Understanding information technology usage: a test of competing models
Abstract
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.
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Employees' perceptions of organizational support, such as facilitating conditions or external control, lead to greater user acceptance of new systems.
“Prior research has suggested that employees' perceptions regarding organizational support-that is, facilitating conditions or perceptions of external control (Taylor & Todd, 1995;Venkatesh, 2000;Venkatesh et al., 2003)-will lead to greater user acceptance of new systems.”
From Technology Acceptance Model 3 and a Research Agenda on Interventions (2008) · cites this paper as Taylor & Todd, 1995
The fundamental assumption of the Theory of Reasoned Action is that users' beliefs influence their behavioral intentions, and these intentions, in turn, determine their actual behavior toward using a given technology.
“The fundamental assumption of the theory is that users’ beliefs influence their behavioral intentions, and these intentions, in turn, determine their actual behavior toward using a given technology (Taylor and Todd, 1995).”
From A two-step structural equation modeling and explainable machine learning framework for understanding university students’ adoption of generative AI: balancing intrinsic motivations and perceived risks (2026) · cites this paper as Taylor and Todd, 1995
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- Authors
- Taylor, S., & Todd, P. A.
- Affiliations
- Queen's University (CA)
- Venue
- Information Systems Research
- Published
- 1995-06
- Volume
- 6
- Issue
- 2
- Pages
- 144-176
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W1987198869
- Cited by
- 8,815
- References
- 52
- Citations by year
- 2026: 226 · 2025: 285 · 2024: 376 · 2023: 421 · 2022: 485 · 2021: 558 · 2020: 448 · 2019: 422 · 2018: 428 · 2017: 357 · 2016: 384 · 2015: 481 · 2014: 453 · 2013: 487 · 2012: 410
- FWCI
- 53.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Systems Research (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- information technology use, technology acceptance model, theory of planned behavior, behavioral intention, student users, belief structures, model comparison
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