Exploring the Spatial-Temporal Disparities of Urban Land Use Economic Efficiency in China and Its Influencing Factors under Environmental Constraints Based on a Sequential Slacks-Based Model

Abstract

Using a sequential slack-based measure (SSBM) model, this paper analyzes the spatiotemporal disparities of urban land use economic efficiency (ULUEE) under environmental constraints, and its influencing factors in 270 cities across China from [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. The main results are as follows: (1) The average ULUEE for Chinese cities is only 0.411, and out of the 270 cities, only six cities are always efficient in urban land use in the study period. Most cities have a lot of room to improve the economic output of secondary and tertiary industries, as well as environmental protection work; (2) The eastern region of China enjoys the highest ULUEE, followed by the western and central regions. Super-scale cities show the best performance of all four city scales, followed by large-scale, small-scale and medium-scale cities. Cities with relatively developed economies and less pollutant discharge always have better ULUEE; (3) The results of slack variables analysis show that most cities have problems such as the labor surplus, over-development, excessive pollutant discharge, economic output shortage, and unreasonable use of funds is the most serious one; (4) The regression results of the influencing factors show that improvements of the per capita GDP and land use intensity are helpful to raise ULUEE. The urbanization rate and the proportion of foreign enterprises' output account for the total output in the secondary and tertiary industries only have the same effect in some regions OPEN ACCESSSustainability 2015, 7 10172 and city scales. The land management policy and land leasing policy have negative impact on the ULUEE in all the three regions and four city scales; (5) Some targeted policy goals are proposed, including the reduction of surplus labor, and pay more attention to environmental protection. Most importantly, effective implementation of land management policies from the central government, and stopping blind leasing of land to make up the local government's financial deficit would be very helpful to improve the ULUEE of Chinese cities.

Introduction to the Special Issue on the Sustainable Asia Conference 2015

“…Urbanization should be promoted with detailed fine-tuning, as it also triggers problems of social disparity and degradation of human health. Using a sequential slack-based measure (SSBM) model, another paper analyzed the spatiotemporal disparities of urban land use economic efficiency (ULUEE) under environmental constraints, and its influencing factors in 270 cities across China during the period 2003-2012 [4]. The empirical results show that most cities face urbanization problems, such as oversupply of labor, over-development, excessive pollutant discharge, and shortage of economic output.…”

Land Use Efficiency and Total Factor Productivity—Distribution Dynamic Evolution of Rural Living Space in Chongqing, China

“…In terms of land use efficiency, foreign scholars place more emphasis on this analysis, which is different from the breadth and depth of urban system research [7][8][9]. In comparison with the documentation on urban system research, theoretical and practical research on rural land use efficiency is relatively weak because rural systems and the problems related with the subsystems have not yet been addressed in depth by scholars.…”

Measuring the Performance of Industrial Green Development Using a Non-Radial Directional Distance Function Approach: A Case Study of Jiangxi Province in China

“…As pointed out, the AHP and PCA approaches are unsuitable for the task, because the value of weights in the AHP method is determined by subjective scoring, and the dimension reduction in PCA is accompanied by information compression [16]. In contrast, the distance function approach has the advantage of not needing to set parameter weights and compress data information [17].…”