Special Issue: Statistical and computational methods in environmental protection and efficiency evaluation
Guest Editors
Prof. Zejun Li
Hunan Institute of Technology, China
Email: Lzjfox@hnit.edu.cn
Prof. Peng Wang
Hunan University, China
Email: pwang@hnu.edu.cn
Manuscript Topics
The economic development was accompanied by a series of environmental problems, where the significant ones are like climate warming, environmental pollution, reduction in biodiversity and so forth. The society was facing a growing environment stress. National governments and organizations have been on the lookout for possible ways to improve the environmental quality and reduce the environmental stress. To mitigating the global warming, the wellknown Kyoto Protocol, claimed by thirty-seven industrialized nations and came into force in 2005, devotes to stabilizing the greenhouse gas concentration in the atmosphere at an appropriate level, so as to prevent severe climate change from damaging human welfare. Some Emission Trading Scheme (ETS) have been set up around the world with the goal of attaining the lowest cost of carbon emission. Digital transformation of enterprises has been widely stimulated to reduce pollutant discharge into the atmosphere. Some financial products like green credit and green insurance were rolled out in succession. To promote the environmental awareness, when evaluating producers’ production efficiency and enterprises’ economic efficiency, environmental factors should be taken into consideration and involved into the measurement indexes.
In academia, many authors have paid much attention to problems relevant to environmental protection and efficiency evaluation by various research approaches. To further discuss these relevant problems, this special issue aims to collect high quality works addressing environmental problems and measuring relevant efficiencies by employing statistical methods and computational methods. Both theoretical and empirical research are encouraged. We hope that this special issue will provide an interdisciplinary platform linking statistic tools, algorithms, simulation, econometric models, environment and efficiencies.
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