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ESG Misreporting: Role of Assurance, Assurance Provider, ESG Issue Characteristics and Personal Environmentalism in Employee Reporting Decisions

Corporate environmental social and governance (ESG) reporting is becoming subject to increased scrutiny by regulators, investors and public. This dissertation will contribute to several research streams in the extant literature. This dissertation is the first to show the impact of employee environmental values and attitudes on reporting and whistleblowing decisions, making contributions to accounting, management, whistleblowing and environmental psychology literatures. Next, it is among the first to examine the role of the identity of ESG assurance provider in ESG reporting context. Further, it is among the first to examine the impact of SEC assurance mandate and the value of assurance over ESG information, thus contributing to audit literature. Using experimental methodology, I examine how ESG report assurance, ESG report assurance provider, ESG issue type, and environmentalism as a personality factor influence employee decisions to accede to a supervisory request to misrepresent ESG information, to report management's actions to a corporate hotline, to post information about management wrongdoing on social media, to switch jobs, and to judge ESG misreporting actions as unethical. The results indicate that (1) employee personality factor environmentalism impacts their ESG reporting decisions; (2) pro-environmental employees are more likely to whistleblow when assurance is not mandated, and they …
Date: July 2023
Creator: Sapounova, Gloria N.
System: The UNT Digital Library
The Effect of Social Norms on Client Responses to Audit Inquiries (open access)

The Effect of Social Norms on Client Responses to Audit Inquiries

Audit inquiry can be a valuable source of information for auditors, particularly when the client provides useful information about important issues that could affect the audit. Recent studies indicate that the way an audit inquiry is conducted can affect the level of cooperation in the client's response. In this study, I investigate the use of social norms as an intervention auditors could include in their inquiries to increase the likelihood of client cooperation. To test my hypotheses, I conducted a 2x2 between-subjects experiment with 138 MBA and senior accounting students who proxied for non-accounting and accounting managers, respectively. I manipulated the auditor's use of a positive descriptive norm, which informed participants that the desired behavior is typical among similar others. I also manipulated the auditor's use of a negative injunctive norm, which informed participants of social disapproval for not engaging in the desired behavior. The dependent variable was a scaled measure of the likelihood the participant would disclose useful information in their response to the auditor. I find evidence of a main effect for both social norms I test. I do not find evidence of an interaction between the two social norms. My findings contribute to the audit literature as …
Date: July 2023
Creator: Jordan, Jason
System: The UNT Digital Library

Unveiling Hidden Problems: A Two-Stage Machine Learning Approach to Predict Financial Misstatement Using the Existence of Internal Control Material Weaknesses

Prior research has provided evidence that the disclosure of internal controls material weaknesses (ICMWs) is a powerful input attribute in misstatement prediction. However, the disclosure of ICMWs is imperfect in capturing internal control quality because many firms with control problems fail to disclose ICMWs on a timely basis. The purpose of this study is to examine whether the existence of ICMWs, including both the disclosed and the undisclosed ICMWs, improves misstatement prediction. I develop a two-stage machine learning model for misstatement prediction with the predicted existence of ICMWs as the intermediate concept; my model that outperforms the model with the ICMW disclosures. I also find that the model incorporating both the predicted existence and the disclosure of ICMWs outperforms those with only the disclosure or the predicted existence of ICMWs. These results hold across different input attributes, machine learning methods, and prediction periods, and training-test samples splitting methods. Finally, this study shows that the two-stage models outperform the one-stage models in predictions related to financial reporting quality.
Date: July 2023
Creator: Sun, Jing
System: The UNT Digital Library