Promoting the greening of industry is the key to achieving high-quality and sustainable development of the urban economy. It is particularly important for resource-based cities (RBCs) that exploit natural resources as the leading industries. In this paper, the Windows-Bootstrap-DEA model was used to calculate the industrial eco-efficiency (IEE) of 114 RBCs in China from 2003 to 2016, and the regional differences and dynamic evolution characteristics of the IEE were analyzed. The panel Tobit model was used to explore the factors associated with IEE in RBCs. The results showed that the IEE of RBCs in China was at a low level during the study period, and the resource utilization process had not reached an optimal state. There were large regional differences in IEE, and there was a significant degree of spatial agglomeration. The results of conditional probability density estimation showed that the distribution of IEE had strong internal stability on the whole, and the distributions of IEE of RBCs in different regions, different resource types, and different development stages showed significant differences. The results of the panel Tobit model showed that per capita GDP, ownership structure, science and technology input, and industrial agglomeration had significant positive effects on IEE, while industrial structure and employment structure showed significant negative effects. The conclusions of this paper can provide a scientific decision-making basis for industrial transformation planning of RBCs.
Keywords: Conditional probability density; Industrial eco-efficiency; Influencing factor; Resource-based city; Windows-Bootstrap-DEA model.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.