Assessment actions for improving railway sector performance using intuitionistic fuzzy-rough multi-criteria decision-making model

Abstract

The selection and prioritization of appropriate actions to improve the performance of the railway sector pose a common challenge for policymakers and transport planners. This challenge is further complicated by factors such as political power shifts, policy changes, and socio-economic and environmental impacts, introducing various uncertainties. To address this issue, a novel multi-criteria decision-making framework was developed in this study. The framework introduces the weighted geometric Dombi Maclaurin Symmetric Mean operator within an intuitionistic fuzzy environment, enabling the identification of the most appropriate action from nine different alternatives to enhance the performance of railway sector. Moreover, the study makes an additional contribution by combining this approach with an interval rough PIvot Pairwise RElative Criteria Importance Assessment to determine the weight coefficients of the criteria. To assess the robustness of the proposed methodology, sensitivity analysis and a comparative study were conducted. The findings of the study indicate that “enhancing the governance of the transport sector” emerged as the most appropriate action to improve the performance of the railway sector.