Journal of Theoretical and Applied Electronic Commerce Research

AI recommendation agents increasingly mediate consumer decision-making in electronic commerce, yet algorithm-based agents often suffer credibility deficits relative to human sources. This research examines how recommendation agent type (human vs. AI) influences behavioral intentions through perceived credibility and how psychological ownership moderates this process. Across two controlled online experiments, consumers evaluated recommendations delivered by human or AI agents. Study 1 shows that baseline AI agents are perceived as less credible than human agents, while AI agents receiving minimal user involvement (naming) exhibit partially improved credibility, and that credibility mediates the effects of agent type on intention to use the system, recommendation acceptance, and purchase intention. Study 2 introduces a stronger psychological ownership manipulation through AI agent customization. Results indicate that customization strengthens psychological ownership, which reduces the credibility gap between AI and human agents and, when ownership is high, even allows AI agents to be evaluated as more credible. Conditional process analyses confirm that psychological ownership moderates both the effect of agent type on credibility and the indirect effects on behavioral intentions. Overall, the findings demonstrate that credibility toward AI recommendation agents is dynamically shaped by user–agent relational experiences. By integrating algorithm aversion, source credibility, and psychological ownership perspectives, this research advances understanding of consumer–AI interaction and provides design insights for AI-enabled recommendation systems in electronic commerce.

This study examines how different types of experienced harm influence trust in sellers and platforms in secondhand, platform-mediated markets. Drawing on attribution theory, we distinguish between fulfillment harm and integrity harm and investigate how these two forms of harm differentially affect seller trust and platform trust. Using data from the Consumer Market Evaluation Index on secondhand marketplaces, we find that both fulfillment and integrity harm are negatively associated with seller trust and platform trust compared to no-harm experiences. When both types of harm occur together, trust deterioration becomes more pronounced. Importantly, fulfillment harm is primarily associated with lower seller trust, whereas integrity harm is more strongly related to platform trust. These findings indicate that trust redistribution depends on attributional evaluations regarding causal locus and controllability. This study contributes to the existing literature by demonstrating how attribution processes allocate trust among multiple market actors and by revealing how different types of failures are attributed to these market actors. Moreover, the findings provide practical guidance for platform governance and seller behavior by highlighting the importance of targeted safeguards in sustaining trust in platform-mediated marketplaces.

Consumers are increasingly utilizing their smartphones to pay for goods and services, taking advantage of a variety of mobile payment options. Among these, Peer-to-Peer (P2P) mobile payment systems have gained global momentum, becoming one of consumers’ preferred choices. This study aims to examine the factors influencing consumers’ continuance intention to use CliQ, a P2P mobile payment system in Jordan. Following a thorough literature review, we extend the Theory of Planned Behavior (TPB) by integrating perceived structural assurance, perceived usefulness, and satisfaction. The Partial Least Squares Structural Equation Modeling (PLS-SEM) results indicate that perceived structural assurance significantly affects both consumer attitude and perceived security. The findings also suggest that attitude is the most influential factor in the proposed research model, while perceived usefulness and perceived behavioral control emerged as key drivers of user satisfaction and continuance intention. Furthermore, satisfaction was found to be a strong predictor of consumers’ continuance intention. These findings enrich the literature and provide valued implications for mobile-payment service providers and application developers.