A New Framework for Evaluating City–Industry Integration in New Urban Districts: The Case of Xixian New Area, China

Assessing city–industry integration levels is a critical diagnostic approach for promoting sustainable urban development. However, existing evaluation frameworks are mainly based on overlaying the level of development of individual systems and rely on statistical data, lacking analysis of spatial attributes. This study addresses these gaps by constructing an “industry–city–population” (I–C–P) evaluation system based on the interaction mechanisms among industry (I), city (C), and population (P), viewed through the lens of spatial correlation. Focusing on Xixian New Area and using 2022 sectional data, the study applies the CRITIC method to calculate the overall level of city–industry integration and the interaction levels across different dimensions in the district, and the Entropy Method (EM) is used to validate the results. The findings indicate the following: (1) The overall level of city–industry integration in Xixian New Area remains relatively low, with Fengdong and Fengxi significantly outperforming the other three new cities. (2) The interactions between “P–I” and “C–P” exhibit lower levels compared to the “I–C” interactions. Additionally, the spatial characteristics of the dimensional levels reveal both variability and consistency. The integrated indicator system, incorporating both spatial big data and traditional statistical data, significantly expands the data sources and dimensions for evaluating city–industry integration, which helps to provide a reference for the assessment of the potential for high-quality sustainable development in the new district and other regions.

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Publication Details

Journal
Sustainability
Published
2025-03-24
DOI
https://doi.org/10.3390/su17072882
Primary Topic
Regional Economic and Spatial Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

A New Framework for Evaluating City–Industry Integration in New Urban Districts: The Case of Xixian New Area, China

Xue Ma, Dan Zhao, Qingsong Ni, Tingting Wang et al.
Sustainability
Regional Economic and Spatial Analysis
article

A New Framework for Evaluating City–Industry Integration in New Urban Districts: The Case of Xixian New Area, China

Xue Ma, Dan Zhao, Qingsong Ni, Tingting Wang, Peng Cui, Kewei Liu, Xin Wu
article en

Abstract

Assessing city–industry integration levels is a critical diagnostic approach for promoting sustainable urban development. However, existing evaluation frameworks are mainly based on overlaying the level of development of individual systems and rely on statistical data, lacking analysis of spatial attributes. This study addresses these gaps by constructing an “industry–city–population” (I–C–P) evaluation system based on the interaction mechanisms among industry (I), city (C), and population (P), viewed through the lens of spatial correlation. Focusing on Xixian New Area and using 2022 sectional data, the study applies the CRITIC method to calculate the overall level of city–industry integration and the interaction levels across different dimensions in the district, and the Entropy Method (EM) is used to validate the results. The findings indicate the following: (1) The overall level of city–industry integration in Xixian New Area remains relatively low, with Fengdong and Fengxi significantly outperforming the other three new cities. (2) The interactions between “P–I” and “C–P” exhibit lower levels compared to the “I–C” interactions. Additionally, the spatial characteristics of the dimensional levels reveal both variability and consistency. The integrated indicator system, incorporating both spatial big data and traditional statistical data, significantly expands the data sources and dimensions for evaluating city–industry integration, which helps to provide a reference for the assessment of the potential for high-quality sustainable development in the new district and other regions.

SustainabilityVol. 17(7)
Northwest University (CN)
Openalex Percentile: Top 92%
Regional Economic and Spatial Analysis
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