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The purpose of this study is to examine how corporate communication of their social programs on their websites affects the ratings of those programs by independent rating agencies. Firms expend resources on corporate social programs (CSPs) to promote their corporate social responsibility and sustainability credentials. Stakeholders, however, often respond to such “self-promotion” with skepticism because they believe that there are inconsistencies between corporate claims and actions. This research draws on attribution theory as a framework to examine how the perceived CSP performance of firms by uncontrollable sources are affected when firms disseminate CSP information on firm websites, i.e. a controllable source, where their claims may not be verifiable.

This study uses a two-step, mixed method study for the analysis using data from Fortune 500 companies. A qualitative content analysis process identifies the interfaces of CSP and their communications on firms’ website. The process allows the authors to collect CSP data systematically from firm websites and to identify relevant variables through the patterns that emerge from the analysis. The findings are used in a quantitative analysis to study how the patterns underlying CSP communication on their websites affect the ratings of firms’ CSP by independent rating agencies.

Results show that the location, the manner, the content and the scope of CSP information dissemination on firm websites, as well as perceived commitment to CSP identified on the website are important drivers of perceived CSP performance. A robustness check using an alternative independent rating of CSP also provides results that are supportive of the findings. In addition, the effects are found to differ by sector of operation, firm age and profitability.

This research suggests that communication of CSPs at controllable sources of firm information dissemination can have a significant effect on the evaluation of CSP at uncontrollable sources when such communication facilitates the assessment of other information from a firm to determine the motive underlying a firm’s CSP.

The findings show that firms and managers can influence the perceived ratings, rankings or scores of their CSP by stakeholders when they put the right information at the right place on their corporate websites. One of the findings shows that even moderate levels of CSP commitment demonstrated on firm websites result in positive perceptions of CSP, which has marked practical implications.

The findings show that integrating even a medium level of commitment to CSP increases the positive perceptions of a firm’s CSP. Thus, society benefits from the firm’s action without a substantial impact on the firm’s profits.

This research shows that firm-controlled sources of CSP information dissemination to stakeholders can affect uncontrollable sources of CSP information evaluation.

This study aims to investigate the associations between audit firm attributes (i.e. audit firm size, non-audit services, auditor industry specialization and auditor-client tenure) and specific indicators of audit quality. It also aims to test whether these relationships are moderated by a set of other factors like legal system and US versus non-US settings.

The method of Hunter et al. (1982) is used as a meta-analysis technique to test the study hypotheses and achieve the study aims. A total of 71 published papers from 1992 to 2017 are included.

There are significant positive relationships between all audit firm attributes and audit quality. Additionally, the associations between all audit firm attributes and audit quality are moderated by proxies for audit quality. Furthermore, these associations are moderated by other variables, such as US and non-US studies, pre-SOX and post-SOX periods, the legal system, the strength of auditing and reporting standards and country classification (developed or developing country).

The number of studies is insufficient for some variables, and therefore, the results should be interpreted with caution. In addition, the analyzed studies include several proxies, and thus, the number of studies is inadequate for the incorporation of other factors in the meta-analysis (e.g. audit firm experience and audit firm reputation).

This study contributes to audit quality research by providing empirical evidence of the associations between a specific set of audit firm attributes and audit quality using the meta-analysis method. More importantly, the study provides evidence on factors that moderate these associations.

Competitor analysis is a key component in operations management. Most business decisions are rooted in the analysis of rival products inferred from market structure. Relative to more traditional competitor analysis methods, the purpose of this paper is to provide operations managers with an innovative tool to monitor a firm’s market position and competitors in real time at higher resolution and lower cost than more traditional competitor analysis methods.

The authors combine the techniques of Web Crawler, Natural Language Processing and Machine Learning algorithms with data visualization to develop a big data competitor-analysis system that informs operations managers about competitors and meaningful relationships among them. The authors illustrate the approach using the fitness mobile app business.

The study shows that the system supports operational decision making both descriptively and prescriptively. In particular, the innovative probabilistic topic modeling algorithm combined with conventional multidimensional scaling, product feature comparison and market structure analyses reveal an app’s position in relation to its peers. The authors also develop a user segment overlapping index based on user’s social media data. The authors combine this new index with the product functionality similarity index to map indirect and direct competitors with and without user lock-in.

The approach improves on previous approaches by fully automating information extraction from multiple online sources. The authors believe this is the first system of its kind. With limited human intervention, the methodology can easily be adapted to different settings, giving quicker, more reliable real-time results. The approach is also cost effective for market analysis projects covering different data sources.

Wonders whether companies actually have employees best interests at heart across physical, mental and spiritual spheres. Posits that most organizations ignore their workforce – not even, in many cases, describing workers as assets! Describes many studies to back up this claim in theis work based on the 2002 Employment Research Unit Annual Conference, in Cardiff, Wales.

The purpose of this paper is to examine whether audit firms use transparency reports (TRs) as a tool to standardize their brand image or whether the semantic and content analysis in these reports indicates a higher importance of country effects.

The sample includes 28 TRs published in English by the Big-4 audit firms from five EU countries (the UK, Ireland, Luxemburg, Hungary and Malta), as well as in the USA and Australia.

Using content analysis, this research finds that there is variation in the language used in TRs both across audit firms and jurisdictions. Most TRs from different countries of the same firm tend to be clustered, suggesting that audit firms use transparency reporting as a strategy to differentiate themselves from their competitors. In fact, EY and KPMG seem to have more standardized internal procedures and standardized information. Regarding country effects, the results indicate that TRs in the UK are longer and show more detailed information.

Overall, this research is innovative in the sense that it applies a new methodological approach to an emerging topic such as audit transparency reporting. It identifies emerging topics of voluntary disclosure, such as financial data of the firm, gender and ethnic origin of employees, community involvement or sanctions, among other topics of interest which might be explored in detail by future research to understand the construction of the profession.

We contribute to the emerging literature on strategic corporate social responsibility (CSR) and its antecedents by undertaking a systematic analysis of the effect of rivalry on firm and industry CSR. We deal with the codetermination of competition and CSR by using instrumental variables in the firm-level analysis and by modeling it directly in the industry-level analysis. We find that higher intensity of rivalry and CSR of competitors increase firm CSR, ceteris paribus; however, in a more dynamic setting when firms can change their production output, more competition in fact decreases aggregate industry CSR. While seemingly contradictory, these findings suggest interesting implications for both managers and public policy makers.

This study investigates the association between debt overhang and carbon emissions (both direct and indirect emissions) using a sample of US publicly listed firms.

The study applies generalized least squares (GLS) regression analyses to a sample of 2,043 US firm-year observations over a period of 14 years from 2007 to 2020. The methods include contemporaneous effect, lagged effect, alternative measures of carbon emissions and debt overhang, intensive versus non-intensive analysis, channel analysis, firm fixed effects, change analysis, controlling for credit rating analysis, propensity score matching approach, instrumental variable analysis with industry and year fixed effect.

This study's findings reveal that the debt overhang problem increases carbon emissions. This finding holds when the authors use alternative measures of carbon emissions and debt overhang. The authors find that carbon abatement investment is a channel that is negatively impacted by debt overhang, which in turn increases carbon emissions. This study's results are robust for several endogeneity tests, including firm fixed effects, change analysis, propensity score matching approach and two-stage least squares (2SLS) instrumental variable analysis.

The outcome of this research has policy implications for several stakeholders, including investors, firms, market participants and regulators. This study's findings offer insights for investors and firms, helping them allocate resources effectively and make financing decisions aimed at reducing carbon emissions. Regulators and policymakers can also use the findings to formulate policies that promote alternative sustainable finance practices.

The outcome of this research is likely to help firms develop their understanding of the debt overhang problem and undertake strategies that yield a significant amount of funding to invest in reducing carbon emissions.

The purpose of this paper is to give a comprehensive review and synthesis of automated textual analysis of corporate disclosure to show how the accuracy of disclosure tone has been incremented with the evolution of developed automated methods that have been used to calculate tone in prior studies.

This study have conducted the survey on “automated textual analysis of corporate disclosure and its impact” by searching at Google Scholar and Scopus research database after the year 2000 to prepare the list of papers. After classifying the prior literature into a dictionary-based and machine learning-based approach, this study have again sub-classified those papers according to two other dimensions, namely, information sources of disclosure and the impact of tone on the market.

This study found literature on how value relevance of tone is varied with the use of different automated methods and using different information sources. This study also found literature on the impact of such tone on market. These are contributing to help investor’s decision-making and earnings and returns prediction by researchers. The literature survey shows that the research gap lies in the development of methodologies toward the calculation of tone more accurately. This study also mention how different information sources and methodologies can influence the change in disclosure tone for the same firm, which, in turn, may change market performance. The research gap also lies in finding the determinants of disclosure tone with large scale data.

After reviewing some papers based on automated textual analysis of corporate disclosure, this study shows how the accuracy of the result is incrementing according to the evolution of automated methodology. Apart from the methodological research gaps, this study also identify some other research gaps related to determinants (corporate governance, firm-level, macroeconomic factors, etc.) and transparency or credibility of disclosure which could stimulate new research agendas in the areas of automated textual analysis of corporate disclosure.

The authors aim to obtain the optimal combinations of factors from institutional environment adaptation mechanisms and internal resources or capabilities that influence the sustainability of a firm.

The authors develop a new index, called the sustainability index, based on the stakeholder perspective by employing a corporate credit risk index, an evaluation of a firm's corporate governance, corporate financial performance and firm age. The authors then apply both Ordinary Least Squares (OLS) Regression Analysis and Fuzzy set Qualitative Comparative Analysis (FsQCA) to obtain the optimal models for firms' sustainability.

The OLS analysis shows that the variables including financial leverage, slack, innovation capability, manufacturing capability and human capital that have significant influences on the sustainability of firms. Our FsQCA analysis obtains configurations of several solutions for firm sustainability and concludes that the fit of combinations of institutional factors and/or internal resources and capabilities of a firm is related to its sustainability.

The limitations in our new index include these: first, one may add more key metrics to measure the index; second, the findings do not provide any necessary nor a sufficient condition to get sustainability for sure. The limitations of using multiple regression analysis are that it is not able to reveal the combinations of causal conditions that can lead to the outcome in the real world as well as to the sustainability of a firm in our study. To overcome the limitations, the authors apply fsQCA analysis to identify combinations of causal conditions to a firm's sustainability in our study.

Introducing the sustainability index enables us to find out all factors influencing the sustainability of a firm. The authors’ analysis can be used to identify combinations of causal conditions to lead to outcomes in the real world. Their analysis enables managers to know how to predict the sustainability of the firm. For example, the authors’ fsQCA analysis shows that low marketing capability will lead to the high sustainability of the firm. This information helps managers to make the decision or plan to achieve good results toward their businesses and get better allocate their resources and get a better investment.

The authors’ analysis can be used to identify combinations of causal conditions to lead to outcomes in the real world and enable managers to know how to predict the sustainability of the firm. A correct prediction can assist companies in developing their future operations, which would enhance their competitiveness vis-à-vis rivals during this time of global economic volatility, which, in turn, enables firms to perform better and employ more employees that could help the entire society.

The sustainability index the authors developed in our paper is new in the literature and the findings obtained by both OLS Regression Analysis and FsQCA are new in predicting a firm's sustainability. The authors’ findings are useful for academics, managers and policymakers in predicting and maintaining a firm's sustainability.

The paper aims at providing insights on the relationship between capital structure and performance of the firm by employing meta-analytical approach to obtain a synthesized result out of controversial studies as well as the sources for such inconsistency.

Using secondary data, the analysis is divided into two main parts with concerns to the overall strength of the relationship, the effect size and the potential paper-specific characteristics influencing the magnitude of impacts between leverage and firm performance (moderators of the relationship). Overall, a total number of 32 journals, reviews and school presses were selected besides online libraries and publishing platforms. There were 50 papers with 340 studies chosen from 2004 to 2019, of which data range from 1998 to 2017.

Using Hedges et al. (1985,1988), descriptive and quantitative analysis have been conducted to confirm that corporate performance is negatively related to capital decisions, which inclines toward trade-off model with agency costs and pecking order theory. The estimation induces rather small effect size that implies sufficiently large sample size to be effectively investigated. In terms of moderator analysis, random-effects meta-regression models of three different techniques are used to increase the robustness in research findings, showing statistically significant elements as publication status, factor of industry and proxy of firm performance.

This paper is one of the first papers presenting meta-analysis in capital structure and performance for two languages, Vietnamese and English, providing a consistent result with previous worldwide papers.