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

Any opinions expressed here are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but the institute itself takes no institutional policy positions. The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post World Net. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. IZA Discussion Paper No. 3333

Computer skills are key to organizational performance, and past research indicates that behavior modeling is a highly effective form of computer skill training.The present research develops and tests a new theoretical model of the underlying observational learning processes by which modeling-based training interventions influence computer task performance.Observational learning processes are represented as a second-order construct with four dimensions (attention, retention, production, and motivation).New measures for these dimensions were developed and shown to have strong psychometric properties.The proposed model controls for two pretraining individual differences (motivation to learn and self-efficacy) and specifies the relationships among three training outcomes (declarative knowledge, post-training self-efficacy, and task performance).The model was tested using PLS on data from an experiment (N = 95) on computer spreadsheet training.As hypothesized, observational learning processes significantly influenced training outcomes. A representative modeling-based training intervention (retention enhancement) significantly improved task performance through its specific effects on the retention processes dimension of observational learning.The new model provides a more complete theoretical account of the mechanisms by which modeling-based interventions affect training outcomes, which should enable future research to systematically evaluate the effectiveness of a wide range of modeling-based training interventions.Further, the new instruments can be used by practitioners to refine ongoing training programs.

In this paper, we uncover a new potential application for multi-media technologies: affective intelligent car interfaces for enhanced driving safety. We also describe the experiment we conducted in order to map certain physiological signals (galvanic skin response, heart beat, and temperature) to certain driving-related emotions and states (Frustration/Anger, Panic/Fear, and Boredom/Sleepiness). We demonstrate the results we obtained and describe how we use these results to facilitate a more natural Human-Computer Interaction in our Multimodal Affective Car Interface for the drivers of the future cars. 1

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Abstract. The design of workplaces, namely the physical arrangement of people and machines, has an active influence on work-related issues, such as productivity and efficiency. However, even an ideal physical arrangement of machines is subject to the social and emotional intelligence of the people. It is possible to formalise the former using rules of social order, and to capture the latter using the ideas from Affective Computing. Our intention, then, is to demonstrate that by integrating affective states and participatory/pervasive adaptation of social norms in workplace design, the quality of experience in a working environment can be improved. 1

Information behavior is an important topic area for the future Internet, Information Systems developers, and the information research community. This article shows two main factors of information behavior—information motivation and information capability—and its relationship to job performance based on the literature review of psychology, management, IS, and IT training fields. This article reviews the wide range of literature on the information behavior, provides the summarized tables of literature, and proposes the future research framework based on the literature review.

Information behavior is an important topic area for the future Internet, Information Systems developers, and the information research community. This article shows two main factors of information behavior—information motivation and information capability—and its relationship to job performance based on the literature review of psychology, management, IS, and IT training fields. This article reviews the wide range of literature on the information behavior, provides the summarized tables of literature, and proposes the future research framework based on the literature

needed. Please do not return it to the U.S. Army Research Institute for the Behavioral and Social Sciences.