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Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing

Author

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  • Peter Seele

    (Università della Svizzera Italiana)

  • Claus Dierksmeier

    (Universität Tübingen)

  • Reto Hofstetter

    (University of Lucerne)

  • Mario D. Schultz

    (Corporate Social Responsibility and Business Ethics, Università della Svizzera Italiana (USI))

Abstract

Firms increasingly deploy algorithmic pricing approaches to determine what to charge for their goods and services. Algorithmic pricing can discriminate prices both dynamically over time and personally depending on individual consumer information. Although legal, the ethicality of such approaches needs to be examined as often they trigger moral concerns and sometimes outrage. In this research paper, we provide an overview and discussion of the ethical challenges germane to algorithmic pricing. As a basis for our discussion, we perform a systematic interpretative review of 315 related articles on dynamic and personalized pricing as well as pricing algorithms in general. We then use this review to define the term algorithmic pricing and map its key elements at the micro-, meso-, and macro levels from a business and marketing ethics perspective. Thus, we can identify morally ambivalent topics that call for deeper exploration by future research.

Suggested Citation

  • Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
  • Handle: RePEc:kap:jbuset:v:170:y:2021:i:4:d:10.1007_s10551-019-04371-w
    DOI: 10.1007/s10551-019-04371-w
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    Cited by:

    1. Aleksandar B. Todorov, 2022. "Algorithmic pricing and concerted behaviour – competitive challenges?," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 90-107.
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    3. Masuyama, Ryo, 2024. "Endogenous targeted pricing with vertical structure," MPRA Paper 121680, University Library of Munich, Germany.
    4. Kirsten Martin, 2023. "Predatory predictions and the ethics of predictive analytics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(5), pages 531-545, May.
    5. Hallikainen, Heli & Luongo, Milena & Dhir, Amandeep & Laukkanen, Tommi, 2022. "Consequences of personalized product recommendations and price promotions in online grocery shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    6. Jake B. Telkamp & Marc H. Anderson, 2022. "The Implications of Diverse Human Moral Foundations for Assessing the Ethicality of Artificial Intelligence," Journal of Business Ethics, Springer, vol. 178(4), pages 961-976, July.
    7. Pizzi, Gabriele & Vannucci, Virginia & Shukla, Yupal & Aiello, Gaetano, 2022. "Privacy concerns and justice perceptions with the disclosure of biometric versus behavioral data for personalized pricing tell me who you are, I’ll tell you how much you pay. Consumers’ fairness and p," Journal of Business Research, Elsevier, vol. 148(C), pages 420-432.
    8. Nunan, Daniel & Di Domenico, MariaLaura, 2022. "Value creation in an algorithmic world: Towards an ethics of dynamic pricing," Journal of Business Research, Elsevier, vol. 150(C), pages 451-460.
    9. Yuanyuan Zhou & Zhuoying Fei & Yuanqiong He & Zhilin Yang, 2022. "How Human–Chatbot Interaction Impairs Charitable Giving: The Role of Moral Judgment," Journal of Business Ethics, Springer, vol. 178(3), pages 849-865, July.
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