An ESG Assessment Approach with Multi-Agent Preference Differences: Based on Fuzzy Reasoning and Group Decision-Making Article Swipe
Yihe Lü
,
Yinyun Yu
,
Ting Qu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/su151612235
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/su151612235
The adoption of Environmental, Social, and Governance (ESG) to measure the green development, social responsibility, and public interest of companies is a commonly accepted theme and approach in the industry and academia at present. As ESG assessment is characterized by heterogeneity of subjects, complexity of contents, diversity of scales, and uncertainty of weights, it has led to the variability of ESG assessment results given by different assessment organizations in the same company, which has attracted a lot of criticism. This paper proposes a group decision-making method based on the preferences of multiple subjects to solve the problem of heterogeneity of subjects in ESG assessment. Specifically, for the given ESG evaluation data, the first step is to identify the preferences of subjects and structure the initial group matrix; secondly, the fuzzy inference system is employed to mine the hidden preference information; further, the initial group matrix is revised using the preference information; and finally, the TOPSIS method is applied to aggregate the information and obtain the final ESG score and ranking of each company. This study was tested using statistics from 30 companies released by Harvest Fund in May 2021, which verified the validity and advantages of the method proposed in this paper. The proposed method integrates the preferences of heterogeneous subjects and mines the possible hidden preference information, which increases the interpretation of the information contained in the original ESG data and facilitates the achievement of group consensus.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/su151612235
- https://www.mdpi.com/2071-1050/15/16/12235/pdf?version=1691669841
- OA Status
- gold
- Cited By
- 6
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385740897
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4385740897Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/su151612235Digital Object Identifier
- Title
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An ESG Assessment Approach with Multi-Agent Preference Differences: Based on Fuzzy Reasoning and Group Decision-MakingWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-08-10Full publication date if available
- Authors
-
Yihe Lü, Yinyun Yu, Ting QuList of authors in order
- Landing page
-
https://doi.org/10.3390/su151612235Publisher landing page
- PDF URL
-
https://www.mdpi.com/2071-1050/15/16/12235/pdf?version=1691669841Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2071-1050/15/16/12235/pdf?version=1691669841Direct OA link when available
- Concepts
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Preference, Ranking (information retrieval), Aggregate (composite), TOPSIS, Fuzzy logic, Computer science, Group decision-making, Data mining, Operations research, Artificial intelligence, Engineering, Psychology, Mathematics, Statistics, Materials science, Composite material, Social psychologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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6Total citation count in OpenAlex
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2025: 2, 2024: 3, 2023: 1Per-year citation counts (last 5 years)
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34Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3100922249, https://openalex.org/W3123195241, https://openalex.org/W2557601883, https://openalex.org/W2151933910, https://openalex.org/W2899031003, https://openalex.org/W2792795217, https://openalex.org/W2530914357, https://openalex.org/W3124578221, https://openalex.org/W3046042161, https://openalex.org/W6767200292, https://openalex.org/W2741574316, https://openalex.org/W2624689968, https://openalex.org/W4313465658, https://openalex.org/W4365448621, https://openalex.org/W4317356206, https://openalex.org/W4318163980, https://openalex.org/W4317935064, https://openalex.org/W4361257175, https://openalex.org/W4361248197, https://openalex.org/W3197113812, https://openalex.org/W2054846646, https://openalex.org/W4361269673, https://openalex.org/W4313436180, https://openalex.org/W4288053649, https://openalex.org/W4213422205, https://openalex.org/W4310074527, https://openalex.org/W2735645818, https://openalex.org/W3153605852, https://openalex.org/W3088443796, https://openalex.org/W6791743602, https://openalex.org/W6859436514, https://openalex.org/W3195374454, https://openalex.org/W2969781339, https://openalex.org/W3136982811 |
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| corresponding_author_ids | https://openalex.org/A5050758411 |
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| institutions_distinct_count | 3 |
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