Generative AI Review Summaries and Their Impact on Ambivalence and User Behavior: An Eye-Tracking Study

Tucker Nicholas Todd, Akshat Lakhiwal, Hillol Bala (), Pierre-Majorique Léger, Ikram El Kamouni and Jared Boasen
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Tucker Nicholas Todd: Indiana University
Akshat Lakhiwal: University of Georgia
Hillol Bala: Indiana University
Pierre-Majorique Léger: HEC Montreal
Ikram El Kamouni: HEC Montreal
Jared Boasen: HEC Montreal

A chapter in Information Systems and Neuroscience, 2025, pp 1-9 from Springer

Abstract: Abstract Online purchase environments such as Amazon are beginning to utilize generative artificial intelligence (GenAI)-based review summaries (GARS) as representations that aggregate product information and associated valence from large numbers of product reviews. Although GARS may enable the unprecedented, accurate summarization of large volume of information found within product reviews, potentially assisting users’ decision-making, they are likely to tease out and juxtapose the positive and negative valence prevalent in product reviews concurrently. We examine how such GARS heighten the simultaneous activation of positive and negative dispositions—ambivalence—and theorize how such ambivalence affects users’ attention and purchase intentions in online contexts. We design and conduct an eye-tracking based within-subject laboratory experiment to investigate these effects. Results suggest that the presence of GARS in online purchase environments is likely to increase users’ perceived ambivalence and subsequently impact their cognitive and behavioral outcomes, which are identifiable via eye-tracking techniques.

Keywords: Ambivalence; Representations; Generative AI; Eye-tracking (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-71385-9_1

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