Investigating the Spatiotemporal Disparity and Influencing Factors of Urban Construction Land Utilization Efficiency: Empirical Evidence from Panel Data of China

• Main Authors: Qingfeng Zhou, Xianqiang Wu, Xian Zhang, Yan Song
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: Advances in Civil Engineering
• Online Access: http://dx.doi.org/10.1155/2021/1613978

This paper corrected the long-term misunderstanding of the land utilization efficiency concept. The Undesirable-Window-DEA model, Dagum Gini coefficient, and spatial panel autoregressive model with fixed effect were used to explore the spatial heterogeneity and influencing factors of urban construction land utilization efficiency in China from 2004 to 2016. The results show the following: (1) China’s overall utilization of urban construction land is still at a low level. It decreased first and then rose, with a “flat V-shaped” evolution pattern. (2) During the study period, the Gini coefficient of urban construction land utilization efficiency for all provinces decreased first, then rose, and decreased again. The utilization efficiency Gini coefficients within provincial grouping were eastern region (0.063), central region (0.101), and western region (0.128). The Gini coefficients within provincial grouping were central versus western (0.121), eastern versus western (0.161), and eastern versus central (0.168). For the contribution to overall inequality of land utilization efficiency, the inequality within groups contributes the most (57.57%), and the inequality between groups accounts for about 25.62%. The overall efficiency is improved, with an evolution pattern of “difference narrowed–differences expanded–difference narrowed.” (3) “economic development,” “industrial structure,” “research development investment,” and “land urbanization level” have significantly positive effect on urban construction land utilization efficiency, while other factors have a negative effect, including “urbanization level of population,” “urban population density,” “cultivated field resources level,” “government influence level,” “land urbanization level,” and “financial dependence level.” This study could provide theoretical support for the implementation of cross-provincial/regional urban construction land quotes reallocation and differential construction land management policies.