The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Reexamining a Model for Evaluating Information Center Success Using a Structural Equation Modeling Approach
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.
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Self-citationThe Impact of Technostress on Role Stress and Productivity
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Self-citationTrust and risk in e-government adoption
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Self-citatione-Government Adoption Model (GAM): Differing service maturity levels
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Investigating the effects of smart technology on customer dynamics and customer experience
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Antecedents of Customer Loyalty in Banking Sector: A Mediational Study
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An Analysis of Factors Affecting User Acceptance of ERP Systems in the United States
Bandyopadhyay, K., & Barnes, C. (2012) · International Journal of Human Capital and Information Technology Professionals · doi:10.4018/jhcitp.2012010101 · Cited by 19
Metadata
- Authors
- Chau, P. Y. K.
- Venue
- Decision Sciences
- Publisher
- Wiley
- Published
- 1997-04
- Volume
- 28
- Issue
- 2
- Pages
- 309-334
- ISSN
- 0011-7315 (ISSN-L)
- 1540-5915
- OpenAlex
- W2010983589
- Cited by
- 854
- References
- 6
- FWCI
- 19.54
- 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).
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