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The Research On Pricing And Recovery Decision Of Closed-loop Supply Chain With Government Subsidy

Posted on:2020-09-01Degree:MasterType:Thesis
Country:ChinaCandidate:X ChenFull Text:PDF
GTID:2439330590993373Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Traditional supply chain management usually only focuses on the economic interests of enterprises,but ignores the negative impact of production and consumption on the environment.Reverse logistics focuses on recycling and recycling remanufacturing,through the recycling and remanufacturing of waste materials,strive to minimize the negative impact of production and consumption activities on the environment.The closed-loop supply chain integrates forward logistics and reverse logistics,so that the material can be in a way of minimum loss for a circular flow,thus improve the social environmental benefits,and decrease the negative impact on the environment to a minimum brought by each link of the production activities.Therefore,based on the newsvendor model,this paper studies a closed-loop supply chain system,which consists of a manufacturer,a retailer and a third-party recycler,and the recycler is solely responsible for the recycling of reverse logistics.By constructing a Stackelberg game model,studies how manufacturer,retailer and third-party recycler maximize their expected profits by making decisions on wholesale price,retail price,order quantity and recovery rate when facing uncertain consumer market demand.Moreover,starting from the internal coordination of supply chain system,a profit sharing incentive mechanism based on government subsidy and a profit sharing incentive mechanism based on cost savings of reproductive manufacturing are established,which is dominated by manufacturer and the third party,respectively,to explore the decision-making behavior of supply chain members under incentive mechanism and two different situations of incentive mechanism with or without profit sharing strategy.
Keywords/Search Tags:Remanufacturing, Newsvendor Model, Random Demand
PDF Full Text Request
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