the teams a very good basis for discussion during project meetings and it helped to maintain development goals clear and fixed. The effects of the first round of MEC data collection are shown in Figure 7. The team members expressed a high degree of satisfaction with the information from the first round of MEC data collection. Regarding the second round of MEC data collection, the team preferred that the respondents had been able to taste prototypes of the developed concepts. This indicates that, when using a means-end approach for product development in the food industry, it may be advantageous to have the respondents taste the product. It was clear from the interviews with the team members that the results from the first round of MEC data collection were used to a much larger extent than results from the second round. The team indicated that, since the hierarchical value maps from the second round of data collection (based on product concepts) supplied information at a different level of abstraction, the information gave little further inspiration to the development process and would have been more useful for the design of communication and advertising. This result is consistent with our

Figure 7. Empirical results of the MEC intervention

expectations regarding the utility of the MEC-approach in product development, which is expected to be highest for the early phases of the development process where ideas are generated and concepts developed at a more abstract level. The means-end chain approach shows clear advantages for market oriented product development. Product developers perceive the MEC data presented in HVMs as easily accessible information about consumer perceptions regarding product attributes and perceived consequences. They understand that negative consequences identified by consumers should be avoided while the positive should be emphasized as suggested by MEC literature (Reynolds and Whitlark, 1995). The information in the hierarchical value maps can trigger discussions about the goals of the development process and can help keep the project on track. It could prove useful to develop an appropriate design for data collection in the food industry taking into account its special demands regarding the development process knowing that taste is paramount. Without the element of taste, the MEC approach as a concept test is only useful for indications of initial purchase. For repeated purchase, it is necessary to include tasting in the design. The MEC intervention was unable to secure that the NPD process took place in a collaborative manner. The organisational structures and routines regarding the new product development process are crucial for the extent of collaboration and are difficult to influence. This points towards a possible analysis of the effects of a MEC-intervention with an organisational learning perspective, where the company’s degree of orientation towards learning or willingness to change mediates the influence a means-end approach may have on product development (Baker and Sinkula, 1999). A learning orientation; defined as commitment to learning, shared vision, open-mindedness and intra-organisational knowledge sharing in Calantone et al. (2002) has proved to affect both firm innovativeness and firm performance. A possible way of illustrating the role of learning orientation in this study can be seen in Figure 8 where the learning orientation acts as a mediator on the way the MEC-intervention affects the use of market information and inter-functional integration and on the way these factors affect successful product development.

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Figure 8. The possible effect of a learning orientation on a MEC intervention

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It is important for further research in enhancing market oriented product development by means of a MEC-approach to take into account that the changes, which most likely will take place in central areas, may be dependent on the learning orientation of the company. A certain willingness to change may be a prerequisite for the successful implementation of the instrument. It would be relevant to look further into the literature on the effects of learning orientation on “change projects” in companies. It is also important for companies to be aware of the limited effects of a MEC approach to product development (or other instruments) if the company as a whole or certain functions are unwilling to accept changes to the daily routines. This should not deter the companies from initiating changes only make them aware of the importance of the company’s willingness to change and learning orientation.

References Adams, M.E., Day, G.S. and Dougherty, D. (1998), “Enhancing new product development performance: an organizational learning perspective”, Journal of Product Innovation Management, Vol. 15, pp. 403-22. Baker, W.E. and Sinkula, J.M. (1999), “The synergistic effect of market orientation and learning orientation on organizational performance”, Journal of the Academy of Marketing Science, Vol. 27 No. 4, pp. 411-27. Biemans, W.G. and Harmsen, H. (1995), “Overcoming the barriers to market-oriented product development”, Journal of Marketing Practice: Applied Marketing Science, Vol. 1 No. 2, pp. 7-25. Bisp, S. (2000), “Barriers to increasing market-oriented activity”, PhD dissertation, Aarhus School of Business, Aarhus. Calantone, R.J., Cavusgil, S.T. and Zhao, Y. (2002), “Learning orientation, firm innovation capability, and firm performance”, Industrial Marketing Management, Vol. 31, pp. 515-24. Cooper, R.G. and Kleinschmidt, E.J. (1995), “Benchmarking the firm’s critical success factors in new product development”, Journal of Product Innovation Management, Vol. 5 No. 12, pp. 374-91. Dougherty, D. (1992), “Interpretive barriers to successful product innovation in large firms”, Organization Science, Vol. 3 No. 2, pp. 179-202. Griffin, A. and Hauser, J.R. (1992), “Patterns of communication among marketing, engineering and manufacturing – a comparison between two new product teams”, Management Science, Vol. 38, pp. 360-73. Griffin, A. and Hauser, J.R. (1993), “The voice of the customer”, Marketing Science, Vol. 12 No. 1, pp. 1-27. Griffin, A. and Hauser, J.R. (1996), “Integrating R&D and marketing: a review and analysis of the literature”, Journal of Product Innovation Management, Vol. 13 No. 3, pp. 191-215. Gronhaug, K. and Olson, O. (1999), “Action research and knowledge creation: merits and challenges”, Qualitative Market Research, An International Journal, Vol. 2 No. 1, pp. 6-14. Grunert, K.G. and Grunert, S.C. (1995), “Measuring subjective meaning structures by the laddering method: theoretical considerations and methodological problems”, International Journal of Research in Marketing, Vol. 12, pp. 209-25. Grunert, K.G. and Valli, C. (2001), “Designer-made meat and dairy products: consumer-led product development”, Livestock Production Science, Vol. 72, pp. 83-98.

Gupta, A.K. and Wilemon, D. (1988), “The credibility-cooperation connection at the R&D marketing interface”, Journal of Product Innovation Management, Vol. 5, March, pp. 20-31. Gupta, A.K. and Wilemon, D. (1990), “Improving R&D/marketing relations: R&D’s perspective”, R&D Management, Vol. 20 No. 4, pp. 277-90. Gupta, A.K., Raj, S.P. and Wilemon, D. (1985), “The R&D marketing interface in high technology firms”, Journal of Product Innovation Management, Vol. 2, pp. 12-24. Gutman, J. (1982), “A means-end chain model based on consumer categorization processes”, Journal of Marketing, Vol. 46 No. 2, pp. 60-72. Han, J.K., Kim, N. and Srivastava, R.K. (1998), “Market orientation and organizational performance: is innovation a missing link?”, Journal of Marketing, Vol. 62, pp. 30-45. Hart, S., Tzokas, N. and Saren, M. (1999), “The effectiveness of marketing information in enhancing new product success rates”, European Journal of Innovation Management, Vol. 2 No. 1, pp. 20-35. Henard, D.H. and Szymanski, D.M. (2001), “Why some new products are more successful than others”, Journal of Marketing Research, Vol. 38 August, pp. 362-75. Jaworski, B.J. and Kohli, A.K. (1996), “Marketing orientation: review, refinement, and roadmap”, Journal of Market-Focused Management, Vol. 1 No. 2, pp. 119-36. Kahn, K.B. (1996), “Interdepartmental integration: a definition with implications for product development performance”, Journal of Product Innovation Management, Vol. 13, pp. 137-51. Kahn, K.B. (2001), “Market orientation, interdepartmental integration, and product development performance”, Journal of Product Innovation Management, Vol. 18 No. 5, pp. 314-23. Kohli, A.K. and Jaworski, B.J. (1990), “Marketing orientation: the construct, research propositions, and managerial implications”, Journal of Marketing, Vol. 54, April, pp. 1-18. Lukas, B.A. and Ferrell, O.C. (2000), “The effect of market orientation on product innovation”, Journal of the Academy of Marketing Science, Vol. 28 No. 2, pp. 239-47. Moenaert, R.K. and Souder, W.E. (1996), “Context and antecedents of information utility at R&D/marketing interface”, Management Science, Vol. 42 No. 11, pp. 1592-610. Montoya-Weiss, M.M. and Calantone, R. (1994), “Determinants of new product performance: a review and meta-analysis”, Journal of Product Innovation Management, Vol. 11, pp. 397-417. Moore, W.L. (1987), “New product development practices of industrial markets”, Journal of Product Innovation Management, Vol. 4, pp. 6-19. Moorman, C. (1995), “Organizational market information processes: cultural antecedents and new product outcomes”, Journal of Marketing Research, Vol. 32, August, pp. 318-35. Narver, J.C., Slater, S.F. and Tietje, B. (1998), “Creating a market orientation”, Journal of Market-Focused Management, Vol. 2 No. 1, pp. 241-55. Olson, J.C. and Reynolds, T.J. (1983), “Understanding consumers’ cognitive structures: implications for marketing strategy”, in Percy, L. and Woodside, A.G. (Eds), Advertising and Consumer Technology, Lexington Books, Lexington, MA. Olson, E.M., Walker, J.O.C., Ruekert, R.W. and Bonner, J.M. (2001), “Patterns of cooperation during new product development among marketing, operations and R&D: implications for project performance”, Journal of Product Innovation Management, Vol. 18, pp. 258-71. Ottum, B.D. and Moore, W.L. (1997), “The role of market information in new product success/failure”, Journal of Product Innovation Management, Vol. 14, pp. 258-73.

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Reynolds, T.J. and Craddock, A.B. (1988), “The application of the MECCAS model to the assessment of advertising strategy”, Journal of Advertising Research, Vol. 29, pp. 43-54. Reynolds, T.J. and Gutman, J. (1988), “Laddering theory, methods, analysis, and interpretation”, Journal of Advertising Research, Vol. 18 No. 1, pp. 11-31. Reynolds, T.J. and Whitlark, D.B. (1995), “Applying laddering data to communications strategy and advertising practice”, Journal of Advertising Research, July/August, pp. 9-17. Souder, W.E. (1981), “Disharmony between R&D and marketing”, Industrial Marketing Management, Vol. 10, pp. 67-73. Souder, W.E. (1988), “Managing relations between R&D and marketing in new product development projects”, Journal of Product Innovation Management, Vol. 5, pp. 6-19. Valli, C., Loader, R.J. and Traill, W.B. (1999), “Pan-European Food market segmentation: an application to the yoghurt market in the EU”, in Kaynak, E. (Ed.), Cross-national and Cross-cultural Issues in Food Marketing, Haworth Press, New York, NY, pp. 77-99. Walker, B.A. and Olson, J.C. (1991), “Means-end chains: connecting products with self”, Journal of Business Research, Vol. 22 No. 2, pp. 111-9. Zirger, B.J. and Maidique, M.A. (1990), “A model of new product development: an empirical test”, Management Science, Vol. 36 No. 7, pp. 867-83.



Innovation projects in Israeli incubators

Israeli incubators

Categorization and analysis Bernard Kahane

91

Institut Supe´rieur de Technologie et Management (ISTM), Cite´ Descartes, Noisy le Grand, France, and

Tzvi Raz Faculty of Management, Tel Aviv University, Ramat Aviv, Israel Abstract Purpose – Based on an Israeli innovation incubators program, aims to describe a procedure to define relevant categories in order to reduce the complexity of representing the population of projects supported by an innovation program in a meaningful way. Design/methodology/approach – Provides a concise description of the Israeli innovation incubators program and presents the characteristics of the data available. Introduces the analysis methodology and describes in detail its application to the specific data set and the classification scheme that it induces. Discusses the information that can be obtained based on this classification, and outlines some policy implications. Concludes with remarks regarding possible applications and extensions of the methodology. Findings – Finds that the classification induced by the iterative category exclusion (ICE) procedure can serve as the basis for more sophisticated analysis using statistical tools such as regression analysis. Once the relevant categorization is obtained, it becomes easier to collect meaningful data about incubator performance for analysis at various levels of aggregation. The ICE procedure has the advantage that it does not give a priori preference to any category or to any relationship between categories, and does not require a priori identification of the categories that are to be kept and those that are to be deleted. Further, it does not need to classify categories under headings such as “scientific and technological” on the one side, and “sector applications” on the other. Both are seen as equal from the beginning to the end and thus avoid any bias in the process. The subjectivity inherent in the selection process is reduced, perhaps even eliminated. The same values provided the basis for the identification and quantification of overlap and proximities between the final categories, throwing some light on their mutual dependencies and interactions and leading to a level of representation from which strategic assessment and thinking can start. Originality/value – The core principle of ICE is to eliminate categories that do not convey sufficient information to justify the additional complexity. This principle is universal and can be applied to a wide variety of situations that suffer from too much data and not enough information. Keywords Incubators, Classification, Innovation, Israel Paper type Case study

Introduction Assessment of government innovation policy and programs is a valuable way of providing knowledge to decision makers and constituencies that will improve Partial support for this research was provided by the Henry Crown Institute for Business Research in Israel and by a European Community Marie Curie Fellowship (http://www.cordis.lu/ improving). Disclaimer: The authors are solely responsible for the information communicated and the European Commission is not responsible for any views or results expressed.


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performance. Often, because innovation is about exploring and exploiting what emerges and is not yet known, the categorization of the activities being assessed is a difficult task. Thus, innovation programs rapidly give rise to a proliferation of entities that do not fit prior categorization established by operators of a specific government innovation scheme. Quite often, as innovation programs develop and the nature of the projects they support evolves, it becomes increasingly difficult to understand what is actually being supported, how and why. As any evaluation professional knows, with a blurred picture and improper categorization it becomes virtually impossible to gain any meaningful understanding of what has happened and is happening, the results achieved, or what should/could be improved, how and where. Thus, innovation scheme operators start to rely on instinct, assumptions, personal representation and decision that are taken more on a power regulation basis than on a shared rationale based on a common and robust data representation. Projects supported by innovation schemes show a tendency to proliferate and multiply in terms of the underlying science and technology, on the one hand, and the industrial and commercial applications, on the other. At the same time, categories created and used by innovation scheme operators expand as well, to the point where they become too numerous and lose a great deal of their interest. To be sure, an individual project can always be located by using keyword analysis and search engines (e.g. find all projects in a certain program that are at the crossroads of biotechnology, electronics, diagnostic tools, medical instrumentation). Nevertheless, the aggregated representation needed for assessment and strategic decision-making becomes increasingly difficult since categorization-overlap patterns differ from one project to the other without any possibility of knowing what the relevant overlaps are and how important they are for each category. Thus, looking at the range of all projects supported, innovation program operators often face databases that contain a lot of data but do not provide the simplified relevant information needed for program assessment and strategic decision-making. This means that data on characteristics and performance can only be provided at the global level of the whole population of projects ($X million of capital valuation, Y jobs created, a Z percent rate of sustainable projects, etc.) or at the level of the individual project (project P succeeded, reached a valuation of $Q million and created R jobs, etc.) with nothing at the intermediate level. It is difficult if not altogether impossible to assess the performance of a project sub-population in a specific category in relation to another without having a meaningful, exhaustive and mutually exclusive framework for classifying projects. Thus, quite often, databases used to monitor projects become the computerized equivalent of matrices with very large rows and columns of various sizes, making it difficult to focus attention on the key entities and relationships of the program. The identification of characteristics that will allow clustering of projects and the analysis of relevant overlaps and proximities between them is a key issue. This will contribute to reducing the complexity of the representation of reality and help strategic assessment and decision-making. There are of course numerous clustering techniques and algorithms in the literature. However, each domain of human activity has its own idiosyncrasies and these preclude the direct application of standard techniques. In this paper, we use the Israeli innovation incubators program to describe an approach to defining relevant categories in order to reduce the complexity of

representing a population of projects supported by an innovation program in a meaningful way. The approach relies on an exclusion methodology, where categories are withdrawn in an iterative manner, taking into account how much information is kept or deleted from the database at each step. Using this approach, out of 461 projects listed originally in 33 scientific/technological and industrial/commercial application categories, defining 1,239 listings (since most of the projects are listed in more than one category), we identify the six out of the 33 categories that allow for a simplified and meaningful classification of all the projects and then demonstrate that these categories show minimal overlap. We then use this categorization to test the possible field specialization of incubators and assess their relative performance using project graduation rate as an indicator. This paper is organized as follows. Following a concise description of the Israeli innovation incubators program in the next section, we present the characteristics of the data available. Then, we introduce the analysis methodology and describe in some detail its application to the specific data set and the classification scheme that it induces. Next, we discuss the information that can be obtained based on this classification, and outline some policy implications. We conclude with remarks regarding possible applications and extensions of the methodology. The Israeli innovation incubators program Incubation is a concept aimed at assisting the growth of entrepreneurial firms through a dedicated facility providing subsidized space, consultation and other relevant aids. Although it originated in the US, incubation is now a worldwide phenomenon that has spread to countries as diverse as the UK, France, Sweden, Italy, the Philippines, China and Brazil (Rice and Matthews, 1995; Kalis, 2001). For cultural and strategic reasons, individuals, organizations and communities in Israel have long promoted knowledge as a basis for individual and collective survival as well as for their economic sustainability and growth. After a serious economic crisis at the beginning of the 1980s, Israel decided to make a concerted effort to improve the realization of its science and technology potential, which until then had been largely the domain of its seven main internationally recognized universities and research centers, with the business arena being excluded for the most part. The centralized and powerful Office of the Chief Scientist (OCS) was established for this purpose at the Ministry of Trade. Gradually the OCS managed to increase its legitimacy, resources, power and influence (Mani, 2002). The innovation programs it established over the years were associated with individual industrial R&D grants (Justman and Zuscovitch, 2002), financial venture capital emergence (Avnimelech and Teubal, 2002), R&D consortia and incubators. Government intervention through its OCS branch is seen as having been a crucial factor in boosting the performance of the Israeli economy (Trajtenberg, 2001) up to the end of year 2000, before the outbreak of the current violence in the Middle East, the crash of the NASDAQ and the September 11, Twin Towers attack. Indeed, in the 15 years prior to 2000, Israel had transformed itself from a mainly agriculture collective economy into a high-tech export-oriented entrepreneurial one and had established itself as one of the world’s leading high-tech powerhouses. The Israeli innovation incubators program was adapted from the experience of other countries, mainly the US due to the strong cultural and strategic links between

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the two countries. As implemented, the program has shown a strong specificity and homogeneity, both in its content and its rules of implementation. It was established in 1990, not only as one of the different and complementary OCS schemes aimed at fostering innovation but also as a possible answer to immigration needs and to local development problems in peripheral areas. From 1990 to 2000, more than one million people came to Israel from the ex-USSR (200,000 in the first two years, and more than 70,000 on average per year over the next eight years). This resulted in a population increase of 20 percent and in a doubling of Israel’s per capita ratio of scientists and engineers, already one of the highest in the world, from 70/10,000 to 140/10,000 (compared to 77/10,000 in the US and 73/10,000 in Japan). Dealing with this massive influx of highly skilled scientists and technologists was perceived as much a problem as an opportunity, and the innovation incubators program, although not restricted to Russian immigrants, was one of the answers provided. It aimed at providing managerial and commercial help as well as training to people who lacked these skills and often even knowledge of the rules and ways of a capitalist economy, but who, on the basis of their scientific and technical knowledge, had developed an idea that could potentially translate into commercially valuable products. Further, as Israel is isolated from its neighbors and still building itself, the development of peripheral areas is a challenge with not only economic implications but demographic and strategic ones as well. Thus, setting up incubators in these areas became a complementary goal of the program. It was seen as a way to help settle the Russian immigration in the peripheral areas to be developed rather than the already over-populated three main urban centers, Te Aviv, Jerusalem and Haifa. From its establishment in 1990 up to the year 2000, about $250 million were spent by the OCS in the incubators program, with a fairly stable annual budget in the last years of about $30 million. At the start of the program, the OCS selected proposals from those who wanted to establish and run an incubator, following a bottom-up approach. Proponents of a selected incubator would have to put together the relevant infrastructure, a management team and an executive board of non-paid professionals, and would be entitled to $175,000/year of government support ($50,000 more in peripheral areas) to cover their administrative costs. They had to be independent non-profit entities, would be able to receive support from additional sources beside the government and would get up to 20 percent of the share of the incubated companies, to be supplemented with additional funding if they wished. All of the incubators were established in the first three years of the program, the last one in 1992. A management team of six persons on the average manages between ten and 20 projects per year. As projects have to prove their viability in less than two years, that makes five-ten new projects entering each year. Since the program was established, the OCS has closed three incubators, and 24 are currently in operation. They are located throughout the country, from the Tel Aviv central area to the proximity of the Lebanese border in the north and the Negev desert area in the south. The program emphasizes high-tech developments and exports rather than research centers, and has no predetermined scientific/technological or industrial sector preferences. Incubators may specialize as they see fit, but in practice, with two exceptions – one in biotechnology and another in software – very few have chosen to do so. The focus on the Russian newcomer population has progressively decreased as immigrants have integrated into mainstream Israeli society.

The performance of the innovation incubators program is still an open issue, particularly because few indicators of performance are available other than project graduation rates. On the one hand, it can be said that the incubators have provided job opportunities with valuable in situ business and commercial training as well as networking resources when a specific population needed them and when financial capabilities in the local economy were nearly non-existent. Further, one should not forget that the incubator program was initiated to foster the sustainable integration of Russian immigrants with scientific and technological skills but poor language proficiency and no business experience. On the other hand, economic performance of projects, whether in terms of job creation or exports, is still being debated and is probably very much related to the performance of specific incubators. This may have been behind the drive of the OCS to make the incubator program evolve as it has done, through the privatization of some incubators – three to five as a first prototype step, flexibility and proportionality in equity distribution, increased support for projects in peripheral incubators, the creation of the new biotechnology-specific incubators, etc. Overall, by the end of the year 2000, that is, before the international high-tech crisis, exacerbated locally by the violent regional conflicts of the Middle East and by international terrorism, OCS claimed that 52 percent of incubator projects had attracted third-party investment and survived two years or longer after leaving the incubator and more than $500 million had been poured into incubator and incubator “graduate” projects. In parallel, 1900 jobs were registered in firms surviving outside the incubators, to which 900 in projects inside the incubators themselves can be added (OCS – Office of the Chief Scientist, 2000). However, performance breakdown by sector or by incubator does not appear in the OCS publication. Data set The data for the analysis reported here was obtained from an OCS publication (OCS – Office of the Chief Scientist, 2000), which includes all incubators and all projects since the beginning of the program. It covers 24 incubators with 461 projects, exclusive of projects that were abandoned before completing the two-year incubation period. The OCS classifies projects according to 33 categories, pertaining to both scientific/technological fields and industrial/commercial application areas. For its own purposes, the OCS classified each project into one or several categories, according to its technical and commercial characteristics. In this analysis we will use the term “listing” or “project listing” to refer to any given instance of a specific project being classified under a specific category. Most of the projects had multiple listings, for a total of 1,239 listings, or about 2.69 listings per project on the average. The OCS classification scheme had the additional shortcoming that it lacked a distinction between the principal (most dominant) classification and the secondary ones. As a result, all listings of any given project appear to be of equal importance and relevance, making it difficult to identify its main thrust. The breakdown of the 1239 listings across the 33 categories appears in Table I. Table I shows none of the categories accounts for more than 8 percent of the listings. Further, the number of categories is greater than the number of incubators, impairing any attempt to look at specialization in relation to incubators. Thus, this classification of projects does not elicit any preferential category that can be used to drive an analysis of the program’s performance. The existence of numerous redundant and

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Table I. Breakdown of project listings across categories

Project category Agrobiotechnology Automation, robotics Biotechnology Ceramic, glass Chemistry Coating Communication Computers – courseware Computers – hardware Computers – software Construction Diagnostics Electricity and electromechanics Electro-optics, Optics, Lasers Electro-chemistry Electronics Energy Environment Food processing, beverages Health care Instrument, measurement, testing Materials Mechanical engineering Medical instrumentation Metal treatment Pharmaceutics, cosmetics Quality control Safety, security Sport, recreation Textile industry Thermodynamics, heat exchange Traffic Voice and image processing Total

Number of listings

Percent of listings

54 21 88 16 89 21 37 8 10 72 13 29 18 46 29 80 15 40 25 94 42 63 75 80 10 36 11 29 10 3 27 21 27 1,239

4 2 7 1 7 2 3 1 1 6 1 3 1 3 3 6 1 3 2 8 3 5 6 6 1 3 1 2 1 1 2 1 3 1

overlapping categories blurs the picture of incubator activity and thus induces perception complexity. It is also difficult to address questions such as: . Which are the most dominant categories? Which categories are more likely to result in project success (i.e., graduation from the incubator)? . Is there any type of affinity or proximity among the various categories? . Are some incubators more specialized than others? Does specialization affect the project success rate? Dealing with research questions such as those listed above would have been much easier if each project had a single listing into the category that best describes its nature. In fact, out of the 461 projects 44, or slightly less than 10 percent, were single listing projects (SLPs). Based on the information provided by the OCS report it is not possible to determine, for each project with more than one listing, which category is the

dominant one. However, had there been fewer categories to start with, the same number of projects would have yielded a larger proportion of SLPs, improving our ability to analyze the data. This argument provides the basis for the categorization methodology that will be presented in the following section.

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Iterative category exclusion Seeking to reduce the number of categories used to classify the projects in order to increase the proportion of SLPs among the 461 projects in the data set, we made a preliminary analysis of the correlation among categories, which failed to produce any significant patterns that could have supported the merging of related categories. Consequently, rather than merging categories our approach consists of eliminating categories while minimizing the loss of information about the projects. The larger the number of SLPs in a given category, the more informative it is, and the larger the loss of information (in terms of projects that will remain unclassified) that will result from its exclusion. Thus, it appears reasonable to exclude from the classification those categories in which the number of SLPs is zero or very small. Of course, as the exclusion of any given category from the data set may affect the distribution of SLPs among the remaining categories, the exclusion analysis has to be done in an iterative manner. At each iteration, we calculate the number of SLPs for each of the remaining categories in the data set, and identify the category to be excluded as the one with the smallest number. Any SLPs that belonged to that category are reclassified as belonging to a generic category called “Other”. The cumulative number of projects classified as “Other” is a measure of the amount of information lost during the process, and may be used to determine the point at which any further category exclusion will seriously affect the value of the data set. Table II shows the application of the iterative category exclusion (ICE) procedure to our data set. The first two columns on the right of the iteration sequential number respectively show the smallest number of SLPs by category present in the data set at that iteration and the name of the corresponding category. In the case of a tie, the category with the smallest total number of listings was selected. For example, at the first iteration there were several categories with no SLPs, but “Textile industry”, had the smallest number of listings (3). Once that category was removed, the total number of listings dropped from 1,239 to 1,236, as shown in the next column to the right. The remaining columns in Table II show the total number of SLPs in the data set and the cumulative loss of information, in terms of number and percentage of projects classified as “Other”. It is interesting to note that the number of SLPs increased steadily as the iterations progressed, with a concurrent reduction in the total number of listings. We chose to stop the process when the cumulative number of projects classified as “Other” reached 15 percent of the total number of projects (iteration 27), which we felt was the upper limit on the loss of information that we were willing to accept. Further, continuing beyond that iteration would have resulted in a major jump in the number of projects classified as “Other” – another 40 in addition to the 67 projects that already resulted from the first 27 iterations. After the 27th iteration 309 projects were SLPs, or about 78 percent of the 394 projects that were not classified as “Other”, compared to 0 percent at the beginning of the process. There were only five projects with three listings each and 80 projects with two listings. The average number of listings per project, exclusive of

97

0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 2 2 3 4 5 7 8 9 10 13 40

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

Table II. Summary of ICE procedure

Iteration Textile industry Computers – courseware Computers – hardware Metal treatment Sports recreation Quality control Construction Automation, robotics Coating Food processing, beverages Thermodynamics, heat exchange Diagnostics Pharmaceutics, cosmetics Communication Traffic Materials Energy Electricity and electro-mechanics Safety-Security Voice and image processing Environment Ceramic glass Electro-optics, optics, laser Agrobiotechnology Health care Electro-chemistry Instrumentation, measurement, testing Electronics

Category with smallest number of SLPs 3 8 10 10 10 11 13 21 21 25 27 29 36 37 21 63 15 18 29 27 40 16 46 54 94 29 42 80

Number of listings in category 1,236 1,228 1,218 1,208 1,198 1,187 1,174 1,153 1,132 1,107 1,080 1,051 1,015 978 957 894 879 861 832 805 765 749 703 649 555 526 484 404

Number of remaining listings (except “Other”) 44 44 48 49 50 54 55 58 65 71 74 83 86 101 116 120 149 153 157 164 176 193 195 212 238 290 295 309

Total number of SLPs 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 4 6 8 11 15 20 27 35 44 54 67 107

Cumulative number of projects in “Other”

98

Smallest number of SLPs by category

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.22 0.43 0.87 1.30 1.74 2.39 3.25 4.34 5.86 7.59 9.54 11.71 14.53 23.21

Percent of projects in “Other”

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“Other”, is 484=394 ¼ 1:24, down from 1; 239=461 ¼ 2:69 prior to the analysis. These statistics are indicative of the improvement in clarity of the data set that was obtained with the ICE procedure. Table III presents summary statistics of the six original categories that remained when the ICE procedure was stopped. From Table III we can see that the ICE procedure generated a fairly balanced classification of the projects into categories of roughly equal size. It is also notable that the extent of overlap among the six final categories is quite small. This fact can be appreciated from Table IV which shows, for each pair of categories, the extent of overlap measured as the fraction of projects classified into both categories out of the total number of projects classified by either one. For example, there were 12 projects classified as both Chemistry and Biotechnology and 165 classified as either Chemistry or Biotechnology. The extent of overlap was calculated as12=165 ¼ 0:0727 < 0:07, as shown in the first row, second column of Table IV. Findings In this section we will indicate some of the main findings that emerge from the analysis of the data based on the reduced set of classification categories. Program focus By examining the distribution of projects and SLPs across the six categories, as shown in Table III, we note that about one third of the innovation activity involved projects in either Chemistry or Biotechnology, while there is only about one sixth in Electronics, a field in which about 78 percent of Israel’s national expenditure on R&D is invested, and about another sixth in Computer software, which represents about half of Israel’s high-tech exports. Thus, it appears that the distribution of incubator activity does not mirror the distribution in the national economy at large. This finding can be interpreted as follows. Chemistry and Biotechnology are part of the broader field of Life science and technology, which is inherently high risk due to health-related regulation, very large investments and relatively long-term returns. Projects in this area will have had difficulties obtaining venture capital funding and will therefore have come to incubators. On the other hand, at least during the period of time covered by the data set, projects in Electronics and computer software will have found it easier to find venture capital funding and consequently will have had a weaker incentive to operate within the confines of a government program. Thus, we could argue that the distribution of incubator projects complements that in the private sector, and that in a sense incubators “level the playing field” for projects in areas with inherent difficulties. One may also note that the relative importance of Chemistry and Biotechnology may mirror their strong presence in public research compared to their relative weakness in industry, indicating a strong connection of incubators with academic research potential. Another interesting observation that can be drawn from Table III pertains to the proportion of SLPs out of the total number of listings for each category. In each category, with the exclusion of Electronics, about two-thirds of the projects are SLPs, implying that their major and possibly only focus is within their own specific category. Electronics is the single instance of a category with a proportion of SLPs of 50 percent, implying that the other 50 percent of the projects had some significant, perhaps even

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Table III. Data summary after the 27th iteration 58 89 65 16 18

63 88 65 16 18

Biotechnology 40 80 50 15 16

Electronics

49 80 61 15 16

Medical instrumentation

53 75 70 14 15

Mechanical engineering

46 72 64 13 15

Computer software

100

SLPs Total number of listings SLPs as percent of total number of listings Percent of listings Percent of listings excluding “Other”

Chemistry

67 67 100 12

Other

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principal aspect that belongs to another of the main classification categories. Thus, Electronics, a major area of innovation in the Israeli economy, appears to fulfill a supportive, even secondary role among the population of incubator projects. Proximity analysis Other interesting insights can be obtained by analyzing the overlaps and proximities among the six major categories that emerged from the ICE procedure. Figure 1 shows a multidimensional scaling (MDS) map of the six final categories, derived from the distances between the categories, which were calculated as the complement to unity of the similarities presented in Table IV. For example, the distance between Chemistry and Biotechnology was calculated as 1 2 0.07 ¼ 0.93. The map was obtained with the MDS procedure of a standard statistical analysis software package, SPSS in our case. Basically, these procedures project the objects in a multidimensional space into two dimensions while preserving, within certain computational tolerances, the Euclidian distances among them. Although the horizontal and vertical dimensions have no meaning of their own, the relative positioning of the points on the map can be informative. Here we can interpret the proximities between categories as follows: . Medical instrumentation is half way between Biotechnology and Electronics, suggesting its place at the intersection between these two fields. Indeed, medical instruments are often based on electronics (e.g. micro-surgery devices) and frequently rely on biotechnology (e.g. instruments for blood cell or gene analysis). . Biotechnology is half way between Chemistry and Medical instrumentation, showing the important interaction of Biotechnology with these two fields. Chemistry often contributes to Biotechnology and Medical instrumentation is often based on Biotechnology (see above). . Computer software is half way between Mechanical engineering and Electronics, testimony to the increasing presence of software in these two latter fields. . Electronics is half way between Computer software and Medical instrumentation showing the increased incorporation of Software in Electronics developments and products on the one side, and of Electronics in Medical instrumentation on the other.

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Medical Mechanical Computer Chemistry Biotechnology Electronics instrumentation engineering software Chemistry Biotechnology Electronics Medical instrumentation Mechanical engineering Computer software

1 0.07 0.04

0.07 1 0.01

0.04 0.01 1

0.02 0.06 0.11

0.06 0.00 0.05

0.01 0.03 0.10

0.02

0.06

0.11

1

0.02

0.02

0.06

0.00

0.05

0.02

1

0.04

0.01

0.03

0.10

0.02

0.04

1

Table IV. Overlap among pairs of categories in the final classification

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Figure 1. Multidimensional mapping of the six main categories

From Table IV we note that Mechanical engineering is the most isolated category, based on the fact that its maximum extent of overlap (0.06 with Chemistry) is the smallest from among the maxima of the other categories. Leaving Mechanical engineering aside for the moment, there seems to be a continuum among the other categories, starting with a pure science that deals with the properties of materials and compounds (Chemistry), moving on to human-life related technology that is based to a significant extent on that science (Biotechnology), then on to another human-life related technology (Medical instrumentation), to the science that provides a main basis for that technology (Electronics) and finally to the discipline that enables the application of that science (Computer software). Graduation rate analysis The only indicator of performance of individual projects listed in the OCS publication (OCS – Office of the Chief Scientist, 2000) relates to their graduation rate. Further, the extent of detail regarding project graduation that is available from the official OCS publication is rather limited and general in nature. In particular, information regarding the specific timing of project graduation and about the number of pre-graduation, still active projects in each incubator is not available. Nevertheless, the aggregate analysis carried out on total graduation rates broken down according to the six main categories that were identified by the ICE procedure produces some interesting insights. Looking at the graduation rates that appear in Table V we note that the lowest graduation rates were achieved in Chemistry and Biotechnology: 21.3 percent and 19.3 percent

respectively. These two categories were previously identified as being more prevalent in the incubator population than in industry at large, probably due to the high risk involved. The fact that their graduation rates are the lowest reinforces the notion that the innovation and business risks in these categories are higher than in the other project categories. For example, drug development is a costly 10-year process in which major uncertainties persist till the end of the path because of individual human variability. Thus, a drug that appeared satisfactory at the early stages of the clinical trial phase may fail at a later stage or even after commercialization has already begun, due to unanticipated side effects. Computer software and Electronics, two areas with a record of innovation and entrepreneurship in Israel, including many highly visible successes, had somewhat higher graduation rates (27.8 percent and 32.5 percent respectively), while the highest graduation rates were in Medical instrumentation (40 percent) and Mechanical engineering (41.3 percent). We may hypothesize that in the last two categories the projects entailed relatively more tangible products that were less difficult to define, design, develop and assess, possibly because they were based on better understood and less complex technologies. It is interesting to note that the category “Other”, which includes the 15 percent of the projects that were not classified into one of the main six categories, exhibited the highest graduation rate (46.3 percent). One possible explanation could be that projects that did not belong to any of the main categories might be less suitable for the incubator framework, perhaps because they entail less risk; hence their higher graduation rate. They may also face increased selective pressure for incorporation into the incubator’s program, thus raising their graduation rate later on. These are hypotheses worth investigating with a more complete data set.

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Specialization Table VI shows the number of project listings in each main category for each one of the 24 incubators. The second column from the right shows, for each incubator, the percentage of project listings belonging to the largest category for that incubator. This percentage can be interpreted as a measure of incubator specialization: the greater the fraction of projects in the most common category, the more specialized it is. As it turns out, the extent of specialization is rather small, ranging from about 23 percent (incubator 25) to a maximum of about 78 percent (incubator 18). In only five of the 24 incubators does the largest category account for more than half of the project listings. No category shows predominance in these incubators or in others. Thus, Israeli incubators are mostly characterized by an absence of specialization. Analysis of the

Chemistry Biotechnology Electronics Medical instrumentation Mechanical engineering Computer software Other

Number of listings

Graduation rate (%)

89 88 80 80 75 72 67

21.3 19.3 32.5 40 41.3 27.8 46.3

Table V. Breakdown of project graduation rate by category

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Table VI. Breakdown of graduation rates and diversity characteristics per incubator

1 3 4 5 6 7 8 11 12 13 14 15 16 17 18 19 20 22 23 24 25 26 27 28 All

16 21 38 22 15 40 18 6 12 18 24 22 14 21 19 23 9 12 19 15 17 22 24 14 461

4 4 16 13 8 9 8 0 0 2 1 7 4 3 9 9 4 7 12 6 6 7 8 5 152

25 20 42 59 50 20 50 0 0 11 4 32 28 14 47 39 45 58 63 40 35 32 33 36 33

5 4 4 3 2 19 2 2 4 3 1 5 4 5 2 2 0 1 2 1 1 3 14 0 89

2 9 3 2 0 8 8 0 2 1 8 6 5 8 0 2 5 3 4 1 3 5 2 1 88

4 2 7 2 5 4 2 3 3 6 6 4 0 4 4 4 0 1 4 5 3 2 3 2 80

3 2 10 7 4 7 1 1 0 2 5 7 1 4 0 6 3 2 4 1 1 5 4 0 80

5 2 8 5 3 5 3 0 4 7 2 1 1 1 3 3 0 4 1 6 3 5 1 2 75

1 1 4 2 1 2 2 0 4 2 7 0 2 5 14 2 1 1 3 3 2 5 4 4 72

1 4 6 4 2 3 2 0 0 2 2 3 3 2 1 7 1 2 5 1 4 3 3 6 67

33 53 31 39 38 51 50 50 33 44 36 37 45 42 78 38 63 40 29 43 23 26 67 50 23

1.33 1.18 1.13 1.17 1.15 1.22 1.13 1.00 1.42 1.31 1.32 1.21 1.18 1.42 1.28 1.19 1.13 1.20 1.29 1.21 1.00 1.32 1.33 1.13 1.23

Average Percent number of largest listings per Number Incubator Number of Medical category project identification graduated Graduation (exclusive (exclusive of instrument- Mechanical Computer of Other) number projects projects rate Chemistry Biotechnology Electronics ation engineering software Other of Other)

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correlation between the incubator graduation rate and the extent of specialization measured as described above failed to reveal any statistically significant relationships. Project focus and graduation rate The right-most column in Table VI shows the average number of listings per project for each incubator. We can interpret this number as a measure of the technological focus of the projects in the incubator: projects classified into multiple categories are less focused, from the perspective of scientific and technological discipline, than projects falling neatly into a single category. The correlation between graduation rate and average number of listings for the entire sample of 24 incubators was 2 0.28, but not statistically significant. If we remove from the sample the two incubators that had no graduated projects (11 and 12), then the correlation becomes 2 0.42, with a level of statistical significance of 0.051 (R 2 ¼ 0:18). The evidence thus suggests that incubators in which the projects encompass fewer categories are more likely to graduate than those that have multiple classifications. Of course, these are tentative and preliminary conclusions, and additional analysis should be done taking into account actual graduation dates, and possibly other variables not currently available from the OCS publication. Concluding remarks Quite often government-sponsored programs generate large amounts of detailed data meant to support decision-making, which turns out to be difficult to analyze and interpret. In this paper we described how a relatively simple procedure can be applied to reduce the complexity of the data base pertaining to one such program, in order to facilitate performance assessment and policy making. In the specific context of the Israeli government’s innovation incubators program, we presented some insights regarding the relationships among final categories as well as graduation rates. We also illustrated how the classification induced by the ICE procedure can serve as the basis for more sophisticated analysis using statistical tools such as regression analysis. Of course, further analysis incorporating other data besides that collected by the OCS is also possible. In fact, once the relevant categorization is obtained, it becomes easier to collect meaningful data about incubator performance for analysis at various levels of aggregation. In addition to its ease of implementation and application, the ICE procedure has the advantage that it does not give a priori preference to any category or to any relationship between categories, and does not require a priori identification of the categories that are to be kept and those that are to be deleted. Further, it does not need to classify categories under headings such as “scientific and technological” on the one side, and “sector applications” on the other. Both are seen as equal from the beginning to the end and thus allow us to avoid any bias in the process. In addition, by basing the choice of the category to be excluded at each stage on objective, directly measurable attribute values, the subjectivity inherent in the selection process is reduced, perhaps even eliminated. The same values provided the basis for the identification and quantification of overlap and proximities between the final categories, throwing some light on their mutual dependencies and interactions and leading to a level of representation from which strategic assessment and thinking can start.

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The core principle of ICE is to eliminate categories that do not convey sufficient information to justify the additional complexity. We believe that this principle is universal and can be applied to a wide variety of situations that suffer from too much data and not enough information. References Avnimelech, G. and Teubal, M. (2002), “Venture capital-startup co-evolution and the emergence of Israel’s new hi-tech cluster”, in Centidamar, D. (Ed.), The Growth of Venture Capital, Greenwood Publishing Group, Westport, CT. Justman, M. and Zuscovitch, E. (2002), “The economic impact of subsidized industrial R&D in Israel”, R&D Management, Vol. 32, pp. 191-9. Kalis, N. (2001), Technology Commercialization through New Company Formation. Why US Universities are Incubating Companies, NBIA Publications, Athens, OH. Mani, S. (2002), Government, Innovation and Technology Policy: An International Comparative Analysis, New Horizons in the Economics of Innovation Series, Edward Elgar, Cheltenham. OCS – Office of the Chief Scientist (2000), Technological Incubators in Israel, OCS Publications. Rice, M. and Matthews, J. (1995), Growing New Ventures, Creating New Jobs: Principles and Practices of Successful Business Incubation, Kauffman Center for Entrepreneurial Leadership, Kansas City, MO. Trajtenberg, M. (2001), R&D Policy in Israel: an overview and reassessment, science, technology and the economy program (STE), Working Papers Series, The Samuel Neaman Institute, Technion, Haifa.



Innovation through acquisition The Jiangsu Little Swan Group Company in the People’s Republic of China Robert M. Pech

Innovation through acquisition 107

CFBT, Berakas, Bandar Seri Begawan. Brunei

Richard J. Pech Graduate School of Management, Faculty of Law and Management, La Trobe University, Melbourne, Australia, and

Ding Wei and Hong Shi Business School, Southern Yangtze University, Wuxi, The People’s Republic of China Abstract Purpose – Through a case study of the Jiangsu Little Swan Group Company in the People’s Republic of China aims to describe the transition from initial attempts at imitation of products through to the realisation that innovation would need to be purchased Design/methodology/approach – Relates the ensuing strategic alliance between the Jiangsu Little Swan Group Company and Matsushita of Japan, the acquisition of critical technology, and finally, the development of the company’ own R&D culminating in over 150 technology patents by the end of the year 2002. Findings – Finds that Little Swan has demonstrated that it is possible to successfully make an extraordinary revolutionary shift from one industry into another. Originality/value – The case of Little Swan clearly demonstrates that innovation can be successfully integrated into a firm from external sources through direct acquisition. Keywords Innovation, Strategic alliances, China Paper type Case study

First-class enterprises form standards and benchmarks; second-class enterprises form brands; and third class enterprises form products. (Xu Yuan, Deputy General Manager, the Jiangsu Little Swan Group Company, 18 November 2002).

Background Having a population of four and a half million, Wuxi is a city situated approximately 120 kilometres north-west of the great commercial centre of Shanghai, on the shores of Lake Taihu. To the Chinese, it is best known for its production of light to medium sized household appliances and its prolific textile industry. The People’s Republic of China (China) has been in the process of tumultuous change particularly with its provisional entry to the World Trade Organisation in November 2000 to be finalised in 2005. It has been slowly moving away from a planned economy to a mixed economy and with these changes, demand for new products has grown rapidly. Such growth was anticipated with great international optimism in the


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1990s and attracted large international investments in an attempt to tap the supposedly larger market opportunities that this growing economy could present to the world. Due to problems with infrastructure, regional government requirements, and market resistance, many of the foreign firms withdrew after suffering large losses (Singh et al., 2004). However, there are positive changes happening within Chinese industry that will continue to increase capital flows in the future. Transfer technology figures alone are sizeable: Dougherty (2003) points out technology transfer contracts amounted to several billion US dollars per year in the 1980s, climaxing to over ten billion in 1995 and this represented about one-sixth of total machinery and transport imports. Actual foreign direct investment ranged from one-half to nearly the same amount as machinery and transport imports, flooding in at the rate of about ten billion in 1995. Little Swan’s technology acquisition was a contributing part of China’s economic change as that country embarked on momentous upheaval. While a considerable amount has been written concerning the failures and successes of foreign firms operating in China, little has been revealed about the Chinese firms that have had to make the shift from a planned economy to an economy that is beginning to respond to market forces. Little has been told about the Chinese firms that have had to compete with large and experienced multinational corporations. It could easily be surmised that Chinese manufacturers have survived and prospered because of the protected environment in which they operate, particularly in relation to their favourable exchange rate. As the following case demonstrates, there are inventive anomalies. The example of the Jiangsu Little Swan Group Company (Little Swan) highlights how success is being achieved through the application of innovation and pragmatism, but the really revelatory detail about this company concerns its early methods for acquiring such innovations. About Jiangsu Little Swan Group Company Limited Little Swan is one of China’s 100 largest companies, with a domestic labour force of approximately 10,000. Its core business is manufacturing household appliances, some of which, such as dryers and washing machines are also constructed in commercial dimensions. The washing machine is their largest seller, but the company also manufactures air conditioners, refrigerators, freezers, dishwashers, dryers, and dry-cleaning appliances. Little Swan had total assets of 10.6 billion yuan in 2003. In 2003 it achieved sales of over ten billion yuan. In 2002, its exports totalled $US 180 million (Littleswan.com, 2004). The Little Swan washing machine, consisting of three action variations, has been the top selling brand in China since 1994, the year they sold 640,000 units, which put the company in first place. The company began washing machine sales in twenty-fourth place in 1989. But only five years later, it made a profit of 70 million yuan from washing machine sales alone. How did a former ceramics, pottery and tool producer achieve this, and in such a short timeframe? Did the re-combination of foreign technology and domestic innovative activity lead to productivity improvements? Innovation at Little Swan The company has achieved innovation in both product and process, more particularly in latter years as it changed direction and underwent major changes in management. To put this innovation into context requires an outline of the company’s main

developmental phases. Innovation has been integral to that development, but surprisingly it did not consist of the normal in-house “breakthrough” variety. The company’s history can be divided into four periods: from 1958 until 1978, it produced mainly pottery, ceramics and a variety of tools; from 1979 until 1989, the company relinquished ceramics and explored the market for domestic appliance demand, and began producing washing machines in 1979; from 1989 until 1999, a major strategic plan witnessed rapid development in home appliance production, with particular emphasis on the washing machine; and in the fourth phase from 2000 to the present, the development has been in high technology expansion into a variety of appliances, with the washing machine as the lead product and the most profitable one. An important aspect of the fourth phase has been the improvement of the lead product to make it a globally competitive product. The hi-tech device which now distinguishes later models from their previous siblings is “fuzzy logic”, which is a sensor that automatically adjusts water levels and the power that is used to drive the turbine depending on washing weight and condition. The company is now not only China’s main washing machine supplier but it also exports to South East Asia, North America and the Middle East. From 1989 to the present, the company has expanded at a rate of about 18 per cent per year. There are American, European and Australian white-ware manufacturers who also produce the washing machine as a basic “must have” domestic appliance in the contemporary family, each with its own style of technological development. From where, or how, did Little Swan obtain its technology when it did not have a history of technological advancement prior to 1979? It is a considerable shift to go from producing ceramics like exterior wall-cladding tiles, to producing electrically powered white-ware. In a study completed by Wu et al. (2002), which focused on productivity increases in businesses in Zhejiang Province, they found that the technology acquisition was far from successful. It was found that 21 per cent of businesses could only imitate foreign products and technology; 30 per cent of small businesses and 12 per cent of medium size businesses could innovate independently; 20 per cent of businesses could create new products independently and 22 per cent of businesses could make their own technological innovations. Wu et al. (2002) concluded that the greater the sophistication of the technology acquired, the lesser the chance of successful improvement in Chinese productivity. They also concluded that “cooperation and coordination with the foreign enterprise is one of the channels to improve Chinese enterprises’ ability to gain a late-comer’s advantage.” How then did Little Swan succeed? Technology transfer: innovation acquired In the mid-1970s, the company strategy focused on the production of the washing machine, and in order to commence this, they bought washing machine components from Matsushita in Japan. However, the components were difficult to clone, and this resulted in a product which only had the “appearance” of the original. In 1987, the company took the step which propelled it into serious production. They imported critical technology from Matsushita at a cost of US$4.1 million. Ten years of relatively unsuccessful imitation was capped by a technology transfer fee, and the external sourcing of Matsushita’s high technology product and some of their engineers. This propulsion into high technology expertise acted as an instant catalyst, which enabled


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the company to design further proprietary technology of their own. By 2002, it had 150 technology patents, one of which was held in the USA. The expertise consisting of purchased knowledge as well as incremental innovations in washing machine technology from their own R&D gave the company its competitive advantage. In the year the company paid Matsushita its transfer fee, its newly acquired technological accelerant led to speedy market acceptance of its washing machines, and its sales were split 75 per cent in the Chinese market, and 25 per cent in markets abroad, mainly Thailand. The external sourcing of technology from Matsushita was so successful for Little Swan that between 1999 and 2000, it repeated this means of kick-starting another line of white-ware development. The company paid US$2.9 million for air-conditioning technology, and in so doing it is attempting to repeat the process previously so successful in washing machine manufacture. Management and human resources: innovation in leadership The company was not satisfied to only possess a new technology. It determined that it also needed to innovate in a number of other areas, as manufacturing of new products for new and shifting markets required improved skills in management, as well as employee relations, remuneration and R&D. Management made the decision to purchase technology. At the same time, it engaged in improved marketing and planning, in order to predict market demand. It correctly predicted that the Asian demand for hygiene and cleanliness was underpinned by the need for machinery of high quality and durability. Management opined that if technology could be purchased as a commodity, and make an instant change for the better, then perhaps management skills could be purchased in the same way, and the changes it would effect might produce similarly desirable outcomes. In 1994, the company applied to the Beijing government to create a board that would represent the interest of capital, consisting of nine Chinese members and three from abroad. Such a composition was highly innovative, even radically countercultural, at the time, because China still functioned as a planned and largely isolated economy. The company invited the US Educational Foundation to be one of the three foreign members, and the Foundation accepted this invitation, and continues to hold a seat at the time of writing. As a result of board diversity, the company has achieved what was planned, as explained by the Deputy General Manager, Xu Yuan [1]: We have an innovative plan that has three main planks: To have a lead product, the washer that is first in the market; to have higher return from less investment; and higher return with less risk. This is what I mean: our strategy in focusing on washers is to go in for larger scale production, to absorb technology and to pay attention to patenting our expertise. By a higher return with less investment I mean that we put 2 to 4 per cent of sales into Research and Development, but we know we are still backward in expertise and capital management. By higher return with less risk I mean that we have to make up for our disadvantages. It is hard to find good friends, harder to find good competitors. So we keep on good terms with everyone.

In the same year, the company included reforms in its ownership by a process of “social shareholding” which enabled eleven per cent of shares to be held by foreign companies,

although the company itself owned the largest per centage of shares. The company is now listed on the Sheng Zheng Stock Exchange. Under the new management, the company also diversified its employee base. Technical expertise, especially, was recruited from the United States, Japan, New Zealand and Canada, with skilled talent lending its name to the particular process which the engineer devised. For example, the washing machine metal folding line was created by a New Zealand engineer, and it is called the “Scott” line, even in Mandarin, as a tribute to his ingenuity and contribution to the company. The Deputy General Manager conceded that only one senior engineer came from within China, having completed his PhD in mechanical engineering in France; the rest were, and continue to be, sourced from abroad. The technology which the company develops is the bedrock of its competitive advantage. As a result, the most senior engineers are paid in the region of US$100,000 per year, although some salaries rise above that amount because the top figures are negotiable, with no pre-determined ceilings. This compares to assemblers, sourced locally from the city of Wuxi, who earn between US$2,500 and US$3,000 per year. The top engineering incomes should also be seen as highly favourable in comparison to various strata of management: supervisory management earns about US$4,000 per year, management with a Master’s degree earns about US$8,000, and higher echelons of management, but not top management, earn in the vicinity of US$12,000 per year. The company remunerates on educational qualifications, experience and performance. Those employees with a PhD, regardless of whether they are employed in management or engineering, are accorded a free apartment and the service of a car as a standard remuneration package. The company considers the pay relativities an essential reflection of the primacy of top engineering as the means to create continuous upgrading of their products. Mr Xu states: “The quality of the product reflects the quality of the employees.”. This philosophy straddles the findings of Montemayor (1996) who claims that high performance companies with innovative strategies often have innovative pay policies and that companies that emphasise cost leadership reward differently. To evaluate employee performance, the company has devised an achievement assessment system in which performance is assessed on various criteria, and by a number of co-workers. Working attitude is important to the company. The employee writes a self-assessment, one is written by the manager to whom the employee reports, and anyone else who feels he or she can contribute constructively may offer an assessment in support (or criticism) of a colleague. Staff may be promoted or demoted by this process, which the Deputy General Manager calls “democratic”. The company offers continuous training programmemes for employees who are seen as fading, or under-performing in other ways. The company management believes that a cooperative culture is the key to a successful enterprise. Little Swan has recognised the inadequacies of former management practices. It now attempts to inculcate “individual discipline, and move human management towards logistic management.” With this remark, Xu Yuan believes that managers across China are better off relinquishing an archaic past and embracing a future, albeit one that will suffer growing pains, but which is at least based on sound market analysis. He argues that the market should lead as in a developed market economy, not that production should lead as in a planned economy.


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Research and alliances The company believes it provides its technicians and engineers with an environment to match the company’s technological aspirations. Laboratories in Berlin, Tokyo and Los Angeles have been built to continually upgrade the technology required to maintain and increase the company’s competitive advantage in washing machine technology. Xu Yuan states: “The development strategy is specialisation as the key to success.”. The company has developed strategic alliances with BSH of Germany, Matsushita of Japan, and Motorola and GE from the USA, as well as joint ventures with BSH of Germany. A home-grown example of an alliance is that the company also includes a pack of P&G detergent with every washing machine sold on the domestic market. The company believes that by combining with other researchers and suppliers in their markets all the parties can benefit from sharing some technologies and information. Little Swan and P&G conduct market surveys together, and Motorola researches washing programmes with the company. Innovative philosophies In the late 1990s, Xu Yuan began writing a number of short articles, or position papers, which the Little Swan Group then placed on the world wide web, but only in Chinese. Without significant exposure to Western industrialists or to Western business philosophies, he reveals a mode of philosophy that espouses many Western business concepts. However, for him, the development of his own thought about the strategic direction which his company should pursue, was not so much a coherent philosophy as a series of shared revelations, or epiphanies. The articles were intended only for a Mandarin readership, as a “wake-up call” to industrial peers in the Peoples’ Republic. In “Corporations and markets”, Xu (2001) states his belief that despite the problems Chinese industry faces with capital and organisational structure, the “crux of the problems is the problem of management.” His initial standpoint is that the era of economic shortages should now be relegated to the past, and that “the market has gone from an emphasis on sellers to an emphasis on buyers . . . Nonetheless many enterprises still hold on to the thought that was prevalent in 1998 when China first began moves towards becoming a market economy. They are still hoping that the market will flourish on its own and they are still expecting that the government will turn on the water and raise the fish. These are the troubles left behind by an era of a planned economy.” Once Chinese managers understand that the problems of the planned economy have given way to a new raft of problems, Xu Yuan exhorts them to analyse the market: “The front line of the enterprise is the market.” He has devised an aphorism: “The enterprise is only able to live if the market lives, the market can do without the enterprise, but the enterprise cannot do without the market.” This counters the still oft-held view that “production is the front line,” reminiscent of a planned, but failed, economy. Xu Yuan’s focus on the market orientation of future companies is all pervasive: An important step that enterprises must take is ‘all staff must be market orientated Above all, enterprises must nurture the potential of young workers and encourage them to be market oriented. About 60 per cent of current staff members were selected from the open market. A total of 100 per cent of management staff were selected from the open market. Receptionists,

sales people and so on must all be selected one by one. All of the enterprise’s resources must be put to good use. Human capital is first, but product development and production must also be closely, if not inseparably, coiled around the market. At the moment, Little Swan has won segment after segment of market share that way.

Innovation through acquisition

This is however not an exhortation for a plunge into the market without strategic planning: “Enterprises still need to be creative and apply modern sales theories. In this regard, enterprises need to do some very difficult, very detailed and very sensitive work. It’s not sufficient to just say ‘the market is the leader’ and leave it at that.” Xu Yuan is aware that in a market economy, public perception of a product and service are important:

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What you’ve said to people they won’t remember, but the impression of service you bring to them will always be remembered. So learn to serve, because good service will produce more value. This is an important step to [becoming] a successful enterprise. If we consider service as well as trying our best to do our own work, we can determine the future – this is a cygnet attitude towards customers and also a core value [we need] to serve the customer. [. . .] General Director Chu proposed an idea, that of the “consumer standard”, [and] this is [a] higher [standard] than any standard target.

These comments are not borne of traditional Chinese industrial theory; they are the first steps of a nascent industrial culture in which every such step is demonstrative of the courage and the will to be innovative in order to climb out of a time warp. A number of elements of the innovative approach to industrial change are there: The vision that communicates the need to change on a large scale, in this case, the whole human resource and managerial position from a planned to a market economy; the need to select the workforce on a merit and equitable basis; the need to adopt an analytic approach toward market forces; and the need to lead towards a new model of management as the bedrock towards achieving a better business model. Xu Yuan adds: “The core of administration is to manage operations, but [more importantly] the core of management is to make strategic decisions. This is the new revolution and it has to uplift our foundations.”.

Discussion: the role of innovation According to Xu Yuan , successful innovation in a lead product, namely washing machines, funds the company’s development of secondary products, which are expected to have the potential to grow in market importance in the future. At the time of the interview with Mr Xu in late 2002, Little Swan was deploying profits from the sale of washing machines to continue excelling in washing machine design, to develop its line in air conditioners and other white-ware appliances. This strategy, combined with the acquisition of high technologies, top engineers, regardless of their nationality, as well as the creation of strategic alliances, encourages creative windows of opportunity that can exploit a market more quickly than a company that works in greater isolation. Little Swan’s initial attempt at transforming their business concept by purchasing washing machine components from Matsushita, thereby planning to break into the white-ware market through the act of copying, did not work. Francis et al. (2003) point out that radical organisational transformation requires multiple changes. Strategies must be re-written, cultures realigned, processes reworked, and value chains redesigned. The authors explain that total organisational transformation

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is a risky and uncertain venture. They make two pertinent observations from their research (p. 29): (1) Develop a plan for facilitating radical innovation. (2) Take learning seriously – study what others have done so that potential pitfalls can be avoided.

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Little Swan’s initial foray into washing machines failed because they did not fully understand the industry or the technology, copying was a superficial strategy that would not allow the company to fully transform itself. They needed to source not only washing machine components but the complete process technology. Ettlie (2000, p. 268) describes the tension that often exists between product and process technology. He points out that process re-engineering is difficult to imitate and that it fails more often than not, as was demonstrated by Little Swan when they focused on the product rather than the complete production process. Successful technology transformation therefore requires product and process re-engineering as well as having the will and determination to learn. After their initial failure Little Swan successfully transformed themselves through a total sourcing of technology. There are generally two schools of thought concerning the sourcing of technology. Tushman and O’Reilly (1997) focus mainly on the principle of a company which initiates and develops innovation in-house. They postulate that companies evolve their products predominantly in an incremental way, although their aim is to achieve periodic breakthroughs in technology that accelerate the quality or performance of the service delivery of which the product is capable. For this reason, they advocate the creation of the “ambidextrous organization”, because such an organization operates a conventional division of production as well as a separate but integrated skunkworks facility. Together the concern “can sustain competitive advantage by operating in multiple modes simultaneously – managing for short term efficiency by emphasizing stability and control, as well as for long-term innovation by taking risks and learning by doing.” (Tushman and O’Reilly, 1997, p.167). Tushman and O’Reilly (1997) promote the concept that the “route to sustained competitive advantage [lies in] producing streams of innovation” in which interlinking cycles of product manufacture as well as intermittent radical new product development can evolve. (p. 165). Clearly, Little Swan is a variant because after its initial failure, it has now twice short-circuited this process. They have externally sourced their technology. In purchasing the necessary “breakthrough” technology in washing machines, they controlled its introduction and implementation with a key ready-made innovative component. They then took advantage of market opportunities in air-conditioning in the same way. Little Swan’s own R&D unit then applies itself to the creation of incremental developments in the field, which are less costly than the search for elusive breakthroughs. Tushman and O’Reilly (1997) refer to the breakthrough innovation as a “rare, unpredictable event” (p. 160). Two such “rare” events might include 3M’s 19-year research that led to the invention and manufacture of the measured inhaled dose of asthmatic medication; and secondly, the decade of experimentation it took before Seiko perfected the quartz mechanism to effect wrist-watch accuracy upon which they could then create a reputation as an innovative and quality-conscious company. Some breakthroughs are research driven and cannot be purchased. But where they can be purchased, there can be instantaneous results.

Doz et al. (1989) ask a crucial strategic question of firms considering external sourcing of technology. Their concern relates to the ultimate impact of external sourcing. Will it create the capability for future advances to be made internally or will it merely reinforce dependence? Little Swan has demonstrated that dependency is not necessarily the consequence of external sourcing through its growing list of patents. Ironically, Japanese electronics firms acquired technology from abroad during the 1950s and 1960s to kick-start research programmes that resulted in innovation leadership in later years. These same firms are now cooperating with companies such as Little Swan to provide the same possibilities for growth and leadership by developing their own internal sourcing of technology. Chesbrough (2003, p. 36) distinguishes between “closed” and “open” innovation. He promotes the view that the model of internal technology sourcing is a “closed” approach to innovation, because in this model, the company “generates, develops and commercializes its own ideas. [And continues by stating that] . . . This philosophy of self-reliance dominated the R&D operations of many leading industrial corporations for most of the 20th century.” Chesbrough (2003) has identified the following hallmarks of a company which operates the “closed” innovation model: the most capable employees in the field work for the innovative company itself; to profit from R&D, the company must discover, develop and ship it itself; if the company makes an innovative breakthrough, it believes that it will get to market first; if they are the first to commercialize an innovation, they believe they will “win”; if they create the most and best ideas in the industry, they believe they will “win”; and, this company should control their intellectual property so that their competitors do not profit from their ideas. (Chesbrough, 2003, p.38). It appears that Little Swan has opened a number of “closed” features in the model because of its purchase of proprietary technology and its deployment of strategic alliances (see Figure 1), although it is moving more and more toward a hybrid model that exploits the benefits of external sourcing, internal sourcing, as well as the careful nurturing and management of alliances. Figure 1 attempts to describe the progression of Little Swan from ceramics and a predominantly seller-based focus, through to the present where ceramics are simply viewed as artefacts from the past for a company that now deals in high technology products. The Y axis in Figure 1 represents Little Swan’s shift from a seller focus through to a market and buyer focus. The X axis represents Little Swan’s significant transformation from a position of imitation and very little innovation through to the development of a large R&D programme and the ownership of 150 technology patents in 2002 – evidence of an increasingly high level of innovation. Little Swan has succeeded in being innovative in part by pursuing an “open” model of innovation. The company’s pursuit of innovation to create a competitive advantage also in part allies itself with the Tushman and O’Reilly (1997) model of discontinuous and incremental innovation. In their purchase of technology from Matsushita to establish and continue evolving the washing machine and air-conditioner lines they took the initiative to ignite white-ware production. Chesbrough (2003) refers to this as “open” innovation, and the principles which characterise this approach are as follows: the purchase of knowledgeable employees to bring them into the company when at any given time, the company may lack particular expertise; external R&D can create significant value – internal R&D is needed to claim some portion of that value; the company does not have to originate the research in order to profit from it; building a


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Figure 1. The Jiangsu Little Swan Group Company focus shift since the late 1950s

better business model is better than getting to market first; if the company can make the best use of internal and external ideas, they believe they will win; and, the company should profit from others’ use of their intellectual property (IP), and the company should buy others’ IP whenever it advances its own business model (p. 38). Little Swan over the last decade and a half has been pragmatically deploying whichever methods it deemed necessary to innovate, compete in the market and exploit it commercially with technology and expertise as its two-edged competitive advantage, regardless of its source. At a time during the late twentieth century when all Chinese industry was subject to the dictates of a central government that took the responsibility for the central planning of its economy, Little Swan demonstrated courage and insightful strategic planning in purchasing innovative technology from another company. It developed a human resources policy that hires highly knowledgeable engineers, and constituted a board of governors a quarter of whom hail from abroad, including one vote from an institution sourced from its main international political rival. Little Swan developed a

lead product that met expectations in each of its main markets: the European model is a front loading rotary action, the Asian model is the preferred top-load impeller style, and the American model has an agitator action. From this lead product’s profits, the company purchased additional technology in 1999 for a second major line in air-conditioners. It did not invent the technology, but it was clear that it did not need to. The “discontinuous” technological leap of the Tushman and O’Reilly (1997) model could be purchased from Matsushita, rather than be developed in its own laboratories in which the necessary breakthrough might take considerably longer to achieve. Matsushita clearly saw an advantage for itself in not squirreling its IP for its own profit-motive and any discussion concerning the advantages of such a purchase for Little Swan, should include an explanation of why Matsushita might benefit from such a sale. In the case of Little Swan and Matsushita there is innovation taking place in the process of purchase and sale which benefits both companies. A specialist in intellectual property strategy comments that more and more companies are engaging in “strategic licensing” meaning that they are sharing core technologies with others, “even [with] competitors”, and that contrary to expectations, this “can have significant financial and strategic benefits.” (Kline, 2003, p.89). Kline (2003) makes the point that “Patent licensing has become a growth business – revenues have skyrocketed from only $15 billion annually a decade ago to more than $100 billion today – as companies have sought to tap the value lying fallow in the 70 to 80 percent of corporate technology assets that typically never get used in core products or lines of business.” (Kline, 2003, p. 90). It appears that Matsushita realized over a decade ago that the company that invests in the research and creates new technologies is not necessarily the best one to commercialise every product opportunity, and so it may as well be paid for its IP if it has no wish to go into production itself. Little Swan’s approach for purchasing their washing machine technology must at the time have seemed like a mix of good innovation with good business. The results have demonstrated that Little Swan and Matsushita may have more in common than IP transactions. Doz and Hamel (1997, p. 558) point out that alliances allow one company to intercept the skills of another and give it the opportunity to close skill gaps much faster than internal development would allow, but they also point out repeatedly that such alliances are often more successful if the partners are also strategically, organisationally, or culturally compatible. Conclusion Hislop (2003, p. 162) has argued that knowledge integration for the appropriation of innovation can be facilitated through a number of mechanisms within the firm. He has broadly categorised these as team working, formal education, and the use of documentation. The case of Little Swan clearly demonstrates that innovation can also be successfully integrated into a firm from external sources through direct acquisition, adding a fourth mechanism to Hislop’s (2003) three categories mentioned above. Little Swan has demonstrated that it is possible to successfully make an extraordinary revolutionary shift from one industry into another. Reading between the lines, the organisation and its immediate stakeholders showed remarkable tolerance as well as patience as management realigned the strategic thrust of the company to transform its centre of gravity from ceramics to domestic appliances. Once the decision makers arrived at the conclusion that change was needed, they literally opened the


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gates to integrate knowledge into their operations through the importation of technology from a foreign competitor no less. Visionary leadership and management have been combined to ensure that Little Swan did not stop with the acquisition of knowledge, but that this was simply the catalyst for commencement of the firm’s own research and development work. While the case has not focused greatly on the leadership aspect of the transition processes, Harborne and Johne (2003) have argued that leadership and the creation of a climate that is conducive to ongoing change is a requisite element for successful product innovation. This is not without risk as has been pointed out by Celeste’s (1996) study of strategic alliances. Little Swan’s managers committed the firm to a high-risk, long term venture that exposed and altered their core technology. They were also exposed to outside influence and potential tampering as well as potential leaks. The Deputy General Manager, Xu Yuan has clearly demonstrated his company’s visionary attitude through his thoughts and references to their actions over the turbulent years of the firm. The audacity of the suggestion of an initial alliance between Little Swan and Matsushita is in itself worthy of the axiom of innovative and visionary leadership. The subsequent and ongoing negotiations must have been ‘interesting’ to say the least. Note 1. The statements attributed to Mr Xu Yuan in this article are derived from a personal interview, conducted at the Jiangsu Little Swan Group Company in Wuxi, Jiangsu Province, 18 November, 2002. References Celeste, R.F. (1996), “Strategic alliances of innovation: emerging models of technology-based twenty-first century economic development”, Economic Development Review, Vol. 14 No. 1, pp. 4-8. Chesbrough, H.W. (2003), “The open-innovation model”, MIT Sloan Management Review, Vol. 44 No. 3, pp. 35-41. Dougherty, S. (2003), “Foreign technology, innovation and productivity effects in mainland China”, available at: www.sean.dougherty.org/econ/papersshanghai.pdf (accessed 19 April 2004). Doz, I.L. and Hamel, G. (1997), “The use of alliances in implementing technology strategies”, in Tushman, M.L. and Anderson, P. (Eds), Managing Strategic Innovation and Change, Oxford University Press, New York, NY, pp. 556-80. Doz, I.L., Hamel, G. and Prahalad, C.K. (1989), “Collaborate with your competitors – and win”, Harvard Business Review, January-February, pp. 133-9. Ettlie, J.E. (2000), Managing Technological Innovation, Wiley, New York, NY. Francis, D., Bessant, J. and Hobday, M. (2003), “Managing radical organisational transformation”, Management Decision, Vol. 41 No. 1, pp. 18-31. Harborne, P. and Johne, A. (2003), “Creating a project climate for successful product innovation”, European Journal of Innovation Management, Vol. 6 No. 2, pp. 118-32. Hislop, D. (2003), “Knowledge integration processes and the appropriation of innovations”, European Journal of Innovation Management, Vol. 6 No. 3, pp. 159-72. Kline, D. (2003), “Sharing the corporate crown jewels”, MIT Sloan Management Review, Vol. 44 No. 3, pp. 89-93.

Littleswan.com (2004), available at: www.littleswan.com/en/company/aboutus.htm. Montemayor, E.F. (1996), “Congruence between pay policy and competitive strategy in high performance firms”, Journal of Management, Vol. 22 No. 6, pp. 889-908. Singh, K., Pangarkar, N. and Heracleous, L. (2004), Business Strategy in Asia: A Casebook, 2nd ed., Thomson, Singapore. Tushman, M. and O’Reilly, C. (1997), Winning Through Innovation: A Practical Guide to Leading Organizational Change and Renewal, Harvard Business School, Boston, MA. Wu, X., Ni, Y. and Cao, Z. (2002), “The factor analysis on China’s manufacturing enterprises’ technology acquisition performance”, available at: www-mmd.eng.cam.ac.uk/cim/ imnet/papers2002/yifang.pdf (accessed 19 April 2004). Xu, Y. (2001), “Corporations and markets”, unpublished position paper, translated by Hong Shi, University of Southern Yangtze, Yangtze.




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Methods for modeling and supporting innovation processes in SMEs

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Barbara Scozzi and Claudio Garavelli Dipartimento di Ingegneria per l’Ambiente e lo Sviluppo Sostenibile, Politecnico di Bari, Bari, Italy, and

Kevin Crowston School of Information Studies, Syracuse University, Syracuse, New York, USA Abstract Purpose – Sets out to investigate business modeling techniques (BMTs) which can be used to support and improve innovation processes within small and medium-sized enterprises (SMEs). Design/methodology/approach – Based on a literature review, different analysis perspectives on innovation processes are identified and discussed, and some firm needs and problems are pointed out. The importance of BMTs to firms is further tested by an empirical study whose initial results are reported. Finally, by matching problems and techniques characterized by the same ontology, the BMTs most suitable to address SME needs are identified and their role within the innovation process discussed. Findings – The main result of the paper is the identification of the problems facing SMEs in innovation processes and the possible support offered by BMTs. Though methods and models alone do not assure the success in the innovation development process (IDP), they are enabling factors and can support the creation of strategies, reasoning, insights and communication. Originality/value – The adoption of such BMTs, facilitating the codification of the characteristics of the IDP, might be particularly useful in those environments where, due to the lack of specialized resources, it is difficult to structure all of the information related to the innovation process and to exploit the related benefits and opportunities Keywords Innovation, Modelling, Small to medium-sized enterprises, Italy Paper type Case study


Introduction An innovation is a product, service, or process that is new or perceived as new by its developers (Van de Ven, 1986). Some processes (e.g. new product development) are essential to develop innovations within companies. This paper discusses the use of modeling techniques to support innovation processes. We argue that techniques for process modeling and analysis, which we refer to collectively as business modeling techniques (BMTs), can be used to support and improve innovation processes. Such techniques are commonly used in many fields, e.g. for information system development. In these fields, the importance of such techniques is broadly recognized and benefits of their use have been shown empirically in the literature (Maylor, 2001; Wheelwright and Clark, 1992). However, BMTs have often been considered inappropriate for processes such as new product development (NPD) that are highly unstructured and characterized by difficult-to-forecast activities linked by reciprocal rather then sequential dependencies. Nevertheless, interest in modeling techniques to support innovation is rapidly increasing, though as yet, few modeling

techniques have been proposed to support innovation processes (Presley et al. 2000). We suggest that there may be BMTs that are appropriate to support such processes (e.g., design rationale techniques or cognitive mapping). By providing models of the innovation process, BMTs can support the identification of problems and the assessment of alternative modes to perform the process. Moreover, by their adoption organizations can learn how they innovate and improve the process. We specifically focus on BMTs to support the innovation development process (IDP) within small and medium-sized enterprises (SMEs). The importance SMEs play for economic development is widely recognized in the literature and their role as innovators is indisputable (Rothwell and Zegveld 1982). Nevertheless, there are few studies to support the management of innovation within SMEs (Hoffman et al., 1998, March-Chorda` et al., 2002, Motwani et al., 2000) and little attention has been devoted to how innovation is pursued or how to support it (project management techniques and quality function deployment are among the few supporting tools to be considered). Furthermore, a lack of specialized resources to effectively manage IDPs makes it difficult for such firms to identify suitable methods and adopt them. The research question this paper addresses are which BMTs can be used to support and improve IDPs in SMEs. Addressing this question requires the assessment of the specific characteristics of IDP within SMEs, the analysis of existing BMTs and a study of their effectiveness in modelling such a process. In particular, based on a review of the analysis perspectives on IDP and some theoretical and empirical insights, SMEs’ specific needs and problems are assessed and BMTs to support such needs are identified. For each technique the role and IDP phase they can be adopted are also discussed. Finally, some conclusions and future research lines are drawn. Insights on innovation processes: seven perspectives for analysis IDPs are complex, knowledge-intensive and often not ex-ante defined or definable. Characteristics of innovation processes have been deeply investigated in the literature (detailed reviews on this issue are proposed in Gopalakrishnan and Damanpour , 1997; Slappendel, 1996; Tang, 1998; and Wolfe, 1994), though most studies focuses on a few aspects, such as information management, creativity, management and organization etc. In order to present a complete picture of IDP, in this section different analysis perspectives are reviewed and discussed. Within each perspective a brief description of the most significant studies and research approaches is also proposed. Note that the proposed perspectives describe the same process: an IDP is simultaneously a sequence of tasks, a political process, a cognitive process etc. But recognition of different analysis perspectives is useful for identifying problems and needs that arise within firms and assessing suitable supporting techniques. Sequence of tasks IDP can be described as the set of tasks aimed at the creation of a new product/process. Several studies have identified stages and tasks necessary (but not sufficient) to the development of successful innovations (Cooper, 1983, 1994; Cooper and Kleinschimdt, 1986; Saren, 1984). For example, Wolfe (1994) classifies two generations of models, namely stage models and process-based models (which are in particular referred to NPD). In both cases, normative models are more common (Saren, 1984). Case studies and quantitative analysis have also been developed to study tasks and

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interdependences among them so as to identify suitable management techniques (e.g., concurrent engineering and project management), suggest the appointment of some specific organizational roles (e.g., gatekeeper or innovation champion) and define general models for project design (Koput, 1997, Van de Ven and Poole, 1990). As reported in Table I (2nd column), the main problems studied within this research track are associated with IDP design (task definition and decision-making power allocation), coordination (identification and management of interdependencies among tasks so as to guarantee an effective management of the whole process) and control (definition of milestones and control tools). Decisions that evolve over time The IDP can be described as the set of decisions made during its design and execution (Marples, 1961; Mintzberg et al., 1976; Thomke et al., 1998; Wheelwright and Clark, 1992). An IDP is triggered by the decision to create a new object. The creation requires consideration of alternative options, each requiring the identification and solution of some technical and organizational problems. Different options must thus be rated and ranked based on some criteria (feasibility, cost, time etc.). Problem solving is complicated because these criteria are often uncertain (not all the information necessary to rate options is available) and ambiguous (information can be misunderstood, priorities and criteria to be adopted to rate options are not clear or well defined). Although at a macro-level of analysis an innovation requires the solution to new problems, some tasks and decisions (at a micro-level of analysis) repeat over time. For this reason it is important to keep trace of the adopted decision-making criteria. As reported in Table I, the main problems studied in this research area are those associated to the analysis of the decision-making rationale (e.g., difficulties in problem solving, problem setting and retrieval of the adopted criteria). Some general process models, factors and variables to be considered during innovation development are also discussed in the literature. Strategic process The strategic role of innovation processes within firms has been stressed in several studies (e.g. Utterback, 1994). Innovation is the main source of competitive advantage for many organizations. Studies developed based on this perspective propose models to develop innovation strategies that are coherent with market needs, the overall firm strategy, and the technologies and resources a firm can use (Clark and Wheelwright, 1994; Tushman and Moore, 1982; Utterback, 1994). Other studies suggest market time and entry modes (Abernathy and Clark, 1985; Abernathy and Utterback, 1978). Strategy development is complicated by the existence of targets that vary over time mainly due to environmental changes. As reported in Table I, major problems in this research area are the definition of an innovation strategy (e.g. the kind of innovation to develop, variables to take into account etc.) Political process Innovation processes may have a political dimension. Some scholars have studied and stressed the symbolical relevance and the political difficulties new projects may encounter (Kidder, 1981). Management of attention, creation of a good currency, internal conflict management and resistance to change are considered as crucial

Task definition; management and control; role assignment; management of the part-whole relationship Problem framing and problem solving; storing/retrieval decisions associated to past projects and their rationale Strategy development and communication Management of attention; creation of a good currency; change management; conflict management Communication among departments due to the development of different thought world Creativity and motivation; blame culture Lack of structured communication (internal and external to the firm); NIH syndrome; loss of architectural knowledge; selection of supporting technologies

Sequence of tasks

Creative process Communication and information flow

Interpretative process

Strategic process Political process

Decisions that evolve over time

Main problems

Analysis perspective

Communication among departments due to the development of different thought world Blame culture Lack of structured communication (internal and external to the firm)

Lack of a strategic vision (short-term vision) Change management; conflict management

Problem framing and problem solving; lack of a structured organizational memory

Procedure neglect; responsibility avoidance; lack of process control; management deficiencies

Hypothesis: SMEs crucial problems


Table I. Innovation process perspective of analysis: problems and needs within SMEs

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problems in innovation development (Van de Ven, 1986). As reported in Table I, to address such problems, the development of agreements among those who are involved in the process and the creation of common perspectives and vision are necessary. Interpretative process Innovation processes have a cognitive and interpretative dimension. Studies in this research area deal with the analysis of the involved actors, cognitive characteristics and the way they interpret their role and the roles of other participants (Dougherty, 1992; Heller, 2000). For example, Dougherty (1992) observed that departments often interpret process goals and operative approaches from different “thought worlds”, making inter-departments communication and collaboration hard. Organizational routines also make innovation processes more complex. To address cognitive problems it is necessary to consider cultural factors (e.g. the use of methodologies to support the identification of different perspectives as a required condition to define agreements). Creative process IDP is a creative process (Slappendel, 1996; Tang 1998). Creativity is the ability to develop new ideas or products based on observed patterns and relationships. Studies, developed in this research area, mostly by psychologists, demonstrated that creativity can be stimulated and fostered. In particular domain-knowledge and motivations are considered as the main contributors to creativity whereas the existence of a blame culture can hinder it (Amabile, 1983). Communication and information flow IDP is an information and communication-intensive process. Studies within this research area have investigated the properties of the exchanged information, roles (internal or external to the firm) among which such information should be exchanged and the characteristics of the information networks (Eppinger, 2001; Morelli et al., 1995; Tushman, 1979). Recording information flows can be useful to identify lack of internal or external connections so as to preserve architectural knowledge, i.e. knowledge related to the parts that constitute the innovation-object (Henderson and Clark, 1990). Organizational routines can make people forget architectural knowledge or develop syndromes such as the not invented here (NIH) syndrome, preventing the recognition of the value of external information and knowledge (Katz and Allen, 1982). The impact of the problems described above may differ based on the context of the IDP. In particular, the lack of specialized resources and financial sources can make these problems more critical within SMEs. In the next section, we consider the problems of SMEs in more detail. Innovation development within SMEs: problems and needs A major topic in the innovation literature is the importance of SMEs for innovation. Studies have shown that SMEs contributed to the main innovations of the twentieth century (Oakey, et al., 1988; Rothwell and Zegveld, 1982; Rothwell, 1994). SMEs have some advantages because of their size. Many are flexible and have strong relationships with customers, enabling rapid response to technical and market shifts. Small firms usually have good internal communications and many have a dynamic and entrepreneurial management style (Rothwell, 1994). As well, some

studies suggest that the average capability of technical people is higher in small firms and that innovations in these firms can be less expensive (Cooper, 1964). SMEs usually explore new technical spaces. In summary, innovation in small firms can be (more) efficient and effective (Vossen, 1998). On the other hand, many SMEs are not innovative at all. Researchers have stressed the differences between a limited number of very innovative small firms and a large number of non-innovative firms (Acs and Yeung, 1999; Hadjimanolis and Dickson, 2000) Many obstacles to innovation in SMEs are also stressed in the literature. The lack of financial resources, inadequacy of management and marketing, lack of skilled workers, weakness in external information and linkages, and difficulty in coping with government regulations are factors that limit their competitiveness (Buijs, 1987; Freel, 2000; Rothwell, 1994). SMEs may be unable to exploit new products because of the limited organizational and marketing capabilities. Other studies discuss cultural barriers to innovation, such as reluctance to change, tendency to ignore procedure, focus on short-term requirements, lack of strategic vision and the diffusion of a blame culture (Filson and Lewis, 2000; Freel, 2000). SMEs’ main problems are due particularly to the scarce attention devoted to organizational and managerial problems especially in the field of innovation (Cobbenhagen, 1999). Table I lists problems that are relevant within SMEs, classified according to the perspective of analysis from which they are usually studied. For example, the tendency to ignore procedures (which are often not codified), not to assume responsibility, the absence of process monitoring activities and a poor management are problems mainly stressed in the studies that interpret the innovation process as a sequence of tasks. Issues related to problem framing and problem solving (mainly due to the absence of technology watch and technology search roles) and the lack of structured organizational memory are mentioned as significant problems in the studies that interpret the innovation process as a flow of decisions. A major problem is also considered the lack of a strategic vision to drive the innovation development. Such problems strongly compromise the success of IDP within SMEs. On the contrary, less crucial for SMEs are problems identified in the studies that interpret the innovation process as a political process (because of the low number of employees and the entrepreneur power), as am interpretative process (again due to the low number of employees who often have more roles) and as a communication and information flow. Problems associated to the creative perspective, such as the existence of a blame culture, depend on the skills and capabilities of the entrepreneur, so they are not common to all firms. A field study: some initial results In this section, we present some initial results of a field study carried out on a sample of 19 SMEs that work in the Puglia region (Italy). The study was designed to investigate needs and problems within Italian SMEs in order to properly design a questionnaire to submit to a significant sample of Italian firms in a future study and to provide an initial test for the hypotheses (problems considered as relevant) proposed in the paper. Sample selection The authors started with a list of approximately 100 firms. All the selected firms were SMEs as defined by the European Commission Recommendation published in the EU


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Official Journal No. L 107 (30/4/96). Different industrial sectors were included so as to not bias the final results. The sample includes firms in the textile, mechanical, agricultural and food, and furniture sector. Such sectors are the most significant in the considered region (and indeed in all of Italy). Firms were initially contacted by phone and asked if they would be willing to participate; 19 firms agreed, and they form the sample for this study. The firms in the sample have between seven and 150 employees (an average of 46) and an average annual turnover of e1.75-18 m (an average of e7 m). Method Firms that agreed to take part in the interview were visited in person. Each interview has lasted about an hour and was conducted with the top manager (usually the owner of the firm) or one of the responsible persons for the IDP. A questionnaire (a first draft of the questionnaire we intend to submit to the final sample of firms) was used to collect data. Interviews where organized in the following way. Initially general questions about innovation were asked, so as to understand the firm’s attitude toward innovation (why innovations are developed) and the main kind of innovations. Then, we investigated the innovation process (how innovations start, departments involved, phases and activities carried out, knowledge involved and supporting techniques). The third part was devoted to the identification of problems and needs. Results Our first finding is that few SMEs pay much attention to innovation (reported by 7/19 interviewees). Just one firm stated that innovation represents the main competitive goal of a SME. Innovation is mainly aimed at improving the quality (16 firms) and marketing properties (12 firms) of a product. However, many firms (15) also consider innovation as a means to reduce costs and improve the production process (nine firms). They develop incremental innovation both related to the product and the process. A few radical innovations are also developed. Most of the firms stated that innovations usually develop based on an idea of the owner-entrepreneur (13 firms) and 11 of them said that, in any case, the role of the owner is fundamental for its promotion. He/she usually defines the firm’s strategy (13 firms). Innovation starts from client suggestions (ten firms), the participation at fairs and exhibitions, marketing analysis and the R&D department (nine firms). Two firms said suppliers suggested innovations while only one firm said that it developed innovation in collaboration with the university. Technological know-how is rarely developed in house: it is mainly acquired by purchasing hardware and software technologies or by accessing external laboratories. Most of the past and future three-year investments firms identified deal with productive plants and information technologies (personal computers and software, in particular for administrative support). This contrasts the observation that many firms (eight firms) said thay have R&D and design departments and with their high reported percentage of the turnover invested in R&D (a reported average of 5 percent). Effective intra-firm communication (18 firms) and flexibility (nine firms) are considered as main SME advantages in innovation development compared with large firms. However, most firms also stated that intra-firm communications are mostly exchanged hierarchically and in many cases there are not direct communications

among departments (five firms stated that no communications are exchanged between R&D and design or between marketing and design departments). The lack of infrastructure and the lack of work flexibility are reported as the most serious obstacles to innovation development (according to eight and seven firms, respectively). Six firms also mentioned as important the difficulty in collecting relevant information and knowledge. Contrary to the literature, just three firms mentioned financial resources as relevant. Finally, only one firm mentioned the difficulty in finding good managers and carrying out the IDP. Process planning and development/execution are the innovation phases recognized as important by most of the firms (nine firms), though not all of them. Just two firms mentioned a learning phase as important. Strategic planning is performed by seven firms, while nine firms stated that the strategy has never been developed. Almost all of the firms mentioned the cost-benefits analysis as one of the performed activities (16 firms). Many firms also mentioned idea generation and design and just a few also considered initial problem-solving/screening of different ideas and final assessment of the innovation results. Most of the firms stated they do not adopt structured techniques or standard procedures to monitor the market (customer needs, technological advancements and competitor performance), develop an innovation strategy or control the IDP. The most used supporting techniques (five firms) were flowcharts. Only one firm mentioned simulation techniques. Many firms declared their interest in the techniques of the IDEF family. Most of the firms were not interested in any of the proposed supporting techniques (techniques are reported in the following section). Finally, based on the different perspective of analysis above mentioned, we asked firms to talk about problems that usually occurred during innovation development. Interviewees generally found it hard to talk about problems. Most of them considered as frequent problems resource allocation and coordination, process monitoring, innovation strategy definition and new idea selection. Less frequent but relevant were information and communication management and collection of information and rationale related to innovation in progress. On the contrary, many firms stated that they never collected innovation-related decision rationales and developed knowledge repository. This is coherent with the fact that learning is not considered as an important innovation process phase. Only five firms said that they would need methods and techniques to support ex-ante and ex-post learning, whereas most of them said they would need techniques to support the process execution. Many of them (nine firms) stated they would not be interested in analysing a SME best practice database. Analysis The picture that emerges from the previous analysis shows a reactive rather than proactive attitude towards innovation by the contacted SMEs (it is important to stress that the sample is composed of the 19 firms that were interested enough to be willing to be interviewed). They are interested in innovation development, but they do not develop an innovation strategy (or even an overall strategy), do not adopt any methods to control and monitor the innovation process and do not record information and knowledge acquired during development and the rationale for it. They ignore many of the activities reported in the literature as fundamental to the development of successful innovations. Moreover, most of the firms were not able to identify problems that occur


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during innovation development. They usually recognize problems that occur very rarely. They are not interested in supporting techniques, so showing cultural barriers to improving the process. They also provided some contradictory answers. For example, firms report few problems with intra-firm communication but also stress lack of communication among departments, which is quite important for IDP (such as marketing and design). The interviews thus provide support for the identification of problems in previous section, as reported in Table I. In next section we propose a review of modelling techniques to support and improve innovation development within SMEs. Techniques to support innovation processes In this section models and techniques to support and improve IDPs within SMEs are examined. Some recent studies showed that innovation can be fostered and supported by the use of structured techniques (Buijs, 1987; Cardinal, 2001). To adopt them, firms would have to follow well-defined procedures and practices. Moreover, they would become more aware of some innovation issues and aspects. The techniques proposed below are indeed adopted by very innovative and successful firms (Libutti, 2000; Maylor 2001; Rinholm and Boag, 1987). Models and techniques are enabling structures (Chiesa et al., 1996): their adoption represents a necessary, though not sufficient, condition to achieve success. Of course, not all innovation problems can be addressed by adopting some technique. Some problems require cultural solutions or government support (such as an increase in the work flexibility, infrastructure building, definition of gatekeeper roles among firms and universities). As a result, such aspects are not examined here. Innovation development process: a model for SMEs Models are tools that can support reasoning and the analysis of the world (Pidd, 1996). They can be used as “facilitators” (i.e., they facilitate the representation of different perspectives about the world and support communication and coordination), to support decision making (i.e., they allow the assessment of the consequences of a decision, so supporting the choice) and to codify knowledge and support learning. Several BMTs can be used during IDP. To group similar BMTs, we present a simple model of an IDP, based on a review of the literature (e.g. During, 1986; Cooper and Kleinschimdt, 1986; Marquis, 1982; Tushman and Moore, 1982; Utterback, 1971; Wheelwright and Clark, 1992; Wolfe, 1994). According to this model, an IDP has three main phases (or macro-activities), namely planning (phase I), development (phase II) and learning (phase III). It is important to note that the phases are not sequentially accomplished; they are rather linked by reciprocal dependencies. As showed by the literature review and field study results, phases I and III (though crucial) are often neglected by SMEs (Rinholm and Boag, 1987). Models for planning. We can distinguish between strategic planning (definition of the firm’s strategy and policy with respect to innovation) and operative planning (design of how a project will be developed). Both cases require agreement among the functions involved in innovation development and between management and operative/technical functions, which in turn requires a common perspective and vocabulary. By making views and vocabularies explicit, models can facilitate communication and understanding of different worldviews, needs and relationships

(Dougherty, 1992). For strategic planning, models might support the communication of the owner/entrepreneur’s vision (often kept tacitly) and criteria for decisions. For operative planning, models explicate assumptions and knowledge, so helping in capturing knowledge of downstream activities at earlier stages of a project (Heller, 2000). This anticipation can avoid mismatch among functions and rework, so reducing cost and time to market. Models can also support the relationships with customers, i.e. to better understand their needs and problems. The use of models for planning is particularly important for SMEs. The lack of resources (temporal, financial, and human resources) makes the planning stage critical for these firms. Planning would prevent SMEs from making technical decisions based on contingencies. Models for development. Innovation development involves exploration of a variety of solutions, the result of which influence successive decisions in a fashion that cannot be defined ex ante. Even so, process models might be used to determine the possible consequences of actions and choices. The execution of a project also requires monitoring and controlling tools. Models can guide action and be used as a standard against which progress is measured (where we are, where we are going). They can represent who is doing what so as to improve the effectiveness of communications. Models can show the relationship between the parts and the whole, so that the vision is not lost when functions focus on their specific needs. Having guidelines to follow is valuable for SMEs (Zutshi et al., nd) who often have technical but not managerial competencies and experiences. Models for learning. Learning means the internalization of knowledge. Within IDP, models can support both ex-ante and ex-post learning. Ex-ante, models can be used to clarify ideas and externalize tacit knowledge. As stated in (Weick, 1979) “you don’t know what you are thinking until you hear what you are saying”. In this way, models provide a base for reasoning and communication. SMEs often work based on very tacit knowledge, so codification of this knowledge is a means to improve how things are done and to industrialize activities. Ex-post models can be used to recollect the sources of problems, problem-solving modes and best practices so as to learn from them. Though every innovation is new, elementary tasks repeat over time, so IDPs usually do not evolve in a completely unpredictable way (Westfechtel, 1999). Models can thus be used to acquire knowledge based on past experiences. Learning is a critical function rarely supported in SMEs (Rinholm and Boag, 1987). As well, models might preserve the knowledge of workers leaving the firm, a particularly pressing problem in SMEs, which have fewer employees, making the loss of even one a serious problem.

BMTs to support innovation development within SMEs In this section we review BMTs for IDP in SMEs. We draw on the database proposed by (Kettinger et al., 1997), which contains 72 techniques and supporting methodologies. The techniques are reviewed based on the perspective of analysis mentioned in the second section. To make the connection, the methods are classified according to their ontology, that is, the entities, categories or class of objects that model uses to describe the world and the relationships among those classes. We identified six main ontologies, namely, activities, states, decision criteria and decision variables, roles, concepts and data flow, that characterize BMTs. Such information is then used to identify, for each perspective, the most suitable supporting techniques, as shown in Table II.


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Sequence of tasks This perspective is a common one for BMTs as many of them represent tasks. Flowcharts, IDEF0, IDEF3 are the most common (e.g. Grover and Kettinger, 1995; Kettinger et al., 1997, Presley et al., 2000). Flowchart and IDEF0 represent what the process does (the activities), IDEF3 and grammatical models show the way process actors work. In particular, IDEF3 depict links among actions developed within a given scenario, defined as the organization structure, based on which it is possible to characterize the goal and define the process border line. The main advantage of these techniques is the possibility to represent different relationships among actions as well as their temporal nature (synchronous or asynchronous). However, due to the difficulty of anticipating the specific activities to be performed and the importance of feedback loops, the creation of a fine-grained task model of the innovation process is probably impossible. On the other hand, coarse-grain models such as the stage models are likely too general to be very useful for a specific project. Still, IDPs are rarely completely new and unpredictable, so a medium-grain level might be useful both in the planning and in the execution phase (Cooper, 1983). It is thus useful to start with a medium-grain level model and to modify it during the process. During phase I, such models can be used to model and compare different alternative strategic approaches. They can also be used to allocate resources and define gates and milestones to measure performance (Goldense, 1993). During phase II, models can help monitor and control the project. Finally, these models might provide valuable insight a-posteriori, so allowing the company to learn about the way the project was performed. For example, a task model might be recorded as the project unfolds and analyzed after the fact to identify problems and possible solutions. Decisions over time These aspects of an IDP can be supported by modeling techniques based on decisions and states, such as simulation models (qualitative and quantitative), decision trees, design rationale, analytical hierarchy process, Petri net, and state transition diagrams (Aalst and Hee, 1996; Lee and Lai, 1991, MacLean et al., 1991, Marples, 1961). Design rationale models provide a structured and formalized framework to make and record decisions. Such models could be extremely useful in SMEs, where decisions are often made based on contingencies. The adoption of these models can force people to consider alternatives so avoiding choices determined by contingent solutions. These techniques can thus be used to structure strategic and operative planning (phase I), to support problem solving during planning and execution (phase I and II) and as knowledge repository during the learning phase (phase III).

Table II. Perspective of analysis and related ontology

Perspective

Ontology

Sequence of tasks Decisions that evolve over time Strategic process Political process Interpretative process Creative process Communication and information flow

Activity, states, roles Decisions, data flow, states Concepts Concepts, roles Concepts, roles Data flow, concepts Data flow, roles

Strategic process Problems associated to this perspective require techniques able to represent concepts. To support the definition of an innovation strategy the use of maps (such as marketing, engineering or manufacturing maps) and models such as the critical success factors are suggested (Wheelwright and Clark, 1992). These models can be extremely useful to SMEs, given that one of their main limits identified was the lack of strategic planning. Maps, such as cognitive maps can be used both as a guide to the definition of a strategy and also as a means to their externalization and communication (Eden and Ackermann, 1992; Fiol and Huff, 1992; Pidd, 1996). Cognitive maps are characterized by two ontologies: concepts and relationships (usually causal relationships) among them, as they are defined by those who the map refer to. Relationships are usually associated to a direction and a value (that measures the intensity of the relationship). The importance of cognitive maps for IDP is stressed in (Russell, 1999; Swan, 1995). Maps are useful to reduce problems associated to communication misunderstandings. For example, Russell (1999) proposes a cognitive map that shows concepts and relationships a SME manager associates to the issue of corporate entrepreneurship. Map development can be a useful means managers can adopt to codify their strategy and vision, to support reasoning (e.g. about the innovation policy and its coherence with the firm strategy) and communication. These techniques can thus be used both as facilitators and learning tools, mainly during the planning and learning phase (phase I and III). Political process Models to support this view and to address the related problems are those whose ontologies are concepts and action for agreement, such as cognitive maps, active-workflow models, and speech interaction modeling (Kettinger et al., 1997; Winograd and Flores, 1986). They can be extremely helpful in providing a base for discussion as well as to formalize and clarify the way it should proceed. Agreements are based on obtainable results and require the definition of responsibilities. Metrics for performance assessment (Goldense, 1993) and role-based models such as role activity diagrams can provide useful (Huckvale and Ould, 1995). Political problems usually arise during planning (phase I) and execution (phase II). The above mentioned techniques can mainly be used as facilitators. Interpretative process Models to address problems related to this perspective are those whose ontologies are concept-based such as cognitive maps and IDEF5 (Grover and Kettinger, 1995). IDEF5 was designed to depict the so-called typologies (or ontologies), which are graphically represented by circles. Different ontologies are related by classification mechanisms (such as generalization, a kind of etc). Such techniques can be mainly used as facilitators. They can be particularly useful during phase I and II. Creative process Problems related to this perspective require cultural solutions, for this reason there are not many supporting techniques. However, some models and methods have been developed to foster creative attitude and brainstorming such as affinity diagramming, Delphi technique, and the “out of the box thinking” method (Giaglis, 1999; Kettinger


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et al., 1997). Also, some studies have shown that engineers solve problems by adopting knowledge and solutions used in the past in new ways (Marples, 1961; Thomke and Fujimoto, 2000). The importance of models to collect the knowledge created during the development of a project and transfer it from one to another project is thus critical (Thomke and Fujimoto, 2000). To this aim design rationale and IDEF3 models as well as most of the earlier mentioned models can be adopted to preserve the project knowledge. Such techniques can be used as learning tools, so trying to eliminate the blame culture that is particularly dangerous during phase I and II. Information and communication flow To address problems related to this perspective, models that facilitate the identification of the characteristics of the information exchanged (and their main properties) as well as persons/roles among which it is exchanged can be useful. Thus, models whose ontologies are entity, information and role-based, such as data flows diagrams, IDEF1 and role active diagrams can be adopted (Albino et al., 2003; Chen, 1976; Giaglis, 1999; Grover and Kettinger, 1995). Such techniques can also be also useful to select the Information and Communication Technologies to support information exchange and to improve the process (Morelli et al., 1995, Tushman 1979). By recording information and communication flows such methodologies provide information that can help identifying the lack of internal and external links, so preserving architectural knowledge (Henderson and Clark, 1990). Due to routine and/or the NIH syndrome, architectural knowledge can be easily lost (Katz and Allen, 1982). These techniques are thus particularly useful during phase I and II to support process management. Also they can be useful during phase III to memorize the adopted rationale and reason about the process development. Based on the above analysis, we argue that different BMTs can be used to support and address several needs and problems that emerge during IDP within SMEs. The analysis is also summarized in Table III, where for each of the mentioned problems (those considered as more relevant for SMEs) the most suitable BMTs, their role and process phase are reported. Conclusions The main result of the paper is the identification of the problems facing SMEs in innovating and possible useful supporting BMTs. Though methods and models alone do not assure the success in IDP, they are enabling factors and can support the creation of strategies, reasoning, insights and communication. The adoption of such techniques, facilitating the codification of the characteristics of the IDP might be particularly useful in those environments where, due to the lack of specialized resources, it is difficult to structure all of the information related to the innovation process and to exploit the related benefits and opportunities. Moreover, formal techniques and methods can have a didactic role. They can teach firms how to develop innovations and also make them more sensible towards innovation, so reducing their tendency to act based solely on intuitions and routine rather than structured knowledge. Among BMTs, design rationales and cognitive maps are most relevant. Design rationales can be used to structure the decision process, capture the decisions made about products and create a sort of organizational memory whereas cognitive maps can be used to

Techniques and models

Procedure neglect; responsibility avoidance; IDEF0; IDEF1, IDEF3; grammatical models; lack of process control; management deficiencies stage models; state transition diagram; role active diagram Problem framing and problem solving; lack of a Design rationale; simulation; decision tree; structured organizational memory state transition diagram Lack of a strategic vision (short-term vision) Maps; IDEF5 Change management; conflict management Active workflow diagram; role-active diagram; tools for performance measurement Communication among departments due to the Cognitive maps; IDEF5 development of different thought world Blame culture Affinity diagramming; Delphi technique; “out of the box thinking” method; design rationale; IDEF3 Lack of structured communication (internal and IDEF1; data flow diagram; role-active diagram external to the firm)

SMEs crucial problems

Role

Facilitator

I, II, III Facilitator; learning support

I, II, III Learning support

I, II

I, II, III Decision-making support; learning support I, III Learning support; facilitator I, II Facilitator

I, II, III Facilitator; learning support

Phase


Table III. The problems/methods matrix

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capture the different interpretations held by various players in the IDP and support the strategy development. Of course, identifying possible methods is easier than seeing them implemented. What is lacking therefore is not applicable BMT methods, but rather process-based research to identify the problems and needs SMEs encounter during innovation development. Our paper has made a start in this direction. We call for further process research on SMEs and IDP to fill this gap in the current literature. These studies could also be useful to record best practices and provide a guide to innovation, similar to the approach adopted for large firms by (Van de Ven and Poole, 1990). This knowledge could be used to create a generalized model of IDP in SMEs and a handbook such as that proposed by (Malone et al., 1999). In this way SMEs could have a standard against which compare their performance as well as a repository of knowledge and a reference to guide their work. This paper represent the first stage of a research project aimed at studying innovation development within SMEs and methods to support it. The field study we presented only refers to SMEs that work in traditional and mature markets, which mostly develop incremental innovations. However they are not representative of all the typologies of SMEs. The analysis we proposed thus needs to be extended to a larger sample of firms and to firms working in new sectors, such as information technology and biotechnology. References Aalst, W.P.M. and Hee, K.M. (1996), “Business process redesign: a Petri net-based approach”, Computers in Industry, Vol. 29, pp. 15-26. Abernathy, W.J. and Clark, K. (1985), “Innovation: mapping the wind of creative destruction”, Research Policy, Vol. 14, pp. 3-22. Abernathy, W.J. and Utterback, J. (1978), “Patterns of industrial innovations”, Technology Review, Vol. 80 No. 7, pp. 40-7. Acs, Z.J. and YEUNG, B. (1999), Small and Medium-sized Enterprises in the Global Economy, The University of Michigan Press, Ann Arbor, MI. Albino, V., Pontrandolfo, P. and Scozzi, B. (2003), “Improving innovation projects by an information-based methodology”, International Journal of Automotive Technology and Management, Vol. 3 No. 3-4, pp. 249-78. Amabile, T.M. (1983), “The social psychology of creativity: a componential conceptualization”, Journal of Personality and Social Psychology, Vol. 45, pp. 357-76. Buijs, J.A. (1987), “Innovation can be taught”, Research Policy, Vol. 16, pp. 303-14. Cardinal, L.B. (2001), “Technological innovation in the pharmaceutical industry: the use of organizational control in managing research and development”, Organization Science, Vol. 12 No. 1, pp. 19-36. Chen, P. (1976), “The entity-relationship model toward a unified view of data”, ACM Transactions on Database Systems, Vol. 1 No. 1, pp. 9-36. Chiesa, V., Coughlan, P. and VOSS, C. (1996), “Development of a technical innovation audit”, Journal of Product Innovation Management, Vol. 13, pp. 105-36. Clark, K.B. and Wheelwright, S.C. (1994), The Product Development Challenge: Competing through Speed, Quality, and Creativity, Harvard Business School Press, Boston, MA. Cobbenhagen, J. (1999), Successful Innovation Towards a New Theory for the Management of Small and Medium-sized Enterprises, Edward Elgar, Cheltenham.

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