Abstract

Industrial eco-efficiency has been an invaluable measurement for the relationship between production activities and environmental depletion, which is important to investigate when aiming for sustainable development. For the textile industry, however, limited rigorous studies have comprehensively evaluated the eco-efficiency from a firm-level perspective, and research on multi-level comparisons of the sub-sectors has also been lacking. Given the differences in environmental impacts due to the selection of various raw materials and unstandardized production processes in the textile industry, we focused on three sub-sectors, i.e., the cotton, chemical fibers textile sector (CCTS), the non-cotton textile sector (NCTS), and the printing and dyeing sector (PDS). By applying the slacks-based measure (SBM) model based on the principle of the data envelopment analysis (DEA), i.e., the SBM-DEA model, the eco-efficiency of China's textile industry was measured at the firm level from 2001 to 2011 using a large sample dataset. We then further analyzed the factors affecting eco-efficiency using the Tobit regression model. An empirical analysis showed an upward trend of eco-efficiency over time in the eastern, central, and western regions of China with great disparities for the three sub-sectors. Analyses of the typical provinces in the eastern region all showed increasing trends in eco-efficiency, with Shandong Province consistently performing the best. We also found that large-scale firms had the highest annual average eco-efficiency than that of small- and medium-scale firms. For the influencing factors on the eco-efficiency, our results indicated that the economic scale and export delivery value both had a significant positive correlation with the eco-efficiency, while foreign direct investment and environmental regulation were both significantly negative for the eco-efficiency in all three sub-sectors. These findings provide valuable insights into helping the textile industry address high-quality green development and sustainability.

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