An integrated waterfall–DEMATEL–fuzzy TOPSIS approach to post-COVID-19 customer demand resilience: Evidence from fast-fashion MSMEs

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
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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