IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2308.12242.html
   My bibliography  Save this paper

Recent Developments in Pandora's Box Problem: Variants and Applications

Author

Listed:
  • Hedyeh Beyhaghi
  • Linda Cai

Abstract

In 1979, Weitzman introduced Pandora's box problem as a framework for sequential search with costly inspections. Recently, there has been a surge of interest in Pandora's box problem, particularly among researchers working at the intersection of economics and computation. This survey provides an overview of the recent literature on Pandora's box problem, including its latest extensions and applications in areas such as market design, decision theory, and machine learning.

Suggested Citation

  • Hedyeh Beyhaghi & Linda Cai, 2023. "Recent Developments in Pandora's Box Problem: Variants and Applications," Papers 2308.12242, arXiv.org.
    • Handle: RePEc:arx:papers:2308.12242
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2308.12242
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael Choi & Anovia Yifan Dai & Kyungmin Kim, 2018. "Consumer Search and Price Competition," Econometrica, Econometric Society, vol. 86(4), pages 1257-1281, July.
    2. Cremer, Jacques & Spiegel, Yossi & Zheng, Charles Zhoucheng, 2007. "Optimal search auctions," Journal of Economic Theory, Elsevier, vol. 134(1), pages 226-248, May.
    3. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    4. Armstrong, Mark & Vickers, John, 2015. "Which demand systems can be generated by discrete choice?," Journal of Economic Theory, Elsevier, vol. 158(PA), pages 293-307.
    5. Mark Armstrong & John Vickers, 2010. "A Model of Delegated Project Choice," Econometrica, Econometric Society, vol. 78(1), pages 213-244, January.
    6. Doval, Laura, 2018. "Whether or not to open Pandora's box," Journal of Economic Theory, Elsevier, vol. 175(C), pages 127-158.
    7. Keller, Godfrey & Oldale, Alison, 2003. "Branching bandits: a sequential search process with correlated pay-offs," Journal of Economic Theory, Elsevier, vol. 113(2), pages 302-315, December.
    8. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-654, May.
    9. Robert Kleinberg & Bo Waggoner & E. Glen Weyl, 2016. "Descending Price Optimally Coordinates Search," Papers 1603.07682, arXiv.org, revised Dec 2016.
    10. Ke, T. Tony & Villas-Boas, J. Miguel, 2019. "Optimal learning before choice," Journal of Economic Theory, Elsevier, vol. 180(C), pages 383-437.
    11. Karni, Edi & Schwartz, Aba, 1977. "Search theory: The case of search with uncertain recall," Journal of Economic Theory, Elsevier, vol. 16(1), pages 38-52, October.
    Full references (including those not matched with items on IDEAS)

    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. Rafael P. Greminger, 2022. "Optimal Search and Discovery," Management Science, INFORMS, vol. 68(5), pages 3904-3924, May.
    2. Greminger, Rafael, 2019. "Optimal Search and Awareness Expansion," Other publications TiSEM ac47e6ff-42a4-4d70-addd-6, Tilburg University, School of Economics and Management.
    3. Rafael P. Greminger, 2019. "Optimal Search and Discovery," Papers 1911.07773, arXiv.org, revised Feb 2022.
    4. Greminger, Rafael, 2019. "Optimal Search and Awareness Expansion," Discussion Paper 2019-034, Tilburg University, Center for Economic Research.
    5. Petrikaitė, Vaiva, 2022. "Escaping search when buying," International Journal of Industrial Organization, Elsevier, vol. 82(C).
    6. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    7. T. Tony Ke & Song Lin, 2020. "Informational Complementarity," Management Science, INFORMS, vol. 66(8), pages 3699-3716, August.
    8. Chen, Yanbin & Li, Sanxi & Lin, Kai & Yu, Jun, 2021. "Consumer search with blind buying," Games and Economic Behavior, Elsevier, vol. 126(C), pages 402-427.
    9. Raluca Ursu & Stephan Seiler & Elisabeth Honka, 2023. "The Sequential Search Model: A Framework for Empirical Research," CESifo Working Paper Series 10264, CESifo.
    10. Pavan, Alessandro & Fershtman, Daniel, 2020. "Sequential Learning with Endogenous Consideration Sets," CEPR Discussion Papers 15018, C.E.P.R. Discussion Papers.
    11. Pak Hung Au & Mark Whitmeyer, 2018. "Attraction versus Persuasion: Information Provision in Search Markets," Papers 1802.09396, arXiv.org, revised May 2022.
    12. Murali Agastya & Oleksii Birulin, 2023. "Optimal Task Scheduling under Adverse Selection and Hidden Actions," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 660-698, May.
    13. Haan, Marco A. & Moraga-González, José L. & Petrikaitė, Vaiva, 2018. "A model of directed consumer search," International Journal of Industrial Organization, Elsevier, vol. 61(C), pages 223-255.
    14. Peter Gibbard, 2022. "A Model of Search with Two Stages of Information Acquisition and Additive Learning," Management Science, INFORMS, vol. 68(2), pages 1212-1217, February.
    15. Chen, Xuqi & Gao, Yujuan & Gao, Zhifeng, 2022. "Impacts of color-coded nutrition facts panel and consumer responses," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322206, Agricultural and Applied Economics Association.
    16. Pak Hung Au & Mark Whitmeyer, 2021. "Attraction Versus Persuasion," HKUST CEP Working Papers Series 202102, HKUST Center for Economic Policy.
    17. Petrikaitė, Vaiva, 2018. "A search model of costly product returns," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 236-251.
    18. Rafael P. Greminger, 2022. "Heterogeneous Position Effects and the Power of Rankings," Papers 2210.16408, arXiv.org, revised Dec 2023.
    19. Jason Abaluck & Giovanni Compiani, 2020. "A Method to Estimate Discrete Choice Models that is Robust to Consumer Search," NBER Working Papers 26849, National Bureau of Economic Research, Inc.
    20. Chen Jin & Luyi Yang & Kartik Hosanagar, 2023. "To Brush or Not to Brush: Product Rankings, Consumer Search, and Fake Orders," Information Systems Research, INFORMS, vol. 34(2), pages 532-552, June.

    More about this item

    Statistics

    Access and download statistics

    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:arx:papers:2308.12242. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.