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Evaluation of Sustainability Information Disclosure Based on Entropy

Disclosure of sustainability information is important for stockholders and governments. In order to evaluate the quality of sustainability information disclosure in heavily polluting industries, the quality of the disclosure is proposed to be evaluated from completeness, adequacy, relevance, reliabi...

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Detalles Bibliográficos
Autores principales: Li, Ming, Wang, Jialin, Li, Ying, Xu, Yingcheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513212/
https://www.ncbi.nlm.nih.gov/pubmed/33265778
http://dx.doi.org/10.3390/e20090689
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author Li, Ming
Wang, Jialin
Li, Ying
Xu, Yingcheng
author_facet Li, Ming
Wang, Jialin
Li, Ying
Xu, Yingcheng
author_sort Li, Ming
collection PubMed
description Disclosure of sustainability information is important for stockholders and governments. In order to evaluate the quality of sustainability information disclosure in heavily polluting industries, the quality of the disclosure is proposed to be evaluated from completeness, adequacy, relevance, reliability, normativeness and clarity aspects. The corresponding evaluation indicator system is constructed. Due to the ambiguity and complexity of the evaluation information, the intuitionistic fuzzy sets are applied to model the linguistic ratings. Entropy is used to derive the weight of experts, the object weight and the subject weight of the indicators. which are integrated when dealing with the evaluation information. The quality of sustainability information disclosure of seven representative companies in heavily polluting industries is evaluated. The importance of indicators and ranking of the companies are derived. Based on the evaluation results, the discussion and suggestions are also provided.
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spelling pubmed-75132122020-11-09 Evaluation of Sustainability Information Disclosure Based on Entropy Li, Ming Wang, Jialin Li, Ying Xu, Yingcheng Entropy (Basel) Article Disclosure of sustainability information is important for stockholders and governments. In order to evaluate the quality of sustainability information disclosure in heavily polluting industries, the quality of the disclosure is proposed to be evaluated from completeness, adequacy, relevance, reliability, normativeness and clarity aspects. The corresponding evaluation indicator system is constructed. Due to the ambiguity and complexity of the evaluation information, the intuitionistic fuzzy sets are applied to model the linguistic ratings. Entropy is used to derive the weight of experts, the object weight and the subject weight of the indicators. which are integrated when dealing with the evaluation information. The quality of sustainability information disclosure of seven representative companies in heavily polluting industries is evaluated. The importance of indicators and ranking of the companies are derived. Based on the evaluation results, the discussion and suggestions are also provided. MDPI 2018-09-10 /pmc/articles/PMC7513212/ /pubmed/33265778 http://dx.doi.org/10.3390/e20090689 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Ming
Wang, Jialin
Li, Ying
Xu, Yingcheng
Evaluation of Sustainability Information Disclosure Based on Entropy
title Evaluation of Sustainability Information Disclosure Based on Entropy
title_full Evaluation of Sustainability Information Disclosure Based on Entropy
title_fullStr Evaluation of Sustainability Information Disclosure Based on Entropy
title_full_unstemmed Evaluation of Sustainability Information Disclosure Based on Entropy
title_short Evaluation of Sustainability Information Disclosure Based on Entropy
title_sort evaluation of sustainability information disclosure based on entropy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513212/
https://www.ncbi.nlm.nih.gov/pubmed/33265778
http://dx.doi.org/10.3390/e20090689
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