A comparative analysis of channel strategies for refurbished products: The influence of blockchain, brand spillover on co‐opetitive supply chain
Zhou Fang and
Yang Bai
Managerial and Decision Economics, 2024, vol. 45, issue 4, 2042-2058
Abstract:
Industry insiders and researchers have widely recognized refurbishment as an environmentally friendly activity that reduces raw material waste and energy consumption. Simultaneously, blockchain is increasingly used in the supply chain with its information transparency and traceability. The refurbished product market possesses substantial potential. Nevertheless, refurbished products carry an inherent risk of brand spillover. Within this framework, manufacturers must weigh broader considerations in selecting product distribution channels. In this study, we discuss three sales models for new and refurbished products in the secondary market, namely, Scenarios M (where the manufacturer sells new products to consumers through the retailer and sells refurbished products to consumers directly), R (where the manufacturer sells new products to consumers through the retailer, and the retailer produces and sells refurbished products alongside new products), and C (where the manufacturer sells new products to consumers, and the remanufacturer sells refurbished products to consumers through a retailer). Upon examining the equilibrium outcomes of each model, it is evident that a manufacturer's decision to produce refurbished products hinges on market demand. High demand for refurbished goods inclines manufacturers towards the M scenario, whereas insufficient demand leads to cessation of refurbishment activities. Conversely, retailers navigate between R and C scenarios based on market demand. The advent of blockchain technology shifts the strategic focus: the extent of brand spillover supersedes market demand as the pivotal factor influencing retailers' production strategies. Blockchain technology can increase manufacturers' profits. Interestingly, in Scenario C, blockchain does not always improve retailer profits.
Date: 2024
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https://doi.org/10.1002/mde.4118
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Persistent link: https://EconPapers.repec.org/RePEc:wly:mgtdec:v:45:y:2024:i:4:p:2042-2058
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