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Understanding Information Technology Usage: A Test of Competing Models
Abstract
The Technology Acceptance Model and two variations of the Theory of Planned Behavior were compared to assess which model best helps to understand usage of information technology. The models were compared using student data collected from 786 potential users of a computer resource center. Behavior data was based on monitoring 3,780 visits to the resource center over a 12-week period. Weighted least squares estimation revealed that all three models performed well in terms of fit and were roughly equivalent in terms of their ability to explain behavior. Decomposing the belief structures in the Theory of Planned Behavior provided a moderate increase in the explanation of behavioral intention. Overall, the results indicate that the decomposed Theory of Planned Behavior provides a fuller understanding of behavioral intention by focusing on the factors that are likely to influence systems use through the application of both design and implementation strategies.
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“Prior research has suggested that employees' perceptions regarding organizational support-that is, facilitating conditions or perceptions of external control (Taylor & Todd, 1995;Venkatesh, 2000;Venkatesh et al., 2003)-will lead to greater user acceptance of new systems.”
From Technology Acceptance Model 3 and a Research Agenda on Interventions (2008) · cites this paper as Taylor & Todd, 1995
In the citing paper
“The fundamental assumption of the theory is that users’ beliefs influence their behavioral intentions, and these intentions, in turn, determine their actual behavior toward using a given technology (Taylor and Todd, 1995).”
From A two-step structural equation modeling and explainable machine learning framework for understanding university students’ adoption of generative AI: balancing intrinsic motivations and perceived risks (2026) · cites this paper as Taylor and Todd, 1995
Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
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
(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
(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
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
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
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AGGELIDIS, V, & CHATZOGLOU, P. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2008.06.006 · Cited by 553
What drives Malaysian m-commerce adoption? An empirical analysis
Tsu Wei, T., Marthandan, G., Yee‐Loong Chong, A., Ooi, K., & Arumugam, S. (2009) · Industrial Management & Data Systems · doi:10.1108/02635570910939399 · Cited by 550
Information Technology Continuance: A Theoretic Extension and Empirical Test
Bhattacherjee, A., Perols, J. L., & Sanford, C. C. (2008) · Journal of Computer Information Systems · doi:10.1080/08874417.2008.11645302 · Cited by 547
Liu, Y., Li, H., & Hu, F. (2013) · Decision Support Systems · doi:10.1016/j.dss.2013.04.001 · Cited by 541
A meta-analysis of mobile commerce adoption and the moderating effect of culture
Zhang, L., Zhu, J., & Liu, Q. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2012.05.008 · Cited by 541
A task–technology fit view of learning management system impact
McGill, T. J., & Klobas, J. E. (2008) · Computers & Education · doi:10.1016/j.compedu.2008.10.002 · Cited by 593
Adoption of WAP-enabled mobile phones among Internet users
Teo, T. S. H., & Pok, S. H. (2003) · Omega · doi:10.1016/j.omega.2003.08.005 · Cited by 553
Critical factors of WAP services adoption: an empirical study
Hung, S., Ku, C., & Chang, C. (2003) · Electronic Commerce Research and Applications · doi:10.1016/s1567-4223(03)00008-5 · Cited by 540
Hansen, J. M., Saridakis, G., & Benson, V. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.11.010 · Cited by 629
de Luna, I. R., Liébana-Cabanillas, F. J., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2019) · Technological forecasting & social change · doi:10.1016/j.techfore.2018.09.018 · Cited by 468
Software Piracy in the Workplace: A Model and Empirical Test
Peace, A. G., Galletta, D. F., & Thong, J. Y. L. (2003) · Journal of Management Information Systems · doi:10.1080/07421222.2003.11045759 · Cited by 530
Hu, Q., Dinev, T., Hart, P., & Cooke, D. K. (2012) · Decision Sciences · doi:10.1111/j.1540-5915.2012.00361.x · Cited by 538
Sykes, T. A., Venkatesh, V., & Gosain, S. (2009) · MIS Quarterly · doi:10.2307/20650296 · Cited by 522
Khalifa, M., & Liu, V. (2007) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000711 · Cited by 568
The impact of trust and perceived risk on internet banking adoption in India
Kesharwani, A., & Bisht, S. S. (2012) · International Journal of Bank Marketing · doi:10.1108/02652321211236923 · Cited by 583
Determinants of intention to use the mobile banking apps: An extension of the classic TAM model
Muñoz‐Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. J. (2017) · Spanish Journal of Marketing - ESIC · doi:10.1016/j.sjme.2016.12.001 · Cited by 556
Bassellier, G., & Benbasat, I. (2004) · MIS Quarterly · doi:10.2307/25148659 · Cited by 517
What have we learned? A review of stated preference and choice studies on autonomous vehicles
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Yousafzai, S., Foxall, G. R., & Pallister, J. (2010) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.2010.00615.x · Cited by 559
Students’ perceptions about the use of video games in the classroom
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Lim, K. H., Sia, C. L., Lee, M. K. O., & Benbasat, I. (2006) · Journal of Management Information Systems · doi:10.2753/mis0742-1222230210 · Cited by 505
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Antecedents of the adoption of the new mobile payment systems: The moderating effect of age
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Understanding Online Community User Participation: A Social Influence Perspective
Zhou, T. (2011) · Internet Research · doi:10.1108/10662241111104884 · Cited by 538
Exploring influencing variables for the acceptance of social robots
de Graaf, M. M. A., & Ben Allouch, S. (2013) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2013.07.007 · Cited by 499
Extending the Technology Acceptance Model to assess automation
Ghazizadeh, M., Lee, J. D., & Boyle, L. N. (2011) · Cognition Technology & Work · doi:10.1007/s10111-011-0194-3 · Cited by 498
Consumer attitudes towards online shopping
Al‐Debei, M. M., Akroush, M. N., & Ashouri, M. I. (2015) · Internet Research · doi:10.1108/intr-05-2014-0146 · Cited by 605
Consumer behavior in online game communities: A motivational factor perspective
Hsu, C., & Lu, H. (2005) · Computers in Human Behavior · doi:10.1016/j.chb.2005.09.001 · Cited by 499
Manis, K. T., & Choi, D. (2019) · Journal of Business Research · doi:10.1016/j.jbusres.2018.10.021 · Cited by 494
Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention
Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, M. S. (2016) · Procedia Economics and Finance · doi:10.1016/s2212-5671(16)00050-2 · Cited by 625
Zheng, X., Men, J., Yang, F. Y., & Gong, X. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.02.010 · Cited by 542
The Use of the UTAUT Model in the Adoption of E-Government Services in Kuwait
AlAwadhi, S. A., & Morris, A. (2008) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2008.452 · Cited by 488
TUNG, F., CHANG, S., & CHOU, C. (2008) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2007.06.006 · Cited by 476
Adoption of Mobile Internet Services: An Exploratory Study of Mobile Commerce Early Adopters
Pedersen, P. E. (2005) · Journal of Organizational Computing and Electronic Commerce · doi:10.1207/s15327744joce1503_2 · Cited by 499
Hsu, M.-H., Yen, C.-H., Chiu, C.-M., & Chang, C.-M. (2006) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2006.04.004 · Cited by 490
Toward a unified theory of consumer acceptance technology
Kulviwat, S., Bruner, G. C., Kumar, A., Nasco, S. A., & Clark, T. W. (2007) · Psychology and Marketing · doi:10.1002/mar.20196 · Cited by 527
Leong, L.-Y., Hew, T.-S., Tan, G. W., & Ooi, K. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.04.018 · Cited by 519
The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value
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McElroy, J. C., Hendrickson, A. R., Townsend, A. M., & Demarie, S. M. (2007) · MIS Quarterly · doi:10.2307/25148821 · Cited by 508
The impact of use context on mobile services acceptance: The case of mobile ticketing
Mallat, N., Rossi, M., Tuunainen, V. K., & Öörni, A. (2009) · Information & Management · doi:10.1016/j.im.2008.11.008 · Cited by 479
Mobile banking and economic development: linking adoption, impact, and use
Donner, J., & Tellez, C. (2008) · Asian Journal of Communication · doi:10.1080/01292980802344190 · Cited by 493
Thakur, R., & Srivastava, M. (2014) · Internet Research · doi:10.1108/intr-12-2012-0244 · Cited by 606
Analysis of users and non-users of smartphone applications
Verkasalo, H., López‐Nicolás, C., Molina‐Castillo, F., & Bouwman, H. (2009) · Telematics and Informatics · doi:10.1016/j.tele.2009.11.001 · Cited by 469
Factors affecting purchase intention on mobile shopping web sites
Lu, H., & Yu‐Jen Su, P. (2009) · Internet Research · doi:10.1108/10662240910981399 · Cited by 466
Akour, I. A., Al-Maroof, R. S., Alfaisal, R., & Salloum, S. A. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100052 · Cited by 499
Perceptions of senior managers toward knowledge‐sharing behaviour
Lin, H., & Lee, G. (2004) · Management Decision · doi:10.1108/00251740410510181 · Cited by 468
Yi, M. Y., Fiedler, K. D., & Park, J.-S. (2006) · Decision Sciences · doi:10.1111/j.1540-5414.2006.00132.x · Cited by 461
Yang, Y., Asaad, Y., & Dwivedi, Y. K. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.03.066 · Cited by 520
Organizational Mechanisms for Enhancing User Innovation in Information Technology1
Nambisan, S., Agarwal, R., & Tanniru, M. R. (1999) · MIS Quarterly · doi:10.2307/249468 · Cited by 452
Derks, D., van Duin, D., Tims, M., & Bakker, A. B. (2014) · Journal of Occupational and Organizational Psychology · doi:10.1111/joop.12083 · Cited by 470
The mediation of external variables in the technology acceptance model
Burton‐Jones, A., & Hubona, G. S. (2006) · Information & Management · doi:10.1016/j.im.2006.03.007 · Cited by 509
Meléndez, A. P., Obra, A. R. D. Á., & Garrido‐Moreno, A. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.12.014 · Cited by 484
Hong, W., Thong, J. Y. L., Wong, W.-M., & Tam, K.-Y. (2002) · Journal of Management Information Systems · doi:10.1080/07421222.2002.11045692 · Cited by 827
Sullivan, Y. W., & Kim, D. J. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.12.008 · Cited by 443
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Lowry, P. B., Gaskin, J. E., Twyman, N. W., Hammer, B. I., & Roberts, T. (2013) · Journal of the Association for Information Systems · doi:10.17705/1jais.00347 · Cited by 504
Mobile banking: proposition of an integrated adoption intention framework
Puschel, J. P., Mazzon, J. A., & Hernandez, J. M. D. C. (2010) · International Journal of Bank Marketing · doi:10.1108/02652321011064908 · Cited by 450
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Terzis, V., & Economides, A. A. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.11.017 · Cited by 444
Extending the TAM for a t-commerce
Yu, J., Ha, I., Choi, M., & Rho, J. J. (2005) · Information & Management · doi:10.1016/j.im.2004.11.001 · Cited by 446
User acceptance of wireless short messaging services: Deconstructing perceived value
Turel, O., Serenko, A., & Bontis, N. (2006) · Information & Management · doi:10.1016/j.im.2006.10.005 · Cited by 440
Niehaves, B., & Plattfaut, R. (2014) · European Journal of Information Systems · doi:10.1057/ejis.2013.19 · Cited by 347
Health monitoring through wearable technologies for older adults: Smart wearables acceptance model.
Li, J., Ma, Q., Chan, A. H. S., & Man, S.-S. (2019) · Applied Ergonomics · doi:10.1016/j.apergo.2018.10.006 · Cited by 386
Moore, G. C., & Benbasat, I. (1996) · Springer eBooks · doi:10.1007/978-0-387-34982-4_10 · Cited by 451
Predicting consumer intentions to shop online: An empirical test of competing theories
Lin, H.-F. (2007) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2007.02.002 · Cited by 435
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Jenkin, T. A., Webster, J., & McShane, L. (2010) · Information and Organization · doi:10.1016/j.infoandorg.2010.09.003 · Cited by 461
Molla, A., & Licker, P. S. (2005) · International Journal of Electronic Commerce · doi:10.1080/10864415.2005.11043963 · Cited by 429
Dinev, T., & Hu, Q. (2007) · Journal of the Association for Information Systems · doi:10.17705/1jais.00133 · Cited by 451
Awa, H. O., Ojiabo, O. U., & Emecheta, B. C. (2015) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-04-2014-0012 · Cited by 525
User-centered E-Government in practice: A comprehensive model for measuring user satisfaction
Verdegem, P., & Verleye, G. (2009) · Government Information Quarterly · doi:10.1016/j.giq.2009.03.005 · Cited by 437
Xi, N., Chen, J., Gama, F., Riar, M., & Hamari, J. (2022) · Information Systems Frontiers · doi:10.1007/s10796-022-10244-x · Cited by 480
Wang, G., Wu, W. W., Zeng, W., Chou, C.-L., & Shen, R.-F. (2006) · Journal of Proteome Research · doi:10.1021/pr050406g · Cited by 423
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Bansal, H. S., & Taylor, S. F. (1999) · Journal of Service Research · doi:10.1177/109467059922007 · Cited by 440
Self-citationKim, H.-B., Kim, T. T., & Shin, S. W. (2008) · Tourism Management · doi:10.1016/j.tourman.2008.07.001 · Cited by 425
Joo, Y. J., So, H.-J., & Kim, N. H. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.01.003 · Cited by 420
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Destination in a country image context
Nadeau, J. P., Heslop, L. A., O’Reilly, N., & Luk, P. (2008) · Annals of Tourism Research · doi:10.1016/j.annals.2007.06.012 · Cited by 443
Sutanto, J., Palme, E., Tan, C.-H., & Phang, C. W. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.4.07 · Cited by 412
Kulviwat, S., Bruner, G. C., & Al-Shuridah, O. (2009) · Journal of Business Research · doi:10.1016/j.jbusres.2007.04.014 · Cited by 406
Yang, Q., Pang, C., Liu, L., Yen, D. C., & Michael Tarn, J. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.03.058 · Cited by 410
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Wu, I., Li, J.-Y., & Fu, C.-Y. (2011) · Decision Support Systems · doi:10.1016/j.dss.2011.03.003 · Cited by 429
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The role of system trust in business-to-consumer transactions
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Intentions to Use Self-Service Technologies: A Confluence of Multiple Attitudes
Curran, J., Meuter, M., & Surprenant, C. F. (2003) · Journal of Service Research · doi:10.1177/1094670502238916 · Cited by 445
Ifinedo, P. (2013) · Information & Management · doi:10.1016/j.im.2013.10.001 · Cited by 404
Teo, T. P., Lee, C. B., Chai, C. S., & Wong, S. L. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.05.017 · Cited by 403
Pavlou, P. A., & Chai, L. (2002) · Journal of electronic commerce research · Cited by 398
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Wallace, L. G., Keil, M., & Rai, A. (2004) · Information & Management · doi:10.1016/j.im.2003.12.007 · Cited by 399
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Wang, W., & Wang, C. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.02.021 · Cited by 424
Adoption of internet banking: proposition and implementation of an integrated methodology approach
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Defining, Assessing, and Promoting E‐Learning Success: An Information Systems Perspective*
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Emotions as determinants of electric car usage intention
Moons, I., & Pelsmacker, P. D. (2012) · Journal of Marketing Management · doi:10.1080/0267257x.2012.659007 · Cited by 380
Shi, S., Wang, Y., Chen, X., & Zhang, Q. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.09.001 · Cited by 415
Chang, S., & Tung, F. (2007) · British Journal of Educational Technology · doi:10.1111/j.1467-8535.2007.00742.x · Cited by 391
Metadata
- Authors
- Taylor, S., & Todd, P. A.
- Affiliations
- Queen's University (CA)
- Venue
- Information Systems Research
- Published
- 1995-06
- Volume
- 6
- Issue
- 2
- Pages
- 144-176
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W1987198869
- Cited by
- 8,815
- References
- 52
- Citations by year
- 2026: 226 · 2025: 285 · 2024: 376 · 2023: 421 · 2022: 485 · 2021: 558 · 2020: 448 · 2019: 422 · 2018: 428 · 2017: 357 · 2016: 384 · 2015: 481 · 2014: 453 · 2013: 487 · 2012: 410
- FWCI
- 53.52
- 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 › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- information technology use, technology acceptance model, theory of planned behavior, behavioral intention, student users, belief structures, model comparison
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