How to subsidizing the used apparel recycling supply chains effective? An analysis based on the game framework
RAIRO. Operations Research, Tome 56 (2022) no. 6, pp. 4063-4081

Motived to find the optimal subsidy strategies in the used apparel recycling supply chains, this paper establishes a benchmark recycling model including a brand retailer and a remanufacturer, and extends the benchmark model based on different subsidy scenarios: (a) the government subsidizes the remanufacturer, (b) the government subsidizes the retailer’s remanufacturing part, (c) the government subsidizes all recycled apparel from the retailer. The constructed models show some interesting results. (1) Both the strategies (a) & (b) drove the same recycling efforts. The remanufacturer maybe mistakenly believe its profits could increase with the lower procurement price in scenario (b). However, the profits were the same in both scenarios. (2) The strong consumer sensitivity to recycling efforts not only increases the retailer’s profits but also drops the remanufacturer’s profits. Therefore, strong consumer sensitivity is only good for some players. (3) The donation ratio should be within a reasonable range. Otherwise, the remanufacturer’s profit decreases, and even the remanufacturer withdraws from the supply chain. (4) The optimal subsidy strategy for the supply chain members is that the government subsidizes all recycled from the retailer. Based on our findings, some management insights and suggestions are presented.

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DOI : 10.1051/ro/2022193
Classification : 91A40, 91B24
Keywords: Consumer sensitivities, recycling efforts, apparel industry, subsidy, game theory
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     title = {How to subsidizing the used apparel recycling supply chains effective? {An} analysis based on the game framework},
     journal = {RAIRO. Operations Research},
     pages = {4063--4081},
     year = {2022},
     publisher = {EDP-Sciences},
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Wang, Zongxian. How to subsidizing the used apparel recycling supply chains effective? An analysis based on the game framework. RAIRO. Operations Research, Tome 56 (2022) no. 6, pp. 4063-4081. doi: 10.1051/ro/2022193

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