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Dynamic Pricing in Social Networks: The Word-of-Mouth Effect

Author

Listed:
  • Amir Ajorlou

    (Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Ali Jadbabaie

    (Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Ali Kakhbod

    (Department of Economics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

We study the problem of optimal dynamic pricing for a monopolist selling a product to consumers in a social network. In the proposed model, the only means of spread of information about the product is via word-of-mouth communication; consumers’ knowledge of the product is only through friends who already know about the product’s existence. Both buyers and nonbuyers contribute to information diffusion, while buyers are more likely to spread the news about the product. By analyzing the structure of the underlying endogenous dynamic process, we show that the optimal dynamic pricing policy for durable products with zero or negligible marginal cost drops the price to zero infinitely often. The firm uses free offers to attract low-valuation agents and to get them more engaged in the spread. As a result, the firm can reach potential high-valuation consumers in parts of the network that would otherwise remain untouched without the price drops. We provide evidence for this behavior from the smartphone app market, where price histories indicate frequent zero-price sales. Moreover, we show that despite dropping the price to zero infinitely often, the optimal price trajectory does not get trapped near zero. We demonstrate the validity of our results in the face of forward-looking consumers and homophily in word-of-mouth engagement. We further unravel the key role of the product type in the optimality of zero-price sales by showing that the price fluctuations disappear after a finite time for a nondurable product.

Suggested Citation

  • Amir Ajorlou & Ali Jadbabaie & Ali Kakhbod, 2018. "Dynamic Pricing in Social Networks: The Word-of-Mouth Effect," Management Science, INFORMS, vol. 64(2), pages 971-979, February.
  • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:2:p:-971-979
    DOI: 10.287/mnsc.2016.2657
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    References listed on IDEAS

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    Cited by:

    1. Alexei Parahonyak & Nick Vikander, 2024. "Strategic Use of Product Delays to Shape Word-of-Mouth Communication," Economics Series Working Papers 1032, University of Oxford, Department of Economics.
    2. Xiong, Yifan & Li, Ziyan, 2022. "Staffing problems with local network externalities," Economics Letters, Elsevier, vol. 212(C).
    3. Kakhbod, Ali & Loginova, Uliana, 2023. "When does introducing verifiable communication choices improve welfare?," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 139-162.
    4. Çavdar, Bahar & Erkip, Nesim, 2023. "Word-of-Mouth on Action: Analysis of Optimal Shipment Policy When Customers are Resentful," Omega, Elsevier, vol. 118(C).
    5. Andrei Hagiu & Julian Wright, 2020. "Platforms and the Exploration of New Products," Management Science, INFORMS, vol. 66(4), pages 1527-1543, April.
    6. Yuichiro Kamada & Aniko Öry, 2020. "Contracting with Word-of-Mouth Management," Management Science, INFORMS, vol. 66(11), pages 5094-5107, November.
    7. Sheng Bin, 2023. "Social Network Emotional Marketing Influence Model of Consumers’ Purchase Behavior," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    8. Zhen, Xueping & (George) Cai, Gangshu & Song, Reo & Jang, Sungha, 2019. "The effects of herding and word of mouth in a two-period advertising signaling model," European Journal of Operational Research, Elsevier, vol. 275(1), pages 361-373.
    9. Jadbabaie, Ali & Kakhbod, Ali, 2019. "Optimal contracting in networks," Journal of Economic Theory, Elsevier, vol. 183(C), pages 1094-1153.
    10. Foerster, Manuel & Hellmann, Tim & Vega-Redondo, Fernando, 2024. "Strategic use of social media influencer marketing," UC3M Working papers. Economics 43985, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Li, Feng & Du, Timon C. & Wei, Ying, 2023. "This is what’s in store for you: How online social learning affects product positioning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    12. 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.
    13. Kakhbod, Ali & Song, Fei, 2020. "Dynamic price discovery: Transparency vs. information design," Games and Economic Behavior, Elsevier, vol. 122(C), pages 203-232.
    14. Xueke Du & Rui Dong & Wenli Li & Yibo Jia & Lirong Chen, 2019. "Online Reviews Matter: How Can Platforms Benefit from Online Reviews?," Sustainability, MDPI, vol. 11(22), pages 1-20, November.

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