Empirical research is an important methodology for the study of conceptual modeling practices. The recently published article "Representing Part-Whole Relations in Conceptual Modeling: An Empirical Evaluation" (Shanks et al. 2008) uses the lens of ontology to study a relatively sophisticated aspect of conceptual modeling practice, the representation of aggregation and composition. It contends that some analysts argue that a composite should be represented as a relationship while others argue that a composite should be represented as an entity. We find no evidence of such a dispute in the data modeling literature. We observe that composites are objects. By definition, all object-types should be represented as entities. Therefore, using the relationship construct to represent composites should not be seen as a viable alternative. Additionally, we found significant conceptual and methodological issues within the study that call its conclusions into question. As a way to offer insight into the requisite methodological procedures for research in this area, we conducted two experiments that both explicate and address the issues raised. Our results call into question the utility of using ontology as a foundation for conceptual modeling practice. Furthermore, they suggest a contrary but at least equally plausible explanation for the results reported by Shanks et al. In conducting this work we hope to encourage dialogue that will be beneficial for future endeavors aimed at identifying, developing, and evaluating appropriate foundations for the discipline of conceptual modeling.
Ad hoc query formulation is an important task in effectively utilizing organizational data resources. To facilitate this task, managers and casual end-users are commonly presented with database views expressly constructed for their use. Differences in the way in which things, states, and events are represented in such views can affect a user's ability to understand the database, potentially leading to different levels of performance (i.e., accuracy, confidence, and prediction of the accuracy of their queries). An experiment was conducted over the Internet involving 342 subjects from 6 universities in North America and Europe to investigate these effects. When presented with an event-based view, subjects expressing low or very low comfort levels in reading entity-relationship diagrams expressed confidence that better predicted query accuracy although there were no significant differences in actual query accuracy or level of confidence expressed.
Despite their potential to significantly reduce transaction costs for both buyers and sellers, e-marketplaces have struggled. Recent literature has examined the value propositions of e-marketplaces and proposed conceptual frameworks for their analysis. In this research, we move beyond conceptual analysis by developing a game-theoretic model of return on-investment (ROI)-driven e-marketplace participation growth. This model provides insights into expected e-marketplace growth and participation, and can be used to determine both the viability and expected long-run size of a given e-marketplace. Our results indicate that the pricing policy of the e-market-place intermediary can affect the rate at which participation grows and, therefore, sentiment about its prospects. We focus on e-marketplaces that add value to buyers and sellers by increasing the efficiency of administrative tasks but also simultaneously add value to buyers and reduce value to sellers by lowering prices for goods purchased. Value to participants in these e-marketplaces is determined by the volume of transactions that can be conducted using the e-marketplace, resulting in a two-sided network effect-buyers reacting to sellers and sellers reacting to buyers. The game-theoretic model identifies an e marketplace equilibrium at which participation growth is predicted to stop.
Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioral science paradigm seeks to develop and verify theories that explain or predict human or organizational capabilities by creating new and innovative artifacts. Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology. Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research. In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact. Three recent exemplars in the research literature are used to demonstrate the application of these guidelines. We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community.
Successful use of a computerized database by end users requires both an understanding of the structure of the database and knowledge of the available query language. Previous research has focused almost exclusively on query languages with little concern for how database structure is represented. This paper reports on an experiment that explores the influence of database structure representation on the ability of users to learn and use a database system. Four alternative representations of the same databases are developed and compared. These representations differ in semantics, symbols, and means of representing relationships. Interestingly, representation features that aid in communicating the contents of a database appear to hinder the learning of the SQL query language. We conclude that database representation is an important factor in database use and that the interaction between a database structure representation and a query language may dramatically affect database leaning and use.
While information is recognized as an important corporate resource, its management has not been accomplished to the extent of other major resources. A major reason for this condition is that the information resource is not as well defined as other resources. To manage any resource effectively, the nature of that resource must be well defined. In this article, we first propose a model for corporate data. This model represents the data definition or "metadata" for Information Resource Management (IRM). Through this metadata we define the "state" of the information resource. We characterize a set of dimensions for metadata and discuss its representation and management. Concepts from Information Resource Dictionary Systems (IRDS) are described as they support metadata management. We include IRDS contents, capabilities, and implementation issues. Finally, we assess the diverse impacts of metadata management on related Information System (IS) issues such as end-user computing, corporate is planning, information architecture development, and information system development.