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Production Optimization in Carbon Reduction Engineering Management

Joint decisions on selling mode choice and emission reduction investment under cap-and-trade regulation

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Received 16 Feb 2023, Accepted 10 Dec 2023, Published online: 28 Dec 2023
 

Abstract

Consumers' growing awareness of environmental protection and carbon regulations enacted by the government based on strengthened environmental pressure are forcing manufacturers to curb carbon emissions. This paper considers a manufacturer investing in green technology to reduce carbon emissions under the cap-and-trade regulation, selling products to consumers through a direct channel and an online retail platform. The platform could choose to operate either in an agency mode or a reselling mode. A three-stage game is constructed to examine the interactions between the manufacturer's investment and the platform's operation mode under the cap-and-trade regulation, as well as the influences of the regulation on the interactions, and the supply chain coordination. The findings suggest that green technology investment in either operation mode leads to Pareto improvement in profits of both the platform and the manufacturer, and the investment induces the platform to prefer the reselling mode. Besides, the cap-and-trade regulation encourages the platform to opt for the agency mode, while the investment could mitigate the influence of the regulation on the platform's mode choice, with greater investment efficiency resulting in better mitigation. Furthermore, the investment could induce supply chain coordination under two modes through two different contracts.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Sustainable development goal keywords

SDG 12: Responsible consumption and production.

Data availability statement

Data sharing concerns are not applicable to this article, as no new data were created or analysed in this study.

Notes

7 This paper uses ‘she’ to indicate the manufacturer and ‘he’ to indicate the platform for convenience.

8 The unified pricing strategy is widely studied in the literature on the omni-channel supply chain, such as Ji, Zhang, and Yang (Citation2017), Gao and Su (Citation2017) and Zhou, Guo, and Zhou (Citation2018). In reality, Suning has developed an O2O mode with a uniform pricing strategy; Amazon opened the first offline bookstore ‘Amazon Books’ in Seattle University Village in November 2015, and the prices in ‘Amazon Books’ are the same as those in online sales.

9 Actually, the linear demand function can be formulated as qij=a1a2+τgeja2pja2. For the convenience of model calculation, we normalise a2=1.

Additional information

Funding

This work was supported by National Natural Science Foundation of China (Nos. 72101242, 72071093, 72171219, and 72001064), the RGC TRS Proiect (No. T32-707-22-N), the China Postdoctoral Science Foundation (No. 2020M682053), the Fundamental Research Funds for the Central Universities (No. JZ2022HGTBO303), the 2019 Guangdong Special Support Talent Program C Innovation and Entrepreneurship Leading Team (China) (No. 2019BT02S593), the Philosophy and Social Sciences Planning Project of Guangdong Province (No. GD22XGL62), and the New Liberal Arts Fund of USTC (FSSF-A-230104).

Notes on contributors

Qiang Wang

Qiang Wang received the Ph.D. degree in Management Science and Engineering from the School of Management, University of Science and Technology of China, Hefei, China, in 2020. He is currently an Associate professor at the School of Management, University of Science and Technology China. His research interests mainly focus on supply chain management and OM-Marketing interface. He has published in Omega-The International Journal of Management Science, Annals of Operations Research, Journal of the Operational Research Society, Computers & Industrial Engineering, Electronic Commerce Research, etc.

Su Xiu Xu

Su Xiu Xu is currently a professor in the School of Management and Economics, Beijing Institute of Technology, Beijing, China. He received his B.S. in mathematics from Harbin Institute of Technology (Harbin, China) in 2008 and PhD in industrial engineering from the University of Hong Kong in 2014. His major research interests are smart city, auction mechanism design, logistics and operations management. He has published more than 60 papers in such journals as International Journal of Production Research, IISE Transactions, Transportation Science, Transportation Research Part B, Transportation Research Part E, Transportation Research Part A, Transportation Research Part C, Production and Operations Management, Ecological Economics, International Journal of Production Economics, Omega, IEEE Transactions on Automation Science and Engineering, etc.

Xiang Ji

Xiang Ji is currently an Associate Professor in the School of Management at the University of Science and Technology of China, Hefei, China. He received his B.S. in Mathematics and Applied Mathematics and Ph.D. in Management Science and Engineering from the University of Science and Technology of China, Hefei, China, in 2011 and 2017 respectively. His research interests include supply chain management, data driven decision analytics, and OM-Marketing interface. He has published over 40 papers in peer-refereed academic journals such as European Journal of Operational Research, International Journal of Production Research, International Journal of Production Economics, Annals of Operations Research, and Omega-International Journal of Management Science.

Nenggui Zhao

Nenggui Zhao received the Ph.D. degree in Management Science and Engineering from the School of Management, University of Science and Technology of China, Hefei, China, in 2019. She is currently a Lecturer at the School of Management, Hefei University of Technology. Her research interests mainly focus on supply chain management and OM-Marketing interface. She has published in European Journal of Operational Research, Omega-The International Journal of Management Science, Annals of Operations Research, Journal of the Operational Research Society, Computers & Industrial Engineering, etc.

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