The purpose of this study is to apply a combination of sentiment mining techniques and a sustainability balanced scorecard to CEO messages in sustainability management reports to predict corporate financial ratios. We classify the contents of CEO messages into the six perspectives suggested by the sustainability balanced scorecard (SBSC). From the sentiment mining results, we first document that positive words dominate CEO messages in sustainability management reports. Moreover, words related to the sustainability perspective do not generally exhibit a significant relationship with financial ratios. This finding indicates that CEOs’ messages in sustainability management reports seemingly fail to properly represent the firms’ current financial status. Therefore, the results indicate that a stronger supervisory standard may be required to induce CEO disclosures that are more responsible for sustainable management reports.

Despite the general agreement that a firm embodies its own culture, there is still a lack of empirical research on how a firm’s culture affects its value. Another caveat on previous studies is that they implicitly assume that a firm’s culture does not vary over time. In this paper, we examine the following two questions to address this lack: (1) Does a firm’s culture affect the firm’s value? (2) If a firm’s culture varies at different life cycle stages, do these changes have an impact on firm value? By using a competing values framework, we identify four types of corporate culture—adhocracy, market, clan, and hierarchy—and use life cycle stages to proxy for changes in a firm’s environment. The results reveal that adhocracy culture has a positive effect on a firm’s value. In contrast, we find a negative association between hierarchy culture and a firm’s value. This can be interpreted as the features of adhocracy culture, which gives autonomy to its members (flexible and discretion) and keeps challenging a firm to grow (external focus and differentiation), positively impacting firm value more than the other cultures. Furthermore, at a growth stage in which a firm faces dynamic environmental changes, both adhocracy and clan cultures have an incrementally positive effect on firm value. This implies that firms in mature or decline stages lose dynamic changes in their operational environment, therefore, the effect of culture on firm value is restricted in those stages.

(1) Background: The Chief Executive Officer’s (CEO’s) message on a hospital’s homepage on the Internet contains various components, such as the hospital’s future vision, promises to customers, availability of upgraded services and public activities. This statement usually includes non-financial information as well as financial information about the corporate entity owning/operating the hospital. In addition, it provides useful information about not only the company’s goals and vision, but also firm performance targets and strategies for the future. This study aims to investigate associations between the CEO’s message and the financial status of the institution. We used the balanced scorecard framework to analyze what content on the hospital’s homepage is related to the hospital’s various financial ratios. (2) Methods: We adopted a text-mining method to extract significantly repeated keywords from the CEO’s message on the hospital’s website. Then, we classified these keywords using a balanced scorecard approach. To examine the relationship between keywords in the CEO’s message and the hospital’s financial ratios, a t-test was conducted for the difference in the term frequency divided by inverse document frequency (TF-IDF) mean of the home page contents and its relationship with the views of the balanced scorecard framework. (3) Results: According to our empirical results on 65 samples collected from local hospitals, there are some significant relationships between the qualitative content of the hospital’s homepage and the quantitative financial ratios that indicate profitability, activity, leverage, liquidity, and accumulating reserves for proper business purposes. (4) Conclusions: The introduction section of a homepage is the part most accessible to customers, containing the aims and ideals of the hospital and reflecting the institution’s values and visions. In addition, in the coverage of financial status, the organization can either emphasize financial strength or focus on other areas to divert attention from any weakness shown in the financial information. This study reminds us of the importance of the hospital website’s disclosure, and what can be inferred from the financial status of the hospital. It also highlights the need for reconciliation and harmony between the quantitative data, financial statements, and qualitative data in the CEO’s message. (5) Implications: To the best of our knowledge, this paper is the first research attempting to investigate the relationship between text on the hospital’s homepage and the hospital’s financial ratios using text-mining techniques and the balanced scorecard framework. Hospitals play a crucial role in a country’s welfare and healthcare industry. Nevertheless, in many countries, hospital organizations tend to remain a source of critical fiscal deficits due to ineffective and sloppy management. We expect that the result of this paper can provide hospital managers with useful information to address that situation.

Purpose The purpose of this study is to examine the relationship between explanatory language, audit fees and audit hours to demonstrate that auditors use explanatory language in audit reports to explain perceived audit risk. Design/methodology/approach The authors construct the sentiment value, a novel audit risk proxy derived from audit reports, using big data analysis. The relationship between sentiment value and explanatory language is then investigated. The authors present the validity of their new metric by examining the relationship between sentiment value and accounting quality, taking audit fees and hours into account. Findings The authors first find that reporting explanatory language is positively related to audit fees. More importantly, the authors provide an evidence that explanatory language in audit reports is indicative of increased audit risk as it is negatively correlated with sentiment value. As a positive (negative) sentimental value means that the audit risk is low (high), the results indicate that auditors describe explanatory language in a negative manner to convey the inherent audit risk and receive higher audit fees from the risky clients. Furthermore, the relationship is strengthened when the explanatory language is more severe, such as reporting the multiple numbers of explanatory language or going-concern opinion. Finally, the sentiment value is correlated with accounting quality, as measured by the absolute value of discretionary accruals. Originality/value Contrary to previous research, the authors’ findings suggest that auditors disclose audit risks of client firms by including explanatory language in audit reports. In addition, the authors demonstrate that their new metric effectively identifies the audit risk outlined qualitatively in audit report. To the best of the authors’ knowledge, this is the first study that establishes a connection between sentiment analysis and audit-related textual data.

PurposeThe paper aims to estimate abnormal audit fees more precisely than the traditional audit fee model by applying an artificial intelligence (AI) method.Design/methodology/approachThe AI technique employed in this paper is the deep neural network (DNN) model, which has been successfully applied to a wide variety of decision-making tasks. The authors examine the ability of the classic ordinary least squares (OLS) and the DNN models to describe the effects of abnormal audit fees on accounting quality based on recent research that demonstrates a systematic link between accruals-based earnings management and abnormal audit fees. Thus, the authors seek to imply that their new method provides a more precise estimate of abnormal audit fees.FindingsThe findings indicate that abnormal audit fees projected using the DNN model are substantially more accurate than those estimated using the classic OLS model in terms of their association with earnings management. Specifically, when abnormal audit fees predicted using the DNN rather than the OLS are incorporated in the accruals-based earnings management model, the adjusted R2s are larger. Additionally, the DNN-estimated coefficient of abnormal audit fees is more favorably associated to earnings management than the classic OLS-estimated coefficient. Additionally, the authors demonstrate that the DNN outperforms OLS in terms of explanatory power in a negative discretionary accruals subsample and a Big 4 auditor subsample. Finally, abnormal audit fees projected using the DNN method provide a better explanation for audit hours than those estimated using the OLS model.Originality/valueThis is the first approach that utilized a machine learning technology to estimate abnormal audit fees. Because more precise measurement yields more credible research results, the findings of this study imply a significant advancement in calculating unusually higher audit fees.