Abstract:

The application of Multi-Criteria Decision-Making (MCDM) methods in Industry 4.0 is increasingly important as organizations face complex decisions related to digital transformation, automation, and sustainability. This study presents a systematic literature review and bibliometric analysis of 256 peer-reviewed articles published between 2011 and 2024, focusing on how MCDM techniques support decision-making in Industry 4.0 contexts. The analysis reveals that the Analytical Hierarchy Process (AHP), TOPSIS, VIKOR, and PROMETHEE are the most frequently applied methods, often integrated with fuzzy logic to handle uncertainty. Key application areas include production planning, supply chain optimization, energy management, and AI-driven automation. Through co-citation and keyword network analysis using Bibliometrix in R, four main thematic clusters were identified, highlighting trends in sustainability, robotics, and data-driven decision-making. The study also underscores the increasing role of hybrid models that combine MCDM with advanced analytic. These findings provide valuable insights for both researchers and practitioners aiming to leverage MCDM tools in the evolving landscape of Industry 4.0.

Keywords:

MCDM, industry 4.0, bibliometric analysys, co-citation networks.

How to Cite:

Maria Grazia Olivieri and Elisa Fiorenza. Multi-Criteria Decision Making in Industry 4.0: a Systematic Literature Review and Bibliometric Analysis. [ref]: vol.23.2025. available at: https://refpress.org/ref-vol23-a18