Sustainability evaluation of the steel industry in belt and road countries using an ESG-MI and obstacle analysis framework.

As a fundamental raw material industry in the industrial sector, the steel industry is the largest emitter of carbon among the 31 manufacturing sub-sectors. Assessing the sustainability level of the steel industry is thus of critical importance for advancing carbon reduction efforts. In 2024, crude steel production in Belt and Road Initiative countries reached 1.43 billion tons, accounting for 75.8% of global output. However, significant disparities exist in the development of steel industries across these countries, necessitating the construction of a robust model to evaluate their relative sustainability. This study proposes an ESG-MI evaluation model that integrates environmental, social, governance, resource, and industrial dimensions, and applies it to panel data from 64 BRI countries between 2000 and 2023 to assess the sustainability level of their steel industries. Furthermore, an obstacle degree model is employed to identify key hindering factors. The study yields the following key findings: (1) From 2000 to 2023, the sustainability level of the steel industry along the BRI showed a steady upward trend, with an average annual growth rate of 1.04%. (2) Industrial development and governance are the main drivers of sustainable development in the steel sector, while environmental performance remains a major weakness. Additionally, the resource supply chains in BRI countries are fragile and vulnerable to external shocks. (3) The sustainable development of the steel industry along the BRI follows a geographical transmission pattern of "Europe → East Asia → Middle East → Southeast Asia → South Asia." (4) Based on obstacle degree analysis, industrial value added (X20), crude steel output per capita (X11), and the proportion of ores and metals in total exports (X12) are identified as the top three obstacles to sustainable development in the steel industry, with significantly greater hindering effects than other indicators.