Abstract

The interactive development of clusters between manufacturing and producer services is important for China to break its comparative economic dilemma. The scientific novelty in this article is embodied by the interaction of various clusters of manufacturing with producer services. Taking the location quotient as the index measuring cluster, it was found that various manufacturing clusters and producer service clusters in the east achieved comparative equilibrium, while the middle and the west were comparatively imbalanced in development. By comparison of influencing factors, it was shown that decline of energy consumption and technology level, acceleration of multinational corporations, strengthening of competition and cooperation and strictness of regulation are beneficial to traditional industrial clusters. However, the effects of these factors on modern industrial clusters were the opposite. Empirical analysis showed that traditional manufacturing clusters had a close relationship with traditional producer service clusters, and were the opposite with modern producer service clusters. Finally, the countermeasures for achieving the interacting development of industrial clusters were proposed from aspects of the gradient development of producer services clusters, the guidance of dominant industries in manufacturing clusters, promotion of industry clusters by centralising high-levelled elements and the diversity of policy guidance.

Highlights

  • China’s economy has been in a state of obvious comparative dilemma in recent years, which has much relevance to a comparatively unstable international environment inducing, to some extent, relatively blocked development of the export-oriented economy, and comparatively scattered development within industry and comparatively uncoordinated development among different industries, which is important to elevate economic development

  • Zhang and Li (2011) showed that producer services clusters were highly positive for manufacturing clusters, based on China’s provincial data, by taking the Location Quotient Index; Ji, Li, and Su (2012) found that producer services clusters contributed to the relationship with manufacturing clusters in China and showed a balanced development trend by taking the Herfindahl–Hirschman Index and the EG Index; Han, Sun, and Zhang (2012) analysed the effects of producer services clusters and manufacturing clusters on returning to education and salary level by examining industrial panel data

  • Under the background of China’s gradual and in-depth reform and opening up, industrial clustering development cannot ignore the support of foreign direct investment (FDI); this might be an important point of entry for the multinational corporation

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Summary

Introduction

Zhang and Li (2011) showed that producer services clusters were highly positive for manufacturing clusters, based on China’s provincial data, by taking the Location Quotient Index; Ji, Li, and Su (2012) found that producer services clusters contributed to the relationship with manufacturing clusters in China and showed a balanced development trend by taking the Herfindahl–Hirschman Index and the EG Index; Han, Sun, and Zhang (2012) analysed the effects of producer services clusters and manufacturing clusters on returning to education and salary level by examining industrial panel data. The purpose of this article was to detect the interaction between different types of manufacturing clusters and producer services clusters; this was expected to provide a comparatively new angle on industrial cluster research. This article analyses common influencing factors on various types of industrial clusters based on calculating degrees of manufacturing clusters and producer services clusters, and detects effects of various types of producer services cluster on various types of manufacturing cluster, from the national and regional perspectives, proposes some measures for achieving effective cooperative development of clusters between manufacturing and producer services

Calculation method
Data description
Influencing factors and theoretical model
Empirical analysis
Establishment of theoretical model
Conclusions
Countermeasures
Full Text
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