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This paper extends a global slack-based productivity indicator and constructs a unified framework that consists of global and factor levels of total factor productivity (TFP) to evaluate the performance of regional industries, thus enabling global productivity improvement based on factor-level sources. Evaluating regional industrial performance in China during 1995–2014, the findings reveal that rapid growth of industry in China is not only driven by a huge amount of input, but also by TFP improvement, with industrial productivity driven mainly by technology progress and presenting a gradually increasing trend. Regional productivity performances are imbalanced, in which the east ranks first due to its dual advantages of input and output factors. For source identification, input and output jointly contribute to industrial productivity improvement, but output has a much higher contribution ratio to industrial productivity improvement than input, because it is mainly rooted in desirable output. Finally, on the input side, labor is the primary factor driving input productivity improvement followed by energy, while capital productivity shows very slight growth. [ABSTRACT FROM AUTHOR]

The growth in the world economy has resulted in an increase in environmental pollution and ecological destruction in many parts of the world. In particular, economic development in mainland China in recent years has seen a massive rise in environmental pollution such as particulate matter (PM2.5), sulfur dioxide (SO2), and nitrogen oxides (NO2) in many cities; as a result, there has been an increased focus on air pollution and carbon dioxide emission control in recent years. This study used 2013–2017 energy consumption data from 31 cities in China to examine overall and specific efficiencies, for which employees, fixed assets, and energy consumption were taken as the input indicators, and gross domestic product (GDP) and the PM2.5, SO2, and NO2 levels as the output indicators. It was found that from 2013 to 2017, only four cities (Beijing, Guangzhou, Nanning, and Shanghai) had total efficiency scores of 1, with all other cities needing efficiency improvements. The efficiency scores for the different pollutants varied widely, with the NO2 efficiencies being generally higher with less improvement needed, while the SO2 and PM2.5 efficiencies required significantly greater governance measures. [ABSTRACT FROM AUTHOR]