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Optimal pricing and carbon emission reduction decisions for a prefabricated building closed-loop supply chain under a carbon cap-and-trade regulation and government subsidies

Author

Listed:
  • Xuefang Sun
  • Yuyang Wang
  • Yuanyuan Li
  • Wenjing Zhu
  • Dehuan Yan
  • Jiahui Li

Abstract

This paper explores a two-level prefabricated building closed-loop supply chain (CLSC) comprising a retailer and a prefabricated building manufacturer (PBM) under carbon cap-and-trade legislation and the government subsidies of carbon emission reduction (CER). In this CLSC, the PBM and the retailer recycle used products through their independent recycling channels. The optimum pricing and CER strategies within both decentralized and centralized systems, respectively, are analyzed. The Stackelberg game is used in the decentralized system to determine the optimum PBM’s CER level and the retailer’s pricing. By analysis, it concludes that increasing the carbon trading price can stimulate prefabricated construction corporations to improve their CER level, and that the government subsidy rate has a great effect on the profits of the PBM. Numerical examples with sensitivity analysis are used to further evaluate the roles of important factors in the optimum CER and pricing solutions of the prefabricated building CLSC in two dissimilar systems.

Suggested Citation

  • Xuefang Sun & Yuyang Wang & Yuanyuan Li & Wenjing Zhu & Dehuan Yan & Jiahui Li, 2023. "Optimal pricing and carbon emission reduction decisions for a prefabricated building closed-loop supply chain under a carbon cap-and-trade regulation and government subsidies," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-19, June.
    • Handle: RePEc:plo:pone00:0287684
    DOI: 10.1371/journal.pone.0287684
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    References listed on IDEAS

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    Cited by:

    1. Yangjun Ren & Qiong Chen & Yui-yip Lau & Maxim A Dulebenets & Mengchi Li & Botang Li & Mark Ching-Pong Poo & Pengfei Zhang, 2024. "An Improved Migratory Birds Optimization Algorithm for Closed- Loop Supply Chain Network Planning in a Fuzzy Environment," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-31, June.

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