Systems thinking, mental representations, and unintended consequence identification.

摘要

Scholars and practitioners recently have asserted that systems thinking (ST)---the language, cognitive tool set, and perspectives that facilitate decision makers' mental representations of complex environments---improves accountants' thinking about causality (Bell, Peecher, and Solomon 2002). We have relatively little understanding, however, of how ST influences task performance or determinants of task performance. In this dissertation, I develop and experimentally test theory related to two research questions: (1) How does ST influence individuals' identification of potential consequences, and (2) How does ST interact with domain knowledge when individuals identify such consequences? I investigate these questions in domains involving redundant controls---multiple controls designed to prevent or mitigate the same negative outcome. I hypothesize that ST helps individuals develop mental representations that reflect less obvious control interactions and temporal changes in controls' causal relationships, thus increasing the likelihood that individuals identify redundant controls' potential unintended consequences. Experimental results suggest that ST components related to understanding circular causality facilitate identification of redundant controls' potential unintended consequences. Results also suggest that ST influences initial stages of information search---ST-trained participants were more likely to identify system structure information as necessary for task completion. In a second experiment, I investigate evolution of participants' mental representations in response to ST training. I find that ST-trained participants more likely incorporate circular causality in their mental representations of system causal structure, and hence, more likely identify unintended consequences.