Information technology acceptance by individual professionals: a model comparison approach
Abstract
The proliferation of innovative and exciting information technology applications that target individual “professionals” has made the examination or re‐examination of existing technology acceptance theories and models in a “professional” setting increasingly important. The current research represents a conceptual replication of several previous model comparison studies. The particular models under investigation are the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and a decomposed TPB model, potentially adequate in the targeted healthcare professional setting. These models are empirically examined and compared, using the responses to a survey on telemedicine technology acceptance collected from more than 400 physicians practicing in public tertiary hospitals in Hong Kong. Results of the study highlight several plausible limitations of TAM and TPB in explaining or predicting technology acceptance by individual professionals. In addition, findings from the study also suggest that instruments that have been developed and repeatedly tested in previous studies involving end users and business managers in ordinary business settings may not be equally valid in a professional setting. Several implications for technology acceptance/adoption research and technology management practices are discussed.
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Some reviewed studies compared TAM to another model, such as TPB.
“Sometimes, the researchers compared TAM to another model, for example, TPB [48, 102].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [48]
Variables related to compatibility between health IT and clinical work processes were commonly added in the reviewed studies.
“For example, the common addition of variables related to compatibility between the health IT and clinical work processes in the reviewed studies [48, 49, 98, 103, 105, 106, 109] is in line with growing interest in the concept of “fit” as a critical need for successful IT design [131, 132], especially in health care [21, 28, 57, 62, 72, 100, 133-135].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [48]
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- Authors
- Chau, P. Y. K., & Hu, P. J.
- Affiliations
- University of Hong Kong (HK)
- University of Utah (US)
- Corresponding author
- Chau, Patrick Y. K.
- Hu, Paul Jen‐Hwa
- Venue
- Decision Sciences
- Publisher
- Wiley
- Published
- 2001-12
- Volume
- 32
- Issue
- 4
- Pages
- 699-719
- ISSN
- 0011-7315 (ISSN-L)
- 1540-5915
- OpenAlex
- W2078518420
- Cited by
- 1,409
- References
- 50
- Citations by year
- 2026: 19 · 2025: 33 · 2024: 55 · 2023: 61 · 2022: 63 · 2021: 74 · 2020: 66 · 2019: 70 · 2018: 84 · 2017: 67 · 2016: 70 · 2015: 82 · 2014: 98 · 2013: 78 · 2012: 81
- FWCI
- 31.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Decision Sciences (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
- Keywords
- technology acceptance, technology acceptance model, theory of planned behavior, model comparison, telemedicine, physicians, healthcare workers, technology adoption, conceptual replication
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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