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Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs1
Abstract
The process of information technology adoption and use is critical to deriving the benefits of information technology. Yet from a conceptual standpoint, few empirical studies have made a distinction between individuals' pre-adoption and postadoption (continued use) beliefs and attitudes. This distinction is crucial in understanding and managing this process over time. The current study combines innovation diffusion and attitude theories in a theoretical framework to examine differences in pre-adoption and post-adoption beliefs and attitudes. The examination of Windows technology in a single organization indicates that users and potential adopters of information technology differ on their determinants of behavioral intention, attitude, and subjective norm. Potential adopter intention to adopt is solely determined by normative pressures, whereas user intention is solely determined by attitude. In addition, potential adopters base their attitude on a richer set of innovation characteristics than users. Whereas pre-adoption attitude is based on perceptions of usefulness, ease-of-use, result demonstrability, visibility, and trialability, post-adoption attitude is only based on instrumentality beliefs of usefulness and perceptions of image enhancements.
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Citations
Cites
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
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
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
Information Systems Success: The Quest for the Dependent Variable
DeLone, W. H., & McLean, E. R. (1992) · Information Systems Research · doi:10.1287/isre.3.1.60 · Cited by 10,697
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
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006
Bem, D. J. (1972) · Advances in Experimental Social Psychology · doi:10.1016/s0065-2601(08)60024-6 · Cited by 5,241
The Duality of Technology: Rethinking the Concept of Technology in Organizations
Orlikowski, W. J. (1992) · Organization Science · doi:10.1287/orsc.3.3.398 · Cited by 4,957
Mathieson, K. (1991) · Information Systems Research · doi:10.1287/isre.2.3.173 · Cited by 4,216
Cited by
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
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
(2003) · Journal of Management Information Systems · doi:10.1080/07421222.2003.11045748 · Cited by 11,791
Understanding Information Systems Continuance: An Expectation-Confirmation Model1
Bhattacherjee, A. (2001) · MIS Quarterly · doi:10.2307/3250921 · Cited by 8,767
Trust and TAM in Online Shopping: An Integrated Model1
Gefen, D., Karahanna, E., & Straub, D. W. (2003) · MIS Quarterly · doi:10.2307/30036519 · Cited by 8,635
Self-citationTechnology 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
Structural Equation Modeling and Regression: Guidelines for Research Practice
Gefen, D., Straub, D., & Boudreau, M.-C. (2000) · Communications of the Association for Information Systems · doi:10.17705/1cais.00407 · Cited by 6,416
Self-citationDeveloping and validating trust measures for e-commerce: an integrative typology
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002) · Information Systems Research · doi:10.1287/isre.13.3.334.81 · Cited by 5,550
Why do people use information technology? A critical review of the technology acceptance model
Legris, P., Ingham, J., & Collerette, P. (2003) · Information & Management · doi:10.1016/s0378-7206(01)00143-4 · Cited by 4,250
A Theoretical Integration of User Satisfaction and Technology Acceptance
Wixom, B. H., & Todd, P. A. (2005) · Information Systems Research · doi:10.1287/isre.1050.0042 · Cited by 2,835
Validation Guidelines for IS Positivist Research
Straub, D., & Gefen, D. (2004) · Communications of the Association for Information Systems · doi:10.17705/1cais.01324 · Cited by 2,797
Self-citationSun, P.-C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. (2008) · Computers & Education · doi:10.1016/j.compedu.2006.11.007 · Cited by 2,726
Pavlou, P. A., & Fygenson, M. (2006) · MIS Quarterly · doi:10.2307/25148720 · Cited by 2,685
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
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
Wu, J.-H., & Wang, S.-C. (2005) · Information & Management · doi:10.1016/j.im.2004.07.001 · Cited by 2,284
Harrison McKnight, D., Choudhury, V., & Kacmar, C. (2002) · The Journal of Strategic Information Systems · doi:10.1016/s0963-8687(02)00020-3 · Cited by 2,164
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
Self-citationBhattacherjee, A., & Premkumar, G. (2004) · MIS Quarterly · doi:10.2307/25148634 · Cited by 1,764
Understanding e-learning continuance intention: An extension of the Technology Acceptance Model
Roca, J. C., Chiu, C.-M., & Martínez, F. J. (2006) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2006.01.003 · Cited by 1,399
The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents1
Komiak, S. Y. X., & Benbasat, I. (2006) · MIS Quarterly · doi:10.2307/25148760 · Cited by 1,374
Informational influence in organizations: An integrated approach to knowledge adoption
Sussman, S. W., & Siegal, W. S. (2003) · Information Systems Research · doi:10.1287/isre.14.1.47.14767 · Cited by 1,250
Vijayasarathy, L. R. (2004) · Information & Management · doi:10.1016/j.im.2003.08.011 · Cited by 1,218
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
The Role of Espoused National Cultural Values in Technology Acceptance1
Srite, M., & Karahanna, E. (2006) · MIS Quarterly · doi:10.2307/25148745 · Cited by 1,169
Self-citationYi, 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
A Review of the Predictors, Linkages, and Biases in IT Innovation Adoption Research
Jeyaraj, A., Rottman, J. W., & Lacity, M. C. (2006) · Journal of Information Technology · doi:10.1057/palgrave.jit.2000056 · Cited by 1,136
Investigating User Resistance to Information Systems Implementation: A Status Quo Bias Perspective1
Kim, H.-W., & Kankanhalli, A. (2009) · MIS Quarterly · doi:10.2307/20650309 · Cited by 1,135
Angst, C. M., & Agarwal, R. (2009) · MIS Quarterly · doi:10.2307/20650295 · Cited by 1,043
Determining Uses and Gratifications for the Internet
Stafford, T. F., Stafford, M. R., & Schkade, L. L. (2004) · Decision Sciences · doi:10.1111/j.00117315.2004.02524.x · Cited by 1,010
Inexperience and experience with online stores: the importance of TAM and trust
Gefen, D., Karahanna, E., & Straub, D. W. (2003) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2003.817277 · Cited by 965
Self-citationConsumer experiences, attitude and behavioral intention toward online food delivery (OFD) services
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.12.013 · Cited by 956
Hong, S., Thong, J. Y. L., & Tam, K. Y. (2006) · Decision Support Systems · doi:10.1016/j.dss.2006.03.009 · Cited by 955
Lin, H.-F. (2011) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2010.07.006 · Cited by 912
Wu, I.-L., & Chen, J.-L. (2005) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2005.03.003 · Cited by 879
Understanding User Responses to Information Technology: A Coping Model of User Adaptation1
Beaudry, A., & Pinsonneault, A. (2005) · MIS Quarterly · doi:10.2307/25148693 · Cited by 869
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
Dead Or Alive? The Development, Trajectory And Future Of Technology Adoption Research.
University of Arkansas, Venkatesh, V., Davis, F., University of Arkansas, Morris, M., & University of Virginia (2007) · Journal of the Association for Information Systems · doi:10.17705/1jais.00120 · Cited by 789
Leonardi, P. M., & Barley, S. R. (2010) · Academy of Management Annals · doi:10.5465/19416521003654160 · Cited by 733
Avoidance of Information Technology Threats: A Theoretical Perspective1
Liang, H., & Xue, Y. (2009) · MIS Quarterly · doi:10.2307/20650279 · Cited by 733
Chau, P. Y. K., & Hu, P. J. (2002) · Journal of Management Information Systems · doi:10.1080/07421222.2002.11045699 · Cited by 707
Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2011.08.019 · Cited by 679
Determinants of customer repurchase intention in online shopping
Chiu, C., Chang, C., Cheng, H., & Fang, Y. (2009) · Online Information Review · doi:10.1108/14684520910985710 · Cited by 657
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
Davis, F. D., & Venkatesh, V. (2004) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2003.822468 · Cited by 582
It's all about attitude: revisiting the technology acceptance model
Yang, H.-D., & Yoo, Y. (2004) · Decision Support Systems · doi:10.1016/s0167-9236(03)00062-9 · Cited by 578
Predicting collaboration technology use: integrating technology adoption and collaboration research
Brown, S. A., Dennis, A. R., & Venkatesh, V. (2010) · Journal of Management Information Systems · doi:10.2753/mis0742-1222270201 · Cited by 592
Sharma, R., Yetton, P., & Crawford, J. (2009) · MIS Quarterly · doi:10.2307/20650305 · Cited by 496
Manis, K. T., & Choi, D. (2019) · Journal of Business Research · doi:10.1016/j.jbusres.2018.10.021 · Cited by 494
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
TUNG, F., CHANG, S., & CHOU, C. (2008) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2007.06.006 · Cited by 476
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
Albayati, H., Kim, S. K., & Rho, J. J. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101320 · Cited by 464
A Meta-Analysis of Research on Information Technology Implementation in Small Business
Premkumar, G. (2003) · Journal of Organizational Computing and Electronic Commerce · doi:10.1207/s15327744joce1302_2 · Cited by 444
A conceptual model for the process of IT innovation adoption in organizations
Hameed, M. A., Counsell, S., & Swift, S. (2012) · Journal of Engineering and Technology Management · doi:10.1016/j.jengtecman.2012.03.007 · Cited by 442
Clohessy, T., & Acton, T. (2019) · Industrial Management & Data Systems · doi:10.1108/imds-08-2018-0365 · Cited by 436
Al-Rahmi, W. M., Yahaya, N., Aldraiweesh, A. A., Alamri, M. M., Aljarboa, N. A., Alturki, U., & Aljeraiwi, A. A. (2019) · IEEE Access · doi:10.1109/access.2019.2899368 · Cited by 435
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
Adopters and non-adopters of e-procurement in Singapore: An empirical study
Teo, T. S. H., Lin, S., & Lai, K.-H. (2009) · Omega · doi:10.1016/j.omega.2008.11.001 · Cited by 397
How perceptions of intelligence and anthropomorphism affect adoption of personal intelligent agents
Moussawi, S., Koufaris, M., & Benbunan-Fich, R. (2021) · Electronic Markets · doi:10.1007/s12525-020-00411-w · Cited by 406
Beyond usability: Designing effective technology implementation systems to promote patient safety
Karsh, B.-T. (2004) · Quality and Safety in Health Care · doi:10.1136/qshc.2004.010322 · Cited by 414
Schaper, L. K., & Pervan, G. P. (2007) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2006.05.028 · Cited by 371
Lee, Y., & Kwon, O. (2011) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2010.11.005 · Cited by 343
Kim, S. S., & Son, J.-Y. (2009) · MIS Quarterly · doi:10.2307/20650278 · Cited by 339
Kim, M. J., Lee, C.-K., & Preis, M. W. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2020.101349 · Cited by 361
A unified model of IT continuance: Three complementary perspectives and crossover effects
Bhattacherjee, A., & Lin, C.-P. (2015) · European Journal of Information Systems · doi:10.1057/ejis.2013.36 · Cited by 336
Zhang, P. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.1.11 · Cited by 331
Senior citizens’ acceptance of information systems: A study in the context of e-government services
Phang, C. W., Sutanto, J., Kankanhalli, A., Li, Y., Tan, B. C. Y., & Teo, H.-H. (2006) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2006.883710 · Cited by 331
Cho, V., Cheng, T. C. E., & Lai, W. M. J. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.01.014 · Cited by 329
Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement
Nadal, C., Sas, C., & Doherty, G. (2020) · Journal of Medical Internet Research · doi:10.2196/17256 · Cited by 320
Understanding the intention to follow the advice obtained in an online travel community
Casaló, L. V., Flavián, C., & Guinalíu, M. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2010.04.013 · Cited by 318
(2004) · Journal of the Association for Information Systems · 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
Factors affecting adoption of online banking: A meta-analytic structural equation modeling study
Montazemi, A. R., & Qahri-Saremi, H. (2015) · Information & Management · doi:10.1016/j.im.2014.11.002 · Cited by 293
Hsieh, J.-K., Hsieh, Y.-C., Chiu, H.-C., & Feng, Y.-C. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2012.05.010 · Cited by 291
Technology acceptance: a meta-analysis of the TAM: part 2
Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2007) · Journal of Modelling in Management · doi:10.1108/17465660710834462 · Cited by 257
A meta-analysis of the UTAUT model: Eleven years later
Khechine, H., Lakhal, S., & Ndjambou, P. (2016) · Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l'Administration · doi:10.1002/cjas.1381 · Cited by 246
Gamal Aboelmaged, M. (2010) · Industrial Management & Data Systems · doi:10.1108/02635571011030042 · Cited by 240
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
E-banking users’ behaviour: e-service quality, attitude, and customer satisfaction
Ayo, C. K., Oni, A. A., Adewoye, O. J., & Eweoya, I. O. (2016) · International Journal of Bank Marketing · doi:10.1108/ijbm-12-2014-0175 · Cited by 206
Al-Rahmi, W. M., Alias, N., Othman, M. S., Alzahrani, A. I., Alfarraj, O., Saged, A. A., & Abdul Rahman, N. S. (2018) · IEEE Access · doi:10.1109/access.2018.2802325 · Cited by 204
Jin, S. V., & Youn, S. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2129277 · Cited by 201
Understanding antecedents of continuance intention in social-networking services
Kim, B. (2011) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2010.0009 · Cited by 201
AI-augmented HRM: Antecedents, assimilation and multilevel consequences
Prikshat, V., Malik, A., & Budhwar, P. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2021.100860 · Cited by 200
Predicting the continued use of Internet-based learning technologies: the role of habit
Limayem, M., & Cheung, C. M. K. (2011) · Behaviour & Information Technology · doi:10.1080/0144929x.2010.490956 · Cited by 191
Modeling Influences on Impulse Purchasing Behaviors During Online Marketing Transactions
Zhang, X., Prybutok, V. R., & Strutton, D. (2007) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679150106 · Cited by 183
Teenagers in social virtual worlds: Continuous use and purchasing behavior in Habbo Hotel
Mäntymäki, M., & Salo, J. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.06.003 · Cited by 178
Factors affecting late adoption of digital innovations
Jahanmir, S. F., & Cavadas, J. (2018) · Journal of Business Research · doi:10.1016/j.jbusres.2018.01.058 · Cited by 177
Magni, M., Susan Taylor, M., & Venkatesh, V. (2010) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2010.03.004 · Cited by 173
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
User acceptance of media tablets: An empirical examination of perceived value
Yu, J., Lee, H., Ha, I., & Zo, H. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2015.11.004 · Cited by 161
Mobile shopping motivation: an application of multiple discriminant analysis
Yang, K., & Kim, H. (2012) · International Journal of Retail & Distribution Management · doi:10.1108/09590551211263182 · Cited by 160
Mäntymäki, M., Islam, A. K. M. N., & Benbasat, I. (2020) · Information Systems Journal · doi:10.1111/isj.12262 · Cited by 171
Park, N. (2010) · Journal of Communication · doi:10.1111/j.1460-2466.2009.01440.x · Cited by 141
Why do users trust algorithms? A review and conceptualization of initial trust and trust over time
Cabiddu, F., Moi, L., Patriotta, G., & Allen, D. G. (2022) · European Management Journal · doi:10.1016/j.emj.2022.06.001 · Cited by 138
Mahzan, N., & Lymer, A. (2014) · Managerial Auditing Journal · doi:10.1108/maj-05-2013-0877 · Cited by 138
Attitudinal and Intentional Acceptance of Domestic Robots by Younger and Older Adults
Ezer, N., Fisk, A. D., & Rogers, W. A. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-02710-9_5 · Cited by 134
Mahmud, I., Ramayah, T., & Kurnia, S. (2017) · Information Systems · doi:10.1016/j.is.2017.05.005 · Cited by 131
Towards reinforcing telemedicine adoption amongst clinicians in Nigeria
Adenuga, K. I., Iahad, N. A., & Miskon, S. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.05.008 · Cited by 120
Rethinking determinants of ICT acceptance: towards an integrated and comprehensive overview
Verdegem, P., & De Marez, L. (2011) · Technovation · doi:10.1016/j.technovation.2011.02.004 · Cited by 119
Metadata
- Authors
- Karahanna, E., Straub, D. W., & Chervany, N. L.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 1999-06-01
- Volume
- 23
- Issue
- 2
- Pages
- 183-213
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1548408014
- Cited by
- 3,692
- References
- 13
- FWCI
- 112.79
- Type
- journal article
- Language
- en
- Open access
- closed
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