Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Technology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted R2 of 70 percent). UTAUT thus provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement of the core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use.

User acceptance of information technology: toward a unified view

Data Mining - Concepts and Techniques.

How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

The ability to detect and accurately estimate the strength of interaction effects are critical issues that are fundamental to social science research in general and IS research in particular. Within the IS discipline, a significant percentage of research has been devoted to examining the conditions and contexts under which relationships may vary, often under the general umbrella of contingency theory (cf. McKeen et al. 1994, Weill and Olson 1989). In our survey of such studies, the majority failed to either detect or provide an estimate of the effect size. In cases where effect sizes are estimated, the numbers are generally small. These results have led some researchers to question both the usefulness of contingency theory and the need to detect interaction effects (e.g., Weill and Olson 1989). This paper addresses this issue by providing a new latent variable modeling approach that can give more accurate estimates of interaction effects by accounting for the measurement error that attenuates the estimated relationships. The capacity of this approach at recovering true effects in comparison to summated regression is demonstrated in a Monte Carlo study that creates a simulated data set in which the underlying true effects are known. Analysis of a second, empirical data set is included to demonstrate the technique's use within IS theory. In this second analysis, substantial direct and interaction effects of enjoyment on electronic-mail adoption are shown to exist.

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A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study

Course Description In this course, we will explore the question of the actual and potential connections between democracy and education. Our focus of attention will be placed on a critical examination of democratic theory and its implications for the civic education roles and contributions of teachers, adult educators, community development practitioners, and community organizers. We will survey and deal critically with a range of competing conceptions of democracy, variously described as classical, republican, liberal, radical, marxist, neomarxist, pragmatist, feminist, populist, pluralist, postmodern, and/or participatory. Using narrative inquiry as a means for illuminating and interpreting contemporary practice, we will analyze the implications of different conceptions of democracy for the practical work of civic education.

Democracy and education.

The relationship between on-line communities and on-line brands is investigated by examining how on-line brand community's characteristics affect community commitment and brand loyalty-in particular, how the hosting type of an on-line brand community affects the relationships between characteristics and community commitment. A survey of 250 respondents revealed that their community commitment was significantly influenced by their community interaction and the rewards for their activities, but not by information quality and system quality. The analysis shows that the hosting type of a community has a significant moderating effect and that community commitment increases brand loyalty. Interpretations and implications of the findings, as well as future research directions, are discussed.

The Influence of On-Line Brand Community Characteristics on Community Commitment and Brand Loyalty

The importance of effective training in ensuring the success of end-user computing (EUC) has been emphasized by several researchers in information systems. A vast amount of evidence from research in related areas such as educational psychology suggests that individual differences, such as learning style, may affect users learning about a new EUC software package. This article reports the findings of a series of studies that examine the influence of a novice's learning style in learning typical EUC tools such as spreadsheets and electronic mail. A consistent pattern of findings emerges that indicates that learning modes is an important predictor of learning performance, both by itself and in interaction with training methods. The findings suggest that in the design of training, it is essential to match training methods to individual difference variables. Based on these findings, guidelines are recommended for IS professionals involved in EUC training and further research directions are discussed.

The importance of learning style in end-user training

This article describes a knowledge management (KM) success model that is derived from observations generated through a longitudinal study of KM in an engineering organization and KM success factors found in the literature, which were modified by the application of these observations and success factors in various projects. The DeLone and McLean (1992, 2003) IS Success Model was used as a framework for the model, since it was found to fit the observed success criteria and provided an accepted theoretical basis for the proposed model.

A Model of Knowledge Management Success

This article proposes a framework for assessing knowledge management system (KMS) success models. The framework uses three criteria: how well the model fits actual KMS success factors, the degree to which the model has a theoretical foundation, and if the model can be used for both types of KMSs. The framework is then applied to four KMS success models found in the literature and is determined to be a useful framework for assessing KMS success models.

Assessing Knowledge Management Success

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Lorne Olfman

Papers

The Influence of On-Line Brand Community Characteristics on Community Commitment and Brand Loyalty

The importance of learning style in end-user training

A Model of Knowledge Management Success

Assessing Knowledge Management Success

Designing Knowledge Management Systems for Teaching and Learning with Wiki Technology