Flexible Automation in Developing Countries: The Impact on Scale and Scope and the Implications for Location of Production (Unu Intech Studies in New Technology and Development, 6)

FLEXIBLE AUTOMATION IN DEVELOPING COUNTRIES

The diffusion of computer-based flexible automation (FA) has been seen as a key to the future industrialization of developing countries. If, as was thought, the impact of FA on economies of scope and optimal scale were to reduce optimal scales and therefore firm sizes, industrial production would be ideally located in developing countries. However, Flexible Automation in Developing Countries reveals that the diffusion of FA may actually act as an obstacle to industrialization in these countries. Ludovico Alcorta examines the extent of, and motives for, the diffusion of FA at a global level and then turns to the local and firm level, bringing together indepth studies of sixty-two firms in Brazil, India, Mexico, Thailand, Turkey and Venezuela. Research focuses upon the impact of computer-numericallycontrolled machine tools on scale and scope by exploring changes in lot sizes and product variety (product scale and scope), total plant output (plant scale) and total firm output (firm scale). Barriers to setting up FA-based operations are discussed, as are factors which may affect a decision to locate in a developing country. The contributed studies reveal a relatively slow diffusion of FA in developing countries and it is demonstrated that while FA possibly increases scope, it also requires that plant output be increased in order to maintain efficiency. Alcorta concludes that location in developing countries will probably only be viable for a few large domestic firms, multinationals seeking to relocate simple but labourintensive assembly processes and in countries with significant domestic markets. This work is unique in addressing scale and scope issues in developing countries and in the wealth of information regarding machine tools which it provides. The data provided in the appendix includes official United Nations data, previously unpublished. This will be of use for all research into trends in the use of machine tools. Ludovico Alcorta is an economist and research fellow at UNU/INTECH. He has conducted research on economic and industrial development for fifteen years, primarily in Latin America.

UNU/INTECH STUDIES IN NEW TECHNOLOGY AND DEVELOPMENT Series Editors: Charles Cooper and Swasti Mitter The books in this series reflect the research initiatives at the United Nations University Institute for New Technologies (UNU/INTECH) based in Maastricht, the Netherlands. This institute is primarily a research centre within the UN system and evaluates the social, political and economic environment in which new technologies are adopted and adapted in the developing world. The books in the series explore the role that technology policies can play in bridging the economic gap between nations, as well as between groups within nations. The authors and contributors are leading scholars in the field of technology and development; their work focuses on: • • • •

the social and economic implications of new technologies; processes of diffusion of such technologies to the developing world; the impact of such technologies on income, employment and environment; the political dynamics of technology transfer.

The series is a pioneering attempt at placing technology policies at the heart of national and international strategies for development. This is likely to prove crucial in the globalized market, for the competitiveness and sustainable growth of poorer nations. 1 WOMEN ENCOUNTER TECHNOLOGY Changing patterns of employment in the Third World Edited by Swasti Mitter and Sheila Rowbotham 2 IN PURSUIT OF SCIENCE AND TECHNOLOGY IN SUB-SAHARAN AFRICA The impact of structural adjustment programmes John Enos 3 THE POLITICS OF TECHNOLOGY IN LATIN AMERICA Edited by Maria Inês Bastos and Charles M.Cooper 4 EXPORTING AFRICA Technology, trade and industrialization in Sub-Saharan Africa Edited by Samuel M.Wangwe 5 TECHNOLOGY, MARKET STRUCTURE AND INTERNATIONALISATION Issues and policies for developing countries Nagesh Kumar and N.S.Siddharthan 6 FLEXIBLE AUTOMATION IN DEVELOPING COUNTRIES The impact on scale and scope and the implications for location of production Ludovico Alcorta

FLEXIBLE AUTOMATION IN DEVELOPING COUNTRIES The impact on scale and scope and the implications for location of production Ludovico Alcorta in collaboration with Ruy de Quadros Carvalho, Lilia Domínguez, Flor Brown Osvaldo Alonso, Francisco Tamayo, Vanessa Cartaya, Ghayur Alam, Hacer Ansal and Peter Brimble

London and New York

INTECH Institute for New Technologies Published in association with the UNU Press

First published 1998 by Routledge 11 New Fetter Lane, London EC4P 4EE This edition published in the Taylor & Francis e-Library, 2005. “To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.” Simultaneously published in the USA and Canada by Routledge 29 West 35th Street, New York, NY 10001 © 1998 UNU/INTECH All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging in Publication Data Alcorta, Ludovico. Flexible automation in developing countries/Ludovico Alcorta. p. cm.—(UNU/INTECH studies in new technology and development; 6) Includes bibliographical references. 1. Automation—Economic aspects—Developing countries. 2. Computers—Economic aspects—Developing countries. 3. Industrial location—Developing countries. I. Title. II. Series. HC59.72.A9A43 1998 338′.064–dc21 98–11152 CIP ISBN 0-203-19352-0 Master e-book ISBN

ISBN 0-203-26540-8 (Adobe eReader Format) ISBN 0-415-19153-x (Print Edition)

CONTENTS

List of figures

x

List of tables

xi

List of contributors

xvi

Acknowledgements

xviii

List of abbreviations

xx

Introduction

1

Background

1

Objectives

4

Research questions

4

Organization of this book

6

PART I Concepts, method and synthesis

8

1

Scale and scope: concepts and issues

9

1.

Introduction

9

2.

Origins of economies of scale theory: from ‘division of labour’ to cost curves

10

3.

Scale, economies of scale and optimal scale: definitions, sources and dimensions

12

4.

Scope and economies of scope: origins, definitions and sources

15

5.

Flexible automation and economies of scale and scope: the ‘modern technology’ literature view and its critics

21

6.

Technical change, costs, scale and scope: a graphical representation of the issues

30

2

Methodology: research design and implementation

36

1.

Introduction

36

2.

Approach, method and unit of analysis

37

vi

3.

Sampling: technology, industries and countries

39

4.

Data requirements

45

5.

The model case study: Hydraul

49

6.

Implementation of the study

63

3

The diffusion of flexible automation in developing countries

68

1.

Introduction

68

2.

International diffusion of metal-cutting machine tools

69

3.

Surveyed countries’ CNC machine-tool diffusion in an international perspective

80

4.

Diffusion of flexible automation in selected firms

83

5.

Flexible automation and new organizational techniques

91

6.

Factors underlying the diffusion of CNC machine tools in surveyed firms

97

7.

The process of intra-firm diffusion of CNC machine tools

102

8.

Conclusions

106

4

Impacts on scale and scope

109

1.

Introduction

109

2.

Changes in product scale

110

3.

Changes in product variety or scope

113

4.

Changes in plant and firm scale

119

5.

Factors underlying increases in plant scale

122

6.

Other price and efficiency effects

134

7.

Conclusions

136

5

Flexible automation and location of production in developing countries

141

1.

Introduction

141

2.

Flexible automation and production and cost conditions in engineering

142

3.

Scale and scope and firm entry

147

4.

Transport costs, just-in-time and infrastructure

153

vii

5.

Factor prices and biases

156

6.

Is large local demand still necessary?

158

7.

Location of production in developing countries: an assessment

159

6

Conclusions and policy recommendations

164

PART II The country studies

172

7

The impact of flexible automation on scale and scope in the Brazilian engineering industry RUY DE QUADROS CARVALHO

173

1.

Economic and technical change, 1980–93

173

2.

Technical change in the Brazilian engineering industry: the case-study evidence

180

3.

The impact of flexible automation on scale and scope

194

4.

Flexible automation and costs

203

5.

Conclusion: industrial restructuring, flexible automation, scale 210 of production, and the prospects for the location of production in Brazil

8

The impact of flexible automation on scale and scope in the Mexican engineering industry LILIA DOMÍNGUEZ AND FLOR BROWN

213

1.

Introduction: macroeconomic and industrial performance

213

2.

Technical change in the manufacturing industry: case-study evidence

217

3.

Economies of scope

229

4.

Plant and firm scale

234

5.

Costs and prices

240

6.

Main findings and conclusions

249

9

The impact of flexible automation on scale and scope in the Venezuelan engineering industry OSVALDO ALONSO, FRANCISCO TAMAYO AND VANESSA CARTAYA

254

1.

Introduction: the political and economic context

254

viii

2.

Technical change in the engineering industry: the case-study evidence

262

3.

The impact of flexible automation on scale and scope

272

4.

Changes in unit costs and profits

279

5.

Conclusion: flexible automation, scale and location of production in Venezuela

290

10

The impact of flexible automation on scale and scope in the Indian engineering industry GHAYUR ALAM

295

1.

Introduction: industrial development in India

295

2.

Diffusion of flexible automation in the Indian engineering industry

300

3.

Flexible automation and economies of scope and scale

311

4.

Production costs

316

5.

Conclusions

322

11

The impact of flexible automation on scale and scope in the Turkish engineering industry HACER ANSAL

326

1.

The Turkish economy and the engineering industry

326

2.

The diffusion of flexible automation at firm level

333

3.

The impact of flexible automation on scale

342

4.

Changes in unit costs

352

5.

Conclusions

358

12

The impact of flexible automation on scale and scope in the Thai engineering industry PETER BRIMBLE

361

1.

Introduction: industrial development in Thailand

361

2.

Evidence on diffusion from the case studies

367

3.

Firm-level impacts of flexible automation

379

4.

Plant scale and unit costs

383

5.

Summary and conclusions

386

Appendices

393

ix

Bibliography

426

Index

449

FIGURES

1 Short-run unit costs in flexible and inflexible plants 2 Output space for a two-product firm 3 Economies and diseconomies of scope 4 Optimal scale of production for composite good Y* under alternative technologies

17 19 32 33

TABLES

2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10 3.11 3.12 3.13 4.1 4.2 4.3 4.4 4.5

Engineering industry’s value added and output as shares of total manufacturing of surveyed countries, 1963–91 Hydraul: basic economic data Hydraul: batch size composition, before and after Hydraul: product diversity, before and after Hydraul: sources of scale increases under old and new technology Hydraul: costs and unit costs Hydraul: unit cost structure Hydraul: main capital investments Hydraul: employment Hydraul: productivity changes Value of world machine-tool consumption, 1974–94 Value of world metal-cutting machine-tool production, 1973–94 Metal-cutting machine-tool net imports, 1978–94 CNC and non-CNC metal-cutting machine-tool production, 1980– 94, in units CNC and non-CNC metal-cutting machine-tool production, 1980– 94, in value Total CNC machine-tool net imports, 1989–94 CNC machine-tool stocks in selected countries, 1982–94 Diffusion of flexible automation by type of equipment in surveyed countries Metal-cutting CNC machine tools in engineering by firm size, industry and type of ownership in surveyed countries Density of automation by firm size, industry and type of ownership Diffusion of new organizational concepts by density of automation Diffusion of new organizational concepts by firm size, industry and type of ownership Motives for diffusion of flexible automation by firm size, industry and ownership Changes in batch size by density of automation Changes in product scale by firm size, industry and type of ownership Changes in product diversity or scope by density of automation Changes in product diversity or scope by firm size, industry and ownership Changes in scale of production by density of automation

41 50 56 57 59 60 60 61 62 62 71 72 73 76 76 77 81 86 87 89 93 94 99 112 112 115 116 120

xii

4.6 4.7 4.8 4.9 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 7.10 7.11 7.12 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 8.10 8.11 8.12 9.1

Changes in unit costs Unit values of CNC metal-cutting machine tools in selected countries, 1975–94 Relative unit values of CNC and non-CNC lathes Relative unit values of machining centres and non-CNC machine tools (excluding lathes) Brazil: industrial manufacturing output, 1980–93 Brazil: the mechanical engineering capital goods industry, 1980–93 Brazil: sales and exports of the autoparts industry, 1980–93 Brazil: basic characteristics of the sampled firms Brazil: sales, employment, productivity and exports in selected engineering firms, 1985 and 1993 Brazil: diffusion of microelectronics-based automation in selected engineering firms, 1994 Brazil: gains in setting-up and machining cycle times for single parts in selected engineering firms, 1985 and 1994 Brazil: distribution of machining batch sizes in sampled firms, 1985 and 1994 Brazil: increase in product diversity in sampled firms, 1985 and 1994 Brazil: estimates of plant capacity in sampled firms, 1985 and 1993 Brazil: indicators of efficiency gains in total plant setting-up time for sampled firms, 1985 and 1994 Brazil: unit cost structures in sampled firms, 1985 and 1994 Mexico: characteristics of sampled firms, 1994 Mexico: types of machines in sampled firms, 1994 Mexico: organization of production processes in sampled firms before and after flexible automation adoption Mexico: labour, organization and administration in sampled firms Mexico: batch sizes in sampled firms Mexico: changes in product diversity in sampled firms Mexico: volume of production and capacity utilization in sampled firms Mexico: gains in lead-time reduction, labour productivity and quality in sampled firms Mexico: changes in price and total unit cost, in local currency real terms, in sampled firms Mexico: structure of costs in sampled firms, 1989 and 1993 Mexico: changes in employment levels in sampled firms Mexico: changes in sales, price, total cost and profit margin, in local currency real terms, in sampled firms Venezuela: average annual growth of GDP, exports and imports, and average export prices for Venezuelan oil industry, 1950–90

120 132 133 133 175 175 177 181 184 189 195 197 198 200 202 205 218 220 225 227 231 233 235 238 241 243 246 247 255

xiii

9.2

Venezuela: structure of manufacturing industry, 1968, 1974, 1984 and 1991 9.3 Venezuela: the engineering and autoparts industries: evolution of the main variables, 1988–91 9.4 Venezuela: CNC equipment by type, 1992 9.5 Venezuela: sampled firms’ size, product and ownership type 9.6 Venezuela: main economic indicators in sampled firms 9.7 Venezuela: efficiency indexes before automation in sampled firms 9.8 Venezuela: flexible automation and organizational improvements in sampled firms 9.9 Venezuela: reasons for adoption of flexible automation in sampled firms 9.10 Venezuela: setting-up times and average batch sizes in sampled firms 9.11 Venezuela: changes in the scope of production in sampled firms 9.12 Venezuela: changes in production volumes in sampled firms 9.13 Venezuela: utilization and efficiency indicators in sampled firms 9.14 Venezuela: changes in unit cost in sampled firms 9.15 Venezuela: changes in unit cost by source in sampled firms 9.16 Venezuela: share of capital and labour in total unit costs in sampled firms 9.17 Venezuela: changes in reject and waste rates and raw material inventories in sampled firms 9.18 Venezuela: changes in energy, maintenance and repair components of unit cost in sampled firms 9.19 Venezuela: R&D, marketing and administration shares in total unit costs in sampled firms 9.20 Venezuela: prices, profits and delivery times in sampled firms 10.1 India: machine-tool industry, 1980–93 10.2 India: machine-tool industry performance in real terms, 1980, 1984, 1988 and 1992 10.3 India: foreign collaborations agreements, 1980–94 10.4 India: employment and diffusion in sampled firms 10.5 India: reasons for the adoption of flexible automation in sampled firms 10.6 India: changes in setting-up times in sampled firms 10.7 India: delivery requirements and batch sizes in sampled firms 10.8 India: changes in product diversity in sampled firms 10.9 India: changes in machining times in sampled firms 10.10 India: changes in rejection rates in sampled firms 10.11 India: changes in machine availability in sampled firms 10.12 India: numbers of conventional machines replaced by CNC machines in sampled firms 10.13 India: cost of equipment in sampled firms

256 260 261 263 265 267 269 271 274 277 277 280 282 282 283 283 285 287 289 298 299 299 303 304 311 312 314 315 316 316 317 318

xiv

10.14 India: changes in labour requirements of sampled firms 10.15 India: changes in annual labour cost in sampled firms 10.16 India: changes in material inventories in sampled firms 10.17 India: changes in space requirements in sampled firms 11.1 Turkey: economic trends, 1977–92 11.2 Turkey: trends in manufacturing, 1977–92 11.3 Turkey: real wage index in manufacturing, 1980–91 11.4 Turkey: share of the engineering industry in total manufacturing value added, 1980–90 11.5 Turkey: structure of the engineering industry, by subsector, 1983–9 11.6 Turkey: value added per employee in the engineering industry, 1987– 90 11.7 Turkey: production, employment and productivity indexes in engineering industry subsectors, 1987–91 11.8 Turkey: main characteristics of sampled firms 11.9 Turkey: changes in machine-tool adjustment time in sampled firms 11.10 Turkey: batch sizes before and after flexible automation adoption 11.11 Turkey: percentage increases in product diversity 11.12 Turkey: export performance of sampled firms before and after flexible automation 11.13 Turkey: cumulative machining times for typical batch sizes in sampled firms 11.14 Turkey: changes in plant output, production capacity and sales in sampled firms 11.15 Turkey: changes in employment and labour productivity in sampled firms 11.16 Turkey: capacity utilization rate in sampled firms, 1993 11.17 Turkey: changes in unit cost in sampled firms 11.18 Turkey: changes in the shares of manufacturing and overhead costs in unit costs in sampled firms 11.19 Turkey: changes in the shares of capital and labour costs in unit costs in sampled firms 11.20 Turkey: changes in raw materials’ share in unit costs and in scrap rates in sampled firms 11.21 Turkey: changes in the share of energy and repairs in unit costs in sampled firms 12.1 Thailand: summary information on companies approached for interview 12.2 Thailand: characteristics of sampled firms 12.3 Thailand: reasons for introducing flexible automation in sampled firms 12.4 Thailand: effects of flexible automation on set-up times in sampled firms

318 319 320 321 327 329 329 330 331 331 332 335 344 345 346 347 348 349 350 351 353 355 356 357 358 368 371 373 380

xv

12.5 Thailand: effects of flexible automation on batch size and processing time in sampled firms 12.6 Thailand: effects of flexible automation on product diversity in sampled firms 12.7 Thailand: effects of flexible automation on unit costs in sampled firms A.1 Total metal-forming and metal-cutting machine-tool production, 1973–94 A.2 World metal-cutting machine-tool production, 1973–94 A.3 CNC and non-CNC lathe production, 1975–94 (units) A.4 CNC and non-CNC lathe production, 1975–94 (US$m.) A.5 Production of machining centres, 1986–94 (units) A.6 Production of machining centres, 1986–94 (US$m.) A.7 Total machine-tool imports, 1962–94 A.8 Total machine-tool exports, 1962–94 A.9 Total metal-cutting machine-tool exports, 1978–94 A.10 Total metal-cutting machine-tool imports, 1978–94 A.11 Total lathe exports, 1978–94 A.12 Total lathe imports, 1978–94 A.13 Total CNC lathe exports, 1989–94 A.14 Total CNC lathe imports, 1989–94 A.15 Total machining centre exports, 1989–94 A.16 Total machining centre imports, 1989–94 A.17 Other CNC metal-cutting machine-tool exports, 1989–94 A.18 Other CNC metal-cutting machine-tool imports, 1989–94 A.19 World machine-tool consumption, 1973–94

382 384 387 393 394 396 398 400 401 402 406 410 412 414 416 418 419 420 421 422 423 424

CONTRIBUTORS

The following contributors have contributed to the second part of this book: Ghayur Alam is a zoologist and business administrator with a PhD from the University of Manchester. He is director of the Centre for Technology Studies, Gurgaon, Haryana, and is a consultant on issues of technology transfer and capabilities. Osvaldo Alonso is an economist with an MSc in Science and Technology from the Centre for Development Studies (CENDES), Central University of Venezuela (UCV). He is a Research Fellow at FIM-Productividad, Venezuela’s research institute on productivity, and a private consultant in the fields of competitiveness, automation and human resource development. Hacer Ansal is a civil engineer with an MSc in Engineering from Northwestern University and a PhD from Sussex University. She is an associate professor in the Faculty of Management, Department of Economics, Istanbul Technical University. Peter Brimble is an economist with MAs in Economics from Georgetown and Sussex Universities and a PhD from Johns Hopkins University. He is currently president of The Brooker Group Ltd, an investment advisory, consultancy and business research firm in Bangkok. Flor Brown is an economist with postgraduate studies in Mexico. Currently she is lecturer at the Graduate Program in Economic Sciences, School of Sciences and Humanities, National Autonomous University (UNAM), Mexico. Vanessa Cartaya is a development sociologist with postgraduate and doctoral studies in France, United States and Venezuela. At the time of writing she was director of the Centre for Economic and Social Research (CIES) in Caracas, Venezuela. Lilia Domínguez is an economist with an MA in Economics from the University of East Anglia and doctoral studies in the New School for Social Research, New York. She is lecturer at the Graduate Program in Economic Sciences, School of Sciences and Humanities, and at the Faculty of Economics, National Autonomous University (UNAM), Mexico. Ruy de Quadros Carvalho is a business administrator with an MA in Political Science from the University of Campinas (UNICAMP) and a PhD

xvii

from Sussex University. He was director of Brazil’s Institute for Applied Economic Research (IPEA) and government advisor on technology and is currently a research fellow at UNICAMP. Francisco Tamayo is a chemical engineer and MBA from the Institute for Advanced Business Studies (IESA) in Venezuela. He is advisor to the Logistics manager in Venezuela’s national telephone company and a private consultant and lecturer on productivity and total quality.

ACKNOWLEDGEMENTS

It would not have been possible to write this book without the assistance and support of many colleagues, and my friends and family. Professor Charles Cooper, UNU/INTECH’s Director, provided the opportunity for me to engage in this research. He set standards of rigour and achievement which I hope have been matched. The academic staff at UNU/INTECH were a source of continual inspiration and helpful comments. Larry Westphal’s insights were particularly useful in the design stage of the project, while my lunch discussions with Nagesh Kumar often helped me to make sense of issues. Towards the end Mary-Anne Schenk was an efficient and organized research assistant, and Sen McGlinn significantly enhanced the text of the country studies. I must thank also the consultants involved in the study who, sometimes against their own judgements, closely followed the requests made of them. In addition, Martin Bell, Geske Dijstra, John Humphrey, Staffan Jacobsson, Jorge Katz, John Meyer, J.Oosterling, Wilson Peres, Charles Sabel, Ed Steinmueller and Erol Taymaz contributed their name and knowledge to a lively workshop held in Maastricht, as well as to the improvement of individual papers delivered there. My special gratitude goes to Staffan Jacobsson whose comments throughout have presented a challenge. The study benefited also from the support of the many manufacturers, users and institutions involved in diverse ways with flexible automation. They are too numerous to name individually here, except perhaps for Brian Stilwell, Jan Raemackers and Les Pratt who were especially helpful in generating understanding of the potential and the limitations of the new technologies. Henri Maurer, from the European Machine Tools Committee (CECIMO) in Brussels, supplied valuable information on machine-tool production. Ronald Janssen, from the United Nations Statistical Division in Geneva, introduced me to the UN’s COMTRADE data and replied promptly to my regularly ‘urgent’ demands. The acknowledgements would not be complete without an expression of my thanks to my wife and children—twins were born during the course of the project —who put up with most of the difficult times I had to go through while completing this research.

xix

None of those acknowledged here are, of course, responsible for any errors that may remain in the book. Ludovico Alcorta Research Fellow Institute for New Technologies United Nations University Maastricht

LIST OF ABBREVIATIONS

AMT CAD CAE CAM CECIMO CM CNC ECE EOS FA FMS GDP GNP GT ISIC ISO JIT MES MIR NAFTA NPD OCEI OECD OEM PDVSA PLCs R&D

Association for Manufacturing Technology Computer-aided design Computer-assisted engineering Computer-aided manufacturing European Committee for Co-operation of the Machine-Tool Industries Cellular manufacturing Computer numerical control Economic Commission for Europe Economies of scale Flexible automation Flexible manufacturing systems Gross Domestic Product Gross National Product Group technology International Standard Industrial Classification International Standards Organization Just-In-Time production Minimum efficient scale Minimum investment requirements North America Free Trade Agreement New product development Oficina Central de Estadística e Informática Organisation for Economic Co-operation and Development Original equipment manufacturer Petroleos de Venezuela Programme logic controllers Research and development

xxi

SITC SMEs TQM UNIDO UNU/INTECH

Standard International Trade Classification Small and medium-sized enterprises Total quality management United Nations Industrial Development Organization United Nations University/Institute for New Technologies

INTRODUCTION

Background Ever since Adam Smith gave expression to his now-famous dictum, ‘the division of labour is limited by the extent of the market’, the issue of economies of scale and optimal scale has figured prominently in the economics discussion. Smith pointed out that larger markets permit greater specialization of labour and machinery, which leads to significant unit-cost reductions. Other factors, such as technological relationships, permitting equipment having greater capacity with a less than proportional increase in investment, and indivisibilities, which make it worthwhile to spread the costs of lumpy equipment, initial product development or setting-up machines over a larger output, also have been considered sources of economies of scale. Economic efficiency, since Smith, has been closely connected to increases in scale. Developing countries’ industrialization has always been limited by increasing optimal scales. The small size of their domestic markets has prevented industries being established or meant that, when established, firms would be producing lower volumes and at unit costs far higher than those of efficient plants elsewhere. Producing at suboptimal levels, in turn, would require high domestic protection, with attendant effects on social welfare. Changes in consumer preferences, income levels, macroeconomic conditions and/or the degree of foreign competition would lead to unused capacity—and, therefore, even higher unit costs and more protection—or to the closure of the facility. Exports could provide a way out of the scale problem, but a minimum of efficiency and learning is often necessary prior to entering foreign markets. During the 1980s and early 1990s a substantial economics, management and engineering ‘modern technology’ literature emerged claiming that new technologies, particularly microelectronics-based forms of automation and design and associated organizational modifications, are leading to fundamental changes in economies of scale. It is said that, contrary to previous ‘mass production’ technologies, where increases in scale were crucial to unit-cost reductions, recent changes in product and process technologies are increasing the flexibility of production units, enabling a switch to the manufacture of a wider variety of goods resulting in falls of optimal scales of output or ‘descaling’.

2 INTRODUCTION

At product level, it is argued that, unlike ‘specialized’ old technologies, the capacity of new technologies or flexible automation (FA) to integrate diverse equipment and functions and to be programmed helps reduce minimum batch sizes—i.e. quantities of the same product treated in a certain process or sequence of operations—by reducing setting-up times and costs. In addition, by allowing production facilities to vary their product range with ease, to use their equipment fully and reduce setting-up costs, FA leads to economies of scope—i.e. cutbacks in unit costs due to joint-production. At plant level, it is asserted that FA is substantially shrinking the size of machinery and plants while at the same time making it possible for most capital equipment to be available in a wider spectrum of capacities, which, together with falling semiconductor prices, are drastically cutting the cost of capital equipment and allowing the emergence of smaller efficient production facilities. Critics argue that there is no reason why FA should lead to reduction in plant scale rather than to ‘scaling-up’. It is claimed that physical size of equipment and plant should not be confused with economic size, as ‘smaller’ equipment may have larger production capacity. Furthermore, by reducing setting-up times and expanding variety, FA may allow increase in total plant output, so that scale and scope economies at product level reinforce scale economies at plant level. It does not follow either that because equipment is physically smaller it costs less. Despite falls in the cost of microchips and computers, and irrespective of their increase in power, the cost of the production equipment that uses them may still be higher than the technologies it replaces. Availability of equipment in smaller capacities would reduce plant scales only if equipment cost falls in line with capacity. Otherwise, it means no more than that smaller firms may have access to these technologies but at lower efficiency levels. At firm level, it is contended, FA will increase research and development (R&D) and marketing ‘fixed’ costs. R&D costs could rise because of the considerable backlog of scientific and engineering knowledge required for the new products, the increasing technical complexity and novelty of many products, the wider range of products on which R&D is done, the larger design efforts required to take full advantage of the more flexible, and faster, manufacturing capabilities, and the sizeable investments in software and computer specialists necessary to link design to manufacturing and other functions of the firm. Marketing costs also could rise because of the higher information requirements for selling and the growing advertising expenditures necessary to inform on the availability of new products. The net effect of these factors, it is argued, could be ‘scaling-up’ rather than ‘de-scaling’, as higher levels of output may be needed to amortize increasing R&D and marketing ‘fixed’ costs. Falling optimal scales resulting from the adoption of FA may have important implications for developing countries, according to the ‘de-scaling’ literature. They may increase the efficiency of small-scale production and, insofar as some minimum optimal or efficient scale is a barrier to entry, lead to more entry and competition. They may help to cope with the uncertainties created by variable demand or by a changing supply of inputs. They may result also in the more widespread impact of the various forms of learning associated with experience

INTRODUCTION 3

and of the externalities ensuing from the acquisition and use of new knowledge. They could pave the way to new patterns of decentralized industrialization based on small production units located outside of urban centres. They may also enhance opportunities for developing countries’ industrial firms to compete successfully in international markets. However, even if plant and firm scales increase, there may still be opportunities for localization of production in developing countries, as long as economies of scope can be reaped. Provided there is demand for the wider product range, it may still be economically justifiable to start industrial production, as total plant or firm capacity may be fully used by producing adequate quantities of individual products. Efficient production for the local market may, in turn, be the first step towards successful entry into foreign markets. In short, working either through lower optimal scales or economies of scope, FA may positively contribute to the establishment of industry in developing countries. Conversely, higher optimal scales and lack of economies of scope mean that any advance towards industrialization achieved by developing countries, particularly in the context of a reduction of trade barriers around the world, will be reversed as local firms have to compete with more efficient producers from abroad. A progressive loss of international industrial competitiveness may, in turn, result in primary product or cheap-labour trade specialization, with a potentially deleterious effect on domestic income, employment and the environment. Higher optimal scales and lack of economies of scope may also result in lower potential for industrial learning and for the spreading of externalities, and so lead to ‘forgetting’ what was learned in the past. They could bring about a more centralized pattern of industrialization based on a small number of firms or ‘enclaves’ selling to world markets but with few ‘spill-overs’ to the rest of the domestic economy. Whatever the merits of these arguments and counter-arguments, and despite the apparent widespread diffusion of FA, especially in developed countries, and the potential impact on location of industrial production, there is very little empirical evidence supporting either the ‘de-scaling’ or the ‘scaling-up’ view. Few systematic studies have been done in developed countries on the impact of FA on product scale and scope, and even fewer on the effect of FA on plant and firm scale. Indeed, by comparison to the wealth of industry-specific and comparative empirical research on scale issues done in the 1950s, 1960s and 1970s by authors such as Bain (1954, 1956), Chenery (1949), Pratten (1975) and Scherer et al. (1975), hardly any fresh research on scale has emerged during the 1980s. What little fresh research there is, is based on a few observations, journalistic sources, or reviews or updating of previous work. In developing countries, despite research showing an increased diffusion of FA, the evidence on scale and scope is even more meagre and amounts to a couple of simulation exercises and case studies.

4 INTRODUCTION

Objectives The potential impact of FA on industrial development clearly warrants careful analytical examination of the issues involved and calls for a body of empirical evidence on which to base such analysis. Accordingly, the main purposes of this book are: to develop a simple conceptual framework for the discussion of the impact of FA on scale and scope; to present the results of empirical research carried out in several developing countries on the effects of FA on scale and scope; and to examine the possible implications for the location of industrial production in developing countries. The conceptual framework will be based on economic production and cost theory. There is a well-established tradition in economics, beginning with Adam Smith (1776) and running through Marshall (1890), Viner (1953) and presentday neo-classical economists, which elaborates on concepts such as returns to scale, economies of scale, optimal scale and indivisibilities. There is also a much younger, albeit equally important, body of neo-classical theory, beginning perhaps with Stigler (1939) and followed, after many years of individual and team effort, by seminal work by Baumol, Panzar and Willig (1988), that has introduced issues of flexibility, output variety and economies of scope into economic theory. These two traditions will constitute the backbone of our conceptual framework. Admittedly, economic theory is ill-equipped to deal with issues of technological change because of its convexity assumption, its lack of a proper understanding of the complexities and dynamics involved in technological change and its disregard of a wealth of empirical evidence on how firms actually operate (Baumol 1987; Morroni 1992; Nelson 1994; Nelson and Winter 1982; Romer 1990, 1994). But for the problem at stake, which is essentially one of a comparatively static nature —whether a change in technology results in changes in economies of scale and scope—static economic theory would seem to be a reasonable starting-point for organizing the issues and data. Given that, unlike many developed countries, hardly any developing country has carried out systematic surveys of use of FA by manufacturing firms on which to base a fully fledged statistical analysis and that, in any case, the overall number of firms using FA in developing countries was expected to be low, the main approach of the research reported here was an in-depth analysis of data obtained from several case studies. Some sixty-two firms in six developing countries— Brazil, India, Mexico, Thailand, Turkey and Venezuela—were examined for this research. Combined with secondary data available internationally, this approach should provide an overall picture of the diffusion and the scale and scope of the impact of FA in developing countries. Research questions The research was essentially exploratory: there was no general presumption of which way the main results would go. Although there were some expectations regarding specific results, these were neither in line with the ‘conventional

INTRODUCTION 5

wisdom’ nor with the views of many colleagues and consultants participating in the project. There was an advantage in engaging consultants with different expectations, as this imposed a much tougher standard on data collection and interpretation. The very categorical views expressed in the literature and shared by many colleagues suggested that the overall research approach had to be slightly indeterminate and framed in terms of open-ended research questions rather than precisely defined hypotheses. Three questions guided this research: 1. Has flexible automation diffused to developing countries? To what extent? What factors account for its diffusion? 2. What has been the impact of flexible automation on product, plant and firm scale and scope? Has flexible automation reduced plant and firm optimal scale and increased economies of scope? Or, conversely, has the adoption of flexible automation enticed the production of larger optimal volumes of plant and firm output? What factors account for the changes? 3. What has been the impact of flexible automation on the location of industrial production in developing countries? The first question is contextual and will be addressed at two levels. First, it will be addressed at the level of developing countries in general. On the basis of secondary data gathered from a variety of official and private sources we will attempt to depict the extent of diffusion of FA in developing countries. Second, it will be examined in the context of each of the six countries under study, particularly regarding the issue of the determinants of the diffusion of FA. The second question addresses the main subject matter of this research and will be examined with the help of country studies data based on firm interviews. Detailed interviews were conducted in selected firms to obtain data on their experience in using old and new technologies, as well as on output level, product variety and costs. Qualitative accounts were obtained which constitute a significant part of our data set, but great effort was expended in obtaining quantitative data. As has been pointed out, much of the discussion in this field is based on impressions built on limited qualitative assertions, simple observations or journalistic evidence which, apart from being academically questionable, does not give any sense of the magnitude of the issues under scrutiny. Identifying indicators for the concepts under analysis forced all those involved to be precise about intended meanings and the data to be collected. Seeking detailed quantitative data in the context of open-ended interviews also allowed for an immediate check on the consistency of what was being said by the interviewee. In some firms where it was not feasible to obtain the quantitative data required, it was possible to resort to qualitative discussions. The third question looks into the implications FA would have on the location of production in developing countries. Of particular interest were the impact which FA, working through scale and scope, has had on changes in industrial organization both internationally and domestically and the implications for entry

6 INTRODUCTION

by developing-country firms. However, because FA may have a bearing also on location through its impact on production and costs conditions, factor prices and biases and infrastructure requirements, we will address these issues too. Lack of relevant skills or transport systems could, for instance, act as a powerful deterrent to the successful use of FA in developing countries. For the purposes of this research we will take a rather broad approach to the definition of flexible automation. Initially, the emphasis was mainly on microelectronics-based automation and design hardware and software. After some preliminary interviews and discussions with colleagues and consultants for the research it became apparent that the diffusion of some of the new technologies in the countries under study had been closely, even ‘inseparably’, associated with the diffusion of a number of ‘organizational techniques’ which pertain to the way human and material resources, including the new hardware, are organized. The ‘complementarity’ between the ‘hard’ and ‘soft’ sides of technology was something emphasized by the literature. It was necessary, therefore, to define FA in such a way as to take this fact into account. Thus, for the purposes of this book, FA should be understood as the combination of the new microelectronicsbased forms of automation and associated organizational techniques. Indeed, the research should help to elucidate the nature of the relationship between the new ‘hardware’ and the new ‘organizational techniques’. Organization of this book The book is divided into two parts. Part I focuses on the conceptual and methodological foundations of the research and presents the main aggregate results. Chapter 1 briefly examines the evolution of scale and scope concepts since their inception in economic theory and develops a graphic conceptual framework of the issues at stake. Chapter 2 discusses the methodological approach taken and presents the detailed firm case study which was used as a model for fieldwork in developing countries. Chapter 3 addresses the questions of the diffusion and the motives for the adoption of FA in developing countries by examining world FA production and trade data and on the basis of the consolidation of diffusion data produced in individual country studies. Chapter 4 summarizes the main findings on the impact of FA on scale and scope at three levels—product, plant and firm —also on the basis of consolidated data from individual country studies. It then analyses the main reasons for such impact. Chapter 5 draws implications of the growing diffusion of FA for location of production in developing countries, and Chapter 6 presents the main overall conclusions and policy recommendations. Part II of the book presents individual country studies: Brazil (Chapter 7); Mexico (Chapter 8); Venezuela (Chapter 9); India (Chapter 10); Turkey (Chapter 11); and Thailand (Chapter 12). Most studies are similarly structured, beginning with a brief description of macroeconomic and industrial trends and policies, then moving on to discuss developments in the engineering industry including, where relevant, the manufacture of FA equipment. Country studies then analyse the diffusion of FA in sampled firms, covering the amount and

INTRODUCTION 7

types of equipment, the extent of operations being covered by FA and the process of diffusion. The analysis of diffusion is followed by a discussion of the impact of FA on product scale and scope, and on plant and firm scale. Total unit costs as well as capital, labour, inputs, R&D and marketing unit costs are then examined.

Part I CONCEPTS, METHOD AND SYNTHESIS

1 SCALE AND SCOPE Concepts and issues

1 Introduction The purpose of this chapter is to explain the conceptual framework developed in this research and used to address the impact of flexible automation on scale and scope. The concepts of scale and economies of scale and of scope and economies of scope have all too often been used loosely in discussions about the impact of technical change on costs, firm size, industrial organization and industrialization. Much of the confusion has arisen from the fact that the circumstances and relationships these concepts attempt to describe involve a combination of physical, organizational and economic phenomena, which normally are not easy to disentangle. Thus, the first step in this research was to develop a proper understanding of their meaning, of the key factors accounting for their changes, of their different dimensions and of the possible relationships that emerge between them on the basis of established economic theory; and to relate this understanding to the ensuing debate on whether or not new technologies reduce optimal scale and increase economies of scope. It must be emphasized that standard economic theory, despite its limitations, clearly remains the basis on which empirical research on issues of economies of scale and scope is conducted because it continues to provide a useful and recognizable heuristic instrument to organize the ideas and the data in this field. It also facilitates understanding and comparability across research. It is, therefore, an obligatory starting-point for any research of this kind. In outlining the development of the conceptual framework the section 2 briefly discusses the origins and development of the theory of economies of scale by examining the contributions of Adam Smith, Marshall and Viner. The main focus is on the intra-firm division of labour, not the inter-firm division of labour, as our concerns extend only to the firm level. Section 3 defines the concepts of scale, economies of scale and optimal scale, and reviews their main sources and dimensions. The sources of economies of scale to be addressed are specialization, indivisibilities and dimensional effects, while the dimensions of economies of scale to be discussed are those of product, plant and firm. Section 4 concentrates on the origins, definition and sources of economies of scope. It begins by

10 CONCEPTS, METHOD AND SYNTHESIS

addressing Stigler’s contribution, in particular the concepts of plant adaptability and flexibility in the short run, and then moves on to discuss the development of economies of scope theory by Baumol and associates. Section 5 reviews the debate between, on the one side, those who argue that new technologies will result in reductions in optimal scale and economies of scale and increased economies of scope and, on the other, those who contend that the effect will be the opposite. The final section of the chapter develops a graphical representation of both sides of the argument by way of clarifying the debate and as a means of organizing subsequent work. 2 Origins of economies of scale theory: from ‘division of labour’ to cost curves There are few propositions in economics that have caused so much debate and controversy as Adam Smith’s dictum ‘the division of labour is limited by the extent of the market’ and the pin factory example he used to illustrate his statement. This assertion is seen in both classical political economy and neoclassical economics as one the main foundations of production and economies of scale theory. In essence, Smith (1776) argued that the principle of the division of labour and the ensuing work specialization was the most important determinant of productive efficiency because of the increase in dexterity which results from making a single, relatively simple, operation the sole activity of the worker; the saving of time arising from not having to move from one type of task to another; and the associated use of machines which ease and abridge labour. In Smith’s celebrated pin factory example, one man draws out the wire, another straightens it, a third one cuts it, a fourth one points it and so on. Up to 18 distinct operations were identified which with no more than 10 labourers could result in thousands of pins produced in one day. A craft workman producing pins by himself would not be able to produce more than twenty pins in the same time. The main outcome of the division of labour was that it reduced direct and indirect labour per unit of output (see also Atallah 1966; Corsi 1991; Morroni 1992; Skinner 1974; Stigler 1951; Tayler 1985).1 The division of labour was, for Smith, a process resulting not so much from any human wisdom but from the gradual increase in the ‘propensity to exchange’. Because expansion of trade and output is at the origin of the division of labour, the extent of that division is limited by the extent of the market. Where the market is small there is no incentive to specialize as few will be able to purchase the output of those engaged in factory production. Where possibilities of economically transporting products elsewhere exist, the extent of the market is potentially increased by the ‘inhabitants of the lands’ within the reach of those transporting means. For any one country taken in isolation, the extent of its market is limited by its internal transporting facilities and grows ‘in proportion to the richess and populousness of that country’ (Smith 1776:124).2

SCALE AND SCOPE: CONCEPTS AND ISSUES 11

Classical political economy built on these ideas (Atallah 1966; Corsi 1991; Gold 1981; Morroni 1992; Tayler 1985; Vassilakis 1987). Babbage (1832) added that increasing specialization of labour reduces apprenticeship time and wastage of material. It also helps to separate in a clear way physical and mental labour and, thus, to allocate each job to workers with the appropriate skills and qualifications, resulting in skilled and creative individuals concentrating on activities that require judgement and on the development of new machines and products, and less skilled individuals dedicating to more narrowly defined tasks. Marshall (1890) brought the link to mechanization more explicitly into the discussion by pointing out that increasing division of labour creates the conditions for the identification and replacement of certain tasks by specialized production equipment. Work that is uniform and monotonous can be gradually taken over by machinery until there is nothing to do by hand except to supply machines with inputs and take away the product when finished. Even the function of overseeing the work of machinery can be replaced by devices which stop movement when anything goes wrong. The main effects of mechanization are to lower the cost of work while making it more accurate because as the division of labour progresses work is continuously subdivided and made highly specialized; and to make possible the manufacture of interchangeable parts. Marshall also pointed out that ‘internal economies’ arise within any manufacturing firm out of the increasing scale of output which is both the cause and the result of further work and skill specialization, increasing mechanization and improved production organization. Internal economies enable firms to increase their output in more than the proportionate increase of all of their inputs (increasing returns to scale).3 Despite Marshall’s major influence on neo-classical economics and his key contribution to what was emerging as an economies of scale theory, it was Viner who formulated the neo-classical theory of economies of scale as it is known today (Tayler 1985). In his seminal article, published originally in 1931, he developed the first graphical representation of cost theory which included ‘the usual assumptions of atomistic competition and rational economic behaviour on the part of the producers’ (Viner 1953:198). In it he distinguished between shortand long-run cost theory. In the short-run, plant capacity and some production factors such as capital are ‘fixed’, in the sense that they cannot be altered, while others such as raw materials and labour are ‘variable’. Costs associated with each type of factor are, respectively, ‘fixed’ and ‘variable’ costs. Because by definition ‘fixed’ costs cannot be altered, average fixed costs tend to decline as output increases. Since any increase in output is the result of the combination of constantly priced ‘fixed’ and ‘variable’ factors and given diminishing returns for the ‘variable’ factors, average costs will fall initially while the productivity of the ‘variable’ factors rise but will subsequently increase as the productivity of ‘variable’ factors declines. The outcome is a U-shaped total average cost curve. In the long-run all factors become variable and plant capacities were assumed, on equilibrium grounds, to be available to the exact level of minimum average cost output required by any individual producer. Any producer then has the choice of producing at the short-run level of output with the risk of getting it wrong, thus

12 CONCEPTS, METHOD AND SYNTHESIS

increasing average costs; or of investing in plant capacity believed to match expected demand at any point in the future (hence, the name ‘long-run’ or ‘planning’ cost curve). Because there are limitless options between the short and the long run, and given diminishing returns also in the long run, it is possible to have a U-shaped long-run average cost curve joining all the short- and long-run output and capacity trade-offs—the ‘envelope’ curve.4 Viner added that economies of large-scale production were long-run phenomena that only arise out of the adjusting of plant capacity to each successive output. Sources of economies were either technical or pecuniary, emerging out of reductions in the technical coefficients of production or from prices paid for the factors of production. Technical economies arise out of savings in labour, material or equipment due to improved organization or methods of production. Pecuniary economies arise from the possibility of obtaining quantity discounts due to a larger scale of purchases. 3 Scale, economies of scale and optimal scale: definitions, sources and dimensions Since Viner, textbook scale economies theory has evolved to become a more empirical set of concepts and relationships. It has been influenced also by developments in applied economics and engineering. In textbook production theory scale refers to size of output or capacity of production units, and economies of scale refers to reductions in unit costs due to increases in size of output. Economies of scale are said to exist if total cost rises proportionately less than does output, while diseconomies of scale arise when total cost rises proportionately more than does output; and optimal scale occurs at the point where any increase in output no longer reduces but raises unit costs. The main sources of scale economies are specialization, indivisibilities and dimensional effects (Morroni 1992; Rosseger 1986; Scherer and Ross 1990). Specialization sources can be further subdivided into static and dynamic sources. Static specialization gains arise out of larger output and had already been identified by Adam Smith in his discussions of division of labour and work specialization. In a nutshell, increasing scale allows the separation of tasks and workers to do their individual jobs rapidly and precisely and with the appropriate skill content, while avoiding the expense of time and effort associated with moving from one task to another. They allow also the use of more efficient purpose-specific machinery and mechanized production processes and an improved production organization. A too-large output, however, may be complex to plan, coordinate and control, leading to management and organizational problems and to losses in efficiency rather than gains. Dynamic specialization gains arise out of the learning potential of long production runs or the cumulative volume of output through time. Where intricate operations and complex process adjustments are involved, efficiency increases as workers learn by doing: the production process is ‘demystified’, for workers and management alike, enabling

SCALE AND SCOPE: CONCEPTS AND ISSUES 13

them to correct for mistakes. Hence, unit costs are reduced as a result of accumulating output. Any commodity is indivisible if there is a minimum size below which it is unavailable. Morroni (1992) identifies two kinds of indivisibility: economic and technical. Economic indivisibilities arise out of the fact that many commodities can only be traded in a given unit, e.g. (a length of) cloth or (a bushel of) corn. Technical indivisibilities arise out of the physical impossibility of dividing a particular commodity into amounts usable for production and consumption. This is normally the case with capital equipment, the capacities of which vary in discrete quantities and have a fixed minimum. In a vertical sequence of production stages, indivisibilities may arise out of the imbalances that emerge due to the different capacities of capital equipment at each stage as, if all machines are going to be fully utilized, it is the machine with the largest minimum capacity that determines the size of the others. Morroni (1992) also points to labour-related indivisibilities. Wherever there is the need for team work, as in the case of joint lifting of weight, labour cannot be decomposed into its constituents, as it would not be possible to carry out that particular activity individually. Specific skills are available only in certain individuals or groups of them, and often in discrete and minimum quantities. Capital equipment and labour indivisibilities create minimum outlays that have to be incurred by any producer, i.e. ‘fixed costs’. Unit costs fall as any unit of production initially required to produce a smaller output increases its output without a proportional increase in costs.5 Sources of dimensional effects relate to the geometrical volume-surface area relationship of certain kinds of capital equipment such as vessels, containers and pipelines. The cost of construction of any container increases in line with its surface area size, whereas its capacity increases with volume. Since the area of a sphere or cylinder varies as the two-thirds power of volume, the cost of building some equipment rises roughly as the two-thirds power of their capacity. Therefore, the higher the capacity the lower the unit costs per unit of capacity. This source of scale economies is commonly known in engineering as ‘the 0.6 rule’.6 According to Scherer et al. (1975), Scherer and Ross (1990) and Silberston (1972), scale and economies of scale are better analysed in terms of three dimensions: product, plant or firm. Product scale refers to the volume of any single batch, sometimes referred to as lot size or production run. Product-scale economies emerge from the indivisibility and fixed costs of the operations of preparation of equipment, exchange of jigs and fixtures, machine adjustment and trial runs necessary to begin manufacturing a particular batch or product run (Carlsson 1989a; Kaplinsky 1991; Pratten 1975, 1991a; Scherer et al. 1975; Silberston 1972; Steudel and Desruelle 1992). Batch or lot size is the quantity of identical items or products manufactured in a certain process or sequence of operations between set-ups. Set-ups or setting-up time is the time spent between the production of the last unit of the last batch and the first good item or product of the new batch.

14 CONCEPTS, METHOD AND SYNTHESIS

Setting-up times and associated costs are key factors in determining whether and when a new product is manufactured, particularly in discrete product industries (Ayres 1991; Morroni 1991). The classical example is Ford’s replacement of the model-T car by the model-A car, which necessitated closing down the factory for nine months in 1926 (Abernathy 1978).7 The car industry has always been under immense pressure not to change car models, which explains why some models remain in the market for years. In the printing industry, the initial typesetting costs can be so high that they sometimes make the publication of specialized or academic books or journals economically unfeasible. Very few books have print runs to match those of the Bible or Porter’s Competitive Advantage. In many operations in the metalworking sector the ‘typical’ set-up time is 20–30 per cent of processing time, while in a US textile factory setting up a roller printing press to print cotton or synthetic fibres takes around 20 per cent of production time (Carlsson 1989a; Scherer et al. 1975). In general, when production is not on a strict to-order basis, specific decisions on how large a batch size or how long a production run should be are taken with the help of the economic batch- or lot-size model (Mansfield 1988; Steudel and Desruelle 1992; Scherer et al. 1975). In essence, the model seeks to determine the size of the ‘optimal’ batch or lot on the basis of expected demand and set-up and inventory carrying costs, as inventories necessarily build up when large batches are produced:

where Q=the optimal batch size being sought; D=the level of expected demand (normally annual); s=the cost per set-up; c=the cost of inventory carrying. What the economic batch- or lot-size model says is that the larger the set-up costs relative to inventory carrying costs, the greater the incentive to continue producing the same item or product if unit costs are going to be kept in check. The lower the set-up costs relative to the inventory carrying costs, the lower the required batch size. As set-up costs approach zero, there is no optimal batch size, and individual batch size can be directly determined as a function of customers’ demand in order to keep low the inventory levels and costs. Plant scale, in turn, is normally associated with the total output of an entire plant in continuous process or ‘fluid-flow’ industries, such as oil refining, chemicals, steel and cement, in a given period of time—normally one year. It is in these industries where dimensional effects and the ‘0.6 rule’ have the largest impact on economies of scale. But plant scale relates also to the total output or capacity of discrete-good industries, such as printing, mechanical engineering, the electronic, clothing and shoe-making industries. Because discrete-good production involves a wide range of possible combinations of technologies, forms of production organization, and inputs and outputs, the key sources of economies

SCALE AND SCOPE: CONCEPTS AND ISSUES 15

of scale are specialization of labour and machinery, improved production organization, and individual equipment and production process indivisibilities. Both in continuous process and in discrete-product industries, plant economies of scale may arise also out of minimum requirements or indivisibilities of certain functions and needs, such as local management, security, safety, maintenance and the availability of reserve equipment and spare parts, particularly in cases where functions cannot be subcontracted.8 Firm scale relates to the output or capacity of the whole firm, which may or may not involve several plants, and firm economies of scale emerge from the indivisible and fixed nature of certain ‘intangible’ investments, such as research and development (R&D), marketing and management. Budgets for the development of new products and processes are normally ‘rule of thumb’ amounts, reached on the basis of previous years’ sales, levels of retained profits, the expenditure of potential competitors, minimum threshold considerations, the average allocation of the industry and the emerging technological opportunities (Freeman 1982; Hay and Morris 1991). Marketing and distribution expenditures also are set amounts resulting from similar factors. For advertising to be effective there are certain minimum threshold levels for messages that have to be transmitted. Consumer durables and office automation industries require specialized dealer networks and after-sales service. Operating a sales force requires investment in training and specialized equipment (Scherer and Ross 1990). Management costs are also pre-set and depend on a minimum number of functions and hierarchical levels—and therefore managers—and of specialized equipment that are required for the normal operation of any firm (Koutsoyiannis 1980). Scale gains arise, therefore, from the possibility of spreading all these fixed costs among a larger total volume while reducing unit costs. 4 Scope and economies of scope: origins, definitions and sources One of the major assumptions underlying cost curves and economies of scale theory is that plants and firms are single-product producers. Reality seems, however, to be extensively populated by production facilities and firms manufacturing many different products, i.e. multi-product plants and firms. Producers of garments, textiles, consumer electronic goods, home appliances, engines and machine tools, have constantly to switch models or manufacture according to varying technical specifications to cater for differentiated demand and, hence, have to adapt or modify their production processes.9 Initial preoccupations within economics with the issue of production flexibility and costs can be traced back to Stigler (1939). He set out to address the issue of production and costs in the short run which, in turn, allowed for the conceptualization of multi-product plants and firms. Consistent with received neo-classical theory, Stigler accepted that in the short run some production factors were ‘fixed’ while others were ‘variable’. However, he pointed out that ‘fixed factors’, in addition to being ‘divisible’ or ‘indivisible’, could also be

16 CONCEPTS, METHOD AND SYNTHESIS

‘adaptable’ or ‘not adaptable’ to changing quantities of the variable factor. A plant, machine or piece of equipment is adaptable if it does not lose ‘acceptable’ efficiency when operated by a varying number of labourers or with a changing amount of material. Adaptable plants imply that output may be reduced without resulting in unemployment of the fixed factor. Stigler pointed out that illustrations of perfect adaptability were difficult to find in reality but that one could envisage some kind of agricultural land which could be combined with varying amounts of ploughing, seeds, etc, within fairly wide limits. Adaptability arises from the capacity to reorganize production processes. According to Stigler, there are four possible combinations of divisibility and adaptability for operations that are outside the optimal point of production. The first two possibilities that arise in the utilization of a fixed plant concern the cases of perfect divisibility or complete indivisibility with total adaptability. In these cases, because of diminishing returns of the variable factor, the resulting short-run unit-cost curve would be smoothly U-shaped, much in the neo-classical vein. The only difference between the two cases is that, in the latter, the cost function would not be continuous over the whole range of output. The third possibility is a combination of an unadaptable but divisible plant. This is the ‘unrealistic’ case of, for instance, a plant with several identical machines which can be used only with a fixed amount of labour and of materials. In this case, shortrun unit costs would be a horizontal line until the plant is fully employed, and it would not be possible to increase output beyond this point. Finally, in the case of an indivisible and completely unadaptable plant the short-run unit-cost curve would be a vertical line, and it would be possible to produce only at a single level of output. In between the last two possibilities there are a number of combinations which arise out of partial adaptability and, hence, short-run cost curves with either a small or a large output for which unit costs are significantly decreasing or increasing. Stigler adds that it may be possible to introduce some flexibility into the operation of a plant so that it can be acceptably efficient over a range of probable outputs. Production ‘flexibility’ is defined as the capacity to produce different amounts of a given product with the best possible technology, but at the cost of being unable to use the best-known technology for any amount of output. It always requires some adaptability, in the sense that the greater the adaptability of inputs the easier it is for a plant to be flexible, but it goes beyond adaptability as it involves the capacity to modify an existing plant and significantly switch the level of output with little loss of efficiency. Sources of flexibility are, first, the degree of divisibility of fixed plant which reduces the costs of producing at suboptimal levels; and second, the capacity to transform fixed into variable costs. Morroni (1992), who builds heavily on Stigler’s contribution, adds that the main sources of flexibility include the capacity to change the number of workers or the number of working hours per worker (numerical flexibility), the ability to adjust workers’ skills within the firm (functional flexibility), the potential to hire or lease equipment or keep old equipment for catering for short term upsurges in demand, the possibility of keeping inventories for compensating for variations in demand, and the capacity to employ subcontractors.

SCALE AND SCOPE: CONCEPTS AND ISSUES 17

Figure 1 Short-run unit costs in flexible and inflexible plants

Curves UCI and UCF in Figure 1 are the unit-cost curves of an inflexibleindivisible and a flexible-divisible plant. When output is OA and OD the flexible plant has smaller unit costs than does the inflexible plant, with the latter producing at prohibitively high unit costs. Between outputs OB and OC the inflexible plant has lower unit costs. If output is expected to fluctuate between OB and OC then the inflexible plant is the more desirable, but if output is going to fluctuate beyond these points the flexible plant may become the better option. Hence, the unit-cost curve of a flexible plant is flatter but with a minimum cost higher than that of the unit-cost curve of the less flexible plant.10 Although Stigler remained very much in the neo-classical tradition, and did not address the issue of firms manufacturing more than one product, there is no doubt that his contributions paved the way for further developments in this direction.11 First, he introduced issues of production adaptability and flexibility, hitherto unexplored, into the economics’ discussion. It was just a step away conceptually, although it took some time, to make the link with multi-product output concepts after ideas pertaining to production process adaptability and flexibility had been established. Second, he raised the possibility that firms, certainly in the shortrun, had a far wider choice of relatively efficient points in which to operate than what received neo-classical theory was prepared to accept, and that the selection of any level of efficiency involved significant trade-offs in terms of the capacity to respond to changes in demand. One important implication of this contribution is that there may not be a short-run optimal point of production but only a set of relatively, more or less, efficient options depending on entrepreneurial expectations of the market.

18 CONCEPTS, METHOD AND SYNTHESIS

Producing more than one good implies considering not only the degree of production adaptability and flexibility, as Stigler contended, or the setting-up, change-over and investment costs, as traditional economies of scale theory showed, but looking also into the potential cost effects of joint-production. Baumol et al. (1988; see also Bailey and Friedlaender 1982) have addressed this issue and have developed the concepts of scope and economies of scope, which they consider complementary to the traditional concepts of scale and economies of scale. Scope stands for product range; economies of scope arise when the cost of making goods jointly is less than that of making the same total quantity of the same goods separately. They can be defined formally in the case of two outputs, q1 and q2, as follows: Economies of scope arise from the sharing or joint-utilization of inputs (Baumol et al. 1988; Bailey and Friedlaender 1982). They are the result of using inputs that may have some properties of a public good, so that when purchased for one production process they may be freely available for another. More often, however, they are the outcome of using a given factor or input which is imperfectly divisible, so that the production of a specific product, or number of them, may lead to under-utilization of that factor or input, and which can be shared in the production of another good. Or, in slightly different terms, such economies often arise when a multi-product set of production techniques employing a common input exhibits ‘strong’ cost complementarities, in the sense that the marginal cost of producing any one product decreases with increases in the quantities of all other products. Baumol et al. (1988) and Bailey and Friedlaender (1982) argue that, historically, technical change has been a crucial factor in creating the conditions for the emergence of economies of scope. Until refrigeration and fast transportation developed, the joint exploitation of wool and mutton, for instance, was not possible. More recently, it was only after the development of technologies that allow the switching of tasks and varying the order in which parts are transferred it has become possible to reap economies of scope. Baumol et al. (1988) and Bailey and Friedlaender (1982) point to several illustrative cases where plant economies of scope in the production of goods and services may be at work. The first one is the case of an input used in different stages of the production process. It is generally cheaper to produce both wool and mutton than it is to raise sheep separately for each product. The second refers to the indivisibility of certain factors of production. In the light of a falling demand for cars, the use of a stamping machine for the production of light trucks as well as for cars may provide economies of scope. A third example comes from the use of an input by more than one product, like the case of a firm that produces abstracts from journals. The firm produces three separate indexes of abstracts, comprising a general index which contains all the information, and two specialized indexes on the basis of the general one. Scope economies arise because the general index is freely available for the other two indexes. The final

SCALE AND SCOPE: CONCEPTS AND ISSUES 19

Figure 2 Output space for a two-product firm

case comes from the economies of networking. Routeing different flights using larger planes through the same airport and then combining passengers with the same destination in other large aircraft can lead to cost reductions in the overall journey. Teece (1980) and Carlton and Perloff (1994) added that generally, at firm level, economies of scope emanate from the nature of knowledge as a public good, from exchanging and pooling the information and know-how available from several projects being undertaken simultaneously, and from using marketing, distribution and management facilities for more than just a single product. In order to relate economies of scale and scope concepts, Baumol et al. (1988; see also Bailey and Friedlaender 1982 for a clear and succinct explanation of the new concepts) develop a number of additional cost concepts in the context of the multi-product firm. To begin with, they point out that in the multi-product context there is no definition of average or unit cost since there is no meaningful way to aggregate two different products into a single output measure. Furthermore, since the composition of output affects costs, care must be taken to differentiate between scale and scope effects. In the multi-product context the concept of scale economies can be made meaningful with the help of two additional concepts: ray economies of scale and product-specific economies of scale. Ray economies of scale indicate the behaviour of costs as the total output of a fixed combination of goods rises. Since for any output level proportions do not change, it follows that average costs, or more precisely ray average costs (RAC), are the total costs of a new ‘combined’ or ‘composite’ commodity divided by output. In this way the problem of adding together oranges and apples is avoided. In the output space for commodities Y1

20 CONCEPTS, METHOD AND SYNTHESIS

and Y2 shown in Figure 2, any output vector moving along a ray through the origin, such as OC, represents the RAC of the ‘composite’ commodity Y1Y2. Because RAC describes only the cost behaviour when output expands or contracts along a given ray, it is necessary also to address cost changes as output proportions change. To look into this issue the concept of product-specific economies of scale was developed. Product-specific economies of scale refers to cost changes as the output of one commodity changes. In Figure 2, these cost changes are reflected in lines FB or EB, where output of the other commodity is held constant in either case. It is measured by estimating first the average or unitincremental cost (AIC), which is defined as the addition to total costs associated with producing a given product at a specific level of output, as compared with not producing it at all, divided by the output of that product. For product Y1:

Product-specific returns to scale (S) for product Y1 are then given by:

where: MC=marginal cost. If S1 is greater than, equal to or lower than 1, there are, respectively, increasing, constant or decreasing returns to scale. To continue addressing the effects on costs of changes in the composition of output, Baumol et al. turn their attention to the impact of joint-production and bring into the analysis the concept of economies of scope. As was said, economies of scope are present when firms with diversified product mixes have lower total costs than the total costs of firms independently producing the same mix for the same level of total output. In Figure 2 point B represents an economies of scope situation as C(B)