The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Influence of Experience on Personal Computer Utilization: Testing a Conceptual Model
Abstract
:The influence of prior experience on personal computer utilization was examined through an extension of a conceptual model developed and tested previously. Respondents were classified on the basis of their self-reported skill level and length of time having used personal computers. Three competing ways of modeling the influence of experience were tested: (1) a direct influence, (2) an indirect influence through six distinct altitude and belief components, and (3) a moderating influence on the relations between the attitude/belief components and utilization. The results suggested that experience influenced utilization directly, that indirect influences were present but less pronounced, and that the moderating influence of experience on the relations between five of six antecedent constructs and utilization was generally quite strong. For researchers, the implications are that prior experience with an information technology (In is an iimportant factor to include when developing, testing, or applying models of IT adoption and use. For practitioners, the results highlight the importance of emphasizing applilcability of the information technology to the current job and professional development early in the adoption process, with more emphasis on future benefits as experience is gained.
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
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
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
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006
Self-citationConsumer trust in an Internet store
Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000) · Information Technology and Management · doi:10.1023/a:1019104520776 · Cited by 2,577
Extending the technology acceptance model with task–technology fit constructs
Dishaw, M. T., & Strong, D. M. (1999) · Information & Management · doi:10.1016/s0378-7206(98)00101-3 · 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
Information technology acceptance by individual professionals: a model comparison approach
Chau, P. Y. K., & Hu, P. J. (2001) · Decision Sciences · doi:10.1111/j.1540-5915.2001.tb00978.x · Cited by 1,409
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
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
Adoption of new information technologies in rural small businesses
Premkumar, G., & Roberts, M. (1999) · Omega · doi:10.1016/s0305-0483(98)00071-1 · Cited by 1,108
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
Chau, P. Y. K., & Hu, P. J. (2002) · Journal of Management Information Systems · doi:10.1080/07421222.2002.11045699 · Cited by 707
Information System Success: Individual and Organizational Determinants
Sabherwal, R., Jeyaraj, A., & Chowa, C. (2006) · Management Science · doi:10.1287/mnsc.1060.0583 · Cited by 685
In Pursuit of Moderation: Nine Common Errors and Their Solutions1
Carte, T. A., & Russell, C. J. (2003) · MIS Quarterly · doi:10.2307/30036541 · Cited by 565
Manis, K. T., & Choi, D. (2019) · Journal of Business Research · doi:10.1016/j.jbusres.2018.10.021 · Cited by 494
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
Zhang, P. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.1.11 · Cited by 331
Investigating mobile wireless technology adoption: An extension of the technology acceptance model
Kim, S., & Garrison, G. (2009) · Information Systems Frontiers · doi:10.1007/s10796-008-9073-8 · Cited by 319
Understanding ERP system adoption from the user's perspective
Chang, M.-K., Cheung, W., Cheng, C.-H., & Yeung, J. H. Y. (2008) · International Journal of Production Economics · doi:10.1016/j.ijpe.2007.08.011 · Cited by 236
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
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
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
Why are experienced users of WeChat likely to continue using the app?
Gong, X., Liu, Z., Zheng, X., & Wu, T. (2018) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-10-2017-0246 · Cited by 47
Okorie Awa, H., Ukoha, O., & Emecheta, B. (2012) · InSITE Conference · doi:10.28945/1676 · Cited by 46
The use of the Internet in Hong Kong: Manufacturing vs. service
Cheng, C. H., Cheung, W., & Chang, M. K. (2002) · International Journal of Production Economics · doi:10.1016/s0925-5273(01)00179-7 · Cited by 25
Metadata
- Authors
- Thompson, R. L., Higgins, C. A., & Howell, J. M.
- Venue
- Journal of Management Information Systems
- Publisher
- Informa UK Limited
- Published
- 1994-06
- Volume
- 11
- Issue
- 1
- Pages
- 167-187
- ISSN
- 0742-1222 (ISSN-L)
- 1557-928X
- OpenAlex
- W1559269151
- Cited by
- 756
- References
- 2
- FWCI
- 16.99
- 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.
