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Volume 2017 (2017), Article ID 9516267, 11 pages
Research Article

A Novel Efficiency Measure Model for Industrial Land Use Based on Subvector Data Envelope Analysis and Spatial Analysis Method

1College of Economics & Management, Northwest A&F University, Yangling, Shaanxi 712100, China
2Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
3College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China

Correspondence should be addressed to Qun Wu; nc.ude.uajn@nuquw

Received 6 July 2017; Revised 11 September 2017; Accepted 23 November 2017; Published 17 December 2017

Academic Editor: Daniela Paolotti

Copyright © 2017 Wei Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the rapid and unbalanced development of industry, a large amount of cultivated land is converted into industrial land with lower efficiency. The existing research is extensively concerned with industrial land use and industrial development in isolation, but little attention has been paid to the relationship between them. To help address this gap, the paper creates a new efficiency measure method for industrial land use combining Subvector Data Envelope Analysis (DEA) with spatial analysis approach. The proposed model has been verified by using the industrial land use data of 30 Chinese provinces from 2001 to 2013. The spatial autocorrelation relationship between industrial development and industrial land use efficiency is explored. Furthermore, this paper examines the effects of industrial development on industrial land use efficiency by spatial panel data model. The results indicate that the industrial land use efficiency and the industrial development level in the provinces of eastern region are higher than those of the western region. The spatial distribution of industrial land use efficiency shows remarkable positive spatial autocorrelation. However, the level of industrial development has obvious negative spatial autocorrelation since 2009. The improvement of industrial development has a significant positive impact on the industrial land use efficiency.