Online reviews generated by generative artificial intelligence versus human: A study of perceived differences and user adoption behavior
Year: 2025
Type: article
Abstract: Companies in various industries are attempting to integrate Generative Artificial Intelligence (GAI) into their existing businesses. In the e-commerce domain, GAI has shown tremendous potential in generating online reviews. However, existing literature has paid less attention to how consumers respond to GAI-generated reviews versus human-generated reviews. Moreover, little research has explored whether and why consumers are willing to use GAI to generate online reviews. By conducting two experiments, this study investigates how consumers respond differently to GAI-generated reviews versus human-generated reviews and identifies potential factors that influence consumers’ willingness to use GAI to generate reviews. Findings indicate that although there is no significant difference in consumers’ perceptions between human-generated and GAI-generated reviews in terms of review credibility, review richness, and review usefulness, only half of the participants are willing to use GAI to generate reviews. Further analysis results suggest that individuals who consider GAI unethical tend to avoid using GAI. Those with high personal innovativeness are more willing to use GAI to generate online reviews. Our findings deepen the understanding of consumer attitudes toward GAI-generated reviews and provide implications for the deployment of GAI in the online review system.
Authors: Xusen Cheng, Ang Zeng, Bo Yang, Yu Liu, Xiaoping Zhang
Institution: Renmin University of China
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,210
Awards: G3862154942, G4859261084, G5364233576
OpenAlex ID: W4408605893