Cited by 2,891Technology Adoption and User BehaviourGender and Technology in EducationInformation Systems Theories and Implementation

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Assessing IT Usage: The Role of Prior Experience

Taylor, Shirley, Todd, Peter·1995·MIS Quarterly

DOI 10.2307/249633

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Abstract

A variety of models that incorporate attitudinal, social, and control factor have been advanced to explain IT usage, of which the Technology Acceptance Model (TAM) is the most well know. One goal of such models is to develop diagnostic tools to predict information systems acceptance and facilitate design changes before users have experience with a system. However, empirical tests of these models have generally focused on either systems that were already in use by the study participants, or systems that the participants were familiar with, such as word processing packages and spreadsheets. Given this, it is unclear (1) whether models such as TAM are predictive of behavior for inexperienced users and, more importantly, (2) whether the determinants of IT usage are the same for experienced and inexperiened users of a system.

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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
Untitled work
(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
Untitled work
(1980) · Medical Entomology and Zoology · Cited by 25,810
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
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
Self-citation
Untitled work
(1993) · Medical Entomology and Zoology · Cited by 7,690
Structural model evaluation and modification: An interval estimation approach
Steiger, J. H. (1990) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2502_4 · Cited by 7,408

Show all 25 references

Research works printed but not linked: 2

Barclay, 1996, The Partial Least Squares Approach to Causal Modelling, Technology Studies
Eagly, 1993, The Psychology of Attitudes

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Authors: Taylor, S., & Todd, P.
Affiliations: Queen's University (CA)
Venue: MIS Quarterly
Publisher: MIS Quarterly
Published: 1995-12-01
Volume: 19
Issue: 4
Pages: 561-570
ISSN: 0276-7783 (ISSN-L)
2162-9730
DOI: 10.2307/249633
OpenAlex: W1503436739
Cited by: 2,891
References: 25
Citations by year: 2026: 63 · 2025: 96 · 2024: 107 · 2023: 109 · 2022: 130 · 2021: 157 · 2020: 124 · 2019: 132 · 2018: 137 · 2017: 110 · 2016: 128 · 2015: 175 · 2014: 182 · 2013: 147 · 2012: 156
FWCI: 19.90
Type: journal article
Language: en
Open access: closed
Locations: MIS Quarterly (publishedVersion)
Journal of the Association for Information Systems (submittedVersion)
Topics: Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Social Sciences › Gender Studies › Gender and Technology in Education
Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
Keywords: information technology use, technology acceptance model, prior experience, user experience, user behavior prediction, inexperienced users, social influence, controlling factors, attitudinal factors

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Assessing IT Usage: The Role of Prior Experience

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