MULTISTAGE GLOBAL SUPPLY CHAIN INVENTORY MODEL WITH THE IMPACT OF CARBON TARIFFS FOR DETERIORATING ITEMS

The European Union intends to adopt a more aggressive unilateral policy-carb on tariffs to promote the reduction of global carbon emissions. In our research, a global supply chain model is developed to determine the effects of carbon tariffs along with domestic carbon policies. Domestic carbon poli-cies in which the retailer country has a (1) carbon tax or (2) cap-and-trade, while the manufacturing country has (1) a carbon tax or (2) no carbon policy are considered. The proposed production -inventory model for a three-stage supply chain comprises the supply of raw materials, a single export manufac-turer's productionand delivery, and a single import retailer's orders and sales for deteriorating items. The exchange rate for transactions among supply chain members is also taken into consideration. Mathematical programming analysis is used to determine the manufacturer's optimal material supply, production, and delivery strategies, as well as the retailer's optimal pricing and replen-ishment strategies. The main goal is to maximize joint total profit in both settings, and this is achieved through numerical and sensitivity analysis. This study found that carbon tariffs have a positive impact on the emission reduc-tion effect of cross-b order supply chain systems. Additionally, it revealed that within a multinational three-stage supply chain, considering the deterioration of raw materials and finished products, the increase in the carbon tariff rates and exchange rates enhance the emission reduction effect of the supply chain and have a positive impact on the joint total profits of the supply chain. Fi-nally, unlike previous studies, this study also explored that the adjustment of carbon tariff relief rate have a complex impact on the profits and emissions reduction of the supply chain members. These results can help enterprises un-derstand the impact of carbon tariffs on supply chain inventory and pricing decisions.