Reexamining a Model for Evaluating Information Center Success Using a Structural Equation Modeling Approach
- 1 April 1997
- journal article
- research article
- Published by Wiley in Decision Sciences
- Vol. 28 (2) , 309-334
- https://doi.org/10.1111/j.1540-5915.1997.tb01313.x
Abstract
Structural equation modeling is a technique that has been widely used for instrument validation and model testing in research in marketing and organizational behavior. The technique has also been introduced to MIS researchers and used in several studies recently reported in the literature. This article offers an example of how the technique can be used for instrument validation and model testing. The illustration is made through a reexamination of a model for evaluating information center (IC) success. With the growth of end‐user computing, the success of an IC is more important than ever. Obtaining a valid model for measuring IC success is thus crucial to organizations with ICs. The results of this study highlight the importance of a strong theoretical base in developing such a valid model, and management should be cautious when using these models to assess the performance of their ICs.Keywords
This publication has 48 references indexed in Scilit:
- Re-Examining Perceived Ease of Use and Usefulness: A Confirmatory Factor AnalysisMIS Quarterly, 1993
- Information center management control measures: a survey and comparisonIEEE Transactions on Engineering Management, 1991
- Strategic and Operational Issues for the Successful Information CenterJournal of Information Systems Management, 1990
- Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information TechnologyMIS Quarterly, 1989
- Validating Instruments in MIS ResearchMIS Quarterly, 1989
- Critical Success Factors for Information Center ManagersMIS Quarterly, 1988
- The Measurement of End-User Computing SatisfactionMIS Quarterly, 1988
- An investigation of the information center from the user's perspectiveACM SIGMIS Database: the DATABASE for Advances in Information Systems, 1985
- Evaluating Structural Equation Models with Unobservable Variables and Measurement ErrorJournal of Marketing Research, 1981
- Convergent and discriminant validation by the multitrait-multimethod matrix.Psychological Bulletin, 1959