Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

A Comprehensive Review of MCDM Applications in Enhancing Textile Supply Chain Management

Version 1 : Received: 8 September 2024 / Approved: 8 September 2024 / Online: 9 September 2024 (09:17:32 CEST)

How to cite: Alimohammadi, M.; Salehi, A.; Babaei, A. A Comprehensive Review of MCDM Applications in Enhancing Textile Supply Chain Management. Preprints 2024, 2024090599. https://doi.org/10.20944/preprints202409.0599.v1 Alimohammadi, M.; Salehi, A.; Babaei, A. A Comprehensive Review of MCDM Applications in Enhancing Textile Supply Chain Management. Preprints 2024, 2024090599. https://doi.org/10.20944/preprints202409.0599.v1

Abstract

The textile industry plays a vital role in the global economy and faces increasing pressures related to sustainability and efficiency. Given the industry's significant environmental impact and the need for improved operational strategies, our review addresses the critical intersection of decision-making methodologies and sustainable practices. Specifically, This review aims to explore the applications of Multi-Criteria Decision-Making (MCDM) techniques within the textile supply chain to enhance operational performance and decision-making processes. Utilizing a systematic literature review method, we analyzed articles from Scopus, Web of Science, and Google Scholar, focusing on those that address MCDM applications in the textile supply chain. The findings reveal a strong emphasis on supplier selection and evaluation as determinants of competitive advantage, with significant trends toward integrating fuzzy set theory and advanced MCDM methodologies to address uncertainties. Additionally, Sustainability emerges as a core theme, emphasizing the necessity for firms to incorporate green practices into decision frameworks. The insights suggest that by adopting innovative analytical techniques, organizations can improve supplier relationships and operational efficiency.

Keywords

Textile industry; Multi criteria decision-making; Supply chain; Sustainability

Subject

Business, Economics and Management, Business and Management

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