Cheryl L. Dunn

The Research Pyramid: A Framework for Accounting Information Systems Research

This paper extends Sowas (1997) Meaning Triangle to develop a framework for accounting information systems (AIS) research—the Research Pyramid. This framework identifies relationships between objects in economic reality, peoples concepts of economic reality, symbols used to record and represent economic reality, and the resultant accounting information systems that capture and present data about economic reality. The Research Pyramid has two major uses. First, the paper illustrates how the Research Pyramid can be used to identify new research questions to extend existing research streams. To be used in this manner, existing AIS research is classified along each of the edges of the Research Pyramid. Once an area of the literature has been analyzed, the edges that have not been studied extensively reveal potential primitive mappings for future exploration. Second, each primitive mapping is evaluated to identify which of four research methodologies (design science, field studies, survey research, and labor...

Critical evaluation of conceptual data models

Abstract Conceptual data models are representations of enterprise databases. Information systems professionals must often critically evaluate conceptual models. After system designers create conceptual models, they or members of their design team corroborate the created models. System auditors also evaluate conceptual models. Little guidance exists to advise system designers and auditors on how to conduct such conceptual model validation. Mistakes in corroborating conceptual models may result in unnecessary changes to valid systems or in false assurance of invalid systems. Evidence from prior studies suggests that evaluators exhibit a cognitive bias that causes them to focus on structural constraints even when there is conflicting information in the surface semantics. Studies also show mixed results for whether relationships involving optional participation of entities are more difficult for users to comprehend than relationships with only mandatory participation. Decompositions of large representations may be easier to evaluate than are the large representations in their entirety. Because conceptual models often are portrayed as large representations that include relationships with optional participation of entities, these concerns must be investigated in the context of system evaluation. This study provides evidence of a debiasing technique for the tendency to focus only on structural constraints, and compares evaluation responses for entities’ optional and mandatory participation in relationships presented in decomposed versus full models.

Resources-Events-Agents Design Theory: A Revolutionary Approach to Enterprise System Design

Enterprise systems typically include constructs such as ledgers and journals with debit and credit entries as central pillars of the systems’ architecture due in part to accountants and auditors who demand those constructs. At best, structuring systems with such constructs as base objects results in the storing the same data at multiple levels of aggregation, which creates inefficiencies in the database. At worst, basing systems on such constructs destroys details that are unnecessary for accounting but that may facilitate decision making by other enterprise functional areas. McCarthy (1982) proposed the resources-events-agents (REA) framework as an alternative structure for a shared data environment more than thirty years ago, and scholars have further developed it such that it is now a robust design theory. Despite this legacy, the broad IS community has not widely researched REA. In this paper, we discuss REA’s genesis and primary constructs, provide a history of REA research, discuss REA’s impact on practice, and speculate as to what the future may hold for REA-based enterprise systems. We invite IS researchers to consider integrating REA constructs with other theories and various emerging technologies to help advance the future of information systems and business research.

Asymmetry in Identification of Multiplicity Errors in Conceptual Models of Business Processes

ABSTRACT Business rules can be represented by multiplicities in a Unified Modeling Language (UML) class diagram. Diagrams containing erroneous multiplicities may be implemented as an inefficient/ineffective database. System validators must be able to validate such diagrams, including multiplicities, to prevent the implementation of design errors. Prior research reveals conflicting evidence regarding the expected accuracy in validating minimum multiplicities, indicating a need for additional research to further our understanding. Ontology research claims that multiplicities that depict optional participation are ambiguous and lead to poorer understanding and accuracy compared to multiplicities that depict mandatory participation. However, other research has reported better accuracy validating multiplicities that depict optional participation compared to mandatory participation. We conducted an experiment to help resolve this apparent contradiction, and to explore whether any asymmetry exists in accuracy fo...