This paper discusses my experiences as a nontenure track faculty member who now serves as an Associate Dean. It is based on my Presidential Scholar Lecture at the 2024 American Accounting Association Annual Meeting. In 2012, the Pathways Commission outlined the need and a path for more practitioners to join academia (Behn et al. 2012), and my academic career advanced partly due to that initiative. Earning a Doctor of Business Administration (D.B.A.) degree from University of Florida allowed me to support my school as a scholarly academic and pursue research that enhances my teaching and provided me with a path to administration as a nontenure track faculty member.

This study examines the impact of ex ante litigation risk on auditor hiring and retention. Using employee data from LinkedIn, we find ex ante accounting-related litigation risk is associated with fewer auditors joining and more auditors leaving an audit office, whereas we fail to find any impact of nonaccounting litigation risk. Moreover, ex ante accounting-related litigation risk is associated with audit firms' hiring less experienced and less educated auditors, suggesting ex ante litigation risk impacts the quality of auditing hires. We also find that the impact of ex ante litigation risk is concentrated in audit offices with more outside job opportunities and in those that are more susceptible to changes in litigation risk. Our results highlight the impact of ex ante litigation risk on audit labor supply, providing insights concerning the unintended consequences of increasing auditors' legal liability. Data Availability: All data used in this study are based on publicly available information obtained through the services or authors cited in the manuscript.

Despite the potential of algorithms to improve judgment quality, recent research suggests that individuals may be averse to algorithmic use. We experimentally examine whether and how managers’ use of an algorithm-advised performance rating is influenced by rating valence and the decision rights managers have to adjust the algorithm. We find that managers are less willing to use an algorithm to evaluate subordinate performance when it advises a low, rather than high, rating. We further show that when the algorithm-advised rating is low, allowing managers to adjust how the algorithm computes the rating, compared with adjusting the rating itself or not allowing any adjustment, increases algorithmic use. Further analyses show this effect to be consistent with managers’ increased understanding of an algorithm when involved in its computation. Our findings inform organizations’ implementation of performance evaluation algorithms by showing how rating valence and decision rights jointly influence managers’ use of the algorithms.

Governments implement wealth transfers with different policy goals and distribution methods. Prior research examines the timing (lump sum/periodic) of transfers but fails to simultaneously consider payment delivery method (standalone/combined with other income). Based on the behavioral life-cycle model, we predict payment timing influences how recipients spend government transfers, but that this effect is muted when the transfer payment is combined with other income. In contrast to prior research, our experimental findings provide theory-consistent results and suggest recipients of a periodic transfer spend more of the transfer than recipients of a lump sum transfer, but only when the transfer is standalone and not combined. Our findings help to explain theory-inconsistent results of prior research and extend the literature on the behavioral life-cycle model and mental budgeting. Moreover, our results suggest policymakers can intentionally structure the distribution of government transfers to encourage household spending or saving consistent with policy goals.