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

accuracy issues more directly. Moreover, this research attracts a great deal of attention because of what many take to be its dismal implications for the accuracy of human social reasoning. These implications are illusory, however, because an error is not the same thing as a "mistake. " An error is a judgment of an experimental stimulus that departs from a model of the judgment process. If this model is normative, then the error can be said to represent an incorrect judgment. A mistake, by contrast, is an incorrect judgment of a real-world stimulus and therefore more difficult to determine. Although errors can be highly informative about the process of judgment in general, they are not necessarily relevant to the content or accuracy of particular judgments, because errors in a laboratory may not be mistakes with respect to a broader, more realistic frame of reference and the processes that produce such errors might lead to correct decisions and adaptive outcomes in real life. Several examples are described in this article. Accuracy issues cannot be addressed by research that concentrates on demonstrating error in relation to artificial stimuli, but only by research that uses external, realistic criteria for accuracy. These criteria might include the degree to which judgments agree with each other and yield valid predictions of behavior. The accuracy of human social judgment is a topic of obvious

Even though intuition is recognized as imperative in strategic thinking management literature is surprisingly silent on the issue. This inquiry thus provides an historical and hermeneutic review of philosophical, psychological and management theory on intuition. It reveals that philosophers conceive intuition as rational while psychologists tend not to. Philosophers do so primarily because intuition is anchored in Ideas, Forms and Archetypes, which are perceived as a priori laws governing and conditioning all existence. The argument is that intuition is the ontological foundation for any normative theory of rationality. Implications for the rationality debate are discussed. Three levels of intuition are discerned and contrasted with analytical thinking. The first and second levels correspond to intuitions from the personal and collective unconscious experience respectively. They can be either introverted or extraverted. The third level corresponds to what some philosophers call the non-dual, integral state of mind. An empirical study including personal interviews with 105 Norwegian top managers indicate that in strategic thinking more emphasis is put on intuition than analysis, especially in exploration of new terrain and technology. They define intuition primarily in accordance with level one. In describing its key features they focus on foresight, new ideas and synthesis. Finally Myers Briggs Type Indicator ® was applied, revealing that they have a strong personality preference for intuition.

The construct of self is indispensable to psychology. Research on the self has increased threefold in the past 30 years, far exceeding the growth rate of published research in psychology as a whole (Tesser, 2000). It is astounding to realize that one out of seven recently published articles in psychology examined aspects of the self. This figure is even more impressive in light of the fact that it does not include research on the construct of "Identity. " The timely publication of this volume reflects this impressive growth and affirms the centrality of the construct of self (and identity) for psychology and, indeed, for all the social sciences. The contributions in this volume document the pivotal role of the self in human functioning, both within psychology (e.g., social and personality, developmental, clinical, cognitive, comparative) and within other social science disciplines (e.g., sociology, anthropology). This chapter complements these contributions by taking an evolutionary perspective on the self. We conceptualize the self as an evolutionary adaptation. We explore ideas concerning the temporal ori

Psychologists have responded to the inadequacies that Mischel (1968) noted in the trait approach to personality by exploring two other facets of personality, cross-situational consistency and self-schemata. These newer approaches have yet to be clearly distinguished conceptually or empirically from the traditional model that they were designed to supplement or replace. Our research tries to do this. In it, two samples of respondents (N = 362) rated the extent to which, of 10 traits applied to them (overall level), rated their consistency on these traits (crosssituational consistency), and rated the importance of these traits to their view of themselves (self-schema). Correlational analyses show that the measures of consistency and self-schema lack discriminant validity from the measures of overall level. Specifically, their correlations with level were as high as their internal consistencies. We argue that the measurement models for cross-situational consistency and for self-schemata do not adequately reflect their theoretical counterparts. This failure undercuts the interpretations of recent research by Markus (1977), Markus, Crane, Bernstein, and Siladi (1982), and S. Bern (1981).

Extensions of latent state-trait models for continuous observed variables to mixture latent state-trait models with and without covariates of change are presented which can separate individuals differing in their occasion-specific variability. The basic model equations are given and the necessary and theoretical meaningful restrictions that must be made to apply the models are elaborated. An empirical application to the repeated measurement of mood states (N = 501) revealed that a model with two latent classes fits the data well. The larger class (76 %) consists of individuals whose mood is highly variable, whose general well-being is comparatively lower, and whose mood variability is influenced by daily hassles and uplifts. The smaller class (24 %) represents individuals that are rather stable, happier, and whose mood is only influenced by daily uplifts but not by daily hassles. The second class can be interpreted as a class of resilient individuals. A simulation study on the model without covariates with five sets of sample sizes (125, 250, 500, 1,000, and 2,000) and five sets of number of occasions (2, 3, 4, 5, and 6 occasions of measurement) revealed that the appropriateness of the parameter estimates of this model depends on number of observations (the higher the better) and the number of occasions (the higher the better). The parameters of the model without covariates can be appropriately estimated with at least 4 occasions and 250 individuals. Another simulation study estimated type I and II errors of the Lo-Mendell-Rubin test. This simulation study shows that the type I error is close to its expected value and the type II error is very low for a sample size of 500 observations. A simulation study with the same 5 sets of sample sizes showed that, for the model with covariates of change, 1,000 observations are necessary for all parameters to be precisely estimated. Mixture Distribution Latent State-Trait Analysis: Basic Ideas and Applications Over the last few years a variety of models for analyzing change have been developed

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