A two-stage eco-efficiency evaluation of China's industrial sectors: A dynamic network data envelopment analysis (DNDEA) approach

Abstract

Past studies used the network data envelopment analysis approach from a two-stage perspective (the production stage and waste/pollutant treatment stage) to evaluate industrial eco-efficiency and assess internal ineffective sources. However, these studies did not consider the dynamic features, i.e., capital investments in the current period are used to establish fixed assets for two stages, which can also be used in the later period, thus affecting its two-stage eco-efficiency. A dynamic network data envelopment analysis approach is adopted to fill this research gap and evaluate Chinese industrial two-stage eco-efficiency during 2010?2015, reflecting the practical production context and achieving comparable efficiencies among different periods. The major results of our study are: Firstly, not considering the dynamic features leads to an underestimation of the two-stage eco-efficiency. Secondly, the production efficiency was higher than the treatment efficiency, and the two-stage eco-efficiency was between the two during the study period. Furthermore, eastern China performed best with respect to the two-stage eco-efficiency, including production and treatment efficiencies, followed by the central and the western areas. Finally, a fifth of the 30 regions had a relatively low value of the input and output efficiencies of both production and treatment stages based on the clustering analysis.