* * Authors listed randomly to denote equal contribution. The authors gratefully acknowledge the very helpful comments of the editor, associate editor and anonymous reviewers of MISQ. cbimisq93,cbimisq93/2-23-93 This paper employs data from 260 public managers to assess two broad images of the potential of information technology and computer-based information (CBI) to serve public managers: the "knowledge executive " and the "CBI consumer. " The data were collected as part

The ability to predict IT usage behavior has been an important area of inquiry in IS research for many years. Yet, to date, the predominant approach has been on the conscious cognitive aspect of this behavior. Consequently, the primary focus has been on the formation of intentions and its impact on the subsequent behavior of IT usage almost to the exclusion of other factors. The purpose of this study is to highlight an alternative viewpoint that suggests the equally important role of the automatic response known as habit. Applying theories of human behavior, we developed a model that shows the impact of both intentions and habit on IT usage. More importantly, we demonstrate that the influence of intention on usage will vary depending on the level of one’s habit. This finding implies that there can be situations where intention will, in fact, have no impact on behavior and that further research is needed to understand these conditions and the factors that lead to such situations. 1.

The recent introduction of a spate of data access applications, such as OLAP and data mining tools, has led to an increased interest on the part of both scholars and practitioners on how best to use and benefit from these tools. This paper reports on six exploratory case studies involving eight decision-makers and seven endusers. A process model based on the Value Chain is proposed and explained. Results show that database usage and information processing practices have indeed grown more sophisticated. Implications for practice and future research aimed at testing the Value Chain model are proposed.

Although the system usage construct has a central place in information systems (IS) research, there has been little discussion to date about how it should be measured. Usage is most commonly measured by selfreported questionnaire data, and, on occasion, interview reports, computer logs, or independent observation. Some researchers have found that the relationship between usage and other constructs differs depending on its method of measurement. Consequently, there is a need to determine how to obtain ‘true’ measures. The objective of this paper is to present a framework for measuring systems use. Specifically, the paper distinguishes two components of systematic variance—common methods bias and distance bias. These can lead to inaccurate measures of usage and inaccurate measures of its relationships with other constructs. The paper then presents an approach to minimizing these two sources of systematic bias and operationalizes this approach in the context of studying the relationship between usage and performance.

Recently, researchers in IS have begun to rely on the theories of innovation diffusion to study implementation problems. A major focus of these studies has been how potential users ’ perceptions of the information technology (IT) innovation influence its adoption. User acceptance of IT has been a primary focus in the MIS implementation research for the past decade. Why do users accept or reject information systems? How user acceptance is affected by system characteristics, perceived usefulness, perceived ease of use, and attitude toward acceptance behavior? The present research addresses these questions. The technology acceptance model (TAM) is used as a base model to produce a causal model resembling a network of relationships among the study’s constructs. A field study of 324 users regarding an end-user system was conducted to validate measures used to operationalize model variables and to test the hypothesized network of relationships. Partial Least Squares (PLS) is a second-generation multivariate analysis technique was used to estimate the parameters of the proposed causal model. The study findings indicate that system features variable has the largest influence on IT acceptance, followed by perceived usefulness. Both constructs have significant direct effects on IT acceptance but also exhibit their indirect effects through perceptions and/or attitude towards acceptance. Ease of use and attitude towards acceptance were found to have an equivalent influence on IT acceptance. Suggestions for future research and implications of findings are discussed.

The purpose of this study is to investigate the evolving relationship between intention and information systems usage over time. Our main argument is that as individuals get into the habit of continuously using a system, the predictive power of intention will be diluted. Consequently, the more usage is performed out of habit, the less cognitive planning is involved. The research model is tested in a longitudinal setting and the results present strong support to the hypotheses. The moderating effect of habit on the relationship between intention and usage increases over time, while the impact of intention on IS continued usage weakens over time. In addition, prior behavior is found to have a strong and significant effect on continued usage. The implications of this study are noteworthy for both researchers and practitioners.

This study develops and tests an integrated model that explains information systems usage at adoption and post-adoption stages. Integrating the theory of planned behavior with the IS continuance model, this research provides insights into the complementary nature of the two theories in explaining IS usage over time. In addition, the integrated model takes into consideration the “habit ” construct in order to better explain the automatic nature of IS continuance. The integrated model is tested in a longitudinal setting. Results present strong support for the existing theoretical links of the theory of planned behavior and IS continuance model, as well as for those newly hypothesized in this study. Initial usage indicates significant affect IS continuance usage, and habit posits a significant moderating impact on the relationship between IS continuance intention and IS continuance usage. The dynamic interrelationship between acceptance and continuance decision and the variability of determinants of IS usage across different adoption stages are demonstrated. The implications