Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163216
Title: AI-enabled investment advice: will users buy it?
Authors: Chua, Alton Yeow Kuan
Pal, Anjan
Banerjee, Snehasish
Keywords: Social sciences::Communication
Issue Date: 2023
Source: Chua, A. Y. K., Pal, A. & Banerjee, S. (2023). AI-enabled investment advice: will users buy it?. Computers in Human Behavior, 138, 107481-. https://dx.doi.org/10.1016/j.chb.2022.107481
Journal: Computers in Human Behavior
Abstract: The objective of this paper is to develop and empirically validate a conceptual model that explains individuals' behavioral intention to accept AI-based recommendations as a function of attitude toward AI, trust, perceived accuracy and uncertainty level. The conceptual model was tested through a between-participants experiment using a simulated AI-enabled investment recommendation system. A total of 368 participants were randomly and evenly assigned to one of the two experimental conditions, one depicting low-uncertainty investment recommendation involving blue-chip stocks while the other depicting high-uncertainty investment recommendation involving penny stocks. Results show that attitude toward AI was positively associated with behavioral intention to accept AI-based recommendations, trust in AI, and perceived accuracy of AI. Furthermore, uncertainty level moderated how attitude, trust and perceived accuracy varied with behavioral intention to accept AI-based recommendations. When uncertainty was low, a favorable attitude toward AI seemed sufficient to promote reliance on automation. However, when uncertainty was high, a favorable attitude toward AI was a necessary but no longer sufficient condition for AI acceptance. Thus, the paper contributes to the human-AI interaction literature by not only shedding light on the underlying psychological mechanism of how users decide to accept AI-enabled advice but also adding to the scholarly understanding of AI recommendation systems in tasks that call for intuition in high involvement services.
URI: https://hdl.handle.net/10356/163216
ISSN: 0747-5632
DOI: 10.1016/j.chb.2022.107481
Schools: Wee Kim Wee School of Communication and Information 
Rights: © 2022 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:WKWSCI Journal Articles

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