Integrating Multiple Criteria Decision-Making Techniques in Sustainable Supplier Selection: A Comprehensive Review

Haya Alastal; Ahmed Sharaf; Shahd Mahmoud; Ola Alsaidi; Zied Bahroun

doi:10.31181/dmame8120251243

Authors

Haya Alastal Department of Industrial Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates https://orcid.org/0009-0000-7822-7529
Ahmed Sharaf Department of Industrial Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates https://orcid.org/0000-0002-5633-2421
Shahd Mahmoud Department of Industrial Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates https://orcid.org/0000-0002-0007-4056
Ola Alsaidi Department of Industrial Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates https://orcid.org/0000-0003-1351-0424
Zied Bahroun Department of Industrial Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates https://orcid.org/0000-0003-1351-0424

DOI:

https://doi.org/10.31181/dmame8120251243

Keywords:

Multiple Criteria Decision-Making (MCDM); Sustainable Supplier Selection; Fuzzy Sets; TOPSIS; Supply Chain Management; Environmental Sustainability; Strategic Sourcing

Abstract

Amidst the increasing emphasis on sustainability and efficiency within global supply chains, this review explores the application of Multiple Criteria Decision-Making (MCDM) methods in optimising supplier selection across diverse sectors, including management, healthcare, manufacturing, and supply chain operations. Adopting a systematic approach, the study commences with a bibliometric analysis of the Scopus database to identify global research trends, influential contributors, key thematic areas, and patterns of collaboration in the utilisation of MCDM for sustainable supplier selection. Furthermore, a detailed content analysis examines the integration and comparative effectiveness of various MCDM techniques—such as TOPSIS, fuzzy logic, and hybrid algorithms—based on sustainability and efficiency criteria. The findings indicate that these methodologies enhance the precision of supplier evaluations and support strategic sourcing decisions, yielding both environmental and economic advantages. Additionally, the review highlights critical research gaps, including the incorporation of Artificial Intelligence (AI) into MCDM frameworks and the necessity of addressing social performance factors in supplier assessments. This study underscores the pivotal role of MCDM in aligning supplier selection processes with sustainable business strategies and provides recommendations for industry practitioners to implement adaptive MCDM models capable of responding to evolving sustainability benchmarks and stakeholder expectations. Moreover, it advocates for the establishment of policies and standards that encourage the adoption of advanced MCDM techniques in procurement practices, thereby fostering transparency, equity, and environmental stewardship. The insights presented aim to inform future research and facilitate practical applications, ultimately enhancing the strategic significance of MCDM in sustainable supplier selection across industries

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