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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 reascription 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 forsellers 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. [ABSTRACT FROM AUTHOR]

Online social cues that utilize user-generated data, such as user reviews and product ratings, have become one of the key factors influencing online user behavior and decisions. Online users who shared their reviews and ratings about a product (or a seller) become an abstract reference group to a focal user interested in the same product. This study focuses on sponsored search results (SSRs), a type of unsolicited information that matches users' search queries and receives high evaluations from prior consumers. We investigate the effects of positive social cues on alleviating users' avoidance responses toward an encountered SSR when searching for a product in a C2C e-commerce context. We synthesize the avoidance literature and identify three forms of SSR avoidance, namely, cognitive, behavioral, and affective avoidance. We apply users' implicit concerns on SSRs to explain users' avoidance of an encountered SSR. In addition, we extend social influence theory to online settings where abstract reference groups are posited to trigger social influence. We examine how and under what conditions the three forms of SSR avoidance can be reduced by various positive online social cues (i.e., product- and seller-related). We conduct three laboratory experiments. Results attest to users' implicit concerns on SSRs and their avoidance of SSRs and reveal different effects of various social cues on reducing the three forms of SSR avoidance. This study uncovers the theoretical mechanisms of social influence on reducing SSR avoidance in online settings. It also offers practical implications for online search service providers to help online users' decision making in their search process. [ABSTRACT FROM AUTHOR]

In today’s emerging and competitive e-marketplaces, sellers must take competitive action to improve their sales performance. E-marketplace platform operators offer sellers a portfolio of platform-based functions that are intended to enhance competitiveness. However, little is known about how these platform-based functions can be used at the repertoire level to improve the sales performance of e-marketplace sellers. Extending the competitive repertoire theory to the e-marketplace context and integrating it with the e-commerce literature on reputation, we posit that a seller could improve sales performance by using these functions as a repertoire, featuring such structural characteristics as large volume, high complexity, and heterogeneity. We also posit that the performance impact of this repertoire approach to function use varies depending on seller reputation, manifested as customer rating. We empirically examined the hypotheses with a unique longitudinal dataset consisting of 43,992 seller-week observations from Taobao, one of the largest e-marketplaces in the world. Our analyses yield a set of interesting findings that unveil more nuanced theoretical relationships between different structural characteristics of the platform-based function repertoire and sales performance under different levels of seller reputation. We elaborate on how these findings contribute to the e-marketplace literature in the information systems field and the competitive action research in the strategy field. We also discuss implications for practice and make suggestions for future work. [ABSTRACT FROM AUTHOR]

By tracking consumers’ browsing and purchase history, web personalization generates taste-matched recommendations for each consumer to stimulate purchases. In addition to taste-matching, mobile personalization matches recommendations to a consumer’s physiological need and current location. These two additional features, referred to as need-matching and location-matching, are believed to be enablers of unplanned purchases. However, mobile advertisers may not be able to generate recommendations that meet all personalization criteria. Hence, mobile recommendations may be imperfect. We examine two questions in relation to imperfect recommendations. First, how do we use a descriptor to promote such recommendations? Second, what personalization criterion should be downplayed to induce unplanned purchases? Drawing upon the theory of mood congruence, we theorize that the effect of imperfect recommendation on consumers’ unplanned purchases depends on their mood. We conducted three field experiments to test our hypotheses. Our findings indicate that (1) consumers in positive moods are more likely to form an urge to buy than those in negative moods, and this difference is larger when the descriptor is partial than when it is complete (Experiment 1); (2) need-matching is more influential on urge to buy for consumers in negative moods than for those in positive moods (Experiment 2); and (3) for taste-and-need-matched recommendations, location-matching exerts a stronger effect on the urge to buy for consumers in negative moods than for those in positive moods (Experiment 3). We validated the relevance of our research findings to practice through interviews with senior executives in personalization solution providers. Pathways for enhancing practical impacts of this line of research are recommended. [ABSTRACT FROM AUTHOR]