Analytics of cap-and-trade policy for dual supply chain network structures

Nowadays, managing clean and green supply chain activities by reducing carbon footprint is a prominent aspect of the research. This study presents a dual supply chain (DSC) model under the cap-and-trade (CAT) emission reduction for the manufacturer-led five different DSC network structures, namely vertically integrated, decentralized, partially integrated retail, partially integrated direct, and horizontally integrated to minimize the carbon footprint. It uses a backward induction method to find optimum decision variables namely wholesale price, selling price, demand, and emission reduction rate. It presents a mathematical analysis to evaluate how the permitted emission quota and emission level of channel members affect the decision variables of various network structures. Further, it conducts a sensitivity analysis to measure how consumers’ channel preferences affect price and emission reduction rates. This study illustrates that (1) the emission reduction investment can increase demand and improve the emission reduction rate with a considerable drop in price. Also, (2) the additional purchased carbon quota can help maintain emission levels up to a certain extent only because any additional buying will be considered a short-term salutation. As a result, channel members are encouraged to invest in emission reduction technology instead of buying additional permits. These results conclude that promoting CAT can help achieve targets to reduce emissions and foster economic and social development.