Cited by 3,575Technology Adoption and User BehaviourInnovation Diffusion and ForecastingGender and Technology in Education

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A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology

Agarwal, Ritu, Prasad, Jayesh·1998·Information Systems Research

DOI 10.1287/isre.9.2.204

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Abstract

The acceptance of new information technologies by their intended users persists as an important issue for researchers and practitioners of information systems. Several models have been developed in the literature to facilitate understanding of the process by which new information technologies are adopted. This paper proposes a new construct that further illuminates the relationships explicit in the technology acceptance models and describes an operational measure for this construct that possesses desirable psychometric properties. The construct, personal innovativeness in the domain of information technology, is hypothesized to exhibit moderating effects on the antecedents as well as the consequences of individual perceptions about a new information technology. The construct was developed and validated in the context of the innovation represented by the World-Wide Web. Implications for theory and practice are discussed.

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The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
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
Structural Equations with Latent Variables
Bollen, K. A. (1989) · Wiley series in probability and statistics · doi:10.1002/9781118619179 · Cited by 17,944
Structural Equations with Latent Variables.
Clogg, C. C., & Bollen, K. A. (1991) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2072165 · Cited by 17,475
Convergent and discriminant validation by the multitrait-multimethod matrix.
Campbell, D. T., & Fiske, D. W. (1959) · Psychological Bulletin · doi:10.1037/h0046016 · Cited by 17,116
Testing Structural Equation Models.
Mueller, C. W., Bollen, K. A., & Long, J. S. (1994) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2074955 · Cited by 14,211
Advances in Consumer Research
(2025) · doi:10.53555/acr.v2i2 · Cited by 13,486
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

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Research works printed but not linked: 9

Brancheau J. C., 1990, Inform. Systems Res., 1, 41
Carroll J., 1996, Comput. Canada, 22, 33
Delmonico D., 1996, Comm. Week, 592, 46
Jackson D. N. A., 1976, Jackson Personality Inventory Manual
Joreskog K. G., 1993, Lisrel 8, User's Reference Guide
Nunnally J. C., 1978, Psychometric Theory
Rogers E. M., 1971, Communication of Innovations
Rogers E. M., 1983, Diffusion of Innovations
Wexler J., 1993, Computerworld, 27, 71

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Authors: Agarwal, R., & Prasad, J.
Affiliations: Florida State University (US)
University of Dayton (US)
ORCID: Agarwal, Ritu
Venue: Information Systems Research
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Published: 1998-06
Volume: 9
Issue: 2
Pages: 204-215
ISSN: 1047-7047 (ISSN-L)
1526-5536
DOI: 10.1287/isre.9.2.204
OpenAlex: W2162061662
Cited by: 3,575
References: 34
Citations by year: 2026: 213 · 2025: 256 · 2024: 262 · 2023: 231 · 2022: 234 · 2021: 233 · 2020: 206 · 2019: 146 · 2018: 173 · 2017: 128 · 2016: 143 · 2015: 178 · 2014: 165 · 2013: 161 · 2012: 149
FWCI: 29.69
Type: journal article
Language: en
Open access: closed
Locations: Information Systems Research (publishedVersion)
Topics: Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
Social Sciences › Gender Studies › Gender and Technology in Education
Keywords: personal innovativeness, information technology adoption, technology acceptance model, moderating effect, operational measurement, psychometric validation, World Wide Web, user perception, construct definition

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A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology

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