Addressing Industry Adaptation Resistance in Combating Brand Deception: AI-Powered Technology vs. Revenue Sharing

This paper studies a supply chain comprising a supplier, a third-party remanufacturer (TPR), and a retailer. The retailer sells both genuine and remanufactured products (i.e., Model O). Leveraging information advantages, the retailer may engage in brand deception by mislabeling remanufactured produc...

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Vydáno v:Journal of theoretical and applied electronic commerce research Ročník 20; číslo 3; s. 154
Hlavní autor: Liu, Peng
Médium: Journal Article
Jazyk:angličtina
Vydáno: Curicó MDPI AG 01.07.2025
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ISSN:0718-1876, 0718-1876
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Shrnutí:This paper studies a supply chain comprising a supplier, a third-party remanufacturer (TPR), and a retailer. The retailer sells both genuine and remanufactured products (i.e., Model O). Leveraging information advantages, the retailer may engage in brand deception by mislabeling remanufactured products as genuine to obtain extra profits (i.e., Model BD). AI-powered anti-counterfeiting technologies (AIT) (i.e., Model BA) and revenue-sharing contracts (i.e., Model C) are considered countermeasures. The findings reveal that (1) brand deception reduces (increases) sales of genuine (remanufactured) products, prompting the supplier (TPR) to lower (raise) wholesale prices. The asymmetric profit erosion effect highlights the gradual erosion of profits for the supplier, retailer, and TPR under brand deception. (2) The bi-interval adaptation effect indicates that AIT is particularly effective in industries with low adaptation resistance. When both the relabeling rate and industry adaptation resistance are low (high), Model BA (Model O) achieves a triple win. (3) Sequentially, when the industry adaptation resistance is low, AIT can significantly improve total profits, consumer surplus (CS), and social welfare (SW). Compared to Model BD, revenue-sharing offers slight advantages in CS but notable disadvantages in SW.
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ISSN:0718-1876
0718-1876
DOI:10.3390/jtaer20030154