AI features and social influence affect Gen Z purchase intention and behavior through trust in an extended SOR model
Year: 2026
Type: article
Abstract: Driven by digital transformation in the global retail sector, this study investigates the psychological and behavioral mechanisms underlying Generation Z college students’ AI-assisted shopping experiences. It examines how four stimuli—AI algorithm transparency, user-friendliness, internet word of mouth (IWOM), and trust propensity—influence consumer trust and purchase intention, alongside the moderating effects of privacy concern and information collection behavior. Drawing on an extended Stimulus-Organism-Response (SOR) model, the research empirically validates the proposed framework using 979 valid online survey responses analyzed via SPSS 32. Results reveal that the four antecedents exert significantly positive effects on both consumer trust and purchase intention, with trust serving as a significant mediator between these antecedents and purchase intention. Additionally, information collection behavior positively moderates the relationship between IWOM and consumer trust, while privacy concern negatively moderates the relationship between AI algorithm transparency and consumer trust. This study offers novel theoretical insights into Gen Z’s AI shopping behaviors and provides practical implications: retailers should enhance AI algorithm transparency, optimize user interfaces, cultivate positive IWOM, and strengthen privacy protection to foster Gen Z’s trust and facilitate purchase conversion.
Source: Scientific Reports
Authors: Li Ma, Shanshan Zheng
Institution: Huaqiao University
Language: English
Topic: AI in Service Interactions
Subfield: Marketing
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7225744326
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