Article

A Textual Analysis of US Corporate Social Responsibility Reports

Authors:
  • University of Toronto; Vector Institute; St Michael's Hospital; Surgical Safety Technologies
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Abstract

We employ computer‐based textual analysis to examine disclosure patterns for a sample of US corporate social responsibility (CSR) reports from the period 2002–2016. Starting from 466 features commonly used in computational linguistics, our results show that the linguistics or disclosure patterns in CSR reports can be used to accurately predict the actual CSR performance type of CSR reporters. Specifically, we find that the two most commonly used disclosure characteristics, number of words and number of sentences, alone can be used to predict reporting firms’ CSR performance type with 81% accuracy. The accuracy of prediction increases to 96% when the top 50 linguistics features most relevant to firms’ CSR performance are included in the prediction model. In addition, we find that the linguistic features of CSR disclosure identified by our study are incrementally value relevant to investors even after controlling for the actual CSR performance score from the professional CSR rating agencies. This finding suggests that the linguistic features of CSR disclosure can be an important venue for capital market participants in evaluating firms’ CSR performance type, especially when professional CSR performance ratings are not available.

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... • Random Forest and XGBoost: These ensemble learning techniques combine multiple decision trees to enhance prediction accuracy and mitigate overfitting. Their application in sentiment analysis and readability assessments has shown robustness and high accuracy, particularly in large-scale SR datasets (Clarkson et al., 2020;D'Amato et al., 2021). ...
... Machine learning models were applied as well, with Clarkson et al. (2020) using XGBoost and Random Forest classifiers to predict CSR performance from sentiment and readability features. Albitar et al. (2022) used regression models to analyze the relationship between corporate governance and CSR tone. ...
... Text Mining Category Data Scope Timespan BERT 60 2011-2020 (Rocca et al., 2020) WF, LDA No report analyzed, posts from companies analyzed Until 2018 (Harymawan et al., 2020) WF 152 reports 2010(Sai et al., 2019 WF(unigram and bi-gram WF ) 36 reports 2015-2018 (Smeuninx et al., 2016) POS, word frequency 470 NA (Albitar et al., 2022) Dictionary-based NA 2008-2017 (Cho et al., 2010) Diction software 190 2002 (Clarkson et al., 2020) Supervised Ml models (random forest, XGBoost classifier) Despite its high complexity and potential to handle medium-sized datasets (hundreds to thousands of SRs), BERT was applied to a small dataset of just 60 SRs. Its inherent strength lies in providing highly detailed and context-aware analysis, identifying complex sentiment patterns and relationships within SRs. ...
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Automated text analysis approaches such as text mining (TM) and natural language processing (NLP) hold great promise for dealing with the growing volume, diversity, and complexity of the data found within corporate sustainability reports (SRs). However, given the novelty of these approaches, we know little about how and how well these research studies have utilized these new tools-specifically, the methods employed, research objectives addressed, and progress in applying these tools in a manner that would allow us to fully maximize the insights generated from the growing wealth of sustainability data. Consequently, we conduct a systematic literature review (SLR) in order to synthesize and assess the literature utilizing TM-NLP to study SRs. Our contribution is threefold: First, we provide an overview of the methodologies and techniques that have been employed in the analysis of SRs. Second, we review the research objectives pursued by scholars employing TM-NLP in the analysis of SRs. Third, based on these, we present a critical assessment of the literature to date. Findings reveal that while there has been some progress, issues related to research depth, breadth, and methodological transparency are evident in the body of literature to date. As such, we argue that the potential of TM-NLP to generate significant insights from SR big data remains largely unrealized and offer suggestions for future research.
... More recently, Du and Yu (2021) document that a more optimistic tone and more readable text in firms' CSR reports contribute to better CSR performance, with the market reacting strongly to report readability and tone in released CSR reports. Similarly, Clarkson et al. (2020) find that the linguistic features of CSR reports can accurately predict firms' CSR performance, with these features incrementally value relevant to investors. While these studies generate important insights for developing our study's predictions, what is not known is whether more readable MSDs resulting from a mandatory regulation are associated with firm value. ...
... Such firms are likely to undertake various authentic measures to mitigate slavery practices, not only within their own operations but also across their supply chains. Previous studies on readability of CSR reports (Clarkson et al., 2020;Du & Yu, 2021) confirm that firms committed to improving the readability of their CSR information enable investors to better understand the firm's earnestness in addressing these issues, subsequently enhancing the firm's value. Therefore, it is argued here that more readable MSDs are likely to have a positive impact on firm value. ...
... Prior studies indicate that management uses complex, lengthy and ambiguous disclosures to obscure poor performance and bad news (Li, 2008;Lo et al., 2017). However, other factors, such as complex business operations, multiple segment reporting, employee stock options, listing requirements, accounting standards and regulatory requirements also contribute to complex and lengthy reports (Bloomfield, 2008;Bushee et al., 2018;Clarkson et al., 2020;Loughran & McDonald, 2014). Bushee et al. (2018) argue that disclosure complexity can result from both obfuscation and efforts to provide detailed information about a firm's fundamentals. ...
... Linguistic analysis deepens an analyst's understanding of how a disclosure's style and structure relates with corporate sustainability performance. For example, keyword frequency and word relationships within oil and gas compliance reports can uncover environmental violation patterns [58], and the syntactic complexity of CSR reports for good CSR performers can also be distinguished [59]. ...
... Additionally, these links can be further processed to evaluate corporate sustainability performance, in the spirit of task (T3) rating. Other applications of syntactic analysis include evaluating the grammatical clauses of disclosure sentences[59], in line with (T5) linguistic patterns, or the parsing of sustainability-related concepts, in a similar vein to the extraction of financial concepts[76]. ...
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Sustainability commonly refers to entities, such as individuals, companies, and institutions, having a non-detrimental (or even positive) impact on the environment, society, and the economy. With sustainability becoming a synonym of acceptable and legitimate behaviour, it is being increasingly demanded and regulated. Several frameworks and standards have been proposed to measure the sustainability impact of corporations, including United Nations' sustainable development goals and the recently introduced global sustainability reporting framework, amongst others. However, the concept of corporate sustainability is complex due to the diverse and intricate nature of firm operations (i.e. geography, size, business activities, interlinks with other stakeholders). As a result, corporate sustainability assessments are plagued by subjectivity both within data that reflect corporate sustainability efforts (i.e. corporate sustainability disclosures) and the analysts evaluating them. This subjectivity can be distilled into distinct challenges, such as incompleteness, ambiguity, unreliability and sophistication on the data dimension, as well as limited resources and potential bias on the analyst dimension. Put together, subjectivity hinders effective cost attribution to entities non-compliant with prevailing sustainability expectations, potentially rendering sustainability efforts and its associated regulations futile. To this end, we argue that Explainable Natural Language Processing (XNLP) can significantly enhance corporate sustainability analysis. Specifically, linguistic understanding algorithms (lexical, semantic, syntactic), integrated with XAI capabilities (interpretability, explainability, faithfulness), can bridge gaps in analyst resources and mitigate subjectivity problems within data.
... Teoh et al. [16] examined the relationship between ESG (Environmental, Social, and Governance) scores and the firm's ROE (Return on Equity) using various machine learning models such as Support Vector Machine (SVM), Random Forest, Naive Bayesian, Multilayer Perceptron (MLP), and Long Short-Term Memory (LSTM). In another study, two machine learning methods, a random forest classifier and an XGBoost classifier are evaluated for their performance in predicting CSRD [17]. ...
... Machine learning is an emerging field in CSR that generally involves analyzing large quantities of text in order to identify meaningful patterns [27][28][29]. Clarkson et al. [17] introduced a predictive method to investigate the CSRD patterns of companies in the US between 2002 and 2016. More specifically, two machine learning methods, a random forest classifier and an XGBoost classifier are used in this study to evaluate their performance in CSRD prediction. ...
Article
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Corporate social responsibility (CSR) has gained a great deal of interest in recent years due to the need for information that can help many stakeholders (e.g., governments, investors, professional organizations, researchers, etc.) understand companies’ contributions to the environment and society. CSR disclosure (CSRD) is now the key source of such information when analyzing, for example, an institution’s future performance. In the current body of CSRD literature, the majority of quantitative CSRD studies have relied on traditional statistical approaches for the correlation analysis of CSRD influencing factors. In this paper, we intend to quantitatively analyze firms’ characteristics related to CSRD in Saudi Arabia, understand CSRD and its influencing factors, and predict CSRD patterns. This study lays the groundwork to help companies make informed decisions. It also helps many other stakeholders better understand CSRD’s impacts. To achieve this, we propose a deep learning framework based on long short-term memory (LSTM) for identifying and predicting CSRD patterns. Moreover, a correlation-based technique is also used to visualize the relationships between variables and identify the significant features. The dataset used in this study was collected from annual reports, CSR reports, and firms’ websites between 2015 and 2018. It contains a variety of variables to explain the CSR behaviour of 117 companies. The proposed framework is evaluated with several approaches, including logistic regression (LR), K-nearest neighbours (KNN), support vector machines (SVM), random forests (RF), and decision trees (DT). Compared to other machine learning models, experiment results show that LSTM achieved acceptable results with the highest accuracy of 88%88_\%.
... In contrast, a negative correlation was observed with the concentration of state ownership. Clarkson et al. (2020) utilised computerised text analysis to analyse disclosure tendencies within a selection of U.S. corporate social responsibility (CSR) reports spanning the years 2002 to 2016. A total of 466 features frequently employed in the field of computational linguistics were identified. ...
... Research shows that producing a stand-alone sustainability report has its benefits. The use of standalone sustainability reports is more likely to mitigate concerns that the linguistic features of sustainability information might affect or be affected by the financial information (Clarkson et al., 2020). Moreover, standalone sustainability reports, on average, are longer and cover more sustainability issues compared to the sustainability information disclosed in the annual or integrated reports (Dhaliwal et al., 2011). ...
... Lang and Stice-Lawrence (2015) use natural-language techniques to analyze reporting data, but their study focuses on annual reports. Clarkson et al. (2020) provide a large-scale textual analysis of CSR reports, but do not examine greenwashing. Albitar et al. (2023) likewise apply NLP to sustainability sections of annual reports, but their analysis is limited to detecting tone. ...
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A textual analysis of corporate‐social responsibility (CSR) reports reveals that companies engaged in environmental violations report differently from firms with a clean record. The violators issue longer, more positive and more frequent reports to relay environmental content that is more copious but less readable. The violator firms appear to modify their reporting practices right after committing a violation. The findings suggest that culpable firms exploit the current unregulated–unaudited state of CSR reporting as a means of greenwashing and call for institutional change. Our results are robust to a number of industry‐firm characteristics, including board composition, ownership dispersion and international presence.
... | COVID-19 disclosure frequency measures We compute the total number of sentences in each COVID-19 disclosure (TOTAL COVID_SENT represents the number of sentences in a COVID-19 disclosure). Using the number of sentences in a disclosure document is an effective textual analysis method for measuring the disclosure length (Bochkay et al., 2023;Clarkson et al., 2020) and finding the relative share the disclosure discussing certain topics (Chen et al., 2022), thus demonstrating the content validity of such measures. Therefore, as shown in Equation (1), we find the relative size or share (SHARE COVID_DISC ) of the COVID-19 disclosure in each disclosure document using the ratio of TOTAL COVID_SENT to TOTAL SENT (the total number of sentences in the disclosure document). ...
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We assess content, evolution and determinants of COVID-19 disclosures in accounting documents using natural language processing for TSX60 firms. We evaluate sentiment, extent of disclosure, choice of disclosure medium, links to governance, and the relationship with performance. We focus on accounting-related disclosures, an understudied aspect of corporate responses to the pandemic, and add to the choice of disclosure media literature. Our unique forward-looking longitudinal approach to understanding the content, evolution and determinants of COVID-19 corporate disclosures includes an evaluation of how these disclosures are affected by corporate governance and jurisdictional factors. Our findings include evidence of an inverse relationship between causal reasoning in disclosures and performance, with firms attributing poor performance to the pandemic across years, consistent with impression management.
... Hexun CSR data draws on information from both standalone CSR reports and annual reports, which makes it a comprehensive and reliable source for analysing CSR performance. This is particularly important, as Clarkson et al. (2020) warn against relying solely on CSR data from corporate annual reports or standalone CSR reports of firms. Therefore, the use of Hexun CSR data helps mitigate sample selection bias and enhance the accuracy of the analysis (Tang, Fu, & Yang, 2019). ...
Article
Purpose The purpose of this study is to examine the relationship between the corporate social responsibility (CSR) performance of job-hopping executives at their former and subsequent firms. Design/methodology/approach We conduct regression analyses using a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020 to examine whether CSR performance is similar from one firm to the next as executives switch jobs. Findings We find a positive relationship between the CSR performance of former and subsequent firms under job-hopping executives. This relationship is the strongest in the year of the job switch; it weakens in the second year and eventually disappears in the third year. In addition, we show that this relationship benefits different CSR stakeholder groups and is contingent on executive and subsequent firm attributes and job-hopping characteristics. Furthermore, we demonstrate that firms that hire a new chief executive officer from a firm with a strong track record in CSR, the new firm experiences a significant surge in CSR performance compared with firms that do not experience such a shock. Practical implications This study has implications for executive hiring decisions. Originality/value This study extends the understanding of CSR determinants through the lens of inter-organisational ties associated with job-hopping executives.
... Wang, Hsieh, and Sarkis [13] adopted three indices, Fog, Kincaid, and Flesch index, to measure the readability of CSR reports. Clarkson et al. [14] used total characters, total vocabularies, and keywords related to social responsibility to measure the readability of CSR reports. Jamal, Karel, and Fereshteh [15] used the length of vocabulary and the length of sentences to obtain the readability of CSR reports. ...
Article
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The literature has confirmed that when managers increase profits through earnings management, the readability of annual reports may be reduced Lo (2017), Ye (2018). Whether this conclusion is suitable for Chinese corporate social responsibility (CSR) reports, however, is still unclear. Based on the panel data of 5083 Chinese non-financial listed companies from 2010 to 2019, this paper adopts multiple linear regression to investigate the impact of earnings management on the readability of Chinese CSR reports. The results show that: (1) There is a significant negative correlation between earnings management and the readability of Chinese CSR reports, with the readability of Chinese annual reports as a mediating variable. (2) The negative effect is more significant when companies are not punished for violations, when the internal control index is low, when companies lack ISO14001 certification and when companies do not have independent third-party authentication for Chinese CSR reports. (3) When earnings management just exceeds zero, the readability of Chinese CSR reports decreases. (4) The economic consequences of reducing the readability of Chinese CSR reports are that financing costs are increased and environmental performance is decreased. To improve the quality of information disclosure of listed companies, the recommendations are as follows: First, the government should issue CSR reporting standards to reduce the manipulation of Chinese CSR reports. Second, Chinese CSR reports disclosed by listed companies must be audited by independent third parties to enhance the credibility of the information. Third, the company needs to strengthen its external and internal supervision to reduce the manipulation space for the readability of Chinese CSR reports. This study extends the negative relationship between earnings management and the readability from annual reports to Chinese CSR reports. To prevent investors from detecting earnings management, the readability of Chinese CSR reports may be reduced. At the same time, the study has definitely added value to the existing literature in the domain of CSR.
... According to Huang et al. (2014), tone management is the abnormal tone used to obscure firms' fundamentals. Furthermore, Clarkson et al. (2020) state that to evaluate the credibility of the disclosed information, the linguistic features are essential and may reveal discretionary attempts. As an illustration, Brennan and Merkl-Davies (2013) highlight that positive bias has been introduced in Enron's annual report before its collapse for manipulation target rather than informative ones. ...
Article
This paper explores how the disclosure quality, measured by the abnormal tone of environmental and social report, may determine the environmental, social and corporate governance (ESG) performance of the firm. This study also investigates the impact of the moderator “board of directors” to explore the extent to which a well-balanced board of directors may affect this association within an impression management strategy.
... According to Huang et al. (2014), TM is the use of an abnormal tone level that could be opportunistically used as an instrument to obscure firms' fundamentals. Indeed, Clarkson et al. (2020) argue that the linguistic features are essential to evaluate the credibility of the disclosed information. These features may reveal discretionary attempts. ...
Article
Purpose This study aims to investigate corporate social responsibility (CSR) as an impression management strategy. It focuses on CSR associated with, both, disclosure tone management (TM) and earnings management (EM) practices to influence stakeholders’ perceptions. Design/methodology/approach Based on a sample of French listed companies (SBF 120) over an eight-year period, this study empirically investigated a total of 616 firm-year observations. This study firstly investigates the impact of EM and disclosure TM practices on CSR. Then, this study examines their joint effect to explore to which extent CSR is abused for impression management inducement. To address potential endogeneity issue that may be caused by reverse causality between CSR and EM, this study used the two-stage least square. Findings Multivariate analyses indicate that CSR is positively and significantly influenced by EM, but negatively correlated to disclosure TM. However, results highlight the absence of a significant joint effect of both discretionary practices Research limitations/implications Because this study deals only with French companies, results are applicable only to large French firms and should be interpreted with caution. Therefore, future research may need to examine another context. Practical implications As CSR may be used for impression management incentives, all actors interested in socially responsible issues have to bring an initiative to prevent the deviation of CSR from moral and ethical standards. Social implications This study sheds light on the impression management strategies used in CSR reporting, so users may have to read between lines. All stakeholders should be more cautious about the reliability of financial and non-financial information and the disclosure tone manipulation practices that may arise in narrative reports. Originality/value This research contributes to the debate around CSR from an impression management perspective. To the best of the authors’ knowledge, this study is one of the first to associate CSR with, both, disclosure TM and EM in a regulated context.
... A common problem with the claims of "sustainable" design is that they are often based on computer-based projection models, which are not transparent or reliable. These models use variables that are determined by formulas hidden in a "black box" [28,29], which may introduce errors, biases, or uncertainties [30]. ...
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Greenery-covered towers are a new generation of tall buildings characterized by substantial integration of vegetation. They aim to improve the quality of urban life by reducing air pollution, enhancing biodiversity, creating microclimates, and providing aesthetic and psychological benefits. This paper examines the innovative design approaches of greenery-covered towers, drawing on examples from different countries and contexts. It analyzes the technical, environmental, social, and economic aspects of these projects, as well as the challenges and opportunities they pose for the future of sustainable architecture. The paper concludes that greenery-covered towers should be further developed and refined to become a potential solution for addressing dense cities’ environmental and health issues.
... Corporate social responsibility report directly reflects the image of an enterprise, which has a significant influence on environmental protection (Clarkson et al. 2020). ...
Article
The discourse of Corporate Social Responsibility (CSR) report can predict the performance of CSR. Research on the CSR report of international well-known companies can provide reference and encouragement for others listed companies. Based on the multi-dimensional analysis method of Biber, this study investigates the linguistic features of the CSR report discourse of Huawei and Apple. This study makes a comparative analysis of the CSR discourse from the two firms, to explore the differences in discourse functional dimensions between Chinese and American corporate CSR reports. This study finds that, on the one hand, there are differences between Chinese and American CSR reports in dimensions of Involved versus Informational Production, Explicit versus Situation-dependent Reference, and Abstract versus Non-abstract Information. Compared with Apple’s CSR reports, Huawei’s CSR reports are more informative and explicit, but less interactive and abstract. On the other hand, there is no significant difference between Huawei’s and Apple’s CSR reports in Narrative versus Non-narrative Concerns and Overt Expression of Persuasion dimensions, indicating that CSR reports are less narrative and persuasive in both Chinese and American firms. This study has implications for improving the quality of Chinese enterprises’ CSR reports and enlightenment value for corporations to improve social responsibility performance.
... Literature assumes that more readable sustainability and integrated reports relate to positive market reactions (Muslu et al., 2019). There are indications that readability increases CSR performance (Clarkson et al., 2020), cumulative abnormal returns (Du and Yu, 2021), analyst following (Sinnewe et al., 2021), Tobin's Q (Caglio et al., 2020), and it decreases analyst forecast error (Muslu et al., 2019). This is in line with the business case argument and legitimacy theory, as more readable reports will be connected with social legitimacy and increased firm reputation. ...
Article
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Purpose This analysis focuses on automated text analyses (ATA) of sustainability and integrated reporting as a recent approach in empirical-quantitative research. Design/methodology/approach Based on legitimacy theory, the author conducts a structured literature review and includes 38 quantitative peer-revied empirical (archival) studies on specific determinants and consequences of sustainability & integrated reporting. The paper makes a clear distinction between analyses of reports due to 1) readability, 2) tone, 3) similarity, and 4) specific topics. In line with prior studies, it is assumed that more readable reports with less tone and similarity relate to increased reporting quality. Findings In line with legitimacy theory, there are empirical indications that specific corporate governance variables, other firm characteristics, and regulatory issues have a main impact on the quality of sustainability and integrated reporting. Furthermore, increased reporting quality leads to positive market reactions in line with the business case argument. Research limitations/implications The author deduces useful recommendations for future research to motivate researchers to include ATA of sustainability and integrated reports. Among others, future research should recognize sustainable and behavioral corporate governance determinants and analyze other stakeholders’ reactions. Practical implications As both stakeholders’ demands on sustainability and integrated reporting have increased since the financial crisis of 2008-09, firms should increase the quality of reporting processes. Originality/value This analysis makes major contributions to prior research by including both sustainability and integrated reporting, based on ATA. ATA play a prominent role in recent empirical research to evaluate possible drivers and consequences of sustainability and integrated reports. ATA may contribute to increased validity of empirical-quantitative research in comparison to classical manual content analyses, especially due to future CSR washing analyses.
... These characteristics also make mutual funds desirable shareholders for their insight into financial, social, political, and environmental issues [1,37]. For that reason, also, firms cannot dismiss their involvement in corporate governance and reporting [38][39][40][41]. ...
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After 40 years of economic ascendancy, China’s environmental challenges and public awareness of them have swelled substantially. Both concern mutual funds that invest in publicly traded Chinese firms, many of which have shown questionable environmental responsibility. This study investigates whether mutual fund ownership of Chinese corporations influences firms’ disclosures of environmental responsibility by empirical methodologies. Annual data for 25,188 firm-year observations of corporations trading as A-shares in Shanghai and Shenzhen from 2007–2019 revealed that ownership by mutual funds, and especially by leading funds, correlates strongly and positively with environmental disclosures. These results imply that mutual funds were activist investors that influenced sampled firms to disclose their environmental responsibility during the period 2007–2019. We also examine environmental reporting and mutual fund stock ownership in relation to security analyst coverage, whether sampled firms are government-owned, and periods before and after the implementation of China’s New Environmental Protection Law. Results are heterogeneous with respect to all three considerations. Our findings are significant for regulators, investors, and corporate managers.
... Using computer-based textual analysis allows the automatic extraction of important text from big data. Accordingly, different computer-based methods are increasing being applied in climate change research, such as deep neural language (Bingler et al., 2021), textual analysis (Chen & Bouvain, 2009aClarkson et al., 2020;Zhang et al., 2020) and bag of words artificial intelligence approach in Engle et al. (2020), to quantitatively and comprehensively measure climate change disclosure. ...
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We explore corporate environmental accountability by examining how carbon emissions affect voluntary climate-related information disclosure based on TCFD principles. Using computerized textual analysis to measure such climate-related disclosure, our results show that firms with higher levels of carbon emissions disclose more climate-related information. This relation is stronger in firms belonging to carbon-intensive industries, such as energy, materials, and utilities. We also examine this relationship at the category level for Governance, Strategy, Risk Management, and Metrics and Targets, finding that carbon emissions drive disclosure in all categories except in Governance. Overall, our findings indicate that high carbon emitting firms appear to discharge their corporate accountability by increasing climate-related disclosure, consistent with legitimizing their potentially unethical actions and submitting to stakeholder and societal pressure.
... For this purpose, we made some adjustments to the financial reports, changed the format of the files, and then extracted words from the text using some of the codes used in language software such as Python. Computer-aided textual analysis is an ongoing development in accounting and finance that involves analyzing large volumes of text, in order to reveal the linguistic features of a document (Clarkson et al. 2020;Al-Shaer et al. 2022;Loughran and McDonald 2014b). After modifying the documents and converting the PDF files to text files, the next step was to convert the qualitative data into quantitative data, in order to facilitate statistical analysis. ...
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The purpose of this study was to examine the relationship between the conciseness and complexity of financial disclosures and market reactions, using the annual reports of Chinese-listed B-share companies over the period 2006–2018. We employed a set of statistical methods that were derived from other fields, such as computational and event studies, in order to derive the English annual reports of Chinese-listed companies, as well as to obtain other key financial indicators from the CSMAR database. Markets react significantly to increased report length, which means that managers that present poor returns with manipulated financial reports could be hiding poor returns. Additionally, the findings of this study are robust to additional tests that use alternative proxies. Furthermore, the results of this paper reinforce the hypothesis that the readability of financial reports affects financial market response. The results indicate that more complex financial reports are correlated with lower current returns, and negatively affect the expectations of future returns. For the purposes of avoiding the effects of the coronavirus pandemic on the results, we utilized data up to 2018. In light of this circumstance, we recommend that future research be conducted that compares results from before and after the coronavirus pandemic. The findings of our study have important implications for regulators, managers, and investors. Investors should obtain relevant information through annual reports; therefore, the importance of style is less relevant. Managers should be encouraged to write their annual reports more concisely. This study concluded that these reports are significant outputs of firms, and are widely read by investors. The study also provides empirical evidence of market reactions that are associated with readability and earnings, as well as with surprise earnings; thus, the complexity of annual reports provided by a variety of investors, using computational and event analysis, should be reduced.
... The voluntary disclosure of CSR information is widely regarded as an important component of firms' information environments (Simnett et al., 2009;Dhaliwal et al., 2011Dhaliwal et al., , 2012Dhaliwal et al., , 2014. 6 From this perspective, CSR reporting can play a direct valuation role because it is directly useful for forecasting future cash flows (the numerator effect) and risk (the denominator effect) (Wang and Li, 2016;Clarkson et al., 2019;Clarkson et al., 2020;Tan et al., 2020). With regard to the direct numerator effect, improved transparency through CSR reporting can enhance the monitoring of managerial investment decisions and reduce managers' opportunities to misuse firm resources in value-destroying projects (Lu et al., 2017). ...
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Using a large international sample of 24,293 observations from 3,991 unique firms in 56 countries, we examine the role of financial analysts in the relationship between voluntary corporate social responsibility (CSR) reporting and firm value. We find that after controlling for firms' CSR performance ratings and other factors, voluntary CSR reporting increases firm value in countries worldwide, and analysts strengthen the positive relationship between CSR reporting and firm value. More importantly, our results show that the positive role of analysts in the relationship between CSR reporting and firm value varies with country-level institutional characteristics, such as the level of investor protection, the development of capital markets and the analyst profession, and stakeholder orientation. Furthermore, the positive role of financial analysts varies according to CSR reporting characteristics, including CSR reporting assurance, choice of assurer, CSR reporting coverage, CSR reporting quantity, and length of CSR report. We also find that financial analysts can strengthen the positive association between CSR reporting and firm value for CSR disclosures published in all types of media (standalone, annual report-based, and web-based CSR disclosures). Overall, our results present global evidence that shows the important role of financial analysts in improving the valuation implications of voluntary CSR reporting.
... The information given can contain positive, negative, and possibly incomplete information, indicating inherent information asymmetry between the sender and receiver. Clarkson et al. (2020) and Albitar et al. (2021) agreed on the purpose of companies on providing information to stakeholders to signal their positive activities on corporate social reports. For companies listed on the stock market, the disclosure of annual financial statements is mandatory according to the regulations of the stock exchange, but each company will disclose information at different times. ...
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This article studied the factors affecting the time taken for annual report submission through an analysis of 654 non-financial listed companies on the Vietnamese stock market from 2016 to 2020. Data collected were processed by using fixed-effect models (FEM), random effect models (REM), adjusted REM, and general least square (GLS) to ensure the validity of research results. The main objective of this paper was to explore the effects of independent variables including retained earnings (RETA), earnings before interest and tax (EBITTA), liquidity (WCTA), capital structure (BVETD), bankruptcy risk (ZSCORE), size (SIZE), number of years in business (AGE), characteristics of financial reports (CONSO), and type of audit firm (AUDIT) on the number of days for publication annual reports (TIME). The results obtained from the adjusted-REM and GLS regression showed that retained earnings, firm age, and firm size have positive effects on time for disclosure annual reports, whereas earnings before interest and tax and audit firm type have negative effects. In addition, the results showed that working capital, capital structure, feature of consolidated reports, and bankruptcy risk have no significant effects on time to publish annual reports.
Article
Synopsis The research problem We investigated the relationship between product market competition and the textual characteristics of corporate social responsibility (CSR) disclosures. Specifically, we investigated three textual characteristics: tone of optimism, tone of tangibility (matter-of-factness), and readability. Motivation or theoretical reasoning On the one hand, the three ways in which CSR disclosure can enhance corporate success in competitive product market situations are as follows: (1) More readable disclosures with more optimistic and matter-of-fact tones help firms attract new customers while enhancing customer loyalty and brand value. (2) Increased market competition is expected to encourage firms to provide more-readable CSR disclosures with optimistic and matter-of-fact tones to enhance their access to external financing at lower costs. (3) CSR disclosure may strengthen a firm’s connections with business stakeholders (e.g., employees and suppliers). These connections are conducive to corporate success in competitive product market situations. On the other hand, it is well established that firms find CSR disclosure to be costly. The test hypotheses A significant relationship exists between product market competition and the three textual characteristics of CSR disclosures, namely, tone of optimism, tone of tangibility (matter-of-factness), and readability. Target population Our sample comprised 2,018 firm-year observations (2002–2020) of listed firms in Australia. Findings Our study found that firms facing an increase in product market competition tend to publish less-readable CSR disclosures with less use of optimism and matter-of-fact tones of language, and vice versa. In practical terms, this indicates that firms fail to leverage CSR disclosure in managing their product market competition, even though CSR disclosure is recognized as an effective marketing and brand strategy. Therefore, our study examined whether or not the CSR committee, as a key sustainability governance mechanism on CSR disclosure, could contribute to mitigating this missed opportunity. We found that the negative relationship between the two variables is attenuated by the presence of a CSR committee and by the CSR committee’s effectiveness. Our study should be of interest to firms, users of CSR disclosures, and regulators.
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Purpose The purpose of this paper is to assess the extent of narrative disclosure in the sustainability-integrated reports of listed companies in the UAE and its effect of firm’ performances. In 2020, The Securities and Commodities Authority issued a circular requiring all public joint stock companies listed on the Abu Dhabi Securities Exchange (ADX) or the Dubai Financial Market (DFM) to publish a sustainability report as part of their set of Integrated Reports. Design/methodology/approach Using all publicly available sustainability integrated reports of listed companies in DFM and ADX over the period 2018–2022, we first gather the report’s content by compiling a list of words using a computational linguistic technique that aims to identify specific characteristics of sustainability reports. Then, we use a GLS model to study the effect of the sustainability reporting on firm financial performance and risk. Findings The paper findings shows the level of sustainability disclosure of observed firms is noticeable. Besides, sustainability reporting has a significant effect on firm’s operational performance (ROA), financial performance (ROE) and market performance (Tobin’s Q). Nevertheless; it does not affect the financial risk. Research limitations/implications Our study makes many contributions to the literature on corporate reporting. First, our analysis complements research that largely focuses on the financial disclosures in corporate reports by examining the sustainability-specific information and providing a full review of sustainability narratives. Second, by examining the effect of sustainability reports on shareholders' wealth, this article contributes to the current knowledge of sustainability reporting. Practical implications Our research offers several practical implications to policymakers, management, shareholders in different ways. The outcomes of this study helps policymakers to assess the effect of the Securities and Commodities Authority circular on the extent of sustainability related information disclosed in the integrated-report. It also helps the government to understand the level of environmental, social and governance (ESG) disclosure per sectors. Besides, this research findings give insight to managers to understand the effect of ESG disclosed information in the sustainability integrated report on firm financial and market performances. In addition, the paper findings assure shareholders of the positive impact on sustainability integrated-report on firm performance. Originality/value To the best of the authors’ knowledge, no research has yet looked at the narratives of sustainability reports in the UAE context taking into account the different important aspects of these reports and its impact on firm performance and risk.
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The purpose of this paper is to develop and validate a text‐based measure of innovation using latent Dirichlet allocation on a sample of 45,409 10‐K filings from US listed companies. We expect that the text‐based innovation measure is associated with innovation and can be used to measure innovation for companies without patents or significant research and development expenditures. The empirical results are consistent with these assumptions, but reveal that thorough initial testing is required to ensure robustness. This study extends the research on innovation measurement and company disclosures, and provides a new method for assessing innovation using company disclosures.
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In a principal-principal setting, the presence in the boardroom of independent directors appointed by minority shareholders can provide a unique and effective corporate governance solution to reduce agency costs related to undue appropriation of the private benefits of control by majority shareholders to the detriment of minority ones and compress information asymmetry issues. Independent minority directors acting as conduits of information to the market facilitate further engagement by active shareholders, promote better communication, and reduce disclosure manipulation. The growing relevance of Corporate Social Responsibility (CSR) related information on decision investment and the easy manipulation of non-financial information has prompted the authors of this paper to investigate whether independent minority directors can play an important monitoring role in conveying non-financial information to the market, thereby reducing managerial self-serving and manipulative practices in non-financial reporting. By examining a sample of Italian-listed companies from 2017 to 2020, we perform a lexicon-based content analysis on their non-financial reports and then use panel data dependence techniques to address our research aim. Our results suggest that, by reducing managerial self-serving and manipulative practices of non-financial reporting, minority shareholders’ representativeness impacts firms’ communication choices. This evidence confirms that independent minority directors are the right path for boosting minority shareholders’ legal protection and ensuring investors’ awareness in the decision-making process.
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This study examines the relationship between financially material content in corporate social responsibility (CSR) reports and the decision usefulness of these reports. Utilizing sustainability disclosure standards and a machine learning topic modeling algorithm, a firm‐specific quantitative measure of financially material content in CSR reports is developed. It is hypothesized that firms providing greater amounts of financially material CSR content enhance their information environment, which enables analysts to make more accurate earnings predictions. The findings confirm a positive relationship between the extent of financially material CSR content disclosed and analyst forecast accuracy. This research demonstrates the effectiveness of using machine learning to identify financially material content within unstructured voluntary disclosures and contributes to the literature on the financial materiality of CSR activities and their related disclosures.
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We investigate whether social capital and trust provide a form of liquidity/trading resilience, more specifically, whether social capital and trust played a role in the speed of stock recovery following activation of the market‐wide circuit breaker (MWCB) that occurred at the beginning of the COVID‐19 pandemic in March 2020. Our finding that high‐social capital firms rebounded more swiftly in terms of stock liquidity and quality of the stock trading environment provides new evidence that social capital and trust can safeguard firms’ stocks against a potential liquidity drain and rapid deterioration in the stock trading environment under extreme market conditions.
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Corporate social responsibility (CSR) is a popular topic among scholars and business professionals alike. While previous literature has investigated the relationship of CSR and corporate performance extensively, longitudinal research on the CSR reporting practices using a comparative approach remains limited. The current study examines CSR disclosures uncovered within annual reports of the companies representing different industries in the United States. The contribution is twofold. First, the study compared the CSR topics disclosed by the food & beverage and energy sectors and upfolded their similar patterns and different emphases. Second, the study examined the dynamics of CSR reporting practices over 8 consequent years in these industries. A mixed method approach was used in this study, combining topic modeling through the Latent Dirichlet allocation (LDA) and complementary content analysis. The empirical analysis was conducted on the CSR disclosures from the annual reports released by six international U.S. organizations (three companies per industry sector) over the period from 2013 to 2020. The results showed that for both industries the social aspect of CSR was significantly reported. Nevertheless, the uncovered topics differed between sectors. Regarding the dynamics of CSR topics, both business sectors revealed variability of CSR aspects covered in the annual reports over the 8 years. Overall, this research sheds light on the relevance of addressing specific topics in CSR reporting as well as how to disseminate information about these topics in the annual reports.
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This study examines the association between textual disclosure readability in modern slavery reports and firm value. Using 212 Australian modern slavery statements for the financial year 2019-2020, a positive association is found between more readable textual disclosures in modern slavery reports and firm value. The study also finds that an optimistic tone in textual disclosures and better firm-level corporate governance accentuate this impact. Further analysis shows that the informative information component of textual disclosures in modern slavery reports is positively priced by investors. Our study's findings contribute to the debate on why firms should consider improving the textual disclosure readability of modern slavery reports. The study also informs various regulators (e.g., Australian Border Force, Australian Securities and Investments Commission [ASIC], European Union [EU] and United Kingdom [UK] government agencies, etc.) and international organisations about firm-level efforts to promote high-quality reporting on the modern slavery risk.
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bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Research problem: Leaders’ messages in corporate social responsibility (CSR) reports provide information about corporate citizenship and play an integral role in realizing communicative goals and influencing stakeholders’ perceptions. However, the linguistic features of such messages are largely underexplored. Research questions: 1. Do Chinese and American CSR reports vary in terms of their linguistic features to the degree that necessitates further exploration? 2. What are the key differing features, and what can we learn about business communication and business culture from those differences? 3. What implications do these differences have for business communication at the multinational level? Literature review: Although some linguists have analyzed CSR reports as a genre, few prior studies have paid attention to various grammatical features of CSR reports at the lexical level, and the special context of emerging economies has also been understudied. In particular, the academic attention to leaders’ messages in such reports is scant. Methodology: In our study, a comparative analytical framework focusing on lexico-grammatical features, namely, Biber's multidimensional analysis, has been adopted to compare the language used in leaders’ messages in the CSR reports issued by Chinese and American businesses on the 2022 Fortune Global 500 list. Results: In comparison to the leaders’ messages created by American companies, those created by Chinese companies are significantly more informationally dense, more narrative, less situationally dependent, less explicit, and display significantly fewer features of strict time-constrained informational elaboration. First-person pronouns, the present tense versus the past tense, nominalizations, adverbs, infinitives, modal verbs, and demonstratives are found to be the major language elements that characterize these register discrepancies. Conclusion: This study adds to the body of knowledge on business communication by utilizing multidimensional analysis to offer a systematic understanding of leaders’ messages through a quantitative lens. It also presents practical implications for various readers after discussing some elements that potentially reflect unconscious culture-specific business communication choices.
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The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation focuses on three primary research questions: the main research themes concerning ESG and AI in finance, the evolution of research intensity and interest in these areas, and the application and evolution of AI techniques specifically in research studies within the ESG and AI in finance domain. Eight archetypical research domains were identified: (i) Trading and Investment, (ii) ESG Disclosure, Measurement and Governance, (iii) Firm Governance, (iv) Financial Markets and Instruments, (v) Risk Management, (vi) Forecasting and Valuation, (vii) Data, and (viii) Responsible Use of AI. Distinctive AI techniques were found to be employed across these archetypes. The study contributes to consolidating knowledge on the intersection of ESG, AI, and finance, offering an ontological inquiry and key takeaways for practitioners and researchers. Important insights include the popularity and crowding of the Trading and Investment domain, the growth potential of the Data archetype, and the high potential of Responsible Use of AI, despite its low publication count. By understanding the nuances of different research archetypes, researchers and practitioners can better navigate this complex landscape and contribute to a more sustainable and responsible financial sector.
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This study examines the ability of crowdsourced employee opinions about their workplace to reveal value‐relevant information about corporate culture. We investigate the employee‐friendly (EF) corporate culture values that are strongly associated with firm value and operating performance using a unique social media dataset of approximately 250,000 crowdsourced employee reviews to evaluate 18 distinct characteristics of a firm's corporate culture. The explainable machine learning model is used to examine the nonlinear associations and relative importance of employee‐friendly cultural values. We find that several employee‐friendly corporate culture features are associated with firms' value (Tobin's Q ) and operating performance (ROA). Our findings reveal two features whose association is clearly superior to other EF culture variables in our explainable machine learning model: pride in the company for Tobin's Q and job security for ROA. Based on the SHAP values, their effects are positive, significant, and relatively linear.
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Based on a sample of more than eleven thousand unique 10‐K reports of US companies filed with SEC in period 2013 to 2018, this study examines the relationship between actual sustainability performance of companies, evaluated by MSCI ESG performance scores, and the extent and the scope of environmental, social, and governance information disclosure in their annual reports. The study shows empirical evidence supporting the signalling theory view of voluntary disclosure of ESG information in annual reports for most industries, while environmentally unfriendly companies belonging to the Mining industry division show excessive reporting behavior favoring environmental topics, which is consistent with incentives to improve public image and mitigate social, political, and legal risks in line with the legitimacy theory of information disclosure. When differentiating between forward‐looking and non‐forward‐looking ESG statements, the study shows that companies providing more forward‐looking ESG information in annual reports show better next‐year ESG performance. This study implements established content analysis techniques with focus on ESG reporting and performance, building up on the study of Baier, Berninger, and Kiesel (2020) that proposed an ESG‐tailored dictionary for textual analysis purposes.
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Purpose This study aims to provide a precise understanding of how corporate sustainability information is used in socially responsible investing (SRI). The study is motivated by the lack of a recognised body of knowledge on this issue. This study, therefore, collates and reviews relevant studies (67 studies) to provide guidance to investors interested in SRI and identify a research agenda for academics desiring to contribute to this area. Design/methodology/approach This study conducts a systemic literature review employing recognised key words and searching the Web of Science. HistCite is utilised to ensure important cited studies are not missed from the collection. The review was conducted from two perspectives: (1) sources of sustainability information and (2) how the information is used in SRI. Findings The review identifies five major sources of sustainability information, including corporate reports, ESG ratings, industry affiliation, news and private communication with firms. These sources of information play different roles in the cross section of SRI strategies (i.e. negative and positive screening, active ownership and integration). This study provides guidance on how to use this information in SRI and provides recommendations for future research on how analysts interact with the information, how different informational characteristics impact implementation, ways to improve data quality, improvements to analysis methods and where data use needs to be extended into new strategies. Originality/value This review contributes to the SRI literature by inventorying studies of an important, yet omitted aspect, namely, sustainability information. This work also enriches the literature on corporate sustainability information by investigating how this information can be used for a specific purpose, namely, SRI. Given the increasing interest in SRI, this review will provide much-needed guidance for a range of practitioners, including investors and regulators.
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Purpose The paper aims to estimate how corporate philanthropy expenditures and corporate philanthropy disclosure (in general and in different spheres) affect investment attractiveness of Russian companies. Design/methodology/approach To assess the degree of corporate philanthropy disclosure the authors compiled lexicons based on a set of techniques: text and frequency analysis, correlations, principal component analysis. To adjust the existing classifications of corporate philanthropic activities to the Russian market the authors employed expert analysis. The empirical research base includes 83 Russian publicly traded companies for the period 2013–2019. To estimate the impact of indicators of corporate philanthropy disclosure on company's investment attractiveness the authors utilized panel data regression and random forest algorithm. Findings We compiled 2 Russian lexicons: one on general issues of corporate philanthropy and another one on philanthropic activities in various spheres (sports and healthcare; support for certain groups of people; social infrastructure; children protection and youth policy; culture, education and science). 2. The paper observes that the disclosure of non-financial data including that related to general issues of corporate philanthropy as well as to different spheres affects the market capitalization of the largest Russian companies. The results of regression analysis suggest that disclosure of altruism-driven philanthropic activities (such as corporate philanthropy in the sphere of culture, education and science) has a lesser impact on company's investment attractiveness than that of activities driven by business-related motives (sports and healthcare, children protection and youth policy). Research limitations/implications Our findings are important to management, investors, financial analysts, regulators and various agencies providing guidance on corporate governance and sustainability reporting. However, the authors acknowledge that the research results may lack generalizability due to the sample covering a single national context. Researchers are encouraged to test the proposed approach further on other countries' data by using the authors’ compiled lexicons. Originality/value The study aims to expand the domains of signaling and agency theories. First, this subject has not been widely examined in terms of emerging markets, the authors’ study is the first to focus on the Russian market. Secondly, the majority of scholars use text analysis to examine not only the impact of charitable donations but also the effect of corporate philanthropy disclosure. Thirdly, the authors provided the authors’ own lexicon of corporate philanthropy disclosure based on machine learning technique and expert analysis. Fourthly, to estimate the impact of corporate philanthropy on company's investment attractiveness the authors used the original approach based on combination of linear (regression), and non-linear methods (permutation importance. The authors’ findings extend the theoretical concept of Peterson et al . (2021): corporate philanthropy is viewed as the company strategy to reinforce its reputation, it helps to establish more efficient relationships with stakeholders which, in its turn, results in the increased business value.
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Purpose This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed. Design/methodology/approach This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987. Findings There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention. Originality/value The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.
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This paper provides a scoping review of European sustainability reporting studies. Previous sustainability studies do not offer a comprehensive discussion of features key to the European setting. Despite their important role in the European economy, research on small and medium-sized enterprises (SMEs) and financial institutions (i.e. insurers and banks) is limited. Furthermore, regions in southern and particularly eastern Europe, which are critical given regulators’ objectives for European Union-wide and global sustainability standards, are neglected. Finally, studies on non-financial effects of sustainability reporting are also limited, and only a few studies differentiate between stakeholder- and shareholder-oriented countries. This is needed for a holistic view on sustainability beyond financial performance. Based on material issues identified for the European context, our study provides a research agenda based on comprehensive and rigorous scientific evidence on the state of the art of sustainability research in Europe.
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The study examines the causal links between earnings quality and corporate social responsibility (CSR) performance using a large sample of United States (US) firms from 1992 to 2013. We first find that the association between earnings quality and CSR performance is positive and significant. We then test the flow of causality using Granger’s (1969) lead-lag analysis to determine whether changes in earnings quality cause changes in CSR performance or vice versa. Our findings show that changes in earnings quality cause changes in a firm’s CSR performance but not vice versa. Further analysis shows that earnings quality reduces the cost of equity capital for firms with higher CSR performance. These findings suggest that one plausible explanation for firms with higher earnings quality to maintain better CSR performance is to reduce their cost of equity capital.
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We show that those Chinese listed companies that are riding high on the media corporate social responsibility (CSR) ranking lists tend to have greater advertising (sales) expenses and poor environmental performance. This observation suggests that some companies opportunistically use media to greenwash their image, hoping to capture economic rents. Indeed, our evidence shows that greenwashing firms benefit in the lending market by exploiting the media to gain a kind of environmental, social, and governance (ESG) endorsement, thereby allowing them to achieve a lower cost of debt and to experience lower collateral obligations. The evidence suggests an adverse incentive to exploit ESG awareness via media coverage in weak institutional environments and opaque ESG disclosure regimes.
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In 2020, the SEC issued amendments to Regulation S-K requiring filers to provide discussions related to their human capital (HC) management practices. We use textual analysis to extract qualitative characteristics of these disclosures for all available 10-Ks during the first two years of the mandate. We document that, instead of evolving towards “best in class” disclosure practices under the principles-based regulation, firms exhibit a regression towards the mean on each qualitative characteristic that we examine: length, number of topics, specificity, numerosity, readability, and similarity. In other words, although firms with poorer-quality disclosures improve over time, those with better-quality disclosures learn that they have overshot the average standard and reduce the quality of their disclosures. Further tests reveal that, notwithstanding their limitations, certain HC disclosure characteristics are significantly associated with employee ratings from Glassdoor as well as with firm value. Keywords: Human capital, ESG, sustainability, linguistic analysis, disclosure, SEC regulation JEL Classification: G38, J80, M41, M48
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US companies are increasingly responding to demand from investors and other stakeholders for transparent information about companies’ environmental, social, and governance (ESG) performance by issuing ESG reports on a voluntary basis. We examine whether these reports help to resolve the previously documented disagreement among ESG rating agencies about individual companies’ ESG performance. Consistent with this possibility, we find that disagreement among ESG rating agencies is lower for firms that voluntarily issue ESG reports. In particular, disclosures about the environmental and social dimensions help reduce disagreement about the company’s performance on those dimensions. Using textual analysis, we find that longer reports are associated with reduced disagreement among ESG raters while reports with more positive tones or that use a greater number of sticky words are associated with heightened disagreement. The association between ESG disclosure and ESG disagreement is more pronounced when firms obtain third-party attestations on their ESG reports, especially from accounting firms, and when firms adhere to advanced levels of Global Reporting Initiative (GRI) reporting standards. Finally, ESG disagreement is positively associated with disagreement and uncertainty in the capital market, providing strong motivation for firms to voluntarily disclose ESG reports to reduce ESG disagreement.
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We critically assess mainstream accounting and finance research applying methods from computational linguistics (CL) to study financial discourse. We also review common themes and innovations in the literature and assess the incremental contributions of work applying CL methods over manual content analysis. Key conclusions emerging from our analysis are: (a) accounting and finance research is behind the curve in terms of CL methods generally and word sense disambiguation in particular; (b) implementation issues mean the proposed benefits of CL are often less pronounced than proponents suggest; (c) structural issues limit practical relevance; and (d) CL methods and high quality manual analysis represent complementary approaches to analyzing financial discourse. We describe four CL tools that have yet to gain traction in mainstream AF research but which we believe offer promising ways to enhance the study of meaning in financial discourse. The four tools are named entity recognition (NER), summarization, semantics and corpus linguistics. This article is protected by copyright. All rights reserved
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This study examines analyst information intermediary roles using a textual analysis of analyst reports and corporate disclosures. We employ a topic modeling methodology from computational linguistic research to compare the thematic content of a large sample of analyst reports issued promptly after earnings conference calls with the content of the calls themselves. We show that analysts discuss exclusive topics beyond those from conference calls and interpret topics from conference calls. In addition, we find that investors place a greater value on new information in analyst reports when managers face greater incentives to withhold value-relevant information. Analyst interpretation is particularly valuable when the processing costs of conference call information increase. Finally, we document that investors react to analyst report content that simply confirms managers’ conference call discussions. Overall, our study shows that analysts play the information intermediary roles by discovering information beyond corporate disclosures and by clarifying and confirming corporate disclosures. The Internet appendix is available at https://doi.org/10.1287/mnsc.2017.2751 . This paper was accepted by Suraj Srinivasan, accounting.
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We analyse the relationship between the complexity of corporate social responsibility (CSR) disclosure and actual CSR performance, and postulate a positive association between actual CSR performance and readability and the size of CSR disclosure documents. Using several readability and disclosure size measures from computational linguistics, we test our hypotheses using a cross-sectional sample of stand-alone CSR reports issued by large U.S. companies. We find that increased CSR disclosure and more readable CSR reports are associated with better CSR performance. Our findings suggest that extending CSR disclosure increases transparency regarding firms’ social and environmental performance, while using less-readable language in CSR reports increases obfuscation. This study contributes to the disclosure literature by documenting that the complexity indices that have been used as measures of obfuscation in prior finance and accounting research can help shareholders, financial analysts, and investors determine the credibility of CSR disclosure.
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Growth in CSR-washing claims in recent decades has been dramatic in numerous academic and activist contexts. The discourse, however, has been fragmented, and still lacks an integrated framework of the conditions necessary for successful CSR-washing. Theorizing successful CSR-washing as the joint occurrence of five conditions, this paper undertakes a literature review of the empirical evidence for and against each condition. The literature review finds that many of the conditions are highly contingent, rendering CSR-washing as a complex and fragile outcome. This finding runs counter to the dominant perception in the general public, among activists, and among a vocal contingent of academics that successful CSR-washing is rampant.
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Information about the affective meanings of words is used by researchers working on emotions and moods, word recognition and memory, and text-based sentiment analysis. Three components of emotions are traditionally distinguished: valence (the pleasantness of a stimulus), arousal (the intensity of emotion provoked by a stimulus), and dominance (the degree of control exerted by a stimulus). Thus far, nearly all research has been based on the ANEW norms collected by Bradley and Lang (1999) for 1,034 words. We extended that database to nearly 14,000 English lemmas, providing researchers with a much richer source of information, including gender, age, and educational differences in emotion norms. As an example of the new possibilities, we included stimuli from nearly all of the category norms (e.g., types of diseases, occupations, and taboo words) collected by Van Overschelde, Rawson, and Dunlosky (Journal of Memory and Language 50:289-335, 2004), making it possible to include affect in studies of semantic memory.
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I investigate whether corporate accountability reporting helps protect firm value. Specifically, I examine (1) whether corporate accountability reporting helps firms prevent the occurrence of high-profile misconduct (e.g., bribery, kickbacks, discrimination), and (2) whether prior corporate accountability reporting reduces the negative stock price reaction when high-profile misconduct does occur. Using multiple methods to address self-selection, I find that, on average, firms that report on their corporate accountability activities are less likely to engage in high-profile misconduct, consistent with the reporting process helping firms to manage their operations better. Additionally, I find that when high-profile misconduct does occur, firms that have previously issued corporate accountability reports experience a less negative stock price reaction, consistent with corporate accountability reports influencing perceptions of managerial intent, which, in turn, influences expected punishments.
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