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 R 2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar

The growing interest in Structured Equation Modeling (SEM) techniques and recognition of their importance in IS research suggests the need to compare and contrast different types of SEM techniques so that research designs can be appropriately selected. After assessing the extent to which these techniques are currently being used in IS research, the article presents a running example which analyzes the same dataset via three very different statistical techniques. It then compares two classes of SEM: covariance-based SEM and partial-least-squares-based SEM. Finally, the article discusses linear regression models and offers guidelines as to when SEM techniques and when regression techniques should be used. The article concludes with heuristics and rule of thumb thresholds to guide practice, and a discussion of the extent to which practice is in accord with these guidelines.

Introduction The task of deciding when and how to innovate is not an easy one. Consider the following managerial quandaries: . A CIO has joined a firm that lags in the adoption of emerging information technologies. He wonders: just how innovative should this firm be going forward, and what can be done to position it to be more willing and able to assume the challenge of early adoption? . A VP of marketing resides in a firm that generally leads in IT innovation, and must decide whether to endorse the immediate adoption of a particular innovation with major implications for marketing strategy. She wonders: are her firm's needs in this area and "readiness" to adopt sufficient to justify taking the lead with this specific innovation? If so, how should the assimilation process be managed? . A product manager must design a deployment strategy for an innovative software development tool. He wonders: how fast can this technology diffu

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The Internet has grown at a remarkable pace since the emergence of the World-Wide Web in the early 1990s. While electronic commerce (e-Commerce) has become an important issue with the growth of the Internet, there has been insufficient empirical research concerning its adoption by Internet users. In this paper, we propose the e-Commerce Adoption Model (e-CAM), which attempts to examine important factors that predict a consumer’s online purchasing behavior. e-CAM integrates the technology acceptance model with the theories of perceived risk to explain the adoption of e-Commerce. Specifically, we examine the impact of the following factors on the consumer’s purchasing behavior: perceived ease of use, perceived usefulness, perceived risk with products/services, and perceived risk in the context of online transaction. We test the e-CAM model using the structural equation modeling technique. Most of the causal relationships between the constructs postulated by our model are well supported, accounting for 33.4 percent of the total variance in e-Commerce adoption. In sum, our study finds that all of the antecedent constructs directly and/or indirectly affect the consumer’s adoption of e-Commerce. Therefore, the findings suggest that firms providing products/services through e-Commerce should consider these contextual factors in order to facilitate consumers ’ adoption behavior.

This study employs a novel method of Web content extraction and analysis to investigate the evolving competitive landscape in an important business-to-consumer (B2C) area: travel and tourism. Findings from a comprehensive Web mining endeavor and a supplier survey shed light on the effectiveness of tourism Web sites. Important dimensions of the automated measurement are ease of navigation, interactive elements such as reservation and booking features, volume of textual and graphical information, number of available languages, and the textual diversity of documents. Precise textual information and interactive features are crucial to the success of a hotel Web site, measured in terms of tourists ’ awareness, electronic inquiries, and online bookings. The article discusses differences between four European destinations and the implications of benchmarks for Web site management. Key words: Content mining; Web site evaluation; Technology acceptance model

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.

During the last decade, Information Technology (IT) has been the primary force driving the transformation of roles in the education industry. More specifically, the World Wide Web (WWW) and associated technologies provided a new playground with new rules and tools to conduct instruction and create novel approaches to learning. We have seen the application of IT in education in the form of CD-ROMs. With the evolution of the WWW we saw education marketed as long distance learning, web based learner centered environments, internet based learning environments, and self instructed learning. With all the different models used on the web, few have studied their acceptance and their effectiveness on learning. Many educational institutions today have embarked in the development of web based courses. However, they face enormous difficulty in achieving successful strategies including the delivery, effectiveness, and acceptance of the courses. This is mainly due to the fact that the problem of developing a successful web based course involves multiple inter-related dimensions ranging from technology related issues to pedagogical considerations. Davis (1989) proposed a Technology Assessment Model (TAM) to explain user acceptance of technology. The TAM identifies ‘perceived usefulness ’ and ‘perceived ease-of-use ’ as the antecedents to ‘behavioral intentions ’ to use a technology. Extensive attention in previous TAM research dealt with business

Theoretical and empirical research on technology acceptance, while acknowledging the importance of individual beliefs about the compatibility of a technology, has produced equivocal results. This study focuses on further theoretical and empirical development of this important belief in technology acceptance. Specifically, unlike prior research which has examined only one aspect of compatibility, we provide a more comprehensive conceptual definition that views compatibility as a multi-dimensional construct. Based on the conceptual definition of compatibility, we develop operational measures of the multiple dimensions of compatibility. The model is tested using the World Wide Web (WWW) as the target innovation. Scale validation indicates that the operational measures of compatibility developed in this study have acceptable psychometric properties and confirmatory factor analysis supports the multi-dimensional structure of this construct. We then assess the nomological validity of this construct by situating it within the Technology Acceptance Model. In contrast to prior research which has regarded beliefs of compatibility as an independent antecedent of attitude, we posit causal linkages among the three beliefs of compatibility, usefulness, and ease of use. Results largely support the theorized relationships. 1 ON THE MULTI-DIMENSIONAL NATURE OF COMPATIBILITY

date vii AFIT/GIR/ENV/05D-01 Information security is an issue that has increased greatly in importance to both industry executives as well as military leadership over the past decade. In this time both practitioner and academic circles have researched and developed practices and process to more effectively handle information security. Even with growth in these areas there has been almost no research conducted into how decision makers actually behave. This is problematic because information security decision makers in the Department of Defense have been observed exhibiting risk seeking behavior when making information security decisions that seemingly violate accepted norms. There are presently no models in the literature that provide sufficient insight into this phenomenon. This study used Prospect Theory, developed by Kahneman and Tversky, as a