An Investigation of Localization as an Element of Cognitive Fit in Accounting Model Representations

Abstract

Abstract Cognitive fit, a correspondence between task and data representation format, has been demonstrated to lead to superior task performance by individual users and has been posited as an explanation for performance differences among users of various problem representations such as tables, graphs, maps, and schematic faces. The current study extends cognitive fit to accounting models and integrates cognitive fit theory with the concept of localization to provide additional evidence for how cognitive fit works. Two accounting model representations are compared in this study, the traditional DCA (Debit‐Credit‐Account) accounting model and the REA (Resources‐Events‐Agents) accounting model. Results indicate that the localization of relevant objects or linkages is important in establishing cognitive fit.