Electric vehicles are of great significance in supporting sustainable transportation and sustainability. In parallel with the increasing demand for such vehicles worldwide, the electric vehicle charging stations (EVCSs) market has grown dramatically. The study presents a practical model for selecting EVCS sites integrating multi-criteria decision-making (MCDM), fuzzy, and rough sets. The research aims to bridge the gap in evaluating EVCS locations by leveraging the superiorities of fuzzy and rough set theories to address vagueness effectively. Firstly, assessment criteria cover the environment, economic, technology, and social drivers. Secondly, a fuzzy Defining Interrelationships Between Ranked criteria (F-DIBR) model is applied to determine the weight values of siting factors. Last, for the first time, the Mixed Aggregation by COmprehensive Normalization Technique (MACONT) with hybrid fuzzy rough numbers (FRN-MACONT) model is proposed to obtain the ranking results. Further, a new approach for defining hybrid fuzzy rough numbers is suggested, based on an improved methodology for determining rough numbers' lower and upper limits, allowing consideration of mutual relations between a set of objects and flexible representation of rough boundary intervals depending on the dynamic environmental conditions. The study's novelties reside in deciding the importance of the driving forces used in determining the EVCS site location with a novel method, F-DIBR, and selecting the optimal site with a new FRN-MACONT approach. The results show that “economy” is the most significant criterion, whereas “system reliability” is the most critical sub-criterion. The findings also indicate that the Konak territory performs the best, whereas the Cigli territory is the second best. Comprehensive sensitivity analysis verifies the proposed framework's validity, robustness, and effectiveness. As per the research findings and analyses, some managerial implications are further discussed. The approach introduced has the potential to contribute to the green transport literature.

In order to achieve sustainable energy consumption and development goals, it is of great importance to find suitable locations for the construction of solar power plants. In this study, Geographic Information System (GIS) and Z-Number iteration of Fuzzy Logarithm Additive Weights Methodology (F-LMAW), a recently adopted Multi-Criteria Decision Making Analysis (MCDA) technique, are used to identify the best locations for solar power plant construction in Mersin province. Nineteen criteria were selected for the study and their relative weights and usefulness in ranking the solar power plant locations were estimated. The Weighted Linear Combination (WLC) technique was used to determine the suitability index for solar power plant siting in the study area. According to the analysis made by taking into account the expert opinions for the site selection of solar power plants, the solar radiation criterion was the most important criterion with a weight value of 0,0664, while the distance from the river criterion was the least important criterion with a weight value of 0,0265. A potential suitability map for the solar power plant was produced with the suitability index values. According to the suitability index values, the study area exhibited suitability degrees for solar power plant siting ranging from “suitable (0,0038 %)” to “moderately suitable (0,0034 %)” and “very slightly suitable (0,0033 %)”. Silifke and Mut regions are considered as good locations for solar power plants in Mersin province. The robustness of the proposed technique was determined by sensitivity analysis.

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.