Fares, Naila, Jaime, Lloret, Kumar, Vikas, Frederico, Guilherme, Kumar, Anil and Garza-Reyes, Jose Arturo (2022) An integrated waterfall–DEMATEL–fuzzy TOPSIS approach to post-COVID-19 customer demand resilience: Evidence from fast-fashion MSMEs. Benchmarking: an International Journal. ISSN 1463-5771 (In Press)
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Abstract / Description
Purpose:
The purpose of this paper is to analyze the resilience of customer demand management post-COVID-19, using fast-fashion MSMEs as an example. Precisely, this paper investigates how waterfall project management can enable stakeholders to build survival operations managerial decisions.
Design/methodology/approach:
Based on interviews and surveys with ten fast-fashion operations experts, and an integrated waterfall DEMATEL Fuzzy TOPSIS methodology of the fuzzy multi-criteria decision making (FMCDM), we explored and prioritized the enablers of resilience management in fast-fashion retail area.
Findings:
Results reveal that the highest priority enabler is maintaining customer loyalty. Other enablers are associated with e-commerce endorsement, customer-focused assortment, and flexible store operations.
Research /implications:
The findings of this paper will enable fast-fashion MSMEs to develop effective actions and prioritize the operations efforts to foster the post-pandemic recovery.
Originality/value:
Despite the importance of the resilience project and the changing fast-fashion customer patterns with Covid, only a handful of research has explored how resilience can be managed in this field. This research thus can help close this gap for operations resilience research and retail context
Item Type: | Article |
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Uncontrolled Keywords: | COVID-19; customer demand resilience; waterfall; project management; fuzzy TOPSIS; fast-fashion MSMEs |
Subjects: | 600 Technology > 650 Management & auxiliary services |
Department: | Guildhall School of Business and Law |
Depositing User: | Anil Kumar |
Date Deposited: | 19 Aug 2022 06:34 |
Last Modified: | 19 Aug 2022 06:34 |
URI: | https://repository.londonmet.ac.uk/id/eprint/7860 |
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