THE OPTIMAL RECYCLE MECHANISM FOR USED APPAREL CONSIDERING SOCIAL DONATION UNDER GOVERNMENT CARBON REGULATIONS

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Abstract

Facing used apparel collection and social donation under government regulations (i.e., carbon tax policy or cap-and-trade policy), this study investigates whether the responsibility should lie with the manufacturer or a third-party platform. Our study indicates that the traditional closed-loop supply chain fails to achieve Social Donation. The findings of this study reveal that both the unit value of recycled products by the manufacturer and the unit value of charitable donations play significant roles in promoting the recycling of used apparel. And the study shows that when the carbon tax rate increases, it diminishes the benefits of supply chain members. On the other hand, when the carbon trading price increases, it reduces the benefits of third-party platforms but enhances the benefits of manufacturers within the carbon quotas while decreasing the benefits beyond the carbon quotas. In addition, this study conducts an analytical examination to determine the optimal used apparel recycling strategy under government regulations mechanism from the perspectives of economic benefit, environmental benefit, social donation contribution and customer surplus. Furthermore, the study reveals that the company’s preference for the carbon tax policy only when the carbon quota is small and identifies that under cap-and-trade regulations, the recycling strategy adopted by the manufacturer yields the highest benefits for the government. Significantly, the study highlights that the most effective approach to reducing carbon emissions and promoting social donation is through the implementation of a circular economy, this entails elevating recycling levels, placing emphasis on remanufacturing, and reducing the production of new products.

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CITATION STYLE

APA

Li, Z. T., Zhang, C. H., & Lyu, R. X. (2024). THE OPTIMAL RECYCLE MECHANISM FOR USED APPAREL CONSIDERING SOCIAL DONATION UNDER GOVERNMENT CARBON REGULATIONS. Journal of Industrial and Management Optimization, 20(3), 1242–1270. https://doi.org/10.3934/jimo.2023123

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