The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Individual characteristics associated with World Wide Web use: an empirical study of playfulness and motivation
Open accessAbstract
This study examines the influence of the individual characteristic of playfulness on the use of the World Wide Web (WWW). Previous research suggests that microcomputer playfulness has an effect on computer usage in general, and we found support for a similar relationship in WWW use. Two samples of students were surveyed in this study; one consisting of undergraduate students and the other comprised of graduate students. Our findings also suggest that both intrinsic and extrinsic factors affect WWW use differentially for entertainment purposes and for course work purposes. Our study confirms previous research in that we found that ability to use the computer has a positive effect on WWW usage.
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
Extrinsic and Intrinsic Motivation to Use Computers in the Workplace 1
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1992.tb00945.x · Cited by 6,231 · cited 4×
“…on use for entertainment purposes and the effect on use for course requirement purposes, since there is evidence that extrinsic versus intrinsic factors may affect usage for work versus leisure differentially (Davis et al., 1992; Igbaria and Nachman, 1990; Igbaria, 1993; and Barnett, 1990).”
BackgroundMethodInfluential
Cited by
User Acceptance of Hedonic Information Systems1
van der Heijden, H. (2004) · MIS Quarterly · doi:10.2307/25148660 · Cited by 3,850
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
Sun, 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
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
What is user engagement? A conceptual framework for defining user engagement with technology
O'Brien, H. L., & Toms, E. G. (2008) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20801 · Cited by 1,397
Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation
Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005) · Information & Management · doi:10.1016/j.im.2003.10.007 · Cited by 1,184
What makes a useful online review? Implication for travel product websites
Liu, Z., & Park, S. (2015) · Tourism Management · doi:10.1016/j.tourman.2014.09.020 · Cited by 963
Roca, J. C., & Gagné, M. (2008) · Computers in Human Behavior · doi:10.1016/j.chb.2007.06.001 · Cited by 732
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
How Classroom Environment and Student Engagement Affect Learning in Internet-based MBA Courses
Arbaugh, J. B. (2000) · Business Communication Quarterly · doi:10.1177/108056990006300402 · Cited by 260
Baumel, A., Faber, K., Mathur, N., Kane, J. M., & Muench, F. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7270 · Cited by 206
“Our finding is congruent with previous studies suggesting that usability might need to be considered as a barrier to, rather than a facilitator of, effective interventions (eg, [59,60]).”
Lalmas, M., O’Brien, H., & Yom-Tov, E. (2015) · Synthesis Lectures on Information Concepts, Retrieval, and Services · doi:10.1007/978-3-031-02289-0 · Cited by 192
Measuring quality in online programs
McGorry, S. Y. (2003) · The Internet and Higher Education · doi:10.1016/s1096-7516(03)00022-8 · Cited by 185
The influence of user affect in online information disclosure
Wakefield, R. (2013) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2013.01.003 · Cited by 172
Baumel, A., & Kane, J. M. (2018) · Journal of Medical Internet Research · doi:10.2196/11491 · Cited by 131
Baumel, A., & Yom-Tov, E. (2018) · Translational Behavioral Medicine · doi:10.1093/tbm/ibx037 · Cited by 128
Analysis of Trust in Internet and Mobile Commerce Adoption
Cho, D.-Y., Kwon, H. J., & Lee, H.-Y. (2007) · 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07) · doi:10.1109/hicss.2007.76 · Cited by 120
A model of user adoption of interface agents for email notification
Serenko, A. (2008) · Interacting with Computers · doi:10.1016/j.intcom.2008.04.004 · Cited by 92
Bossman, A., & Agyei, S. K. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e09200 · Cited by 89
Stress, coping, and internet use of college students.
Deatherage, S., Servaty-Seib, H. L., & Aksoz, I. (2014) · Journal of American College Health · doi:10.1080/07448481.2013.843536 · Cited by 85
Toward an Understanding of Online Lending Intentions: Evidence from a Survey in China
Chen, D., Lou, H., & Van Slyke, C. (2015) · Communications of the Association for Information Systems · doi:10.17705/1cais.03617 · Cited by 54
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
An empirical study of an enjoyment‐based response hierarchy model of watching MDTV on the move
Wan‐Ling Hu, A., & Ming‐Hone Tsai, W. (2009) · Journal of Consumer Marketing · doi:10.1108/07363760910940438 · Cited by 15
Metadata
- Authors
- Atkinson, M., & Kydd, C.
- Venue
- ACM SIGMIS Database: the DATABASE for Advances in Information Systems
- Published
- 1997-04
- Volume
- 28
- Issue
- 2
- Pages
- 53-62
- ISSN
- 0095-0033 (ISSN-L)
- 1532-0936
- OpenAlex
- W2006755985
- Cited by
- 356
- References
- 1
- FWCI
- 17.58
- Type
- journal article
- Language
- en
- Open access
- bronze
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.
