Comprehensive ESG assessment framework for metro industry : a softmax enhanced hybrid weighting method

Abstract

This study seeks to answer how Environmental, Social, and Governance (ESG) indicators can be selected, weighted, and interpreted for the metro industry, while generic ESG frameworks are unable to explore sustainability challenges for the metro industry. Using 2022–2024 operational and ESG disclosure data from two leading metro operators in Asia and Europe, this study develops a sector-specific ESG indicator system and applies a softmax-enhanced hybrid weighting model that integrates DEMATEL and LOPCOW. Fuzzy DEMATEL helps capture causal interdependencies among indicators, LOPCOW derives objective weights from operational data, and the softmax transformation improves discrimination among closely weighted indicators. The results show that social indicators dominate the metro ESG structure, accounting for approximately 81.3% of total priority weight. Furthermore, the three most important indicators are average age, employee turnover rate, and total number of employees, which together represent about 41.0% of the overall ESG priority weight. The findings indicate that workforce structure, retention, and staffing capacity are not only social performance measures but also economically significant levers for operational continuity, service reliability, and long-term resource efficiency. Governance oversight also functions as a causal driver, while environmental indicators appear largely as outcomes influenced by social and governance conditions. The study contributes theoretically by advancing sector-specific ESG materiality and methodologically by reducing weight-compression in MCDM models. In practice, it offers metro operators and policymakers a prioritization tool to align ESG investment, human resource planning, and governance reform with sustainable infrastructure development.