IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v69y2023i6p3536-3560.html
   My bibliography  Save this article

Providing Data Samples for Free

Author

Listed:
  • Kimon Drakopoulos

    (USC Marshall School of Business, University of Southern California, Los Angeles, California 90089)

  • Ali Makhdoumi

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

Abstract

We consider the problem of a seller of data who sells information to a buyer regarding an unknown (to both parties) state of the world. Traditionally, the literature explores one-round strategies for selling information because of the seller’s holdup problem: once a portion of the data set is released, the buyer’s estimate improves, and as a result, the value of the remaining data set drops. In this paper, we show that this intuition is true when the buyer’s objective is to improve the precision of the estimate. On the other hand, we establish that when the buyer’s objective is to improve downstream operational decisions (e.g., better pricing decisions in a market with unknown elasticity) and when the buyer’s initial estimate is misspecified, one-round strategies are outperformed by selling strategies that initially provide free samples. In particular, we provide conditions under which such free-sample strategies generate strictly higher revenues than static strategies and illustrate the benefit of providing data samples for free through a series of examples. Furthermore, we characterize the optimal dynamic pricing strategy within the class of strategies that provide samples over time (at a constant rate), charging a flow price until some time when the rest of the data set is released at a lump-sum amount.

Suggested Citation

  • Kimon Drakopoulos & Ali Makhdoumi, 2023. "Providing Data Samples for Free," Management Science, INFORMS, vol. 69(6), pages 3536-3560, June.
    • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:6:p:3536-3560
    DOI: 10.1287/mnsc.2022.4534
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2022.4534
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2022.4534?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lode Li & Hongtao Zhang, 2008. "Confidentiality and Information Sharing in Supply Chain Coordination," Management Science, INFORMS, vol. 54(8), pages 1467-1481, August.
    2. Dirk Bergemann & Alessandro Bonatti & Tan Gan, 2022. "The economics of social data," RAND Journal of Economics, RAND Corporation, vol. 53(2), pages 263-296, June.
    3. Ozan Candogan & Kimon Drakopoulos, 2020. "Optimal Signaling of Content Accuracy: Engagement vs. Misinformation," Operations Research, INFORMS, vol. 68(2), pages 497-515, March.
    4. Dirk Bergemann & Stephen Morris, 2019. "Information Design: A Unified Perspective," Journal of Economic Literature, American Economic Association, vol. 57(1), pages 44-95, March.
    5. Krishnamurthy Iyer & Ramesh Johari & Ciamac C. Moallemi, 2014. "Information Aggregation and Allocative Efficiency in Smooth Markets," Management Science, INFORMS, vol. 60(10), pages 2509-2524, October.
    6. Dirk Bergemann & Juuso Välimäki, 2019. "Dynamic Mechanism Design: An Introduction," Journal of Economic Literature, American Economic Association, vol. 57(2), pages 235-274, June.
    7. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    8. Davide Crapis & Bar Ifrach & Costis Maglaras & Marco Scarsini, 2017. "Monopoly Pricing in the Presence of Social Learning," Management Science, INFORMS, vol. 63(11), pages 3586-3608, November.
    9. Welch, Ivo, 1992. "Sequential Sales, Learning, and Cascades," Journal of Finance, American Finance Association, vol. 47(2), pages 695-732, June.
    10. Gibbons, Robert & Murphy, Kevin J, 1992. "Optimal Incentive Contracts in the Presence of Career Concerns: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 100(3), pages 468-505, June.
    11. Dirk Bergemann & Juuso Valimaki, 2002. "Information Acquisition and Efficient Mechanism Design," Econometrica, Econometric Society, vol. 70(3), pages 1007-1033, May.
    12. Lode Li, 2002. "Information Sharing in a Supply Chain with Horizontal Competition," Management Science, INFORMS, vol. 48(9), pages 1196-1212, September.
    13. Morris, Stephen, 1994. "Trade with Heterogeneous Prior Beliefs and Asymmetric Information," Econometrica, Econometric Society, vol. 62(6), pages 1327-1347, November.
    14. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    15. Man Yu & Laurens Debo & Roman Kapuscinski, 2016. "Strategic Waiting for Consumer-Generated Quality Information: Dynamic Pricing of New Experience Goods," Management Science, INFORMS, vol. 62(2), pages 410-435, February.
    16. Dirk Bergemann & Alessandro Bonatti, 2019. "Markets for Information: An Introduction," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 85-107, August.
    17. Yi Xiang & Miklos Sarvary, 2013. "Buying and selling information under competition," Quantitative Marketing and Economics (QME), Springer, vol. 11(3), pages 321-351, September.
    18. Saed Alizamir & Francis de Véricourt & Shouqiang Wang, 2020. "Warning Against Recurring Risks: An Information Design Approach," Management Science, INFORMS, vol. 66(10), pages 4612-4629, October.
    19. Joseph B. Kadane & Patrick D. Larkey, 1982. "Subjective Probability and the Theory of Games," Management Science, INFORMS, vol. 28(2), pages 113-120, February.
    20. Yiangos Papanastasiou & Kostas Bimpikis & Nicos Savva, 2018. "Crowdsourcing Exploration," Management Science, INFORMS, vol. 64(4), pages 1727-1746, April.
    21. Pnina Feldman & Yiangos Papanastasiou & Ella Segev, 2019. "Social Learning and the Design of New Experience Goods," Management Science, INFORMS, vol. 65(5), pages 1502-1519, April.
    22. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    23. Mailath, George J. & Samuelson, Larry, 2006. "Repeated Games and Reputations: Long-Run Relationships," OUP Catalogue, Oxford University Press, number 9780195300796.
    24. Albert Y. Ha & Shilu Tong, 2008. "Contracting and Information Sharing Under Supply Chain Competition," Management Science, INFORMS, vol. 54(4), pages 701-715, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alireza Fallah & Michael I. Jordan & Ali Makhdoumi & Azarakhsh Malekian, 2024. "On Three-Layer Data Markets," Papers 2402.09697, arXiv.org, revised Feb 2024.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bingsheng Liu & Wenwen Zhu & Yinghua Shen & Yuan Chen & Tao Wang & Fengwen Chen & Maggie Wenjing Liu & Shi‐Hao Zhou, 2022. "A study about return policies in the presence of consumer social learning," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2571-2587, June.
    2. 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).
    3. Pnina Feldman & Yiangos Papanastasiou & Ella Segev, 2019. "Social Learning and the Design of New Experience Goods," Management Science, INFORMS, vol. 65(5), pages 1502-1519, April.
    4. Li Chen & Yiangos Papanastasiou, 2021. "Seeding the Herd: Pricing and Welfare Effects of Social Learning Manipulation," Management Science, INFORMS, vol. 67(11), pages 6734-6750, November.
    5. Bulow, Jeremy & Klemperer, Paul, 1994. "Rational Frenzies and Crashes," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 1-23, February.
    6. Can Küçükgül & Özalp Özer & Shouqiang Wang, 2022. "Engineering Social Learning: Information Design of Time-Locked Sales Campaigns for Online Platforms," Management Science, INFORMS, vol. 68(7), pages 4899-4918, July.
    7. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2024. "Persuading Risk-Conscious Agents: A Geometric Approach," Operations Research, INFORMS, vol. 72(1), pages 151-166, January.
    8. Lu Xiao & Hang Zhang & Yong Qin, 2020. "Competitive Pricing of Innovative Products with Consumers’ Social Learning," Sustainability, MDPI, vol. 12(9), pages 1-13, May.
    9. Hyoduk Shin & Tunay I. Tunca, 2010. "Do Firms Invest in Forecasting Efficiently? The Effect of Competition on Demand Forecast Investments and Supply Chain Coordination," Operations Research, INFORMS, vol. 58(6), pages 1592-1610, December.
    10. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    11. Jiadong Gu, 2024. "Data Trade and Consumer Privacy," Papers 2406.12457, arXiv.org, revised Jul 2024.
    12. Bonatti, Alessandro & Dahleh, Munther & Horel, Thibaut & Nouripour, Amir, 2024. "Selling information in competitive environments," Journal of Economic Theory, Elsevier, vol. 216(C).
    13. Parakhonyak, Alexei & Vikander, Nick, 2023. "Information design through scarcity and social learning," Journal of Economic Theory, Elsevier, vol. 207(C).
    14. Bar Ifrach & Costis Maglaras & Marco Scarsini & Anna Zseleva, 2019. "Bayesian Social Learning from Consumer Reviews," Operations Research, INFORMS, vol. 67(5), pages 1209-1221, September.
    15. Fishman, Arthur & Fishman, Ram & Gneezy, Uri, 2019. "A tale of two food stands: Observational learning in the field," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 101-108.
    16. Wang, Peiwen & Chen, Minghua & Wu, Ji & Yan, Yuanyun, 2023. "Do peer effects matter in bank risk? Some cross-country evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    17. Saad, Mohsen & Samet, Anis, 2020. "Collectivism and commonality in liquidity," Journal of Business Research, Elsevier, vol. 116(C), pages 137-162.
    18. Feri, Francesco & Meléndez-Jiménez, Miguel A. & Ponti, Giovanni & Vega-Redondo, Fernando, 2011. "Error cascades in observational learning: An experiment on the Chinos game," Games and Economic Behavior, Elsevier, vol. 73(1), pages 136-146, September.
    19. Patrick Hummel & Brian Knight, 2015. "Sequential Or Simultaneous Elections? A Welfare Analysis," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(3), pages 851-887, August.
    20. Jonathan E. Alevy & Michael S. Haigh & John List, 2006. "Information Cascades: Evidence from An Experiment with Financial Market Professionals," NBER Working Papers 12767, National Bureau of Economic Research, Inc.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:69:y:2023:i:6:p:3536-3560. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.