The development efficiency of China’s innovative industrial clusters-based on the DEA-Malmquist model

Abstract

Innovative industrial clusters are regarded as regional innovation centers and have become an important support for the national innovation strategy in China. However, in the actual development process of innovative industrial clusters, there are problems of unbalanced development and low development efficiency. This study selected the data envelopment analysis (DEA)–Malmquist model to analyze the development efficiency, spatiotemporal evolution characteristics, and spatial improvement of China’s innovation industrial clusters. This study is different from previous studies that used a single industrial cluster as a decision-making unit. Instead, it uses provinces as a decision-making unit. In calculation and analysis, provinces are used as decision-making units instead of single industrial clusters as decision-making units in previous studies. The results showed the following: (1) The average development efficiency of the innovative industrial clusters was 0.652, which was relatively low and had great potential for effective development. Meanwhile, the average value of the Malmquist index was 0.932, which declined at an average annual rate of 7.5% during the study period, mainly due to the slowdown in technological progress and to the decline in pure technical efficiency. (2) There were no significant differences in the development efficiency, Malmquist index, or decomposition indices of China’s innovation industry among the four regions investigated, indicating that regional advantages have not been significantly exerted. (3) Through further analysis of the potential for improvement, a quantitative improvement of the space of the input–output factors of China’s 19 DEA-inefficient provinces was obtained.