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Today, environmental issues are one of the key challenges to sustainable development of the social economy of every country in the world. How to effectively solve environmental problems and prevent further deterioration of the environment have attracted tremendous attention from scholars. In recent years, big data, that is, an enormous volume of data, have developed rapidly and widely and have brought major challenges as well as unprecedented opportunities to the world. For example, big data can be used to predict production processes more accurately. However, they make traditional environmental performance evaluation methods ineffective. Thus, studying and improving environmental efficiency evaluation under the background of big data are important to increase environmental efficiency apart from pushing forward discipline development. This study presents a set of scientific and axiomatised methods for environmental performance evaluation based on the big data environment. The findings of this study can provide references for environmental performance evaluation in the new era. [ABSTRACT FROM AUTHOR]

Because of China’s rapid economic development, its transportation system has become one of China’s high-energy-consumption and high-pollution-emission sectors. However, little research has been done which pays close attention to China’s transportation system, especially in terms of energy and environmental efficiency evaluation. In this paper, data envelopment analysis (DEA) is applied to measure the energy and environment performance of transportation systems in China with the goal of sustainable development. This paper treats transportation as a parallel system consisting of subsystems for passenger transportation and freight transportation, and extends a parallel DEA approach to evaluate the efficiency of each subsystem. An efficiency decomposition procedure is proposed to obtain the highest achievable subsystem efficiency. Our empirical study on 30 of mainland China’s provincial-level regions shows that most of them have a low efficiency in their transportation system and the two parallel subsystems. There are large efficiency differences between the passenger and freight transportation subsystems. In addition, unbalanced development has occurred in the three large areas of China, with the east having the highest efficiency, followed by central China and then west. Therefore, more measures should be taken to balance and coordinate the development between the three large areas and between the two subsystems within them. Our analysis approach gives data for determining effective measures. [ABSTRACT FROM AUTHOR]