IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v67y2021i11p6678-6693.html
   My bibliography  Save this article

Why Perfect Tests May Not Be Worth Waiting For: Information as a Commodity

Author

Listed:
  • K. Drakopoulos

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

  • R. S. Randhawa

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

Abstract

Information products provide agents with additional information that can be used to update actions. In many situations, access to such products can be quite limited. For instance, in epidemics, there tends to be a limited supply of medical testing kits, or tests. These tests are information products because their output of a positive or a negative answer informs individuals and authorities on the underlying state and the appropriate course of action. In this paper, using an analytical model, we show how the accuracy of a test in detecting the underlying state affects the demand for the information product differentially across heterogeneous agents. Correspondingly, the test accuracy can serve as a rationing device to ensure that the limited supply of information products is appropriately allocated to the heterogeneous agents. When test availability is low and the social planner is unable to allocate tests in a targeted manner to the agents, we find that moderately good tests can outperform perfect tests in terms of social outcome.

Suggested Citation

  • K. Drakopoulos & R. S. Randhawa, 2021. "Why Perfect Tests May Not Be Worth Waiting For: Information as a Commodity," Management Science, INFORMS, vol. 67(11), pages 6678-6693, November.
  • Handle: RePEc:inm:ormnsc:v:67:y:2021:i:11:p:6678-6693
    DOI: 10.1287/mnsc.2021.4029
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2021.4029
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2021.4029?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. Dirk Bergemann & Alessandro Bonatti, 2019. "Markets for Information: An Introduction," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 85-107, August.
    2. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 218-256, November.
    3. Barbara J. McNeil & James A. Hanley, 1984. "Statistical Approaches to the Analysis of Receiver Operating Characteristic (ROC) Curves," Medical Decision Making, , vol. 4(2), pages 137-150, June.
    4. Qian Liu & Garrett J. van Ryzin, 2008. "Strategic Capacity Rationing to Induce Early Purchases," Management Science, INFORMS, vol. 54(6), pages 1115-1131, June.
    5. Alvin E. Roth, 2002. "The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics," Econometrica, Econometric Society, vol. 70(4), pages 1341-1378, July.
    6. Qian Liu & Garrett van Ryzin, 2011. "Strategic Capacity Rationing when Customers Learn," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 89-107, September.
    7. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    8. Charles E. Phelps & Alvin I. Mushlin, 1988. "Focusing Technology Assessment Using Medical Decision Theory," Medical Decision Making, , vol. 8(4), pages 279-289, December.
    9. Santiago R. Balseiro & Huseyin Gurkan & Peng Sun, 2019. "Multiagent Mechanism Design Without Money," Operations Research, INFORMS, vol. 67(5), pages 1417-1436, September.
    10. Admati, Anat R. & Pfleiderer, Paul, 1986. "A monopolistic market for information," Journal of Economic Theory, Elsevier, vol. 39(2), pages 400-438, August.
    11. Itai Ashlagi & Peng Shi, 2016. "Optimal Allocation Without Money: An Engineering Approach," Management Science, INFORMS, vol. 62(4), pages 1078-1097, 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. Bardey, David & De Donder , Philippe & Zaporozhets , Vera, 2024. "The Health Technology Assessment Approach of The Economic Value of Diagnostic Test: A Literature Review," Documentos CEDE 21041, Universidad de los Andes, Facultad de Economía, CEDE.

    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. Adam J. Mersereau & Dan Zhang, 2012. "Markdown Pricing with Unknown Fraction of Strategic Customers," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 355-370, July.
    2. Negin Golrezaei & Hamid Nazerzadeh & Ramandeep Randhawa, 2020. "Dynamic Pricing for Heterogeneous Time-Sensitive Customers," Manufacturing & Service Operations Management, INFORMS, vol. 22(3), pages 562-581, May.
    3. CARBALLA SMICHOWSKI Bruno & DUCH BROWN Nestor & MARTENS Bertin, 2021. "To pool or to pull back? An economic analysis of health data pooling," JRC Working Papers on Digital Economy 2021-06, Joint Research Centre.
    4. Alessandro Bonatti, 2023. "The Platform Dimension of Digital Privacy," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    5. Dirk Bergemann & Alessandro Bonatti, 2024. "Data, Competition, and Digital Platforms," American Economic Review, American Economic Association, vol. 114(8), pages 2553-2595, August.
    6. Julien Combe & Vladyslav Nora & Olivier Tercieux, 2021. "Dynamic assignment without money: Optimality of spot mechanisms," Working Papers 2021-11, Center for Research in Economics and Statistics.
    7. Vincent Mak & Amnon Rapoport & Eyran J. Gisches, 2018. "Dynamic Pricing Decisions and Seller-Buyer Interactions under Capacity Constraints," Games, MDPI, vol. 9(1), pages 1-23, February.
    8. Javad Nasiry & Ioana Popescu, 2011. "Dynamic Pricing with Loss-Averse Consumers and Peak-End Anchoring," Operations Research, INFORMS, vol. 59(6), pages 1361-1368, December.
    9. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 218-256, November.
    10. Gonca P. Soysal & Lakshman Krishnamurthi, 2012. "Demand Dynamics in the Seasonal Goods Industry: An Empirical Analysis," Marketing Science, INFORMS, vol. 31(2), pages 293-316, March.
    11. 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.
    12. Christian Borgs & Ozan Candogan & Jennifer Chayes & Ilan Lobel & Hamid Nazerzadeh, 2014. "Optimal Multiperiod Pricing with Service Guarantees," Management Science, INFORMS, vol. 60(7), pages 1792-1811, July.
    13. Jun Li & Nelson Granados & Serguei Netessine, 2014. "Are Consumers Strategic? Structural Estimation from the Air-Travel Industry," Management Science, INFORMS, vol. 60(9), pages 2114-2137, September.
    14. Narayan Mishra & Sri Vanamalla Venkataraman, 2022. "Optimal order quantity in the presence of strategic customers," Annals of Operations Research, Springer, vol. 315(2), pages 1871-1894, August.
    15. Jiadong Gu, 2024. "Data Trade and Consumer Privacy," Papers 2406.12457, arXiv.org, revised Jul 2024.
    16. Andrew Sweeting, 2008. "Equilibrium Price Dynamics in Perishable Goods Markets: The Case of Secondary Markets for Major League Baseball Tickets," NBER Working Papers 14505, National Bureau of Economic Research, Inc.
    17. Dong, Junfeng & Wu, Desheng Dash, 2019. "Two-period pricing and quick response with strategic customers," International Journal of Production Economics, Elsevier, vol. 215(C), pages 165-173.
    18. Mohammed Al-Hitmi & Salman Ahmad & Atif Iqbal & Sanjeevikumar Padmanaban & Imtiaz Ashraf, 2018. "Selective Harmonic Elimination in a Wide Modulation Range Using Modified Newton–Raphson and Pattern Generation Methods for a Multilevel Inverter," Energies, MDPI, vol. 11(2), pages 1-16, February.
    19. S. Nageeb Ali & Gregory Lewis & Shoshana Vasserman, 2019. "Voluntary Disclosure and Personalized Pricing," NBER Working Papers 26592, National Bureau of Economic Research, Inc.
    20. Liyang Han & Jalal Kazempour & Pierre Pinson, 2020. "Monetizing Customer Load Data for an Energy Retailer: A Cooperative Game Approach," Papers 2012.05519, arXiv.org, revised Aug 2021.

    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:67:y:2021:i:11:p:6678-6693. 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.