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"Data Mining of Urban New Energy Vehicles in an Intelligent Government Subsidy Environment Using Closed-Loop Supply Chain Pricing Model"

Jing-Hua Zhao1,†, Da-Lin Zeng2,*, Ting-Wei Zhou1,‡, Ze-Chao Zhu1,§

1 School of Business, University of Shanghai for Science and Technology, Shanghai, China
2 School of Management Engineering, Shandong Jianzhu University, Jinan, China

* Corresponding Authors:


Computer Systems Science and Engineering 2020, 35(3), 151-172.


Given the government subsidies for new energy vehicles, this study is conducted to study the closed-loop supply chain comprising individual manufacturers, individual retailers and individual third-party recyclers. In this paper, combine the reality of new energy vehicles with the relevant research of game theory, and establish an no government subsidy model (Model N), a government subsidized consumer model (Model C), a government subsidized manufacturer model (Model M), a government subsidized third party recycler model (Model T), and a government subsidized retailer model (Model R) for quantitative research. Then, numerical examples are used to simulate the impact of government subsidies on closed-loop supply chain pricing and profits.


Cite This Article

J. Zhao, D. Zeng, T. Zhou and Z. Zhu, ""data mining of urban new energy vehicles in an intelligent government subsidy environment using closed-loop supply chain pricing model"," Computer Systems Science and Engineering, vol. 35, no.3, pp. 151–172, 2020.


This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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