Please use this identifier to cite or link to this item: http://hdl.handle.net/10739/2559
Title: EVALUATING SUPPLY CHAIN RESILIENCY STRATEGIES IN THE INDIAN PHARMACEUTICAL SECTOR: A FUZZY ANALYTIC HIERARCHY PROCESS (F-AHP) APPROACH
Authors: Ganguly, Anirban
Kumar, Chitresh
Keywords: Multi-criteria decision-making (MCDM); supply chain resilience; resiliency strategies; Fuzzy Analytic Hierarchy Process (F-AHP); Analytic Hierarchy Process (AHP); Indian pharmaceutical sector
Issue Date: 31-Jul-2019
Publisher: International Journal of the Analytic Hierarchy Process
Citation: Ganguly A., Kumar C. (2019), Evaluating supply chain resiliency strategies in Indian pharmaceutical sector: A Fuzzy Analytic Hierarchy Process (F-AHP) Approach, International Journal of Analytic Hierarchy Process, 11 (2), https://doi.org/10.13033/ijahp.v11i2.620
Abstract: Over the years, aggressive competition and globalization have resulted in tremendous progress in the development and management of supply chains. There are many high- performing supply chains that have benefitted from globalization. However, globalization of supply chains has also resulted in exposure to increased risks and frequent disturbances at various stages. One way to address these disturbances is to make supply chains resilient in nature. This paper identifies and prioritizes a set of important resiliency strategies for supply chains using the Fuzzy Analytic Hierarchy Process (F-AHP). Responses from 23 experts from the Indian pharmaceutical sector have been analyzed. We found that supply chain agility, visibility, and collaboration were the three most important resiliency strategies that a pharmaceutical organization should follow to address the vulnerability within their supply chain. The findings will serve the supply chain managers and the policymakers in designing resilient supply chains through the better understanding of strategies and formulation of action plans, while also introducing MCDM techniques into resiliency studies.
URI: http://hdl.handle.net/10739/2559
ISSN: 1936-6744
Appears in Collections:JGU Research Publications

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