International Journal of Accounting Information Systems 1 (2000) 79–87 1467-0895/00/$ – see front matter © 2000 Elsevier Science Inc. All rights reserved. PII: S1467-0895(00)00004-X Perceived semantic expressiveness of accounting systems and task accuracy effects Cheryl L. Dunn a, *, Severin V. Grabski b a Department of Accounting, Florida State University, Tallahassee, FL 32306-1110 USA b Department of Accounting, Michigan State University East Lansing, MI 48824-1121 USA Abstract Semantic expressiveness refers to how well a model reflects the underlying reality the model represents. Prior research has claimed the REA (Resources-Events-Agents) accounting model is more semantically expressive than is the traditional DCA (Debit-Credit-Account) accounting model. This research demonstrates experimentally that users perceive REA as more semantically expressive than DCA. This study also demonstrates that, control- ling for cognitive fit, accounting knowledge, and field dependence, higher perceived semantic expressiveness is associated with higher task accuracy. © 2000 Elsevier Science Inc. All rights reserved. Keywords: Semantic expressiveness; REA accounting model; DCA accounting model; Cognitive fit. 1. Semantic expressiveness Semantic expressiveness is a term that refers to how well a model reflects the underlying reality the model represents. Computer scientists have long ad- vocated the integration of semantics (real-world mean- ing) into data models and into technologies centered on those models (e.g., Abrial, 1974; Brodie, 1984; Hammer and McLeod, 1981). In accounting, McCar- thy (1982) claimed that semantic expressiveness is an important advantage of the Resource-Event-Agent (REA) accounting model over the traditional Debit- Credit-Account (DCA) accounting model. Dunn and McCarthy (1997) reiterated McCarthy’s (1982) posi- tion that accounting systems that use real world busi- ness phenomena as primitives are more semantically expressive than are accounting systems that use dou- ble-entry artifacts as primitives. They identified ben- efits of a semantically expressive accounting system as including easier integration of accounting phe- nomena with descriptions of non-accounting phe- nomena, and a better understanding by users of the system. To our knowledge, no research has attempted to verify McCarthy’s claim that the REA model is more semantically expressive than the DCA account- ing model, nor have any studies attempted to link se- mantic expressiveness with task accuracy. Two ap- proaches can be taken to evaluate the semantic expressiveness of alternative accounting models. One approach is to identify as many features of the under- lying reality as possible, and then to determine which of those features can be captured by and represented in each of the alternative accounting models. Such an approach (which could be referred to as an ontologi- cal approach) assumes that each and every user will agree on the underlying reality and the representa- tional model, and will interpret the model in exactly the same manner. This approach ignores perceptions of users as to how well the model helps them to un- derstand the underlying reality. A second approach is to assume that the degree of semantic expressiveness of a model (or a system based on the model) is indi- cated by user perceptions as to how well the model represents the underlying reality. This study takes the latter approach, having users of systems based on * Corresponding Author. Tel.: 1-850-644-7878. E-mail: cdunn@cob.fsu.edu