Mitigation Strategy of Land Use Mix for Jobs-Housing Mismatch
The jobs-housing mismatch phenomenon in urban China stems from the combined effects of housing commodification and the improvement of transportation infrastructure. These factors have contributed to the emergence of lengthy commutes and a range of urban challenges. This study examines the issue of j...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
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Series: | Land |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-445X/14/1/82 |
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Summary: | The jobs-housing mismatch phenomenon in urban China stems from the combined effects of housing commodification and the improvement of transportation infrastructure. These factors have contributed to the emergence of lengthy commutes and a range of urban challenges. This study examines the issue of jobs-housing mismatch in large cities, focusing on Hangzhou. It utilizes mobile signaling big data, geographically weighted regression, and spatial analysis to investigate the link between land mixed-use and this mismatch. The results reveal that Hangzhou faces a significant residential-employment mismatch, particularly in a ring-like pattern. Central urban areas are relatively balanced, while residential areas band around the center, and employment areas are scattered both centrally and on the outskirts. Land mixed-use impacts this mismatch spatially. In new developments, increased land use mix exacerbates the mismatch, while in ecological green spaces, it has a suppressive effect. Based on these findings, Hangzhou’s main urban area is divided into nine zones, each with tailored suggestions for balancing residential and employment spaces. This study demonstrates that mobile signaling data can precisely capture micro-level characteristics of residential and employment patterns. A multi-dimensional approach to land mixed-use offers a more comprehensive understanding than a single perspective. The zoning strategy helps establish spatial differences and balance residential-employment relations, providing valuable insights for urban renewal and land function optimization. |
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ISSN: | 2073-445X |