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How displaying price discounts can mitigate negative customer reactions to dynamic pricing

Author

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  • Keller, Alisa
  • Vogelsang, Mila
  • Totzek, Dirk

Abstract

Dynamic pricing has great potential to increase retailers’ profits, but it also creates a risk of negative customer reactions. This paper examines whether and how price discount displays might mitigate negative consequences of dynamic pricing. The results of five studies indicate that when confronted with dynamic pricing customers react negatively due to norm violation, in terms of their perceptions of pricing transparency, price fairness, and value, as well as their purchase intention. However, if retailers display prices as sufficiently high discounts, they can mitigate these negative reactions. The results also suggest that customers tend to focus on the general price-setting process when evaluating a specific transaction in a dynamic pricing context. Therefore, it is necessary to consider both distributive and procedural fairness to explain and predict customers’ reactions to dynamic prices. Further, the results point to how managers may be able to successfully implement dynamic pricing, using price discount displays.

Suggested Citation

  • Keller, Alisa & Vogelsang, Mila & Totzek, Dirk, 2022. "How displaying price discounts can mitigate negative customer reactions to dynamic pricing," Journal of Business Research, Elsevier, vol. 148(C), pages 277-291.
  • Handle: RePEc:eee:jbrese:v:148:y:2022:i:c:p:277-291
    DOI: 10.1016/j.jbusres.2022.04.027
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    2. Jianjun Li & Xiaodi Xu & Yu Yang, 2023. "Research on the Regulation of Algorithmic Price Discrimination Behaviour of E-Commerce Platform Based on Tripartite Evolutionary Game," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    3. Yan Guo & Jiajun Lin & Weiqing Zhuang, 2024. "An Evolutionary Game-Based Regulatory Path for Algorithmic Price Discrimination in E-Commerce Platforms," Mathematics, MDPI, vol. 12(17), pages 1-30, September.
    4. Chen, Jinyu & Zhong, Ziqi & Feng, Qindi & Liu, Lei, 2022. "The multimodal emotion information analysis of e-commerce online pricing in electronic word of mouth," LSE Research Online Documents on Economics 125409, London School of Economics and Political Science, LSE Library.

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