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Measuring Sustainable Development Efficiency of Urban Logistics Industry

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  • Chenglong Cao

Abstract

Logistics plays a basic supporting role in the growth of national economy. However, tail gas, noise, and traffic congestion caused by logistics have a negative impact on the environment. An effective evaluation mechanism for sustainable development of urban logistics industry is necessary. Data envelopment analysis (DEA) is a common tool for efficiency evaluation. But, DEA has a limited effect on resource allocation in advance because it is ex-post evaluation. It requires input-output indications and the output is after-the-fact data. This defect is particularly prominent in the evaluation of ecological logistics because pollution indicators belong to ex-post output data that threaten the human environment. First prediction and then evaluation is a possible idea. In addition, DEA efficiency ranking does not have a good discrimination due to its coarse granularity. To solve the issues, combining DEA with the Bayes method, we propose an efficiency evaluation model without after-the-fact data, where an efficiency level is predicted and an evaluation value is calculated according to different investment combinations. Then, it is applied to logistics industries of Jiangsu province in China. The results show that our DEA-Bayes method has good discrimination and is easy to operate; a city with geographical advantage and environmental awareness generally gets a higher efficiency score. So the method can help decision makers to allocate resources rationally and further promote the coordinated development of logistics industry.

Suggested Citation

  • Chenglong Cao, 2018. "Measuring Sustainable Development Efficiency of Urban Logistics Industry," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, November.
    • Handle: RePEc:hin:jnlmpe:9187541
    DOI: 10.1155/2018/9187541
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    Cited by:

    1. Sebastjan Lazar & Dorota Klimecka-Tatar & Matevz Obrecht, 2021. "Sustainability Orientation and Focus in Logistics and Supply Chains," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    2. Yuxia Guo & Huiying Mao & Heping Ding & Xue Wu & Yujia Liu & Hongjun Liu & Shuling Zhou, 2022. "Data-Driven Coordinated Development of the Digital Economy and Logistics Industry," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    3. Heng Chen & Yan Zhang, 2022. "Research on the Path of Sustainable Development of China’s Logistics Industry Driven by Capital Factors," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    4. Shuquan Hong & Huiyuan Jiang & Shuang Cheng & Yuejun Huang & Chao Feng, 2023. "A Study on the Policy Effects of the Establishment of Guangdong–Hong Kong–Macao Greater Bay Area on Logistics Efficiency," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    5. Chong Ye & Jiawei Pi & Hanqi Chen, 2022. "Coupling Coordination Development of the Logistics Industry, New Urbanization and the Ecological Environment in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 14(9), pages 1-24, April.

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