Pathways to improve energy efficiency under carbon emission constraints in iron and steel industry: Using EBM, NCA and QCA approaches

Abstract

Improving environmental performance of energy- and carbon-intensive sectors represented by the iron and steel (IS) industry is of utmost importance to address the challenges of resource depletion and climate change worldwide. This article adopts a global-super-Epsilon-Based Measure (EBM) model with undesirable output for IS energy efficiency estimation, identifies efficiency determinants based on Technology-Organization-Environment (TOE) framework, and analyzes various pathways for efficiency improvement by grouping Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA). Empirical testing using statistical data of the G20 economies during 2010–2020 demonstrates that: 1) energy efficiency in the IS industry in G20 countries has risen amidst fluctuations, with developed countries performing more efficiently than developing countries; 2) individual factors do not constitute a compulsory condition to achieve high energy efficiency in the IS industry; 3) three different paths to achieve high energy performance are found, that is, technology-structure driven, regulation-economy-technology driven, and regulation-technology-production driven. Heterogenous policy recommendations for efficiency gains in the IS sector of different countries with divergent features are proposed accordingly.