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Kim, Molan
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Too human to trust? How AI human-likeness and context orientation shape consumer preferences in premium high-tech markets

Author(s)
Chae, Myoung-JinKim, Molan
Issued Date
2026-01
DOI
10.1016/j.jretconser.2025.104513
URI
https://scholarworks.unist.ac.kr/handle/201301/87890
Citation
JOURNAL OF RETAILING AND CONSUMER SERVICES, v.88, pp.104513
Abstract
This study investigates how AI assistants' human-likeness (robotic, near-human, and human) influences consumer trust, satisfaction, and product choices, with a particular focus on premium technology products. It further examines how individuals’ context communication orientation (high vs. low) moderates these effects. Two experimental studies were conducted, wherein participants interacted with AI assistants recommending high-tech products under varying levels of AI anthropomorphism. Data on consumer trust, satisfaction, and purchase intentions were collected and analyzed using regression-based models to test the hypothesized relationships. Overall, human AI assistants elicited lower trust and satisfaction than non-human designs in choosing tech products, while the effects were moderated by context communication orientation. In high-tech premium categories, robotic AI proved more persuasive for most consumers, aligning with expectations of transparency and expertise. However, for high-context consumers, the positive impact of robotic AI was attenuated, making human-like AI notably more effective in driving premium product choices. In contrast, low-context consumers demonstrated higher preference for premium recommendations from robotic AI. Firms introducing premium tech products should consider the interplay between AI anthropomorphism and context orientation. Robotic AI may enhance trust for most consumers contemplating premium-tier items, whereas human-like AI can be beneficial in attracting high-context consumers seeking relational cues. By tailoring AI assistant designs to match product tier and context orientation, companies can optimize consumer engagement and purchase intentions.
Publisher
ELSEVIER SCI LTD
ISSN
0969-6989

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