Journal article
An analysis of strategies for adopting blockchain technology in the after-sales service supply chain
Computers & industrial engineering, v 179, 109194
May 2023
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this paper, we explore strategies for implementing blockchain technology in a supply chain where a manufacturer outsources base warranty (BW) repairs to a retailer and the retailer offers additional after-sales service. We developed a mathematical model and calculated the optimal strategies for supply chain members based on the traditional service platform (TSP), in which the retailer does not use blockchain technology, and on the blockchain service platform (BCSP), where the retailer uses blockchain technology to let the consumer track and trace after-sales service. Our analyses found that the benefits of BCSP include gaining consumers’ trust and earning reward tokens as an appreciation, however its implementation costs make it not always the ideal choice. In addition, based on the combined analysis of reward-tokens and consumers’ trust, we discovered ”triple win regions”, where in one of the regions the BCSP benefits manufacturer and retailer simultaneously, but only if the reward-token value exceeds a threshold. The threshold is based on consumers’ trust level, the failure rate of a product, and the cost of blockchain installation and operation. At the end, numerical analysis was conducted to validate the analytical results.
• After sales service on traditional service platform links consumers’ distrust.
• To mitigate the risk of distrust, blockchain service platform can be implemented.
• Blockchain service platform implementation has associated costs and benefits.
• A ‘triple win region’ exists where the blockchain service platform benefits firms.
• Implementing blockchain service platform is not always the optimal decision.
Metrics
Details
- Title
- An analysis of strategies for adopting blockchain technology in the after-sales service supply chain
- Creators
- Azmat Ullah - Hainan UniversityMuhammad Ayat - University of the West of ScotlandYi He - Hainan UniversityBenjamin Lev - Drexel University
- Publication Details
- Computers & industrial engineering, v 179, 109194
- Publisher
- Elsevier
- Grant note
- 720RC568 / Hainan Provincial Natural Science Foundation of China (http://dx.doi.org/10.13039/501100004761) 71872075 / National Natural Science Foundation of China (http://dx.doi.org/10.13039/501100001809)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000965324800001
- Scopus ID
- 2-s2.0-85151412888
- Other Identifier
- 991020277577104721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Industrial