Measuring CSR Disclosure when Assessing Stock Market Effects

Beelitz, Annika; Cho, Charles H.; Michelon, G.; Patten, Dennis M.

doi:10.2308/api-2020-017

Cited by 8 publications

(10 citation statements)

References 61 publications

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“…This suggests that the company's actions can erode the credibility of CSR disclosure. Also, Beelitz et al. (2021) find that simply having a CSR report is not enough to mitigate negative shareholder reactions to an environmental catastrophe.…”

Section: Research On Outcomes Of Csr Disclosure Qualitymentioning

confidence: 96%

“…This suggests that the company's actions can erode the credibility of CSR disclosure. Also, Beelitz et al (2021) find that simply having a CSR report is not enough to mitigate negative shareholder reactions to an environmental catastrophe. Rather, protection from negative reactions only occurred when there was improved environmental disclosure before the catastrophe, which suggests the relevance of the disclosure is necessary.…”

Section: Effects On Firm Valuementioning

confidence: 96%

“…Fairly recently, studies have started to use Bloomberg Environmental, Social, and Governance (ESG) data as a source of disclosure quality ratings (e.g. Beelitz et al. , 2021; Christensen et al.…”

Section: Disclosure Quality Proxies and Measuresmentioning

confidence: 99%

“…Fairly recently, studies have started to use Bloomberg Environmental, Social, and Governance (ESG) data as a source of disclosure quality ratings (e.g. Beelitz et al, 2021;Christensen et al, 2022;Dah and Jizi, 2018;Tan et al, 2020). Until the availability of the Bloomberg ESG disclosure score, a database did not exist to allow researchers to have a comprehensive measure of CSR disclosure across all three of its ESG elements for a large number of companies.…”

Section: Disclosure Quality Proxies and Measuresmentioning

confidence: 99%

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Defining CSR disclosure quality: a review and synthesis of the accounting literature

Stuart

Fuller²,

Heron³

et al. 2022

JAL

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PurposeThis paper aims to review and synthesize the corporate social responsibility (CSR) disclosure literature in order to (1) develop a comprehensive definition of disclosure quality; (2) review the evolution of disclosure quality proxies used by accounting researchers; (3) describe the antecedents to disclosure quality; (4) describe the outcomes of disclosure quality; and (5) identify gaps in the current literature and offer suggestions for future research.Design/methodology/approachThis study conducted a systematic review capturing articles examining CSR disclosure quality. The researchers first searched EBSCO, identifying all relevant articles by searching for “corporate social responsibility,” “CSR,” “ESG” and “sustainability reporting” anywhere in the article. Then, the results were filtered to focus on 23 of the most prominent accounting journals. The search resulted in 592 articles which were individually reviewed for relevance to the authors’ review. This study includes all articles that examine disclosure and provide insight into elements that influence disclosure quality or provide evidence of the effects of disclosure quality on user decision-making.FindingsIt is found that a comprehensive definition of CSR disclosure quality has yet to be developed and that proxies for CSR disclosure quality have evolved over time. This study synthesizes the literature on the antecedents of CSR disclosure quality, and how CSR disclosure quality affects users' decision-making and related outcomes. Overall, the review of this study suggests that assurance and a number of corporate features have important effects on disclosure quality. Also, high-quality disclosures are positively associated with many benefits to market participants.Originality/valueThis study complements Huang and Watson's (2015) CSR literature review by comprehensively reviewing and synthesizing the CSR disclosure quality literature that was only emerging when their review was published. Importantly, this study contributes to the CSR disclosure literature by developing a comprehensive definition of CSR disclosure quality that is grounded in the accounting literature and aligned with current frameworks.

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Section: Research On Outcomes Of Csr Disclosure Qualitymentioning

confidence: 96%

Section: Effects On Firm Valuementioning

confidence: 96%

Section: Disclosure Quality Proxies and Measuresmentioning

confidence: 99%

Section: Disclosure Quality Proxies and Measuresmentioning

confidence: 99%

See 2 more Smart Citations

Defining CSR disclosure quality: a review and synthesis of the accounting literature

Stuart

Fuller²,

Heron³

et al. 2022

JAL

View full text Add to dashboard Cite

show abstract

“…In addition, corporations receiving recent “bad press” tend to suffer from high volatility in their stock price and market value, often experiencing steep stock price declines (Cui and Docherty, 2020; Muller and Kräussl, 2011). Such effects may, however, depend on the extent of corporate ESG disclosures prior to the negative exposure (Beelitz et al , 2021). However, these findings suggest that compliance is of interest to investors and that an ESG rating methodology anchored on compliance would provide ESG information consistent with institutional investors’ preferences.…”

Section: Prior Studies and Theoretical Frameworkmentioning

confidence: 99%

Must social performance ratings be idiosyncratic? An exploration of social performance ratings with predictive validity

Svanberg,

Ardeshiri,

Samsten

et al. 2023

SAMPJ

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Purpose The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies. Design/methodology/approach This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible. Findings The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method. Practical implications This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments. Social implications The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development. Originality/value To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

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