The evaluation of cluster policy by fuzzy MCDM: Empirical evidence from HsinChu Science Park

Chia Chi Sun*, Grace TR Lin, Gwo Hshiung Tzeng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

In the recent years, industrial clusters have received considerable attention from economists and industrial analysts, because they are seen as the main reason for economic growth and success of certain economic region. This study systematically reviews past researches of industrial cluster. The purpose of this paper is to contribute to the understanding of this issue regarding the driving forces for the growth of industrial cluster and find out the priority among these cluster policies. Taiwan HsinChu Science Park is a prime example for this paper, and its connection with the innovative participators. We begin with an examination of the literature on cluster about its driving forces and policies upon which we propose a conceptual framework. In doing so, we explore the cluster-based industrial system. Then this research adopts the Fuzzy Analytic Hierarchy Process as the analytical tool. The Fuzzy Analytic Hierarchy Process method is used to determine the weightings for evaluation dimension among decision makers. From our research results, the Factor Conditions is the most important driving force for advancing the industrial cluster performance. Moreover, the promotion of international linkages policy and broader framework policies rank the first two priorities for cluster policy. Overall, this paper concludes with some simulations of cluster policy alternatives confronting the industry and the Taiwanese government.

Original languageEnglish
Pages (from-to)11895-11906
Number of pages12
JournalExpert Systems with Applications
Volume36
Issue number9
DOIs
StatePublished - 1 Nov 2009

Keywords

  • Driving force
  • Fuzzy Analytic Hierarchy Process
  • Industrial cluster
  • Industrial cluster policy
  • Taiwan HsinChu Science Park

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