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Paper Number
1853
Paper Type
Completed
Description
Discriminatory pricing practices have raised consumers’ negative reactions. This study investigates how AI agent’s presence and the use of explanations impact consumers' acceptance of discriminatory pricing. A scenario-based experiment revealed that AI agent’s presence negatively moderates the negative relationship between offer unfavorability and offer acceptance, which is mediated by perceived justice and invasion of privacy. Moreover, this research indicated that for unfavored price, environment-based explanation is more effective than user-based explanation and the positive effect of AI agent’s presence on offer acceptance is more pronounced when providing user-based explanations. This study contributes to price management literature and AI decision literature by illustrating how the AI agent's presence asymmetrically shapes consumers' perceptions of offer outcomes, enriching our understanding of consumer responses to AI. The findings have implications for firms managing discriminatory pricing, offering insights into optimal AI agents and explanation utilization for enhancing customer experience and business performance.
Recommended Citation
PENG, XIAO; Peng, Xixian; and Xu, David (Jingjun), "Why Users Accept Discriminatory Pricing: The Roles of AI Agent's Presence and Explanation" (2023). ICIS 2023 Proceedings. 6.
https://aisel.aisnet.org/icis2023/hti/hti/6
Why Users Accept Discriminatory Pricing: The Roles of AI Agent's Presence and Explanation
Discriminatory pricing practices have raised consumers’ negative reactions. This study investigates how AI agent’s presence and the use of explanations impact consumers' acceptance of discriminatory pricing. A scenario-based experiment revealed that AI agent’s presence negatively moderates the negative relationship between offer unfavorability and offer acceptance, which is mediated by perceived justice and invasion of privacy. Moreover, this research indicated that for unfavored price, environment-based explanation is more effective than user-based explanation and the positive effect of AI agent’s presence on offer acceptance is more pronounced when providing user-based explanations. This study contributes to price management literature and AI decision literature by illustrating how the AI agent's presence asymmetrically shapes consumers' perceptions of offer outcomes, enriching our understanding of consumer responses to AI. The findings have implications for firms managing discriminatory pricing, offering insights into optimal AI agents and explanation utilization for enhancing customer experience and business performance.
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