Abstract
To study how emissions regulations impact supply chain operations, we consider a supply chain where a supplier produces and sells raw material to a manufacturer, who then uses it to produce a final product to satisfy random market demand. Both firms are equipped with two production technologies, one of which is costlier, but generates fewer emissions than the other. Each firm’s emissions are capped by the amount of allowances it holds, and if the firm over-emits, it pays a penalty. We solve the optimal solutions of a centralized system, both jointly regulated and separately regulated, and a decentralized system. We find that the relationships between the emissions abatement cost, the emissions penalty, and the salvage value of the allowance largely determine the technology choice of the firms. For the centralized system, joint regulation results in a higher profit than separate regulation, but it may not result in a larger production quantity. For the decentralized system, under a more stringent regulation (fewer allowances), the firms may produce more while not using more of the green technology; and if the manufacturer has fewer allowances, the manufacturer and the whole chain may be better-off. The numerical study further illustrates that adding a green technology is always economically beneficial to the centralized supply chain, although it may hurt the manufacturer and the decentralized chain. In the scenarios where only either the supplier or the manufacturer is regulated, we show analytically that the centralized system produces more, uses more green technology, and generates more emissions than the decentralized one. More interestingly, the decentralized supply chain with the regulated supplier produces more, has a higher profit, and emits more than the supply chain with the regulated manufacturer when the emissions intensities of the production technologies are the same for the firms.
Acknowledgements
The authors are grateful to the suggestions and comments from the Area Editor and an anonymous referee, which have helped greatly improve the paper.
Funding
Sean X. Zhou is partially supported by Hong Kong RGC GRF Grant CUHK-419411, National Natural Science Foundation of China NSFC-71471159, NSFC-71531005, and the Asian Institute of Supply Chain and Logistics at the Chinese University of Hong Kong.
Notes
2 In Drake et al. (Citation2016) the unit penalty and the salvage value of the allowances are assumed to be the same. As will be seen later, this assumption would have greatly simplified the analysis and the results.
3 Since the parameters are positive in our models, it is sufficient to consider the domain x > 0 for the function .
4 When and , the two centralized systems have the same optimal solutions.
Additional information
Notes on contributors
Jen-Yen Lin
Jen-Yen Lin joined the National Chiayi University in Taiwan in 2006, where he is currently associate professor in the Department of Applied Mathematics. His research interests include fractional programming, supply chains, and inventory systems.
Sean X. Zhou
Sean X. Zhou is currently a professor in the Department of Decision Sciences and Managerial Economics, The Chinese University of Hong Kong (CUHK) Business School. He is also the Director of the Supply Chain Research Centre under the Asian Institute of Supply Chain and Logistics in CUHK. His main research area is supply chain management with particular interests in inventory control, production planning, dynamic pricing, and game theoretic applications. He serves on the editorial board of IISE Transactions (formerly IIE Transactions), Naval Research Logistics, and OR Letters.
Fei Gao
Fei Gao received her Ph.D. degree from the Chinese University of Hong Kong in 2008, under the supervision of Prof. Frank Youhua Chen. Afterwards, she did postdoctoral research at the Polytechnic University of Hong Kong under the supervision of Prof. Liming Liu in 2008, and at the Chinese University of Hong Kong under the supervision of Prof. Sean Zhou from January 2009 to June 2010. Currently, she is a wealth management manager in the insurance company AIA.