Abstract
The presence of risks that lead to potential disruptions is evident along the Indian medical equipment supply chain. Identifying and prioritising the supply chain risks is pivotal in enhancing supply chain resilience, surplus, and sustainability. This study uses multicriteria Decision-Making to prioritise supply chain risks in the Indian medical equipment industry. Unstructured interviews were conducted with industry experts from six medical equipment firms to identify supply chain risks. The identified risks were prioritised using the Analytic Hierarchy Process (AHP), Fuzzy AHP, and Analytic Network Process (ANP). AHP outlines the relative importance and ranks the risks. Finally, a simulation using ANP ranks the risks under different circumstances, considering the magnitude of impact and frequency of occurrence. A total of nine iterations were run to obtain a generalised rank for the identified supply chain risks under a combination of different scenarios of risk magnitude and frequency. The AHP results indicated that the industry experts considered inventory management risks as the most significant factor, followed by digitalisation and technological infrastructure. The Fuzzy AHP results revealed the triangulated weights in the same rank which was used to reiterate the findings from the AHP results with added dynamics in the form of the nearest neighbouring values. The ANP iterations revealed that supply and demand uncertainties must be managed first amidst any given risk scenario, followed by inventory and technological risks. The originality of this study is that the ANP results derived from nine iterations provide an overall decision matrix that can be generalised across the Indian medical equipment sector.
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Leslie Dass, P., Nair, S. V. R., Kumar Chandar, S., & Kurien, G. P. (2025). A Multicriteria Decision-Making Approach to Building Resilience Along the Indian Medical Equipment Supply Chain. In Smart Innovation, Systems and Technologies (Vol. 413 SIST, pp. 159–178). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-7717-4_12
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