Journal of Resources and Ecology ›› 2021, Vol. 12 ›› Issue (2): 155-164.DOI: 10.5814/j.issn.1674-764x.2021.02.003

• Land Use Efficiency • Previous Articles     Next Articles

Spatiotemporal Differentiation and the Factors Influencing Eco-efficiency in China

LI Qiuying1, LIANG Longwu2,3, WANG Zhenbo2,3,*()   

  1. 1. Institute of Shandong Academy of Social Sciences, Jinan 250002, China
    2. Institute of Geographic Sciences and National Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2020-09-01 Accepted:2020-11-25 Online:2021-03-30 Published:2021-05-30
  • Contact: WANG Zhenbo
  • Supported by:
    The National Natural Science Foundation of China(41771181);The National Natural Science Foundation of China(41661116);The Shandong Social Science Planning Fund Program(20CJJJ04)


Economic development, resource utilization, and environmental protection have always presented clear dilemmas for many countries at the national level. It is clear that the related concepts of eco-efficiency and the evaluation index can help in evaluating these associated issues. Thus, based on the use of undesirable output super Slacks-Based Measure models, this study evaluated the eco-efficiency of 30 Chinese provinces during the period between 2005 and 2016. This evaluation was conducted by analyzing the spatiotemporal dynamics and key factors influencing these changes using a panel regression model. The results of this analysis reveal that eco-efficiency gradually increased over the course of the study period, peaking at different levels among the regions. We used the conventional CV evolutionary method to show that inequalities in eco-efficiency gradually decreased at the national level. Indeed, our estimations of the factors affecting this variable suggest that industrial structure, degree of openness, urbanization, technical innovation, and environmental governance all exert significant positive influences, while energy consumption and traffic exert negative effects. The extent of the impacts of these factors on eco-efficiency varied between the different regions.

Key words: eco-efficiency, super-SBM model, influencing factors, panel regression model