Environmental performance evaluation with big data: theories and methods

被引:0
作者
Ma-Lin Song
Ron Fisher
Jian-Lin Wang
Lian-Biao Cui
机构
[1] Anhui University of Finance and Economics,Collaborative Innovation Center for Ecological Economics and Management
[2] Griffith University,Department of International Business and Asian Studies, Griffith Business School
[3] Dongbei University of Finance and Economics,Center for Industrial and Business Organization
来源
Annals of Operations Research | 2018年 / 270卷
关键词
Big data; Environmental management; Environmental performance; Data envelopment analysis; Life cycle assessment;
D O I
暂无
中图分类号
学科分类号
摘要
Traditional theories and methods for comprehensive environmental performance evaluation are challenged by the appearance of big data because of its large quantity, high velocity, and high diversity, even though big data is defective in accuracy and stability. In this paper, we first review the literature on environmental performance evaluation, including evaluation theories, the methods of data envelopment analysis, and the technologies and applications of life cycle assessment and the ecological footprint. Then, we present the theories and technologies regarding big data and the opportunities and applications for these in related areas, followed by a discussion on problems and challenges. The latest advances in environmental management based on big data technologies are summarized. Finally, conclusions are put forward that the feasibility, reliability, and stability of existing theories and methodologies should be thoroughly validated before they can be successfully applied to evaluate environmental performance in practice and provide scientific basis and guidance to formulate environmental protection policies.
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页码:459 / 472
页数:13
相关论文
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