Coupling coordination degree for urbanization city-industry integration level: Sichuan case

• Published in: Sustainable cities and society Vol. 58; p. 102136
• Main Authors: Gan, Lu, Shi, Huan, Hu, Yuan, Lev, Benjamin, Lan, Hongxing
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2020
• Subjects: City-industry integration; Coupling coordination degree; New urbanization; Urban-Population-Industry system; City-industry integration; Coupling coordination degree; New urbanization; Urban-Population-Industry system
• ISSN: 2210-6707; 2210-6715
• DOI: 10.1016/j.scs.2020.102136

•U, P, I subsystem’s insufficient development is the reason for little coordination level of most cities in Sichuan.•A comprehensive method for calculating the coupling coordination degree is proposed.•Key aspects that influence the level of urbanization city-industry integration are identified by quantitative model.•Urban, population, industry subsystem’s insufficient development is the reason for low coordination level of most cities in Sichuan.•Promotion of urbanization city-industry integration should attention the relevant policies. As the key issue in the process of new urbanization, the problem of city-industry integration has drawn the increasing attention from government and academicians, especially in western China. Based on the Urban-Population-Industry (UPI) system, the study utilizes coupling coordination degree to evaluate urbanization city-industry integration level, and identifies the key factors affecting the level of urbanization city-industry integration. Firstly, this study attempts to comprehensively describe the urbanization city-industry integration by a complex system that combines with U, P, I subsystem. Secondly, a comprehensive method for calculating the coupling coordination degree is proposed to reveal the urbanization city-industry integration level in the process of urbanization, including: (i) Grey Relation Analysis (GRA) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS); (ii) Hesitant Fuzzy Preference Relationship (HFPR) and Entropy Method (EM); (iii) Coupling Coordination Degree Model (CCDM); and (iv) Particle Swarm Optimization Back Propagation Artificial Neural Network (PSOBPANN). Then, identify the key aspects that influence the level of urbanization city-industry integration. Finally, an empirical analysis of panel data of 18 cities in Sichuan Province from 2000 to 2016 was conducted to analyze the development process. The results indicated: (1) At present, most cities in Sichuan, western China, are at the low coordination level of urbanization city-industry integration. Attention should be given to promote common regional development by playing to the radiating role of the central city; and (2) U, P, I subsystem’s insufficient development is the reason for low coordination between the level of urbanization city-industry integration. The key constraint is the low development level and the slow development rate of industry subsystem.