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Toward an Understanding of the Behavioral Intention to Use an Information System
Abstract
Organizational investment in information systems is often large and risky given the variety of information requirements placed on systems today. To make more informed decisions and to meet the challenge of developing systems that satisfy these demands, system developers need to achieve a better understanding of factors that ultimately lead to system usage. To enhance this understanding, we posit a holistic framework to examine several constructs suggested in the literature that lead to the behavioral intention to use an information system. Our framework includes situational involvement, intrinsic involvement, argument for change, perceived usefulness, ease of use, prior usage, and attitude constructs. We extend the Davis, Bagozzi, and Warshaw Technology Acceptance Model (TAM), which is founded on the Theory of Reasoned Action. A diverse sample from industry is used to test our model. Structural equation modeling is used to examine the entire pattern of intercorrelations among the constructs and to test related propositions. A hierarchical structure is used to compare the explanatory ability of TAM with our extension. Our model explains a large portion of the covariance among the constructs that lead to a user's behavioral intention to use an information system and compares favorably with TAM. The results indicate that (1) the direct effect of situational involvement on behavioral intention as well as attitude is significant in the negative direction, (2) attitude seems to play a mediating role, and (3) intrinsic involvement plays a significant role in shaping perceptions. Finally, we conclude that the user involvement construct needs to be separated into its psychological as well as its participative components for developers to understand its impact on the systems development process.
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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
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
Comparative fit indexes in structural models.
Bentler, P. M. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.107.2.238 · Cited by 25,266
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
Mathieson, K. (1991) · Information Systems Research · doi:10.1287/isre.2.3.173 · Cited by 4,216
User Involvement and MIS Success: A Review of Research
Ives, B., & Olson, M. H. (1984) · Management Science · doi:10.1287/mnsc.30.5.586 · Cited by 1,318
Management Information Systems: Appreciation and Involvement
Swanson, E. B. (1974) · Management Science · doi:10.1287/mnsc.21.2.178 · Cited by 529
Chaiken, S., & Stangor, C. (1987) · Annual Review of Psychology · doi:10.1146/annurev.ps.38.020187.003043 · Cited by 518
Attitude-behavior relations: A comparison of the Fishbein-Ajzen and the Bentler-Speckart models
Fredricks, A. J., & Dossett, D. L. (1983) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.45.3.501 · Cited by 290
Cited by
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 meta-analysis of the technology acceptance model
King, W. R., & He, J. (2006) · Information & Management · doi:10.1016/j.im.2006.05.003 · Cited by 2,906
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
The utilization of e-government services: citizen trust, innovation and acceptance factors
Carter, L., & Bélanger, F. (2005) · Information Systems Journal · doi:10.1111/j.1365-2575.2005.00183.x · Cited by 2,207
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019) · Information Systems Frontiers · doi:10.1007/s10796-017-9774-y · Cited by 2,137
“While devising the TAM extension (TAME) model, Jackson et al. (1997) called the researchers to investigate whether perceived usefulness and perceived ease of use influence attitude.”
MethodUnderstanding 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
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
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
Modelling technology acceptance in education: A study of pre-service teachers
Teo, T. (2009) · Computers & Education · doi:10.1016/j.compedu.2008.08.006 · Cited by 1,009
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
Hong, S., Thong, J. Y. L., & Tam, K. Y. (2006) · Decision Support Systems · doi:10.1016/j.dss.2006.03.009 · Cited by 955
An extension of the technology acceptance model in an ERP implementation environment
Amoako-Gyampah, K., & Salam, A. F. (2004) · Information & Management · doi:10.1016/j.im.2003.08.010 · Cited by 922
Kleijnen, M., de Ruyter, K., & Wetzels, M. (2007) · Journal of Retailing · doi:10.1016/j.jretai.2006.10.004 · Cited by 898
An empirical study of the factors affecting social network service use
Kwon, O., & Wen, Y. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2009.04.011 · Cited by 722
Exploring factors affecting the adoption of mobile commerce in Singapore
Yang, K. C. C. (2005) · Telematics and Informatics · doi:10.1016/j.tele.2004.11.003 · Cited by 656
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
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
Consumer attitude and intention to adopt mobile wallet in India – An empirical study
Chawla, D., & Joshi, H. (2019) · International Journal of Bank Marketing · doi:10.1108/ijbm-09-2018-0256 · Cited by 518
Manis, K. T., & Choi, D. (2019) · Journal of Business Research · doi:10.1016/j.jbusres.2018.10.021 · Cited by 494
Kim, T. G., Lee, J. H., & Law, R. (2008) · Tourism Management · doi:10.1016/j.tourman.2007.05.016 · Cited by 369
THONG, J. Y. L., HONG, W., & TAM, K.-Y. (2002) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(02)91024-4 · Cited by 347
Amoako-Gyampah, K. (2007) · Computers in Human Behavior · doi:10.1016/j.chb.2004.12.002 · Cited by 345
Obstacles to social networking website use among older adults
Braun, M. T. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2012.12.004 · Cited by 337
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
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
Al-Rahmi, W. M., & Zeki, A. M. (2017) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2016.09.002 · Cited by 214
A model of customer satisfaction and retention for hotels
Sim, J., Mak, B., & Jones, D. (2006) · Journal of Quality Assurance in Hospitality & Tourism · doi:10.1300/j162v07n03_01 · Cited by 153
Determinants of service quality and continuance intention of online services: The case of eTax
Hu, P. J., Brown, S. A., Thong, J. Y. L., Chan, F. K. Y., & Tam, K. Y. (2009) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20956 · Cited by 139
Park, N. (2010) · Journal of Communication · doi:10.1111/j.1460-2466.2009.01440.x · Cited by 141
ERP implementation factors: A comparison of managerial and end‐user perspectives
Amoako‐Gyampah, K. (2004) · Business Process Management Journal · doi:10.1108/14637150410530244 · Cited by 115
Ramkumar, M., Schoenherr, T., Wagner, S. M., & Jenamani, M. (2019) · International Journal of Production Economics · doi:10.1016/j.ijpe.2019.06.003 · Cited by 96
Clinical acceptance of a low-cost portable system for postural assessment
Van Schaik, P., Bettany-Saltikov, J. A., & Warren, J. G. (2002) · Behaviour & Information Technology · doi:10.1080/01449290110107236 · Cited by 93
Kifle, M., Payton, F. C., Mbarika, V., & Meso, P. (2010) · Telemedicine and e-Health · doi:10.1089/tmj.2009.0008 · Cited by 51
Augmented sport: exploring collective user experience
Pallot, M., Eynard, R., Poussard, B., Christmann, O., & Richir, S. (2013) · Proceedings of the Virtual Reality International Conference: Laval Virtual · doi:10.1145/2466816.2466821 · Cited by 32
Determinants of digitally instigated insurance relationships
Gidhagen, M., & Gebert Persson, S. (2011) · International Journal of Bank Marketing · doi:10.1108/02652321111177803 · Cited by 20
An Analysis of Factors Affecting User Acceptance of ERP Systems in the United States
Bandyopadhyay, K., & Barnes, C. (2012) · International Journal of Human Capital and Information Technology Professionals · doi:10.4018/jhcitp.2012010101 · Cited by 19
Metadata
- Authors
- Jackson, C. M., Chow, S., & Leitch, R. A.
- Venue
- Decision Sciences
- Publisher
- Wiley
- Published
- 1997-04
- Volume
- 28
- Issue
- 2
- Pages
- 357-389
- ISSN
- 0011-7315 (ISSN-L)
- 1540-5915
- OpenAlex
- W2034338878
- Cited by
- 752
- References
- 10
- FWCI
- 15.63
- Type
- journal article
- Language
- en
- Open access
- closed
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