Assessing the corporate green technology progress and environmental governance performance is essential to estimate the technological levels and environment regulation capabilities of enterprises. With the official statistics of collected panel data, we estimate and evaluate the differential levels of provincial corporate green technology and environmental governance performance of industrial enterprises above designated size (IEADSs) in Anhui Province across multiple dimensions. We firstly chose each surveyed city as the decision-making unit (DMU) in data envelopment analysis (DEA). Subsequently, we estimated the green technology efficiency of IEADSs from a static perspective by using the bootstrap DEA model and an improved super-efficiency (SE) DEA model. Secondly, we used the algorithm of Malmquist productivity index to analyze the dynamic efficiency development tendency and spatiotemporal characteristics in the DMUs. From a dynamic perspective, the evolutionary divergence and convergence characteristics of provincial green technology efficiency were brought about by the estimating algorithm of Malmquist productivity index based on the different regional divisions in Anhui Province. Furthermore, in combination with Malmquist-data envelopment analyses, we also used gray correlation analysis to analyze and evaluate the influencing factors of the industrial green technology efficiencies. This study shows many interesting findings across multiple dimensions. Among the 16 DMUs, there are only eight with the regional green technology efficiencies of IEADSs greater than the expected threshold of 0.9. Nevertheless, the green technology efficiencies of provincial industrial enterprises are still far from the national optimized goals in most of the surveyed cities. The regional green technology efficiencies of IEADSs were ranked as South Anhui > North Anhui > Middle Anhui. The overall average industrial green technology efficiency is 0.8650 in Anhui Province, but the provincial differences of sub-area distribution are relatively large and heterogeneous. The average provincial industrial green technology efficiency appeared as the overall tendency to rise, fall, and then rise, although there is an average bootstrapped Malmquist productivity indices of 1.009 in Anhui Province. Among the declined provincial Malmquist productivity indices, the effch, techch, and sech indices are vital causers of the overall decline of the provincial Malmquist productivity indices. Ultimately, based on all these quantitative estimates and findings, we put forward the following concluding remarks with policy implications and corresponding strategies.
Keywords: Data envelopment analysis; Ecological conservation; Environment regulation; Environmental governance performance; Gray correlation analysis; Green technology progress; Malmquist productivity index; Social-economic impact.