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Artificial intelligence and dynamic pricing: a systematic literature review

Régis Chenavaz & Stanko Dimitrov

Journal of Applied Economics2025https://doi.org/10.1080/15140326.2025.2466140article
AJG 1ABDC B
Weight
0.58

Abstract

With dynamic pricing becoming more widespread across various industries, artificial intelligence has made it even more sophisticated and widespread. The authors conducted a systematic literature review and analyzed a dataset of 95 peer-reviewed articles from international journals selected in Web of Science and Scopus to better understand artificial intelligence’s impact on dynamic pricing. The authors identified four clusters related to financial modeling, market dynamics, commodity markets, and behavior and decision-making. They also found that China has overtaken the USA in the number of published articles. They identified the themes of market simulation investment, crude oil commodity dependence, and behavior traders’ prices. A systematic literature review is essential to understand the impact of artificial intelligence on dynamic pricing and its implications for businesses, consumers, and society.

12 citations

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https://doi.org/https://doi.org/10.1080/15140326.2025.2466140

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@article{régis2025,
  title        = {{Artificial intelligence and dynamic pricing: a systematic literature review}},
  author       = {Régis Chenavaz & Stanko Dimitrov},
  journal      = {Journal of Applied Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/15140326.2025.2466140},
}

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Artificial intelligence and dynamic pricing: a systematic literature review

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Evidence weight

0.58

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.58 × 0.4 = 0.23
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.