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Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study

Author

Listed:
  • Xiang Ji

    (University of Science and Technology of China)

  • Jie Wu

    (University of Science and Technology of China)

  • Qingyuan Zhu

    (University of Science and Technology of China)

  • Jiasen Sun

    (Soochow University)

Abstract

Due to recent official policy changes, China’s sustainable urbanization has entered a new type of multi-target heterogeneous situation which has never been scientifically researched before. To deal with this new heterogeneous scenario, we introduce a hybrid heterogeneous data envelopment analysis method that contains input segment estimation and efficient frontier construction. We also introduce a bi-level benchmarking method that benchmarks each city’s eco-efficiency and uses those benchmarks to guide sustainable urbanization completion in an empirical study of 206 Chinese prefecture-level cities’ sustainable urbanization. Our main empirical results show that: (1) China’s urbanization is now suffering from serious unsustainability; (2) China’s sustainable urbanization is independent of urban scale; (3) resource over-consumption and pollutant over-emission are the two complementary forces that slow down China’s sustainable urbanization; (4) almost all prefecture-level cities involved in this empirical study should set “Urban–rural integration” as the urbanization development target; and (5) China’s current urbanization has a serious development target mismatch, and this target mismatch is thought to be an important indirect factor that drives China’s urbanization to a low sustainability level. Based on this empirical analysis, we recommend two urbanization policies, “Constructing a distinctive city” and “Constructing hub-and-spoke urban agglomeration”, for Chinese government consideration.

Suggested Citation

  • Xiang Ji & Jie Wu & Qingyuan Zhu & Jiasen Sun, 2019. "Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study," Annals of Operations Research, Springer, vol. 278(1), pages 281-335, July.
  • Handle: RePEc:spr:annopr:v:278:y:2019:i:1:d:10.1007_s10479-018-2855-6
    DOI: 10.1007/s10479-018-2855-6
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