Repairing Integrity-Based Trust Violations in Ascription Disputes for Potential E-Commerce Customers

In stock
SKU
46.4.06

Publication History

Received: August 15, 2018
Revised: July 26, 2020; April 17, 2021; November 7, 2021
Accepted: December 19, 2021
Published Online as Articles in Advance: November 23, 2022
Published in Issue: December 1, 2022

https://doi.org/10.25300/MISQ/2022/15679

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Abstract
<p><span style="font-weight: 400;">Trust violations of online sellers are widely reported in customer reviews and are often ascribed to the sellers’ lack of integrity. These reported violations reduce potential customers’ trust in the accused sellers, given the critical role of seller integrity in e-commerce. However, accused sellers and buyers often dispute the ascriptions of trust violations (e.g., sellers may argue that a violation is due to their lack of competence instead of their integrity). The trust repair literature has inadequately focused on effective strategies to repair reported integrity-based trust violations in ascription disputes. Drawing upon attribution theory and individuals’ cognitive sensemaking process regarding trust violations, we propose an account-based approach through re-ascription and stability attributions, enabling accused sellers to repair potential customers’ trust in them in the event of such disputes. We theorize the effectiveness of this approach by considering the contingent role of the accused seller’s reputation. The results of our laboratory experiments confirm the effectiveness of our approach in repairing potential customers’ trust for sellers with a high reputation but not for sellers with a low reputation. We further investigate the effectiveness of disclosing substantive amends (i.e., financial compensation) made by the accused seller to the victim as an alternative approach to repairing potential customers’ trust in sellers with a low reputation. The results reveal the significant effects of disclosing substantive amends on repairing potential customers’ trust in the seller, regardless of the seller’s reputation.</span></p>
Additional Details
Author Honglin Deng, Weiquan Wang, and Kai H. Lim
Year 2022
Volume 46
Issue 4
Keywords trust repair, trust violation, ascription, attribution, integrity, social accounts, substantive amends, laboratory experiment
Page Numbers 1983-2014
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