Abstract:

Scientifically evaluating the efficiency of industrial water resources and identifying its influencing factors is an important prerequisite for alleviating the current contradiction between water supply and demand. Based on the super-efficiency EBM model of undesired output， we measure the industrial water resources efficiency along the Yellow River and nine provinces from 2010 to 2019， and then construct a Tobit model to analyze its global influencing factors. On this basis， significant influencing factors are selected and assessed in space and time. Geographically weighted regression model is used to explore the spatiotemporal heterogeneity of each influencing factor. The results show that the overall average value of industrial water resources efficiency along the Yellow River and nine provinces is 0.77， which has not reached the effective level， but shows a fluctuating upward trend. The efficiency difference between provinces is obvious， and Shandong is the highest （1.064）， and Ningxia is the lowest （0.424）. At the macro level of influencing factors， the technological level and the degree of industrialization have a positive effect on improving the overall industrial water resources efficiency. In addition， the effects of highly significant influencing factors have different temporal evolution trends. At the micro level， the main influencing factors and their roles of industrial water resources efficiency in different provinces are spatially different. Based on this， we put forward relevant improvement suggestions for each province.

Key words: industrial water resources efficiency, super-efficiency EBM, Tobit model, geographically and temporally weighted regression, Yellow River Basin