This paper explores the evolution, applications, and prospective developments of a very popular multi-criteria decision-making (MCDM) method called Measurement of Alternatives and Ranking according to COmpromise Solution Method (MARCOS). Employing an extensive bibliometric analysis, the study examines 115 pertinent papers sourced from the Scopus database spanning over the years from 2020 to 2024. This study also provides an evaluation of the methodological significance and outlines potential future directions of MARCOS method. The outcomes indicate "Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS)" by Stević et al. (2020) as the most cited paper. Journals such as "Sustainability (Switzerland)", "Mathematics" and "Expert Systems with Applications" stand out among the most cited journals. "University of East Sarajevo" is an institution distinguished for its prolific research in this field. "Stević Ž." Has been identified as the most cited and published author. The most frequently used keywords are "MARCOS", "MARCOS method", and "MCDM". CRiteria Importance Through Intercriteria. Correlation (CRITIC) method is a weighting model often integrated with MARCOS method. The results of the study provide researchers and practitioners in the field of MCDM with an important insight into the current state of the MARCOS methodology, highlighted studies and potential future developments. It also provides a comprehensive overview of the importance of this method in the multi-criteria decision-making literature, shedding light on future research directions.

Many countries are prioritizing renewable energy sources in response to fossil fuel depletion, environmental concerns, and the need for energy resilience. This study evaluates five renewable energy alternatives: Biomass, Wind, Solar, Geothermal, and Hydro, with the aim of reducing foreign energy dependency and enhancing flexibility under potential geopolitical disruptions. A three-stage hybrid decision-making framework is proposed, integrating Modified Preference Selection Index (MPSI) and Multi-Attributive Border Approximation Area Comparison (MABAC) methods within an Interval-Valued Spherical Fuzzy (IVSF) environment. In the first stage, expert input is collected. The second stage applies IVSF-MPSI to determine the criteria weights under uncertainty. The third stage employs IVSF-MABAC to rank the alternatives based on these weights. The results indicate that Solar Energy, with a distance value of 0.2783, is the most suitable renewable energy, followed by Wind, Hydro, Geothermal, and Biomass. The proposed IVSF-MPSI-MABAC model equips decision-makers with a mathematically rigorous, uncertainty-resilient evaluation framework that supports quantitative trade-off analysis, prioritization of capital-intensive projects, and alignment of renewable energy portfolios with long-term energy security and sustainability objectives, while the integrated sensitivity analysis ensures ranking stability and robustness against variations in decision parameters.