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Cited by 183

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

In Justice We Trust: Predicting User Acceptance of E-Customer Services

Turel, Ofir, Yuan, Yufei, Connelly, Catherine E.·2008·Journal of Management Information Systems

Abstract

High-quality customer service is an integral part of any successful enterprise, but providing it can be a challenge for online merchants, especially when customers are complaining about each other. This study examines how justice and trust affect user acceptance of e-customer services by conducting an online experiment involving 380 participants. The results suggest that trust in the e-customer service fully mediates the effects of trust in the service representative and procedural justice on intentions to reuse the e-customer service. Furthermore, the effect of distributive justice on trust in the e-customer service was fully mediated by trust in the e-service representative. Finally, the effect of informational justice on user intentions to reuse the e-customer service was partially mediated by trust in the service representative and trust in the e-customer service. Theoretical and practical implications are further discussed.

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Metadata

Authors
Turel, O., Yuan, Y., & Connelly, C. E.
Venue
Journal of Management Information Systems
Published
2008-04
Volume
24
Issue
4
Pages
123-151
ISSN
  • 0742-1222 (ISSN-L)
  • 1557-928X
OpenAlex
W1997423894
Cited by
183
References
12
FWCI
24.09
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: In Justice We Trust: Predicting User Acceptance of E-Customer Services. https://app.cochat.ai/papers/10.2753/mis0742-1222240405
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Turel, O., Yuan, Y., & Connelly, C. E. (2008). In Justice We Trust: Predicting User Acceptance of E-Customer Services. Journal of Management Information Systems. https://doi.org/10.2753/mis0742-1222240405

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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.