Jeremiah W. Bentley

Challenges with Amazon Mechanical Turk Research in Accounting

Online research platforms such as Amazon Mechanical Turk (AMT) are an increasingly popular source of experimental subjects for accounting research. In this paper I discuss five challenges that researchers may encounter when using AMT or other platforms. I also present practical methods for overcoming these challenges. The discussion should be of interest to PhD students and other researchers considering using AMT or other online platforms as a source of experimental participants as well as to reviewers and editors who are considering quality control standards for this new class of research.

Measure Management and the Masses: How Acceptability of Operating and Reporting Distortion Varies with Justification, Demography, and Moral Consequences

In three studies totaling almost 5000 subjects, we present respondents with scenarios in which employees manage performance measures by distorting how they report performance or how they operate their organizations. We measure respondents’ judgments about the scenarios and their broader moral values, and interpret statistical associations in light of Moral Foundations Theory (Graham, Nosek, et al 2011) to draw inferences on how respondents view the ‘moral terrain’ of morally-relevant features depicted by the scenarios we present. In our business, public school and hospital settings, we conclude that respondents see reporting distortion as a more appropriate remedy than operating distortion to inequity, and see operational distortions as improving underlying performance more effectively when measures capture true performance more accurately. In our public school and hospital settings, we also conclude that respondents see the organization, (i.e. school or hospital), rather than outside stakeholders, (i.e. students or patients), as representing the in-group to which managers owe loyalty. Respondents also see a sacred element both in reporting and in supporting a school or hospital.

The Effect of Increased Audit Disclosure on Managerial Decision Making: Evidence from Disclosing Critical Audit Matters

We investigate whether and how a “critical audit matter�? (CAM) disclosure affects managers’ real operating decisions in two contexts (issuing a loan that decreases versus increases the average risk profile of loan portfolios, or choosing to hedge versus speculate on commodity risk). We expect a CAM disclosure increases disclosure costs and implies expanded auditor support for both types of activities; but we expect implied auditor support to be valued more highly for risk-increasing than for risk-decreasing activities. As a result, we predict that a CAM disclosure decreases managers’ risk-decreasing activities (due to increased disclosure costs) more than managers’ risk-increasing activities (as the implied auditor support counteracts the increased disclosure costs). We find evidence consistent with our prediction across multiple experiments. Our study sheds light on unintended consequences of a CAM disclosure and provides insight to relevant parties as the new standard goes into effect.