Journal article
Optimal dynamic pricing strategy for non-durable experience goods: the role of consumer AI learning
International journal of production research, pp 1-25
10 Sep 2025
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This study develops a dynamic pricing model for experiential products by explicitly integrating product perceived quality and AI-driven consumer learning. Several interesting and key conclusions are obtained. First, the results demonstrate that companies strategically adjust pricing in response to the strength of AI-enabled information cascades and the perceived quality signals after AI learning. Moreover, AI-driven consumer learning significantly shapes both optimal pricing and revenue. Specifically, consumer AI learning has a significant impact on both pricing and revenue gains. When the information cascade is in a positive state and the perceived quality indicator after AI learning is positive, it indicates strong market demand, and consumers are willing to accept higher-priced products, allowing companies to adjust prices upwards to increase revenue. In contrast, when the information cascade is in a positive state and the perceived quality indicator after AI learning is negative, it suggests weak market demand, and consumers are unwilling to pay higher prices for products, prompting companies to lower prices to stimulate demand. Furthermore, this study explores when demand fluctuations under consumer AI learning for various products increase, prices should be adjusted downward, highlighting the significant effect of demand changes under AI learning on pricing strategies when facing competition.
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Details
- Title
- Optimal dynamic pricing strategy for non-durable experience goods: the role of consumer AI learning
- Creators
- Zhitang Li - Shenzhen UniversityBenjamin Lev (Corresponding Author) - Drexel University
- Publication Details
- International journal of production research, pp 1-25
- Publisher
- Taylor & Francis
- Number of pages
- 25
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:001568318100001
- Scopus ID
- 2-s2.0-105016517776
- Other Identifier
- 991022116083404721
UN Sustainable Development Goals (SDGs)
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Industrial
- Engineering, Manufacturing
- Operations Research & Management Science