An entropy method-based index system for the competiveness of industrial cluster – a case study on the typical clusters in Zhejiang province in China
Weidong Wang1, 2
1College of Public Administration, Zhejiang University, Hangzhou, Zhejiang Province, China
2College of Humanities and Social Sciences, China Jiliang University, Hangzhou, Zhejiang Province, China
Basing on the previous research results, this study constructed an index system for the competiveness of the industrial cluster using analytic network process (ANP) method. Moreover, it employed the entropy method in objective assignment method to assign weights to the indexes and conducted empirical analysis by exampling the typical clusters in Zhejiang province. The results showed that the industrial concentration degree, specialization degree (location quotient), and Herfindahl-Hirschman index (HHI) took relatively high proportions in the indexes concerning the competitiveness of industrial clusters. This study also drawn an important conclusion, namely, high industrial concentration degree was conducive to improve cluster competitiveness and reduce cluster risk, while lower industrial concentration degree facilitated the formation of high overall cluster competitiveness.