Assessing IT Usage: The Role of Prior Experience
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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Subjective norms tend to be more influential during early stages of innovation implementation when users have limited direct experience from which to develop attitudes.
“Subjective norms tend to be more influential during early stages of innovation implementation when users have limited direct experience from which to develop attitudes (Taylor and Todd, 1995).”
From An Analysis of Factors Affecting on Online Shopping Behavior of Consumers (2012) · cites this paper as Taylor and Todd, 1995
The role of intention as a predictor of behavior is well established in the literature.
“The role of intention as a predictor of behavior is well established in the literature (e.g. Sheppard etal. 1988; Taylor and Todd 1995).”
From Understanding the determinants of novel technology adoption among teachers: the case of 3D printing (2020) · cites this paper as Taylor and Todd 1995
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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
- 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 › Sociology and Political Science › 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
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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