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

The present research develops and tests a theoretical extension of the Technology Acceptance Model (TAM) that explains perceived usefulness and usage intentions in terms of social influence and cognitive instrumental processes. The extended model, referred to as TAM2, was tested using longitudinal data collected regarding four different systems at four organizations ( N = 156), two involving voluntary usage and two involving mandatory usage. Model constructs were measured at three points in time at each organization: preimplementation, one month postimplementation, and three months postimplementation. The extended model was strongly supported for all four organizations at all three points of measurement, accounting for 40%--60% of the variance in usefulness perceptions and 34%--52% of the variance in usage intentions. Both social influence processes (subjective norm, voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use) significantly influenced user acceptance. These findings advance theory and contribute to the foundation for future research aimed at improving our understanding of user adoption behavior.

https://www.jstor.org/stable/pdfplus/2634758.pdf

A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies

The Technology Acceptance Model and two variations of the Theory of Planned Behavior were compared to assess which model best helps to understand usage of information technology. The models were compared using student data collected from 786 potential users of a computer resource center. Behavior data was based on monitoring 3,780 visits to the resource center over a 12-week period. Weighted least squares estimation revealed that all three models performed well in terms of fit and were roughly equivalent in terms of their ability to explain behavior. Decomposing the belief structures in the Theory of Planned Behavior provided a moderate increase in the explanation of behavioral intention. Overall, the results indicate that the decomposed Theory of Planned Behavior provides a fuller understanding of behavioral intention by focusing on the factors that are likely to influence systems use through the application of both design and implementation strategies.

Understanding Information Technology Usage: A Test of Competing Models

Much previous research has established that perceived ease of use is an important factor influencing user acceptance and usage behavior of information technologies. However, very little research has been conducted to understand how that perception forms and changes over time. The current work presents and tests an anchoring and adjustment-based theoretical model of the determinants of system-specific perceived ease of use. The model proposes control (internal and external--conceptualized as computer self-efficacy and facilitating conditions, respectively), intrinsic motivation (conceptualized as computer playfulness), and emotion (conceptualized as computer anxiety) as anchors that determine early perceptions about the ease of use of a new system. With increasing experience, it is expected that system-specific perceived ease of use, while still anchored to the general beliefs regarding computers and computer use, will adjust to reflect objective usability, perceptions of external control specific to the new system environment, and system-specific perceived enjoyment. The proposed model was tested in three different organizations among 246 employees using three measurements taken over a three-month period. The proposed model was strongly supported at all points of measurement, and explained up to 60% of the variance in system-specific perceived ease of use, which is twice as much as our current understanding. Important theoretical and practical implications of these findings are discussed.

/pdf/determinants-of-perceived-ease-of-use-integrating-control-10opxseq0g.pdf

Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model

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 selected appropriately. 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-squaresbased 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.

/pdf/structural-equation-modeling-and-regression-guidelines-for-2y96bdeejv.pdf

Structural equation modeling and regression: guidelines for research practice

This paper reports on the development of an instrument designed to measure the various perceptions that an individual may have of adopting an information technology IT innovation. This instrument is intended to be a tool for the study of the initial adoption and eventual diffusion of IT innovations within organizations. While the adoption of information technologies by individuals and organizations has been an area of substantial research interest since the early days of computerization, research efforts to date have led to mixed and inconclusive outcomes. The lack of a theoretical foundation for such research and inadequate definition and measurement of constructs have been identified as major causes for such outcomes. In a recent study examining the diffusion of new end-user IT, we decided to focus on measuring the potential adopters' perceptions of the technology. Measuring such perceptions has been termed a "classic issue" in the innovation diffusion literature, and a key to integrating the various findings of diffusion research. The perceptions of adopting were initially based on the five characteristics of innovations derived by Rogers 1983 from the diffusion of innovations literature, plus two developed specifically within this study. Of the existing scales for measuring these characteristics, very few had the requisite levels of validity and reliability. For this study, both newly created and existing items were placed in a common pool and subjected to four rounds of sorting by judges to establish which items should be in the various scales. The objective was to verify the convergent and discriminant validity of the scales by examining how the items were sorted into various construct categories. Analysis of inter-judge agreement about item placement identified both bad items as well as weaknesses in some of the constructs' original definitions. These were subsequently redefined. Scales for the resulting constructs were subjected to three separate field tests. Following the final test, the scales all demonstrated acceptable levels of reliability. Their validity was further checked using factor analysis, as well as conducting discriminant analysis comparing responses between adopters and nonadopters of the innovation. The result is a parsimonious, 38-item instrument comprising eight scales which provides a useful tool for the study of the initial adoption and diffusion of innovations. A short, 25 item, version of the instrument is also suggested.

https://www.jstor.org/stable/pdf/23010883.pdf

Gary C. Moore

Papers

Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation