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Eco-efficiency of Chinese transportation industry: A DEA approach with non-discretionary input

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  • Song, Yao-yao
  • Li, Jing-jing
  • Wang, Jin-li
  • Yang, Guo-liang
  • Chen, Zhenling

Abstract

In the context of the rapid development of Chinese economy and the advancement of urbanization and industrialization, the transportation industry caused serious environmental pollution and resource waste problems. The eco-efficiency of Chinese transportation industry has become a hot spot of society. Recently, China announced several initiatives to stabilize and expand employment, so that the efficient and sustainable development of industries cannot be based on the premise of reducing the labor force. However, traditional efficiency measures usually assume that inputs can be reduced at will, which is insufficient to correctly represent the observed practice. In this paper, we investigate the eco-efficiency of the transportation industry in 30 Chinese provinces incorporating the non-discretionary input labor and undesirable output CO2 emission. Data envelopment analysis and directional distance function approaches are employed in constructing the measurement model. Our empirical results reveal explicit spatial features of the eco-efficiency in various provinces and show significant correlation between eco-efficiency and industrial structure, technological, and management factors. To examine the validity of our proposed models, comparative studies were further conducted and illustrated that the introduction of non-discretionary inputs and the selection of direction vectors have a crucial impact on the results of eco-efficiency. Based on the empirical results and our summarized policy implications, we found several deficiencies in the real policies and put forward corresponding policy suggestions for the industry and government.

Suggested Citation

  • Song, Yao-yao & Li, Jing-jing & Wang, Jin-li & Yang, Guo-liang & Chen, Zhenling, 2022. "Eco-efficiency of Chinese transportation industry: A DEA approach with non-discretionary input," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:soceps:v:84:y:2022:i:c:s0038012122001781
    DOI: 10.1016/j.seps.2022.101383
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