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Cited by 367

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Examining the integrated influence of fairness and quality on learners’ satisfaction and Web‐based learning continuance intention

Chiu, Chao‐Min, Chiu, Chao‐Sheng, Chang, Hae‐Ching·2007·Information Systems Journal
DOI 10.1111/j.1365-2575.2007.00238.x
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Abstract

Abstract. As with any other information system (IS), the success of Web‐based learning depends largely on user satisfaction and other factors that eventually increase users’ intentions to continue using the service (continuance intention). This research integrates the IS success model and fairness theory to construct a model for investigating the motivations behind learners’ intentions to continue using Web‐based learning. Our model theorizes that the three dimensions of quality (i.e. information, system and service) and the three dimensions of fairness (i.e. distributive, procedural and interactional) affect learners’ satisfaction. We also argue that satisfaction and the three dimensions of fairness will influence learners’ intention to continue using Web‐based learning. The hypothesized model is validated empirically using data collected from 289 learners of a Web‐based learning service. The results show that information quality, system quality, system use, distributive fairness and interactional fairness exhibit significant positive effects on satisfaction. Also, procedural fairness and satisfaction play significant roles in shaping learners’ intention to continue using Web‐based learning.

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Metadata

Authors
Chiu, C., Chiu, C., & Chang, H.
Venue
Information Systems Journal
Publisher
Wiley
Published
2007-06-06
Volume
17
Issue
3
Pages
271-287
ISSN
  • 1350-1917 (ISSN-L)
  • 1365-2575
DOI
10.1111/j.1365-2575.2007.00238.x
OpenAlex
W2121538731
Cited by
367
References
15
FWCI
19.58
Type
journal article
Language
en
Open access
closed

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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).

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