Determinants of service quality and continuance intention of online services: The case of eTax
Abstract
Abstract This article examines the determinants of service quality and continuance intention of online services. We proposed and empirically tested a model with both service and technology characteristics as the main drivers of service quality and subsequent continuance intention of eTax, an electronic government (eGovernment) service that enables citizens to file their taxes online. Our data were collected via a two‐stage longitudinal online survey of 518 participants before and after they made use of the eTax service in Hong Kong. The results showed that both service characteristics (i.e., security and convenience) and one of the technology characteristics (i.e., perceived usefulness, but not perceived ease of use) were the key determinants of service quality. Another interesting and important finding that runs counter to the vast body of empirical evidence on predicting intention is that perceived usefulness was not the strongest predictor of continuance intention but rather service quality was. To provide a richer picture of these relationships, we also conducted a post‐hoc analysis of the effects of service and technology characteristics on the individual dimensions of service quality and their subsequent impact on continuance intention and found assurance and reliability to be the only significant predictors of continuance intention. We present implications for research and practice related to online services.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Continuance intention has been empirically utilized as the endogenous factor in the case of online auctions, online banking, e-Tax and e-commerce.
“Therefore, it has been empirically utilized as the endogenous factor in the case of online auctions [18], online banking [9], e-Tax [86] and e-commerce [87].”
From Investigating the Impact of Critical Factors on Continuance Intention towards Cross-Border Shopping Websites (2019) · cites this paper as [86]
The citation lists haven’t been fetched yet
References 131 · Cited by 139
- Authors
- Hu, P. J., Brown, S. A., Thong, J. Y. L., Chan, F. K. Y., & Tam, K. Y.
- Affiliations
- University of Utah (US)
- University of Arizona (US)
- Hong Kong University of Science and Technology (HK)
- Corresponding author
- Hu, Paul Jen‐Hwa
- Brown, Susan A.
- Thong, James Y.L.
- Chan, Frank K.Y.
- Tam, Kar Yan
- Venue
- Journal of the American Society for Information Science and Technology
- Publisher
- Wiley
- Published
- 2008-10-16
- Volume
- 60
- Issue
- 2
- Pages
- 292-306
- ISSN
- 1532-2882 (ISSN-L)
- 1532-2890
- OpenAlex
- W3122838568
- Cited by
- 139
- References
- 131
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 4 · 2023: 10 · 2022: 15 · 2021: 8 · 2020: 8 · 2019: 15 · 2018: 8 · 2017: 7 · 2016: 15 · 2015: 13 · 2014: 10 · 2013: 6 · 2012: 6
- FWCI
- 7.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Society for Information Science and Technology (publishedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- Hong Kong University of Science and Technology
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Keywords
- service quality, continuance intention, online services, e-government, tax return filing, perceived usefulness, perceived ease of use, security (computing), convenience, assurance, reliability, technology characteristics, service attributes
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