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Environmental, Social and Governance (ESG) Performance Assessment, 2nd Edition
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Environmental, Social and Governance (ESG) Performance Assessment, 2nd Edition

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 6795

Special Issue Editors

Dr. Yelin Fu

E-Mail Website
Guest Editor
1. Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China
2. College of Economics, Shenzhen University, Shenzhen, China
Interests: supply chain finance; ESG; energy and environmental management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zelong Yi

E-Mail Website
Guest Editor
College of Economics, Shenzhen University, 518061 Shenzhen, China
Interests: optimization; supply chain
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. George G.Q. Huang

E-Mail Website
Guest Editor
Department of Industrial and Manufacturig Systems Engineering, The University of Hong Kong, Hong Kong 999077, China
Interests: manufacturing; logistics; ESG
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since its debut in a United Nations report in 2006, environmental, social, and governance (collectively referred to as ESG) performance has shifted from the periphery into the mainstream. ESG performance has become a proxy for a company's resilience and risk management capabilities, but it also manifests and enhances the long-term value of a business. Prominent agencies, for example, MSCI, Sustainlytics, Moody, and others, have developed various ESG ratings to assess the ESG performance of companies, funds, and portfolios. However, different rating agencies usually publish different ESG rating results. The disagreement of ESG ratings introduces uncertainty into any decision that is made based on ESG ratings, and thus indicates a challenge for a wide spectrum of decision makers.

This Special Issue calls for a more critical discussion about how ESG performance could be assessed in a more well-designed manner. We particularly invite articles that explore, examine, and propose ESG performance assessment rationales and methods. Both reviews and prescriptive and experimental research assessing ESG performance in industry and regions are welcome.

Topics of potential interest include, but are not restricted to, the following:

  1. ESG reporting;
  2. ESG ratings;
  3. ESG portfolio optimization;
  4. ESG investing;
  5. Construction of ESG measures;
  6. Uncertainty in ESG performance assessment;
  7. Divergency in ESG rating;
  8. ESG data authenticity;
  9. Decision analytics in ESG;
  10. Efficiency analysis in ESG performance evaluation.

Dr. Yelin Fu
Dr. Zelong Yi
Prof. Dr. George G.Q. Huang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ESG performance assessment
  • ESG rating
  • ESG data authenticity
  • ESG measure
  • ESG investing

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Related Special Issue

Published Papers (4 papers)

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Research

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22 pages, 5105 KB  
Article
From News to Knowledge: Leveraging AI and Knowledge Graphs for Real-Time ESG Insights
by Omar Mohmmed Hassan Nassar, Fahimeh Jafari and Chanchal Jain
Sustainability 2025, 17(24), 11128; https://doi.org/10.3390/su172411128 - 12 Dec 2025
Viewed by 498
Abstract
Traditional Environmental, Social, and Governance (ESG) assessments rely heavily on corporate disclosures and third-party ratings, which are often delayed, inconsistent, and prone to bias. These limitations leave stakeholders without timely visibility into rapidly evolving ESG events. These assessment frameworks also fail to capture [...] Read more.
Traditional Environmental, Social, and Governance (ESG) assessments rely heavily on corporate disclosures and third-party ratings, which are often delayed, inconsistent, and prone to bias. These limitations leave stakeholders without timely visibility into rapidly evolving ESG events. These assessment frameworks also fail to capture the dynamic nature of ESG issues reflected in public news media. This research addresses these limitations by proposing and implementing an automated framework utilising Artificial Intelligence (AI), specifically Natural Language Processing (NLP) and Knowledge Graphs (KG), to analyse ESG news data for companies listed on major stock indices. The methodology involves several stages: collecting a registry of target companies; retrieving relevant news articles; applying Named Entity Recognition (NER), sentiment analysis, and ESG domain classification; and constructing a linked property knowledge graph to structure the extracted information semantically. The framework culminates in an interactive dashboard for visualising and querying the resulting graph database. The resulting knowledge graph supports comparative inferential analytics across indices and sectors, uncovering divergent ESG sentiment profiles and thematic priorities that traditional reports overlook. The analysis also reveals comparative insights into sentiment trends and ESG focus areas across different exchanges and sectors, offering perspectives often missing from traditional methods. Findings indicate differing ESG sentiment profiles and thematic focuses between the UK (FTSE) and Australian (ASX) indices within the analysed dataset. This study confirms AI/KG’s potential for a modular, dynamic, and semantically rich ESG intelligence approach, transforming unstructured news into interconnected insights. Limitations and areas for future work, including model refinement and integration of financial data, are also discussed. This proposed framework augments traditional ESG evaluations with automated, scalable, and context-rich analysis. Full article
(This article belongs to the Special Issue Environmental, Social and Governance (ESG) Performance Assessment, 2nd Edition)
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19 pages, 344 KB  
Article
Evaluating ESG Practices from the Perspective of Transparency and Accountability Through Clustering Analysis and MCDM Methods
by Neylan Kaya, Aslıhan Ersoy Bozcuk, Burçin Tutcu, Mustafa Terzioğlu and Güler Ferhan Ünal Uyar
Sustainability 2025, 17(23), 10440; https://doi.org/10.3390/su172310440 - 21 Nov 2025
Viewed by 652
Abstract
This study explores the Environmental, Social, and Governance (ESG) disclosure practices of 31 information technology firms listed on Borsa Istanbul (BIST), with a particular emphasis on transparency and accountability. Building on legitimacy, stakeholder, and signalling theories, the study develops a composite ESG disclosure [...] Read more.
This study explores the Environmental, Social, and Governance (ESG) disclosure practices of 31 information technology firms listed on Borsa Istanbul (BIST), with a particular emphasis on transparency and accountability. Building on legitimacy, stakeholder, and signalling theories, the study develops a composite ESG disclosure index based on 18 binary indicators covering strategy, environmental performance, social impact, stakeholder engagement, and governance structures. Each indicator is equally weighted and combined into environmental, social, and governance sub-indices, which are then aggregated into a firm-level ESG disclosure score using a single min–max normalisation scheme. K-means clustering, validated through the elbow method and silhouette coefficient, is applied to identify groups of firms with similar ESG disclosure profiles. The empirical results show substantial heterogeneity in disclosure intensity across Turkish IT firms. A small group of companies exhibits proactive and comprehensive ESG communication, whereas many firms disclose only limited and fragmented information. Governance- and reporting-related indicators (C6 and C7) are particularly influential, underscoring the importance of standardised ESG reporting and board-level oversight in strengthening transparency. The study contributes to the emerging ESG disclosure literature by providing a methodologically consistent framework for assessing ESG transparency in the IT sector and offering practical insights for regulators, investors, and corporate decision-makers aiming to improve the reliability of ESG reporting in Turkey. Full article
(This article belongs to the Special Issue Environmental, Social and Governance (ESG) Performance Assessment, 2nd Edition)
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27 pages, 1616 KB  
Article
Evaluating the Anti-Corruption Factor in Environmental, Social, and Governance Indices by Sampling Large Financial Asset Management Firms
by Kenneth David Strang and Narasimha Rao Vajjhala
Sustainability 2024, 16(23), 10240; https://doi.org/10.3390/su162310240 - 22 Nov 2024
Cited by 3 | Viewed by 3277
Abstract
Current Environmental, Social, and Governance (ESG) indices are flawed because the data are incomplete and not reported consistently, and some measured factors may be irrelevant to the industry. Regulators in the financial services industry emphasize reporting CO2 emissions (environmental factor), yet the [...] Read more.
Current Environmental, Social, and Governance (ESG) indices are flawed because the data are incomplete and not reported consistently, and some measured factors may be irrelevant to the industry. Regulators in the financial services industry emphasize reporting CO2 emissions (environmental factor), yet the key resources leveraged for production are rented offices, and internet–governance issues like money laundering, corruption, and unethical behavior would be more relevant. To investigate this problem, we sampled the finance and insurance industry firms in the USA with the greatest economic impact, i.e., those managing at least USD 1 trillion in assets. We used artificial intelligence to collect data about undisclosed legal decisions against firms to measure the ESG anti-corruption governance factor GRI 206-1, defined by the Global Reporting Institute (GRI) for global sustainable development goals (SDGs), which correspond to the United Nations’ SDGs. We applied Bayesian correlation with bootstrapping to test our hypotheses, followed by root cause analysis. We found that ESG ratings from providers did not reflect legal cases decided against firms; the Bayesian BF+0 odds ratio was 3005 (99% confidence intervals were 0.617, 0.965). Also, misconduct fines and arbitration legal case counts were significantly related for the same firm (the Vovk-Selke maximum p-ratio was 4411), but most ESG scores were significantly different for the same firm. We found three other studies in the literature that corroborated some of our findings that specific firms in our sample were considered to be unethical. We propose deeper study of the implications related to our findings based on public interest and stakeholder theory. Full article
(This article belongs to the Special Issue Environmental, Social and Governance (ESG) Performance Assessment, 2nd Edition)
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Review

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19 pages, 309 KB  
Review
Evaluation of Environmental, Social, and Governance Risks? A Critical Literature Review with Practical Implications
by Timotej Jagrič, Damijan Mumel and Aljaž Skaza
Sustainability 2025, 17(18), 8451; https://doi.org/10.3390/su17188451 - 20 Sep 2025
Viewed by 1542
Abstract
The evaluation of environmental, social and governance (ESG) risks is an important yet challenging aspect of the investor decision-making process, largely attributable to the volatility of this domain. A significant proportion of these challenges arise from divergent ESG ratings, which are the consequence [...] Read more.
The evaluation of environmental, social and governance (ESG) risks is an important yet challenging aspect of the investor decision-making process, largely attributable to the volatility of this domain. A significant proportion of these challenges arise from divergent ESG ratings, which are the consequence of absence of clarity and consistency in definitions, data, and rating methodologies. A review of the existing literature revealed that no article summarized findings related to the evaluation of ESG risks based on uniform definitions, which would help with understanding and measure development. The aim of this paper is to address ESG risks evaluation issues through a critical review of literature and deconstruction of associated issues, providing both theoretical and practical insights. The literature review began with the definition of ESG risks, which served as a foundation for the deconstruction and analysis of the ESG risk evaluation process. The findings indicate that there are numerous issues related to the evaluation process, starting with the definition of ESG, continuing through reporting and data issues, which ultimately leads to issues with the evaluation process itself. The conclusion drawn from this analysis is that usability is contingent upon the clarity of definitions and comprehension, thereby ensuring the efficacy of the ratings for investors and other stakeholders. Full article
(This article belongs to the Special Issue Environmental, Social and Governance (ESG) Performance Assessment, 2nd Edition)
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