Blockchain-Enabled Healthcare Supply Chain Management: Identification and Analysis of Barriers and Solutions Based on Improved Zero-Sum Hesitant Fuzzy Game Theory
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Date
2025
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Elsevier Ltd
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Abstract
Blockchain technology has emerged as a transformative approach in the health sector, enhancing efficiency, transparency, and security in Healthcare Supply Chain Management (HSCM). It addresses critical issues such as data privacy, traceability, and fraud reduction, providing a secure and reliable platform. However, significant barriers to its implementation must be overcome to ensure effective healthcare supply chain operations. This study proposes a two-stage decision-making model for identifying barriers and optimizing blockchain adoption solutions in HSCM under uncertainty. The first stage employs the Hesitant Fuzzy Best-Worst Method (HFBWM) to prioritize barriers. Compared to traditional methods such as Analytic Hierarchy Process (AHP), HFBWM achieves high accuracy with fewer pairwise comparisons. In the second stage, the Improved Zero-Sum Hesitant Fuzzy Game Theory (IZSHFG) model, based on the Weighted Sum Operator (WSO) under Hesitant Fuzzy Sets (HFSs), determines the optimal combination of strategies for blockchain application in HSCM. The challenges are modeled as one player and the solutions as another, with the decision matrix established using WSO under HFS. The obtained results indicate the worst-case scenario involves the simultaneous occurrence of four critical barriers: “Lack of Sufficient Knowledge about Blockchain in HSCM” (0.011217), “Lack of Access to Skilled Technical Personnel” (0.025457), “High Maintenance and Support Costs” (0.056076), and “Security Risks of Patients' Data” (0.069367). These findings highlight the need for targeted strategies to address these barriers, ensuring blockchain's successful integration into HSCM. © 2025 Elsevier Ltd
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Blockchain Technology, Game Theory, Healthcare Supply Chain Management, Hesitant Fuzzy Sets, Multi-Criteria Decision-Making
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Source
Engineering Applications of Artificial Intelligence
Volume
154