The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
An empirical test of the DeLone-McLean model of information system success
Abstract
This paper tests the model of information system success proposed by DeLone and McLean using a field study of a mandatory information system. The results show that perceived system quality and perceived information quality are significant predictors of user satisfaction with the system, but not of system use. Perceived system quality was also a significant predictor of system use. User satisfaction was found to be a strong predictor of individual impact, whereas the influence of system use on individual impact was insignificant.
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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
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
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
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
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 1×
“…significant empirical evidence of the indirect effect of perceived ease of use (Davis, 1989; Davis et al., 1989; Mathieson, 1991; Adams et al., 1992; Davis et al., 1992; Igbaria et al., 1995; Igbaria & Iivari, 1995; Chau, 1996; Igbaria et al., 1996; Szajna, 1996; Taylor & Todd, 1995,…”
BackgroundMathieson, K. (1991) · Information Systems Research · doi:10.1287/isre.2.3.173 · Cited by 4,216
Empirical Evaluation of the Revised Technology Acceptance Model
Szajna, B. (1996) · Management Science · doi:10.1287/mnsc.42.1.85 · Cited by 1,656
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
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
Cited by
Evaluating E-learning systems success: An empirical study
Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2019.08.004 · Cited by 1,350
Investigating users’ perspectives on e-learning: An integration of TAM and IS success model
Mohammadi, H. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.07.044 · Cited by 779
Research on information systems failures and successes: Status update and future directions
Dwivedi, Y. K., Wastell, D., Laumer, S., Henriksen, H. Z., Myers, M. D., Bunker, D., Elbanna, A., Ravishankar, M. N., & Srivastava, S. C. (2015) · Information Systems Frontiers · doi:10.1007/s10796-014-9500-y · Cited by 448
An investigation on physicians’ acceptance of hospital information systems: A case study
Chen, R.-F., & Hsiao, J.-L. (2012) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2012.05.003 · Cited by 150
Mobile application user behavior in the developing countries: A survey in Iran
Hajiheydari, N., & Ashkani, M. (2018) · Information Systems · doi:10.1016/j.is.2018.05.004 · Cited by 73
Metadata
- Authors
- Iivari, J.
- Venue
- ACM SIGMIS Database: the DATABASE for Advances in Information Systems
- Published
- 2005-06-07
- Volume
- 36
- Issue
- 2
- Pages
- 8-27
- ISSN
- 0095-0033 (ISSN-L)
- 1532-0936
- OpenAlex
- W2090676165
- Cited by
- 701
- References
- 11
- FWCI
- 34.99
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
