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The Impact of AI personalized Recommendation Scale on Consumer Purchase Decisions

Li Li () and Siqi Li ()
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Li Li: Nanning University, School of Business
Siqi Li: Ningbo University of Finance and Economics, Wealth Management College

A chapter in Proceedings of the 2025 5th International Conference on Informatization Economic Development and Management (IEDM 2025), 2025, pp 251-263 from Springer

Abstract: Abstract In the rapidly changing digital market, AI-based personalized recommendations significantly enhance consumer shopping experiences and drive business growth. This study investigates how the volume of recommendations (independent variable) influences consumer purchase behavior (dependent variable) through perceived attractiveness (mediating variable) and examines the moderating effect of decision-making style. Based on survey data from 380 online shoppers, the results reveal that perceived attractiveness mediates the relationship between recommendation volume and purchase behavior, while decision-making style positively moderates the effect of recommendation volume on perceived attractiveness. These findings uncover the psychological mechanisms underlying the impact of AI personalized recommendations on consumer behavior, offering valuable guidance for optimizing recommendation systems to improve consumer satisfaction and business outcomes.

Keywords: AI personalized recommendations; Recommendation scale; User perception; Decision-making style; Purchase decision (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-724-3_25

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DOI: 10.2991/978-94-6463-724-3_25

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