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• W4386836164 endingPage "138897" @default.
• W4386836164 startingPage "138897" @default.
• W4386836164 abstract "This paper proposes an integrated inventory model of a supply chain system consisting of a single manufacturer and single buyer under stochastic demand. The model considers carbon tax regulation to reduce supply chain operations' emissions. To comply with this regulation, the manufacturer invests in green production technologies and replaces the existing (conventional) facility with a green facility. Thus, the manufacturer can benefit by implementing a hybrid production system involving the simultaneous operation of a conventional and a green facility. The green facility requires higher production costs than the conventional facility, but its emissions are lower. The demand is stochastic and the average demand rate is influenced by the product selling price and green investment level. The goal of this research is to determine the optimal delivery lot, number of shipments, safety factor, selling price and investment level in order to optimize the joint total profit. An efficient algorithm is proposed to solve the problem and a numerical example is provided to demonstrate the applicability of the proposed model. A sensitivity analysis is performed to evaluate the impact of the model's key parameters on its behavior. The results show that green investments made by the manufacturer can effectively reduce the total emissions generated from the supply chain and increase the product's selling price. Furthermore, a hybrid system operated by the manufacturer is proven to control costs and emissions, especially in situations in which the replacement of production facilities must be performed gradually based on the available investment budget." @default.
• W4386836164 created "2023-09-19" @default.
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• W4386836164 date "2023-11-01" @default.
• W4386836164 modified "2023-09-29" @default.
• W4386836164 title "Pricing and green inventory decisions for a supply chain system with green investment and carbon tax regulation" @default.
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• W4386836164 doi "https://doi.org/10.1016/j.jclepro.2023.138897" @default.
• W4386836164 hasPublicationYear "2023" @default.
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