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Environmental performance evaluation with big data: theories and methods
by
Lian-Biao Cui
, Ma-Lin, Song
, Fisher, Ron
, Jian-Lin, Wang
in
Big Data
/ Data envelopment analysis
/ Data management
/ Ecological monitoring
/ Environmental management
/ Environmental performance
/ Environmental protection
/ Life cycle analysis
/ Life cycle assessment
/ Life cycle engineering
/ Literature reviews
/ Operations research
/ Performance evaluation
/ Stability
/ Studies
2018
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Environmental performance evaluation with big data: theories and methods
by
Lian-Biao Cui
, Ma-Lin, Song
, Fisher, Ron
, Jian-Lin, Wang
in
Big Data
/ Data envelopment analysis
/ Data management
/ Ecological monitoring
/ Environmental management
/ Environmental performance
/ Environmental protection
/ Life cycle analysis
/ Life cycle assessment
/ Life cycle engineering
/ Literature reviews
/ Operations research
/ Performance evaluation
/ Stability
/ Studies
2018
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Do you wish to request the book?
Environmental performance evaluation with big data: theories and methods
by
Lian-Biao Cui
, Ma-Lin, Song
, Fisher, Ron
, Jian-Lin, Wang
in
Big Data
/ Data envelopment analysis
/ Data management
/ Ecological monitoring
/ Environmental management
/ Environmental performance
/ Environmental protection
/ Life cycle analysis
/ Life cycle assessment
/ Life cycle engineering
/ Literature reviews
/ Operations research
/ Performance evaluation
/ Stability
/ Studies
2018
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Environmental performance evaluation with big data: theories and methods
Journal Article
Environmental performance evaluation with big data: theories and methods
2018
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Overview
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.
Publisher
Springer Nature B.V
Subject
/ Studies
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