The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Performance Impacts of Information Technology: Is Actual Usage the Missing Link?
Abstract
The relationship between investment in information technology (IT) and its effect on organizational performance continues to interest academics and practitioners. In many cases, due to the nature of the research design employed, this stream of research has been unable to identify the impact of individual technologies on organizational performance. This study posits that the driver of IT impact is not the investment in the technology, but the actual usage of the technology. This proposition is tested in a longitudinal setting of a healthcare system comprising eight hospitals. Monthly data for a three–year period on various financial and nonfinancial measures of hospital performance and technology usage were analyzed. The data analysis provides evidence for the technology usage–performance link after controlling for various external factors. Technology usage was positively and significantly associated with measures of hospital revenue and quality, and this effect occurred after time lags. The analysis was triangulated using three measures of technology usage. The general support for the principal proposition of this paper that “actual usage” may be a key variable in explaining the impact of technology on performance suggests that omission of this variable may be a missing link in IT payoff analyses.
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
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 new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
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
Agarwal, R., & Prasad, J. (1997) · Decision Sciences · doi:10.1111/j.1540-5915.1997.tb01322.x · Cited by 1,669
Empirical Evaluation of the Revised Technology Acceptance Model
Szajna, B. (1996) · Management Science · doi:10.1287/mnsc.42.1.85 · Cited by 1,656
Cited by
Technology 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
Big data analytics and firm performance: Effects of dynamic capabilities
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J.-F., Dubey, R., & Childe, S. J. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.009 · Cited by 2,474
Zhu, K., & Kraemer, K. L. (2005) · Information Systems Research · doi:10.1287/isre.1050.0045 · Cited by 1,723
Zhu, K., Kraemer, K. L., & Xu, S. (2006) · Management Science · doi:10.1287/mnsc.1050.0487 · Cited by 1,440
Pavlou, P. A., & El Sawy, O. A. (2006) · Information Systems Research · doi:10.1287/isre.1060.0094 · Cited by 1,311
Metadata
- Authors
- Devaraj, S., & Kohli, R.
- Venue
- Management Science
- Published
- 2003-03
- Volume
- 49
- Issue
- 3
- Pages
- 273-289
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2117203175
- Cited by
- 1,413
- References
- 6
- FWCI
- 62.65
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Performance Impacts of Information Technology: Is Actual Usage the Missing Link? https://app.cochat.ai/papers/10.1287/mnsc.49.3.273.12736
- The paper
- Devaraj, S., & Kohli, R. (2003). Performance Impacts of Information Technology: Is Actual Usage the Missing Link? Management Science. https://doi.org/10.1287/mnsc.49.3.273.12736
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.
