Cited by 1,409Technology Adoption and User BehaviourTelemedicine and Telehealth ImplementationInformation Systems Theories and Implementation

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Information technology acceptance by individual professionals: a model comparison approach

Chau, Patrick Y. K., Hu, Paul Jen‐Hwa·2001·Decision Sciences

DOI 10.1111/j.1540-5915.2001.tb00978.x

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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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The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Untitled work
(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
From Intentions to Actions: A Theory of Planned Behavior
Ajzen, I. (1985) · Action Control · doi:10.1007/978-3-642-69746-3_2 · Cited by 19,057
Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Understanding information technology usage: a test of competing models
Taylor, S., & Todd, P. A. (1995) · Information Systems Research · doi:10.1287/isre.6.2.144 · Cited by 8,815
Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model
Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664

Show all 50 references

Research works printed but not linked: 3

Bashshur R. L., 1997, Telemedicine: Theory and practice
Nunnally J. C., 1994, Psychometric theory
Rogers E. M., 1995, The diffusion of innovation

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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
ORCID: 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
DOI: 10.1111/j.1540-5915.2001.tb00978.x
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
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor, 2014 d)
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 › Business, Management and Accounting › Management Information Systems › 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

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Information technology acceptance by individual professionals: a model comparison approach

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