Mitigating work conditions that can inhibit learning from errors: Benefits of error management climate perceptions - van Mourik, Oscar; Grohnert, Therese; Gold, Anna (Frontiers in Psychology, 2023)
Professionals do not always learn from their errors; rather, the way in which professionals experience errors and their work environment may not foster, but can rather inhibit error learning. In the wake of a series of accounting scandals, including Royal Ahold in the Netherlands, Lehman Brothers in the US, and Wirecard in Germany, within the context of financial auditing, we explore four audit-specific conditions at the workplace that could be negatively associated with learning: small error consequences, routine-type errors, negative emotions, and high time pressure. Then, we examine how perceptions of an open or blame error management climate (EMC) moderate the negative relationship between the four work conditions and learning from errors. Using an experiential questionnaire approach, we analyze data provided by 141 Dutch auditors across all hierarchical ranks from two audit firms. Our results show that open EMC perceptions mitigate the negative relationship between negative error emotions and error learning, as well as the negative relationship between high time pressure and error learning. While we expected that blame EMC perceptions would exacerbate the negative relationship between negative emotions and error learning, we find a mitigating effect of low blame EMC perceptions. Further, and contrary to our expectations, we find that blame EMC perceptions mitigate the negative relationship between small error consequences and error learning, so that overall, more error learning takes place regardless of consequences when participants experience a blame EMC. Post-hoc analyses reveal that there is in fact an inverted-U-shaped relationship between time pressure and error learning. We derive several recommendations for future research, and our findings generate specific implications on how (audit) organizations can foster learning from errors.