The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The Legacy of the Technology Acceptance Model and a Proposal for a Paradigm Shift.
Abstract
This article presents a critique of a number of shortcomings with the technology acceptance model (TAM) and points to specific remedies in each case. In addition, I present a model for the purposes of providing a foundation for a paradigm shift. The model consists first of a decision making core (goal desire → goal intention → action desire → action intention) that is grounded in basic decision making variables/processes of a universal nature. The decision core also contains a mechanism for self-regulation that moderates the effects of desires on intentions. Second, added to the decision making core are a number of causes and effects of decisions and self-regulatory reasoning, with the aim of introducing potential contingent, contextual nuances for understanding decision making. Many of the causal variables here are contained within TAM or its extensions; also considered are new variables grounded in emotional, group/social/cultural, and goal-directed behavior research.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Culture and the self: Implications for cognition, emotion, and motivation.
Markus, H. R., & Kitayama, S. (1991) · Psychological Review · doi:10.1037/0033-295x.98.2.224 · Cited by 21,995
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Extrinsic and Intrinsic Motivation to Use Computers in the Workplace 1
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1992.tb00945.x · Cited by 6,231
Self-citationIntrinsic and extrinsic motivation
Benabou, R., & Tirole, J. (2003) · Review of Economic Studies · doi:10.1111/1467-937x.00253 · Cited by 2,913
Dabholkar, P. A., & Bagozzi, R. P. (2002) · Journal of the Academy of Marketing Science · doi:10.1177/0092070302303001 · Cited by 1,898
Self-citation
Cited by
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
The Technology Acceptance Model: Its past and its future in health care
Holden, R. J., & Karsh, B.-T. (2010) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.07.002 · Cited by 2,669
Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead
University of Arkansas, Venkatesh, V., Thong, J., Hong Kong University of Science and Technology, Xu, X., & The Hong Kong Polytechnic University (2016) · Journal of the Association for Information Systems · doi:10.17705/1jais.00428 · Cited by 2,513
Pappas, I. O., & Woodside, A. G. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102310 · Cited by 2,254
Synthesizing information systems knowledge: A typology of literature reviews
Paré, G., Trudel, M.-C., Jaana, M., & Kitsiou, S. (2015) · Information & Management · doi:10.1016/j.im.2014.08.008 · Cited by 1,987
Online social networks: Why do students use facebook?
Cheung, C. M. K., Chiu, P.-Y., & Lee, M. K. O. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2010.07.028 · Cited by 1,501
Factors influencing acceptance of technology for aging in place: A systematic review
Peek, S. T. M., Wouters, E. J. M., van Hoof, J., Luijkx, K. G., Boeije, H. R., & Vrijhoef, H. J. M. (2014) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2014.01.004 · Cited by 1,206
Erkan, I., & Evans, C. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.03.003 · Cited by 1,188
Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers
Belanche, D., Casaló, L. V., & Flavián, C. (2019) · Industrial Management & Data Systems · doi:10.1108/imds-08-2018-0368 · Cited by 851
McLean, G., & Osei-Frimpong, K. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.05.009 · Cited by 762
A Framework and Guidelines for Context-Specific Theorizing in Information Systems Research
Hong, W., Chan, F. K. Y., Thong, J. Y. L., Chasalow, L. C., & Dhillon, G. (2014) · Information Systems Research · doi:10.1287/isre.2013.0501 · Cited by 609
Tarhini, A., El-Masri, M., Ali, M., & Serrano, A. (2016) · Information Technology & People · doi:10.1108/itp-02-2014-0034 · Cited by 400
Contemporary Trends and Issues in it Adoption and Diffusion Research
Williams, M. D., Dwivedi, Y. K., Lal, B., & Schwarz, A. (2009) · Journal of Information Technology · doi:10.1057/jit.2008.30 · Cited by 356
Zhang, P. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.1.11 · Cited by 331
Consumer's decision to shop online: The moderating role of positive informational social influence
Lee, M. K. O., Shi, N., Cheung, C. M. K., Lim, K. H., & Sia, C. L. (2011) · Information & Management · doi:10.1016/j.im.2010.08.005 · Cited by 315
Hertzum (2017) · doi:10.1145/3127358 · Cited by 307
Šumak, B., & Šorgo, A. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.07.037 · Cited by 295
Exploring consumers’ intention to accept smartwatch
Wu, L.-H., Wu, L.-C., & Chang, S.-C. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.07.005 · Cited by 226
An empirical investigation of factors affecting e-collaboration diffusion in SMEs
Chan, F. T. S., Yee-Loong Chong, A., & Zhou, L. (2012) · International Journal of Production Economics · doi:10.1016/j.ijpe.2012.04.004 · Cited by 202
Is it the end of the technology acceptance model in the era of generative artificial intelligence?
Mogaji, E., Viglia, G., Srivastava, P., & Dwivedi, Y. K. (2024) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-08-2023-1271 · Cited by 187
Information technology adoption: a review of the literature and classification
Salahshour Rad, M., Nilashi, M., & Mohamed Dahlan, H. (2018) · Universal Access in the Information Society · doi:10.1007/s10209-017-0534-z · Cited by 181
Toward a better understanding of behavioral intention and system usage constructs
Wu, J., & Du, H. (2012) · European Journal of Information Systems · doi:10.1057/ejis.2012.15 · Cited by 175
Shareef, M. A., Dwivedi, Y. K., Kumar, V., & Kumar, U. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.02.003 · Cited by 177
Predictive factors of physicians’ satisfaction with telemedicine services acceptance
Kissi, J., Dai, B., Dogbe, C. S., Banahene, J., & Ernest, O. (2020) · Health Informatics Journal · doi:10.1177/1460458219892162 · Cited by 157
Predictors for e-government adoption: integrating TAM, TPB, trust and perceived risk.
Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017) · The Electronic Library · doi:10.1108/el-08-2015-0141 · Cited by 167
Mettler, T., & Wulf, J. (2019) · Information Systems Journal · doi:10.1111/isj.12205 · Cited by 155
"Alexa is a Toy": Exploring Older Adults' Reasons for Using, Limiting, and Abandoning Echo
Trajkova, M., & Martin-Hammond, A. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376760 · Cited by 154
Assessing AI adoption in developing country academia: A trust and privacy-augmented UTAUT framework
Rana, M. M., Siddiqee, M. S., Sakib, M. N., & Ahamed, M. R. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e37569 · Cited by 143
Technology acceptance research: Meta-analysis
Marikyan, D., Papagiannidis, S., & Stewart, G. (2026) · Journal of Information Science · doi:10.1177/01655515231191177 · Cited by 140
Understanding the Role of Privacy and Trust in Intelligent Personal Assistant Adoption
Liao, Y., Vitak, J., Kumar, P., Zimmer, M., & Kritikos, K. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-15742-5_9 · Cited by 127
Groß, M. (2015) · The International Review of Retail, Distribution and Consumer Research · doi:10.1080/09593969.2014.988280 · Cited by 124
Psychological factors influencing technology adoption: A case study from the oil and gas industry
Roberts, R., Flin, R., Millar, D., & Corradi, L. (2021) · Technovation · doi:10.1016/j.technovation.2020.102219 · Cited by 121
Acceptance of recommendations to buy in online retailing.
Baier, D., & Stüber, E. (2010) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2010.03.005 · Cited by 106
Jariyapan, P., Mattayaphutron, S., Gillani, S. N., & Shafique, O. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.814087 · Cited by 102
Richter, A., & Riemer, K. (2013) · Business & Information Systems Engineering · doi:10.1007/s12599-013-0260-x · Cited by 93
Binyamin, S. S., & Zafar, B. A. (2021) · Health Informatics Journal · doi:10.1177/1460458220976737 · Cited by 89
Exploring biometric identification in FinTech applications based on the modified TAM
Wang, J. S. (2021) · Financial Innovation · doi:10.1186/s40854-021-00260-2 · Cited by 86
“Using the relevant variables of user attitudes and behaviors to assess the acceptance of new technologies (Bagozzi 2007; Schierz et al. 2010), the TAM addresses the most influential arguments in the theory of reasoned action (TRA) and theory of planned behavior (TPB).”
A multi-method approach to examining consumer intentions to use smart retail technology
Fazal-e-Hasan, S. M., Amrollahi, A., Mortimer, G., Adapa, S., & Balaji, M. S. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106622 · Cited by 76
(2016) · Journal of academic language and learning · Cited by 75
Permission email marketing and its influence on online shopping
Reimers, V., Chao, C.-W., & Gorman, S. (2016) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-03-2015-0037 · Cited by 64
Do cultural dimensions differentiate ERP acceptance? A study in the context of Saudi Arabia
Alhirz, H., & Sajeev, A. S. M. (2015) · Information Technology & People · doi:10.1108/itp-07-2013-0127 · Cited by 62
Yang, J., Amrollahi, A., & Marrone, M. (2024) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2024.101864 · Cited by 59
Czaja, S. J., Boot, W. R., Charness, N., A. Rogers, W., Sharit, J., Fisk, A. D., Lee, C. C., & Nair, S. N. (2015) · Contemporary Clinical Trials · doi:10.1016/j.cct.2014.11.004 · Cited by 58
Long, T., Cummins, J., & Waugh, M. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12703 · Cited by 53
Atwal, A., Money, A., & Harvey, M. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3723 · Cited by 52
Intention to adopt services by AI avatar: A protection motivation theory perspective
Park, J., Yun, J., & Chang, W. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.103929 · Cited by 51
Understanding the Adoption of Voice Activated Personal Assistants
Coskun-Setirek, A., & Mardikyan, S. (2017) · International Journal of E-Services and Mobile Applications · doi:10.4018/ijesma.2017070101 · Cited by 44
Lee, S., Jones-Jang, S. M., Chung, M., Kim, N., & Choi, J. (2024) · Information Research an international electronic journal · doi:10.47989/ir291647 · Cited by 36
Message framing and acceptance of branchless banking technology
Kurila, J., Lazuras, L., & Ketikidis, P. H. (2016) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2016.02.001 · Cited by 36
Soror, A. A., Steelman, Z. R., & Limayem, M. (2012) · 2012 45th Hawaii International Conference on System Sciences · doi:10.1109/hicss.2012.219 · Cited by 34
Lim, J. S., Shin, D., Lee, C., Kim, J., & Zhang, J. (2025) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2025.2487679 · Cited by 32
Critical Literature Review of Theory of Planned Behavior in the Information Systems Research
JOKONYA, O. (2017) · DEStech Transactions on Computer Science and Engineering · doi:10.12783/dtcse/ameit2017/12297 · Cited by 29
Alwahaishi, S., & Snášel, V. (2013) · International Journal of E-Adoption · doi:10.4018/jea.2013040103 · Cited by 28
The role of emotional attachment in IPA continuance intention: an emotional attachment model
Mamun, M. R. A., Prybutok, V. R., Peak, D. A., Torres, R., & Pavur, R. J. (2023) · Information Technology & People · doi:10.1108/itp-09-2020-0643 · Cited by 28
Cognitive bias and decision aid use under stressful conditions
Phillips-Wren, G., Jefferson, T., & McKniff, S. (2019) · Journal of Decision Systems · doi:10.1080/12460125.2019.1643695 · Cited by 22
Investigating user identification in remote patient monitoring devices
Ondiege, B., & Clarke, M. (2017) · Bioengineering · doi:10.3390/bioengineering4030076 · Cited by 19
Exploring Factors Impacting Users' Attitude and Intention towards Social Tagging Systems
Allam, H., Blustein, J., Bliemel, M., & Spiteri, L. (2012) · 2012 45th Hawaii International Conference on System Sciences · doi:10.1109/hicss.2012.267 · Cited by 19
Hasebrook, J. P., Michalak, L., Kohnen, D., Metelmann, B., Metelmann, C., Brinkrolf, P., Flessa, S., & Hahnenkamp, K. (2023) · PLOS ONE · doi:10.1371/journal.pone.0280956 · Cited by 19
Aldossary (2024) · doi:10.3390/info15040202 · Cited by 17
Laenens, W., Van den Broeck, W., & Mariën, I. (2018) · Media and Communication · doi:10.17645/mac.v6i4.1652 · Cited by 17
Gerpott, T. J., & Ahmadi, N. (2016) · Transforming Government: People, Process and Policy · doi:10.1108/tg-05-2016-0025 · Cited by 9
Metadata
- Authors
- University of Michigan, & Bagozzi, R.
- Venue
- Journal of the Association for Information Systems
- Publisher
- Association for Information Systems
- Published
- 2007-04
- Volume
- 8
- Issue
- 4
- Pages
- 244-254
- ISSN
- 1536-9323 (ISSN-L)
- OpenAlex
- W2150376909
- Cited by
- 2,035
- References
- 6
- FWCI
- 79.83
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.