Evidence-Informed Audit Standard Setting: Exploring Evidence Use and Knowledge Transfer in Group Audits

• In Event: Group Audits: Insights, Strategies, and Evidence for Standard Setting

Abstract

We employ a design science research approach to investigate the efficacy of an academic prepared research synthesis to transfer knowledge to standard setters via a real-time simulation with former standard setters over a twelve-week period. The simulation is of an actual standard setting problem (where standard setters withdrew the first exposure draft due to a lack of consensus). We first determine that nature of the evidence used at the time of the standard setting decisions through examination of extensive archival records. We find that for this issue, standard setters primarily employ practitioners’ (including standard setters and task force members) tacit knowledge as the evidence base for setting standards. We find no systematic evidence collection by standard setters, task force members, or responders to the exposure draft, and no employment of academic research in the process. We then investigate our proposed improvement to the process, the use of a research synthesis of academic research that existed at the time of the initial standard setting decisions. Following a design science research approach, we develop and evaluate a prototype research synthesis co-created in a real-time simulation with former standard setters. We evaluate the process of synthesis creation as well as the resultant synthesis pragmatic validity as seen by our former standard setters. Based on this evaluation we conclude that we have created one successful instantiation of the proposed knowledge transfer process. Further, our simulation participants identified other standard setting issues where it could be successfully deployed. We conclude that we have provided strong initial evidence that the research synthesis approach to knowledge transfer can be used to systematically transfer audit research knowledge in the audit standard setting domain.

Authors

• Kris Hoang, University of Alabama-Tuscaloosa

• Yi Luo, Queen's University - Kingston

• Steven E Salterio, Queen's University