The role of multicriteria decision making in the supply chain: Literature review

Alejandra Holguin Avila, Luis Asunción Pérez Domínguez, Roberto Romero Lopez and David Luviano Cruz

Data and Metadata, 2025, vol. 4, 619

Abstract: Introduction: The evaluation of supply chain performance has gained significant relevance due to recent events that have transformed its operational dynamics, as well as the advent of Industry 5.0. This new era introduces advanced technologies, such as digital twins, which, when combined with multicriteria models, can identify and prioritize key factors to enhance performance evaluation. These tools have the potential to optimize strategic decision-making in an increasingly dynamic and competitive environment. Methods: A systematic literature review was conducted following the PRISMA framework, analyzing 45 articles published between 2019 and 2024. The sources included scientific databases such as SCOPUS and Web of Science. The search employed terms related to multicriteria models, supply chain, Industry 4.0, and digital twins. Articles were selected based on predefined inclusion and exclusion criteria. Results: Findings revealed that multicriteria methods are widely used to evaluate efficiency, sustainability, and resilience in supply chains. Additionally, digital twins emerged as key tools for real-time monitoring, risk management, and process simulation. However, technological, financial, and regulatory barriers were identified, hindering their practical implementation. Conclusions: The combination of advanced technologies with multicriteria approaches represents a promising solution for improving supply chain performance. Future research should focus on developing hybrid models, promoting organizational training, and establishing international standards to ensure effective adoption. These initiatives will enable organizations to address the challenges of an increasingly complex global environment, strengthening the resilience and sustainability of supply chains.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:4:y:2025:i::p:619:id:1056294dm2025619

DOI: 10.56294/dm2025619

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