The DOI matches its Crossref record; 139 of the 141 references it cites were found in a registry or an index.
Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model
Open accessAbstract
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.
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“Further, previous research (Venkatesh 2000) has shown that ANX is a conceptually and empirically distinct construct.”
From Understanding the determinants of novel technology adoption among teachers: the case of 3D printing (2020) · cites this paper as Venkatesh 2000
In the citing paper
“enjoyment (Venkatesh 2000)”
From Emotional Manipulation by AI Companions (2025) · cites this paper as Venkatesh 2000
In the citing paper
“The tradition of adding variables is common in research on TAM [51, 136, 137] and on more general theories of human behavior [138, 139].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [137]
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Self-citation
Metadata
- Authors
- Venkatesh, V.
- Affiliations
- University of Maryland, College Park (US)
- Corresponding author
- Venkatesh, Viswanath
- ORCID
- Venkatesh, Viswanath
- Venue
- Information Systems Research
- Published
- 2000-12
- Volume
- 11
- Issue
- 4
- Pages
- 342-365
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2166982098
- Cited by
- 6,664
- References
- 141
- Citations by year
- 2026: 229 · 2025: 337 · 2024: 343 · 2023: 418 · 2022: 464 · 2021: 439 · 2020: 344 · 2019: 361 · 2018: 299 · 2017: 297 · 2016: 345 · 2015: 342 · 2014: 365 · 2013: 327 · 2012: 302
- FWCI
- 117.58
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Information Systems Research (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- perceived ease of use, technology acceptance model, anchoring and adjustment, computer self-efficacy, facilitating conditions, intrinsic motivation, computer playfulness, computer anxiety, emotions, perceived enjoyment, user acceptance, employee technology use
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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