Evaluating the development of high-tech industries: Taiwan's science park

doi:10.1016/j.techfore.2005.04.003

Technological Forecasting and Social Change

Volume 73, Issue 4, May 2006, Pages 452-465

https://doi.org/10.1016/j.techfore.2005.04.003 Get rights and content

Abstract

Science park has been widely recognized for its importance to the development of high-tech industries. However, as the space availability is limited, selection of firms with better efficiency and/or growth potential in specific high-tech industries to get into the science parks has become a critical issue for the Taiwan government. Accordingly, this study applies Data Envelopment Analysis (DEA), a multiple inputs–multiple outputs evaluation method, to analyze the comparative performances of the six high-tech industries currently developed at Taiwan's Hsinchu Science Park. Malmquist indices of productivity change are also used to analyze the growth potentials of the six high-tech industries. In addition, individual output/input ratio analysis is done to examine the differences on individual productivity items between the efficient and inefficient industries. The results of these analyses provide some policy implications for Taiwan and other countries facing the similar problems.

Introduction

Science park has been widely recognized for its importance to the development of high-tech industries [1], [2], [3], [4]. For example, the success of Silicon Valley has been the engine of prosperous development of information industry in the United States. Therefore, the development of science park in many countries clearly received its early impetus from the United States' experience [5]. Taiwan was no exception. In 1980, the Taiwan government decided to establish its first science park, Hsinchu Science Park, in Hsinchu city, about one hour drive south to Taipei, for the purpose of attracting high-tech firms to create industry clusters here.

In the past two decades, the development of Hsinchu Science Park was an epitome of development of Taiwan's high-tech industries. With several adequate incentives including abundant supply of technology and skilled engineers, tax credits, excellent infrastructure, and convenient official services, Hsinchu Science Park has grown rapidly in terms of the number of firms, annual sales, and the number of employees. In 1999, 292 high-tech firms in six high-tech industries were attracted to locate in Hsinchu Science Park. These high-tech firms, with working capital of NT 566 billion, hired more than 82,000 skilled employees to create annual sales of about NT 650 billion.

Currently, there are six high-tech industries developed in the Hsinchu Science Park. These six high-tech industries are semiconductor, computer, communications, photo-electronics, precision equipment, and biotech. Notably, the annual sales of semiconductor industry and computer industry amount to 86% of the sales of the six high-tech industries. The successful development of semiconductor and computer industries in Taiwan has been widely recognized [6], [7]. Taiwan's computer industry has grown to be the third largest exporter, surpassed only by that of the USA and Japan. The production volumes of more than 10 products are ranked first in the world, including desktop computers and notebooks, monitors, modems, motherboards, keyboards, power supplies, scanners, and so on [8]. Also in semiconductor industry, Taiwan has become the third largest producing country in the world [9]. These evidences indicate that Hsinchu Science Park has contributed greatly to the smooth transformation of Taiwan's industry structure to high-tech industries, especially semiconductor and computer industries.

As the high-tech firms rapidly occupied Hsinchu Science Park, the Taiwan government planned to expand the size of the park and to establish the second science park, called Tainan Science Park, in southern Taiwan to contain more high-tech firms in the science parks. Though the government has aggressively increased the supply of the parks, it still cannot meet the huge demand from the high-tech firms. Therefore, as the space availability is limited, selection of firms with better efficiency and/or growth potential in specific high-tech industries to get into the science parks has become an important issue for the Taiwan government. In addition, compared to the success of semiconductor and computer industries, other four high-tech industries are still in the emerging status. What are the problems existed among these industries and what kind of roles it should play on the development of these high-tech industries currently in the science park are also critical issues for the Taiwan government to understand.

Accordingly, this study applies Data Envelopment Analysis (DEA), a multiple inputs–multiple outputs evaluation method, to analyze the comparative performances of six high-tech industries currently developed at Hsinchu Science Park in Taiwan. Malmquist indices of productivity change are also used to analyze the growth potentials of the six high-tech industries. In addition, individual output/input ratio analysis is done to examine the differences on individual productivity items between the efficient and inefficient industries. The results of these analyses can provide some directions for Taiwan and other countries facing the similar problems.

The rest of the paper is organized as follows. Section 2 discusses the concepts and contents of DEA and Malmquist indices that are used in this study. Section 3 explains the research design including research procedure, variable measurement, and sample collection. Section 4 provides the empirical results of DEA, Malmquist indices, and individual output/input ratio analysis applied to the six high-tech industries. Finally, section 5 discusses the results and makes some conclusions.

Section snippets

The DEA model and Malmquist indexes

Data envelopment analysis (DEA) is a mathematical programming methodology, using a variety of input and output data, that can be applied to assess the relative efficiency of a variety of institutions such as industrial firms, commercial banks, universities, and hospitals [10], [11], [12], [13]. More recently, the DEA approach has been used to analyze the competitiveness of industries and regions in a country or across countries [14], [15], [16]. The conventional definitions of efficiency used

Research procedure

This study firstly applies DEA to evaluate the relative efficiency of the six high-tech industries in Taiwan's Hsinchu Science Park. The advantages to adopt DEA analysis are: first, DEA analysis can combine many measures without the setting of a priori weights for the various parameters to produce an overall efficiency measure. Secondly, in contrast to conventional econometric techniques such as regression analysis used to estimate a production function, in DEA, more than one input and output

Technical efficiency by CRS model

CRS DEA model was used to obtain technical efficiency (TE) scores for the six high-tech industries in Taiwan's science park from 1991 to 1999, as shown in Table 1. First, we look at each individual industry. The TE scores of semiconductor industry improved from 0.591 in 1991 to 1.000 in 1993 and have kept on the efficient frontier since then. Its average value of TE is 0.932. Computer industry has been most efficient, with TE scores of 1.000, over all the period. Communications industry

Discussion and conclusions

This study applies DEA and Malmquist indices to evaluate the relative efficiency of the six high-tech industries currently developed in Taiwan's Hsinchu Science Park. The results of technical efficiency indicate that computer industry and semiconductor industry had the best performance while other four industries, communications, photo-electronics, precision equipment, and biotech, were operated relatively inefficient. These findings reflect the current situations of the six high-tech

Dr. Chung-Jen Chen is an associate professor at the Graduate Institute of Business Administration, National Cheng Kung University, Taiwan. He received his doctorate in Strategy and Technology Management from Rensselaer Polytechnic Institute, Troy, New York. He is a researcher in the fields of technology management, interfirm collaboration, and entrepreneurship. He has published papers in Information & Management, International Journal of Technology Management, R&D Management, and other journals.

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Dr. Hsueh-Liang Wu is an assistant professor at the Graduate Institute of Business Administration, National Cheng Kung University, Taiwan. He gained his doctorate in Commerce from the University of Birmingham, United Kingdom. His main research interest is in strategic management of policy and technology. Before joining the NCKU in 2002, he had worked as the senior policy specialist for the Council for Economic Planning and Development, the highest economic think tank in the government of Taiwan, for 12 years with wide involvement in science and technology policy and other industrial policy issues. He has published papers in Journal of Organizational Change Management, Journal of Policy Modeling, and other journals.

Dr. Bou-Wen Lin is an associate professor at the Institute of Technology Management, National Tsing Hua University, Taiwan. He received his doctorate in Management of Technology from Rensselaer Polytechnic Institute, Troy, New York. His current research interests include interfirm collaboration, knowledge management, and new product development. He has published papers in International Journal of Production Research, R&D Management, Technological Forecasting and Social Change, and other journals.

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Evaluating the development of high-tech industries: Taiwan's science park

Abstract

Introduction

Section snippets

The DEA model and Malmquist indexes

Research procedure

Technical efficiency by CRS model

Discussion and conclusions

Technovation

Research Policy

Information & Management

Research Policy

Technovation

Socio-Economic Planning

International Journal of Management Science

Socio-Economic Planning Sciences

Energy Economics

European Journal of Operational Research

European Journal of Operational Research