| Title |
Exploring the industrial land use efficiency of China's resource-based cities |
| ID_Doc |
18018 |
| Authors |
Chen, W; Chen, WJ; Ning, SY; Liu, EN; Zhou, X; Wang, YA; Zhao, MJ |
| Title |
Exploring the industrial land use efficiency of China's resource-based cities |
| Year |
2019 |
| Published |
|
| DOI |
10.1016/j.cities.2019.05.009 |
| Abstract |
Resource-based cities (RBCs) are cities that have emerged from the utilization of natural resources and are dominated by resource-based industries. Industry is the leading economic activity of resource-based cities. However, industrial land in resource-based cities is faced with the challenges of inefficient use, to which little attention has been paid. Because RBCs are the location of leading economic activity, improving industrial land use efficiency is pivotal in these cities. This study used sub-vector Data Envelope Analysis (DEA) to calculate the industrial land use efficiency (ILUE) of China's 109 resource-based cities from 2006 to 2015. The empirical results proved that there was redundancy of industrial land in most of China's RBCs, but the overall degree of redundancy is decreasing. There were obvious differences in ILUE among different regions, different resource types and different development stages. Factors influencing ILUE were analyzed using the Tobit model. Regional economic development, industrial development and science and technology development had significant positive effects on ILUE, while the labor structure and the ownership structure of enterprises have significant negative effects. The conclusions that are drawn from the results support recommendations to improve ILUE for RBCs. The ILUE should be taken as the guidance for the layout of industrial land use in a RBC and should be incorporated into new industry spatial development strategy planning. |
| Author Keywords |
Sub-vector DEA; Resource-based cities; Industrial land use efficiency; Influencing factors |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:000488142900019 |
| WoS Category |
Urban Studies |
| Research Area |
Urban Studies |
| PDF |
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