{"title":"Cooperation models in automotive supply chain under low-carbon emission reduction policies","authors":"Yukun Cheng, Zhanghao Yao, Tingting Meng","doi":"10.1007/s10878-024-01160-8","DOIUrl":null,"url":null,"abstract":"<p>For the issue of carbon emission mitigation within the automotive supply chain, the cooperation between the vehicle manufacturers and the retailers has been proved to be an efficient measure to enhance emission reduction endeavors. This paper aims to evaluate the effectiveness of the cooperations between a vehicle manufacturer and multiple retailers based on the differential game method. By utilizing the Hamilton–Jacobi–Bellman equation, the equilibrium strategies of the participants under two different cooperation models, i.e., the decentralized model and the Stackelberg leader–follower cooperation model, are analyzed. To be specific, in the decentralized model, each participant independently decides its strategies, whereas the manufacturer cooperates with retailers by offering subsidies in the Stackelberg leader–follower model. Unlike previous studies that solely focused on participants’ decision-making in carbon emission reduction efforts, this paper also examines the retail pricing decisions of the retailers. Additionally, carbon trading is introduced to enhance the realism of our model. Through the theoretical analysis and the numerical experiments on the carbon emission reduction efforts of manufacturers and retailers, as well as the low-carbon reputation of vehicles and the overall system profit under both models, we conclude that the cooperative Stackelberg model outperforms the decentralized model in providing benefits to both parties. Furthermore, such a cooperative approach can foster the long-term development of the automotive supply chain, ultimately contributing to a more sustainable low-carbon future.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"122 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-024-01160-8","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
For the issue of carbon emission mitigation within the automotive supply chain, the cooperation between the vehicle manufacturers and the retailers has been proved to be an efficient measure to enhance emission reduction endeavors. This paper aims to evaluate the effectiveness of the cooperations between a vehicle manufacturer and multiple retailers based on the differential game method. By utilizing the Hamilton–Jacobi–Bellman equation, the equilibrium strategies of the participants under two different cooperation models, i.e., the decentralized model and the Stackelberg leader–follower cooperation model, are analyzed. To be specific, in the decentralized model, each participant independently decides its strategies, whereas the manufacturer cooperates with retailers by offering subsidies in the Stackelberg leader–follower model. Unlike previous studies that solely focused on participants’ decision-making in carbon emission reduction efforts, this paper also examines the retail pricing decisions of the retailers. Additionally, carbon trading is introduced to enhance the realism of our model. Through the theoretical analysis and the numerical experiments on the carbon emission reduction efforts of manufacturers and retailers, as well as the low-carbon reputation of vehicles and the overall system profit under both models, we conclude that the cooperative Stackelberg model outperforms the decentralized model in providing benefits to both parties. Furthermore, such a cooperative approach can foster the long-term development of the automotive supply chain, ultimately contributing to a more sustainable low-carbon future.
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.