The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Re-Examining Perceived Ease of Use and Usefulness: A Confirmatory Factor Analysis
Abstract
Recently, Adams, et al. (1992) presented the results of two studies designed to replicate previous work by Fred Davis (1989) regarding perceived usefulness, ease of use, and their in-
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
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
Coefficient Alpha and the Internal Structure of Tests
Cronbach, L. J. (1951) · Psychometrika · doi:10.1007/bf02310555 · Cited by 43,931
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
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
Akaike, H. (1987) · Psychometrika · doi:10.1007/bf02294359 · Cited by 5,264
Akaike, H. (1987) · Springer Series in Statistics · doi:10.1007/978-1-4612-1694-0_29 · Cited by 4,027
Cited by
Technology Acceptance Model 3 and a Research Agenda on Interventions
Venkatesh, V., & Bala, H. (2008) · Decision Sciences · doi:10.1111/j.1540-5915.2008.00192.x · Cited by 8,159
Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664
Extending the TAM for a World-Wide-Web context
Moon, J.-W., & Kim, Y.-G. (2001) · Information & Management · doi:10.1016/s0378-7206(00)00061-6 · Cited by 3,802
A Model of the Antecedents of Perceived Ease of Use: Development and Test
Venkatesh, V., & Davis, F. D. (1996) · Decision Sciences · doi:10.1111/j.1540-5915.1996.tb01822.x · Cited by 3,802
Venkatesh, V., & Morris, M. G. (2000) · MIS Quarterly · doi:10.2307/3250981 · Cited by 2,780
Service quality delivery through web sites: a critical review of extant knowledge
Zeithaml, V. A., Parasuraman, A., & Malhotra, A. (2002) · Journal of the Academy of Marketing Science · doi:10.1177/009207002236911 · Cited by 2,729
An Extended Privacy Calculus Model for E-Commerce Transactions
Dinev, T., & Hart, P. (2006) · Information Systems Research · doi:10.1287/isre.1060.0080 · Cited by 2,640
The Technology Acceptance Model: Past, Present, and Future
Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003) · Communications of the Association for Information Systems · doi:10.17705/1cais.01250 · Cited by 2,572
Examining the technology acceptance model using physician acceptance of telemedicine technology
Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999) · Journal of Management Information Systems · doi:10.1080/07421222.1999.11518247 · Cited by 1,951
The Impact of Technostress on Role Stress and Productivity
Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007) · Journal of Management Information Systems · doi:10.2753/mis0742-1222240109 · Cited by 1,904
The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption
Drexel University, Gefen, D., Straub, D., & Georgia State University (2000) · Journal of the Association for Information Systems · doi:10.17705/1jais.00008 · Cited by 1,833
Consumer acceptance of online banking: an extension of the technology acceptance model
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004) · Internet Research · doi:10.1108/10662240410542652 · Cited by 1,772
Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis
Rai, A., Lang, S. S., & Welker, R. B. (2002) · Information Systems Research · doi:10.1287/isre.13.1.50.96 · Cited by 1,611
Trust and risk in e-government adoption
Bélanger, F., & Carter, L. (2008) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2007.12.002 · Cited by 1,235
On-line trust: concepts, evolving themes, a model
Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(03)00041-7 · Cited by 1,200
Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006) · Information & Management · doi:10.1016/j.im.2005.08.006 · Cited by 1,139
Critical success factors for e-learning acceptance: Confirmatory factor models
Selim, H. M. (2007) · Computers & Education · doi:10.1016/j.compedu.2005.09.004 · Cited by 1,055
An Empirical Examination of the Concern for Information Privacy Instrument
Stewart, K. A., & Segars, A. H. (2002) · Information Systems Research · doi:10.1287/isre.13.1.36.97 · Cited by 734
Self-citationHsu, C.-L., & Lin, J. C.-C. (2015) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2014.11.003 · Cited by 662
The Technology Acceptance Model: A Meta-Analysis of Empirical Findings
Ma, Q., & Liu, L. (2004) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.2004010104 · Cited by 660
Chatterjee, S., & Bhattacharjee, K. K. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10159-7 · Cited by 747
Sohn, K., & Kwon, O. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2019.101324 · Cited by 646
Technology acceptance: a meta‐analysis of the TAM: Part 1
Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2007) · Journal of Modelling in Management · doi:10.1108/17465660710834453 · Cited by 624
An empirical validation of a unified model of electronic government adoption (UMEGA)
Dwivedi, Y. K., Rana, N. P., Janssen, M., Lal, B., Williams, M. D., & Clement, M. (2017) · Government Information Quarterly · doi:10.1016/j.giq.2017.03.001 · Cited by 622
Davis, F. D., & Venkatesh, V. (2004) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2003.822468 · Cited by 582
e-Government Adoption Model (GAM): Differing service maturity levels
Shareef, M. A., Kumar, V., Kumar, U., & Dwivedi, Y. K. (2011) · Government Information Quarterly · doi:10.1016/j.giq.2010.05.006 · Cited by 581
Technology use and performance: A field study of broker workstations
Lucas, H. C., & Spitler, V. K. (1999) · Decision Sciences · doi:10.1111/j.1540-5915.1999.tb01611.x · Cited by 561
TUNG, F., CHANG, S., & CHOU, C. (2008) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2007.06.006 · Cited by 476
Kehr, F., Kowatsch, T., Wentzel, D., & Fleisch, E. (2015) · Information Systems Journal · doi:10.1111/isj.12062 · Cited by 410
Citizens' adoption of an electronic government system: towards a unified view
Rana, N. P., Dwivedi, Y. K., Lal, B., Williams, M. D., & Clement, M. (2017) · Information Systems Frontiers · doi:10.1007/s10796-015-9613-y · Cited by 373
Yen, D. C., Wu, C.-S., Cheng, F.-F., & Huang, Y.-W. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.02.005 · Cited by 319
Adoption of online public grievance redressal system in India: toward developing a unified view
Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.02.019 · Cited by 274
Wang, Y.-S., Yeh, C.-H., & Liao, Y.-W. (2013) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2012.09.004 · Cited by 222
Navigating the Complexity of Generative AI Adoption in Software Engineering
Russo, D. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3652154 · Cited by 217
“The compensation for participants (10 minutes) exceeded the U.S. federal minimum wage.”
BackgroundThe relationship between website quality, trust and price premiums at online auctions
Gregg, D. G., & Walczak, S. (2010) · Electronic Commerce Research · doi:10.1007/s10660-010-9044-2 · Cited by 208
Narayanan, S., Jayaraman, V., Luo, Y., & Swaminathan, J. M. (2011) · Journal of Operations Management · doi:10.1016/j.jom.2010.05.001 · Cited by 202
E‐commerce usage and business performance in the Malaysian tourism sector: empirical analysis
Intan Salwani, M., Marthandan, G., Daud Norzaidi, M., & Choy Chong, S. (2009) · Information Management & Computer Security · doi:10.1108/09685220910964027 · Cited by 202
Social influence on technology acceptance behavior: self-identity theory perspective
Lee, Y., Lee, J., & Lee, Z. (2006) · ACM SIGMIS Database: the DATABASE for Advances in Information Systems · doi:10.1145/1161345.1161355 · Cited by 166
Kim, J., & Forsythe, S. (2010) · International Journal of Retail & Distribution Management · doi:10.1108/09590551011027122 · Cited by 150
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
Lindley, J., Coulton, P., & Sturdee, M. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025742 · Cited by 103
Understanding Student Plagiarism: An Empirical Study in Accounting Education
Guo, X. (2011) · Accounting Education · doi:10.1080/09639284.2010.534577 · Cited by 88
Trustworthiness in B2C e-commerce: an examination of alternative models
Serva, M. A., Benamati, J. "., & Fuller, M. A. (2005) · ACM SIGMIS Database: the DATABASE for Advances in Information Systems · doi:10.1145/1080390.1080397 · Cited by 72
Borrelli, B., Bartlett, Y. K., Tooley, E., Armitage, C. J., & Wearden, A. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4420 · Cited by 65
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
Olde Keizer, R. A. C. M., van Velsen, L., Moncharmont, M., Riche, B., Ammour, N., Del Signore, S., Zia, G., Hermens, H., & N’Dja, A. (2019) · Health and Technology · doi:10.1007/s12553-019-00320-9 · Cited by 57
Psychological drivers of referral reward program effectiveness
Orsingher, C., & Wirtz, J. (2018) · Journal of Services Marketing · doi:10.1108/jsm-07-2017-0247 · Cited by 48
Sánchez-Rodríguez, C., Martínez-Lorente, A. R., & Hemsworth, D. (2020) · Benchmarking: An International Journal · doi:10.1108/bij-12-2018-0413 · Cited by 48
Gupta, S., & Jaiswal, R. (2024) · The International Journal of Management Education · doi:10.1016/j.ijme.2024.101070 · Cited by 22
Metadata
- Authors
- Segars, A. H., & Grover, V.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 1993-12-01
- Volume
- 17
- Issue
- 4
- Pages
- 517-525
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1524121127
- Cited by
- 1,515
- References
- 6
- FWCI
- 27.30
- 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.