4.7 Article

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

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 36, Issue 9, Pages 11895-11906

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2009.04.019

Keywords

Industrial cluster; Driving force; Industrial cluster policy; Taiwan Hsinchu Science Park; Fuzzy Analytic Hierarchy Process

Ask authors/readers for more resources

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. (C) 2009 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available