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User Acceptance of Computer Technology: A Comparison of Two Theoretical Models

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TLDR
In this article, the authors address the ability to predict peoples' computer acceptance from a measure of their intentions, and explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables.
Abstract
Computer systems cannot improve organizational performance if they aren't used. Unfortunately, resistance to end-user systems by managers and professionals is a widespread problem. To better predict, explain, and increase user acceptance, we need to better understand why people accept or reject computers. This research addresses the ability to predict peoples' computer acceptance from a measure of their intentions, and the ability to explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables. In a longitudinal study of 107 users, intentions to use a specific system, measured after a one-hour introduction to the system, were correlated 0.35 with system use 14 weeks later. The intention-usage correlation was 0.63 at the end of this time period. Perceived usefulness strongly influenced peoples' intentions, explaining more than half of the variance in intentions at the end of 14 weeks. Perceived ease of use had a small but significant effect on intentions as well, although this effect subsided over time. Attitudes only partially mediated the effects of these beliefs on intentions. Subjective norms had no effect on intentions. These results suggest the possibility of simple but powerful models of the determinants of user acceptance, with practical value for evaluating systems and guiding managerial interventions aimed at reducing the problem of underutilized computer technology.

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Acceptance of Commercially Available Wearable Activity Trackers Among Adults Aged Over 50 and With Chronic Illness: A Mixed-Methods Evaluation

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The role of technology readiness in customers' perception and adoption of self‐service technologies

TL;DR: In this paper, the authors examined how technology readiness (TR) influences customers' perception and adoption of self-service technologies (SSTs) through development of an empirical model to explore the relationships among TR, perceived service quality, satisfaction and behavioral intentions toward SSTs.
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Individual differences and usage behavior: revisiting a technology acceptance model assumption

TL;DR: A study involved 106 professional and administrative staff in the IT division of a large manufacturing company who voluntarily use email and word processing and found that individual user differences have significant direct effects on both the frequency and volume of usage.
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Looking under the Bonnet: Factors Affecting Student Adoption of E-Learning Systems in Jordan

TL;DR: In this article, an extended version of the TAM (TAM) was developed to investigate the underlying factors that influence students' decisions to use an e-learning system and their relationships among these factors.
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Senior Citizens' Acceptance of Information Systems: A Study in the Context of e-Government Services

TL;DR: It is revealed that consistent with previous technology acceptance studies, senior citizens' use intention is driven by their perceived usefulness and perceived ease of use of the service, and their Internet safety perception impacts the acceptance of this online financial service.
References
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TL;DR: In this paper, the author explains "theory and reasoned action" model and then applies the model to various cases in attitude courses, such as self-defense and self-care.
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Self-efficacy mechanism in human agency

TL;DR: The centrality of the self-efficacy mechanism in human agency is discussed in this paper, where the influential role of perceived collective effi- cacy in social change is analyzed, as are the social con- ditions conducive to development of collective inefficacy.
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User Acceptance of Computer Technology: A Comparison of Two Theoretical Models?

This research compares two theoretical models to better understand why people accept or reject computers and increase user acceptance.