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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: email
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Computer Systems Science and Engineering 2020, 35(3), 151-172. https://doi.org/10.32604/csse.2020.35.151

Abstract

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.

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APA Style
Zhao, J., Zeng, D., Zhou, T., Zhu, Z. (2020). "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, 35(3), 151-172. https://doi.org/10.32604/csse.2020.35.151
Vancouver Style
Zhao J, Zeng D, Zhou T, Zhu Z. "data mining of urban new energy vehicles in an intelligent government subsidy environment using closed-loop supply chain pricing model". Comput Syst Sci Eng. 2020;35(3):151-172 https://doi.org/10.32604/csse.2020.35.151
IEEE Style
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"," Comput. Syst. Sci. Eng., vol. 35, no. 3, pp. 151-172. 2020. https://doi.org/10.32604/csse.2020.35.151

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cc 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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