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A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects

Schepers, Jeroen, Wetzels, Martin·2007·Information & Management

DOI 10.1016/j.im.2006.10.007

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Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
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
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Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Cultures and Organizations: Software of the Mind.
Triandis, H. C., & Hofstede, G. (1993) · Administrative Science Quarterly · doi:10.2307/2393257 · Cited by 17,696
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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Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664
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(2003) · International Journal of Electronic Commerce · doi:10.1080/10864415.2003.11044275 · Cited by 5,715
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Agarwal, R., & Karahanna, E. (2000) · MIS Quarterly · doi:10.2307/3250951 · Cited by 4,726
What drives mobile commerce?
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Szajna, B. (1996) · Management Science · doi:10.1287/mnsc.42.1.85 · Cited by 1,656

Show all 17 references

The theory of planned behavior: Frequently asked questions
Ajzen, I. (2020) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.195 · Cited by 3,347
Technology acceptance model: a literature review from 1986 to 2013
Marangunić, N., & Granić, A. (2015) · Universal Access in the Information Society · doi:10.1007/s10209-014-0348-1 · Cited by 2,458
Brave new world: service robots in the frontline
Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018) · Journal of Service Management · doi:10.1108/josm-04-2018-0119 · Cited by 2,315
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
The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education
Scherer, R., Siddiq, F., & Tondeur, J. (2019) · Computers & Education · doi:10.1016/j.compedu.2018.09.009 · Cited by 1,923
Developing a general extended technology acceptance model for E-learning (GETAMEL) by analysing commonly used external factors
Abdullah, F., & Ward, R. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.11.036 · Cited by 986
Extending the two-stage information systems continuance model: incorporating UTAUT predictors and the role of context: Context, expectations and IS continuance
Venkatesh, V., Thong, J. Y. L., Chan, F. K. Y., Hu, P. J.-H., & Brown, S. A. (2011) · Information Systems Journal · doi:10.1111/j.1365-2575.2011.00373.x · Cited by 852
Does the technology acceptance model predict actual use? A systematic literature review
Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010) · Information and Software Technology · doi:10.1016/j.infsof.2009.11.005 · Cited by 851
Gerontechnology acceptance by elderly Hong Kong Chinese: A senior technology acceptance model (STAM)
Chen, K., & Chan, A. H. S. (2014) · Ergonomics · doi:10.1080/00140139.2014.895855 · Cited by 679
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
Integrating the theory of planned behaviour and self-determination theory in health behaviour: a meta-analysis
Hagger, M. S., & Chatzisarantis, N. L. D. (2009) · British Journal of Health Psychology · doi:10.1348/135910708x373959 · Cited by 538
What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age
Zhao, Y., Ni, Q., & Zhou, R. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.08.006 · Cited by 516
The virtual reality hardware acceptance model (VR-HAM): extending and individuating the technology acceptance model (TAM) for virtual reality hardware
Manis, K. T., & Choi, D. (2019) · Journal of Business Research · doi:10.1016/j.jbusres.2018.10.021 · Cited by 494
Exploring consumer perceived risk and trust for online payments: an empirical study in China’s younger generation.
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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Lee, J., Kim, J., & Choi, J. Y. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2018.12.006 · Cited by 382
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Sarkar, S., Chauhan, S., & Khare, A. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.008 · Cited by 375
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Hamari, J., & Keronen, L. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.01.006 · Cited by 368
A review of technology acceptance by older adults
Chen, K., & Chan, A. H. S. (2011) · Gerontechnology · doi:10.4017/gt.2011.10.01.006.00 · Cited by 353
Why travelers use Airbnb again?: An integrative approach to understanding travelers’ repurchase intention
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Yang, H., Lee, H., & Zo, H. (2017) · Industrial Management & Data Systems · doi:10.1108/imds-01-2016-0017 · Cited by 325
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Hertzum (2017) · doi:10.1145/3127358 · Cited by 307
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Authors: Schepers, J., & Wetzels, M.
Venue: Information & Management
Publisher: Elsevier BV
Published: 2007-01
Volume: 44
Issue: 1
Pages: 90-103
ISSN: 0378-7206 (ISSN-L)
DOI: 10.1016/j.im.2006.10.007
OpenAlex: W2100795105
Cited by: 1,656
References: 17
FWCI: 6.02
Type: journal article
Language: en
Open access: closed

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A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects

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