Coupling coordination degree for urbanization city-industry integration level: Sichuan case. (July 2020)

• Record Type: Journal Article
• Authors: Gan, Lu; Shi, Huan; Hu, Yuan; Lev, Benjamin; Lan, Hongxing
• Is Part Of: Sustainable cities and society. Volume 58(2020)
• Publication Date: 2020-07
• Subjects: New urbanization -- City-industry integration -- Urban-Population-Industry system -- Coupling coordination degree; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2020.102136
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: 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. Abstract: 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.