Research on economic benefits of multi-city logistics development based on data-driven analysis |
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| Affiliation: | 1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, PR China;2. Beijing Institute of Electronic System Engineering, Beijing, PR China;3. School of Economics and Management, University of the Chinese Academy of Sciences, Beijing, PR China;4. School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, PR China;5. HKU-ZIRI Lab for Physical Internet, Dept. of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China;1. State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China;2. College of Mechanical Engineering, Chongqing University, Chongqing 400044, China;3. School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China;1. Engineering of Systems and Environment, University of Virginia, Charlottesville, VA 22903, United States;2. University of California Los Angeles, United States;1. Laboratory for Artificial Intelligence in Design, Hong Kong, China;2. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China |
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| Abstract: | This study aims to measure the logistics economic efficiency of major first-tier cities in China and propose the interactive development plan of the green logistics industry based on the division of the urban agglomeration. In this study, the evaluation system for the logistics input and economic output of urban agglomerations is firstly established based on data-driven analytics, and a green logistics economic efficiency model using the dataset from 2008 to 2017 is constructed to estimate the input–output efficiency, development trend, and spatial differentiation of urban agglomerations comprehensively. Finally, the Shapley value method is adopted to obtain the specific distribution plan of logistics investment. The results show that the logistics economic efficiency of the 9 major urban agglomerations is all greater than 1 under the constant returns-to-scale (CRS) hypothesis while the average logistics economic efficiency of Pearl River Delta region, Chengdu-Chongqing region, and Shandong Peninsula region is significantly less than 1 under the medium returns-to-scale (MRS) hypothesis. The comprehensive input–output efficiency of five out of 9 major Chinese urban agglomerations showed a downward trend, with the highest declining rate of 5.9% in the Yangtze River Delta urban agglomeration. The urban agglomeration with the highest increase rate in input–output efficiency from 2013 to 2017 is the Chengdu-Chongqing region, which reached 3.97%. |
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| Keywords: | Urban agglomeration Merger benefit Data envelopment analysis Logistics economic efficiency |
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