Commuting Pattern Recognition of Industrial Parks Using Mobile Phone Signaling Data: A Case Study of Nanjing, China

Xinguo Yuan, Xingping Wang, Yingyu Wang, Juan Li, Yang Zhang (), Zhan Gao and Gai Zhang
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Xinguo Yuan: School of Architecture, Southeast University, Nanjing 210096, China
Xingping Wang: School of Architecture, Southeast University, Nanjing 210096, China
Yingyu Wang: College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China
Juan Li: College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China
Yang Zhang: School of Architecture, Southeast University, Nanjing 210096, China
Zhan Gao: Jiangsu Provincial Planning and Design Group, Nanjing 210019, China
Gai Zhang: Jiangsu Provincial Planning and Design Group, Nanjing 210019, China

Land, 2024, vol. 13, issue 10, 1-24

Abstract: As a novel industrial space to cope with global competition, industrial parks have gradually become important growth poles to promote regional development and provide a large number of employment opportunities. This study utilizes mobile phone signaling data to identify the commuting origins and destinations (OD) of different industrial parks in Nanjing while comparing the distribution of the working population, residential population, and commuting patterns across varying types and levels of industrial parks. The level of coordination of the employment–residential system in each park is quantified by calculating the resident commuting index (HSC i ), employee commuting index (WSC i ), and their coupling coordination degree. Additionally, geographic detectors are employed to identify the influencing factors and interaction effects that impact the employment–residential balance in industrial parks. Results show that industrial parks located in the central urban area attract more residential and working populations. The commuting volume of national and municipal as well as high-tech industrial parks is higher than other types of industrial parks. Most industrial parks experience more inward than outward commuting, and there is an uneven distribution of commuting flows, resulting in a network-like pattern of “central dense, peripheral sparse”. Various industrial parks exhibit a highly coupled job–housing system, and those with high HSC i tend to have high WSC i as well. The coupling coordination of industrial parks ranged from 0.16 to 0.93, with 13 being primary coordination or above and 3 being disordered. Industrial parks are classified into three types: employment-oriented, residential-oriented, and employment–residential balanced, with the residential-oriented type being predominant. The density of public transportation stops, park area, and land use mix are the primary factors affecting the employment–residential balance. Industrial parks with larger scale, better land allocation, and higher service facility levels are more likely to achieve coordination in the employment–residential system. Our work utilizes mobile signaling data to characterize the commuting patterns of industrial parks, providing insights for industrial park planning and promoting the integration of industry and city.

Keywords: commuting; industrial parks; mobile phone signaling data; geodetector; Nanjing (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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