Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation.We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist.To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliarapplication domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.
Recent research has presented a conceptualization, metric, and instrument based on Microsoft Usability Guidelines (MUG; see Agarwal and Venkatesh 2002). In this paper, we use MUG to further our understanding of web and wireless site use. We conducted two empirical studies among over 1,000 participants. In study 1, conducted in both the United States and Finland, we establish the generalizability of the MUG conceptualization, metric, and associated instrument from the United States to Finland. In study 2, which involved longitudinal data collection in Finland, we delved into an examination of differences in factors important in determining web versus wireless site usability. Also, in study 2, based on a follow-up survey about site use conducted 3 months after the initial survey, we found support for a model of site use that employs the MUG categories and subcategories as predictors. The MUG-based model outperformed the widely employed technology acceptance model both in terms of richness and variance explained (about 70 percent compared to 50 percent).
Throughout its history, the information systems (IS) discipline has engaged in extensive self-examination, particularly with regard to its apparent diversity. Our overall objective in this study is to better understand the diversity in IS research, and the extent to which diversity is universal across journals that publish IS research. We developed a classification system that comprises five key characteristics of diversity (reference discipline, level of analysis, topic, research approach, and research method) based on a review of prior literature. We then examined articles over a five-year period, from 1995 to 1999, in five journals acknowledged as the top journals of the field, at least in North America. Analyses reveal considerable diversity in each of the key characteristics. Perhaps not surprisingly, the research approach used is more focused with most studies being conducted using hypothetico-deductive approaches, whereas reference discipline is perhaps the most diverse of the characteristics examined. An interesting finding is that IS itself emerged as a key reference discipline in the late 1990s. The 'Journal of Management Information Systems' and 'Information Systems Research' publish articles displaying the greatest diversity, and 'MIS Quarterly' and 'Decision Sciences' publish articles that focus on subsets of the field. Our research provides a foundation for addressing the direction that diversity in the IS discipline takes over time. In the shorter term, researchers can use our classification system as a guide to writing abstracts and selecting key words, and the findings of our journal analyses to determine the best outlet for their type of research.