Environmental efficiency evaluation of China's iron and steel industry: A process-level data envelopment analysis

To resolve the increasingly higher energy and environmental pressures, the evaluation of environmental efficiency in China's iron and steel industry is essential for identifying a precise energy conservation and emission reduction path. However, current studies have only focused on the efficiency evaluation in national, regional, or enterprise level, lacking the analysis of different processes. Therefore, the objective of this research is to conduct a process-level data envelopment analysis (DEA) to evaluate the environmental efficiency of China's iron and steel industry. Totally, 54 enterprises are contained, as the input-output structure of 5 processes: sintering, coking, ironmaking, steelmaking, and steel rolling are set specifically in this study. In addition, to compare the effects to the efficiency results of different DEA methods, Banker, Charnes & Cooper (BCC) model, Slack-based Measure (SBM) model, and Bootstrap-DEA methods are adopted. Finally, a regression model is used to investigate the key environmental protection strategies influencing the environmental efficiency. The results show that: (1) Within different methods, the average efficiency scores from SBM model are lower than the ones from BCC model, and the Bootstrap-DEA method also has a negative modification. (2) Regional efficiency difference exists, as the enterprises in South China perform best in sintering and coking processes but have the lowest overall efficiency scores. (3) Most enterprises have one or more short board processes. 12 enterprises are the enterprises with individual low environmental efficiency process, while other 25 are the enterprises with imbalanced environmental performances. (4) The coefficient factor between environmental protection investment and the efficiency scores are positive, but the factors of proportion of environmental protection staffs, and whether the enterprise has environmental protection research are negative. In sum, this study is hoped to contribute to formulating more precise environmental management measures in China's iron and steel industry. (C) 2019 Elsevier B.V. All rights reserved.