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Cited by 394

The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.

What determines success of an e-government service? Validation of an integrative model of e-filing continuance usage

Open access
Veeramootoo, Narvadha, Nunkoo, Robin, Dwivedi, Yogesh K.·2018·Government Information Quarterly

Abstract

Abstract The purpose of this study is to validate an integrated model of e-filing continuance usage. The model has its theoretical basis in the expectancy confirmation theory and the DeLone and McLean's IS Success model. The model is extended to include two additional constructs relevant to e-filing continuance usage: perceived risks and habit. The model is tested using data collected from a sample of 645 e-filing users in Mauritius. Structural equation modeling was used to test the hypotheses. Findings suggest that citizens' continuance usage intention of e-filing is influenced by system quality, user satisfaction and habit. User satisfaction had the strongest impact on e-filing continuance usage intention. This study makes a valuable contribution to knowledge through the extension and validation of the ECM and IS Success model to explore salient factors affecting e-filing continuance usage intention. The practical implications of the findings for tax collection agencies are discussed.

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Metadata

Authors
Veeramootoo, N., Nunkoo, R., & Dwivedi, Y. K.
Venue
Government Information Quarterly
Publisher
Elsevier BV
Published
2018-04
Volume
35
Issue
2
Pages
161-174
ISSN
0740-624X (ISSN-L)
OpenAlex
W2793319820
Cited by
394
References
113
FWCI
47.53
Type
journal article
Language
en
Open access
green

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Veeramootoo, N., Nunkoo, R., & Dwivedi, Y. K. (2018). What determines success of an e-government service? Validation of an integrative model of e-filing continuance usage. Government Information Quarterly. https://doi.org/10.1016/j.giq.2018.03.004

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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.