IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v50y2017i4d10.1007_s10614-016-9614-z.html
   My bibliography  Save this article

The Psychological Force Model for Lowest Unique Bid Auction

Author

Listed:
  • Rui Hu

    (Beijing Normal University)

  • Jinzhong Guo

    (Xinjiang University)

  • Qinghua Chen

    (Beijing Normal University)

  • Tao Zheng

    (Beijing Normal University)

Abstract

We study a type of complex system arising from economics, the lowest unique bid auction (LUBA) system which is a new generation of online markets. Different from the traditional auction in which the winner is who bids the highest price, in LUBA, the winner is whoever places the lowest of all unique bids. In this paper, we propose a multi-agent model to factually describes the human psychologies of the decision-making process in LUBA. The model produces bid-price distributions that are in excellent agreement with those from the real data, including the whole inverted-J shape which is a general feature of the real bid price distribution, and the exponential decreasing shape in the higher price range. This implies that it is possible for us to capture the essential features of human psychologies in the competitive environment as exemplified by LUBA and that we may provide significant quantitative insights into complex socio-economic phenomena.

Suggested Citation

  • Rui Hu & Jinzhong Guo & Qinghua Chen & Tao Zheng, 2017. "The Psychological Force Model for Lowest Unique Bid Auction," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 655-667, December.
    • Handle: RePEc:kap:compec:v:50:y:2017:i:4:d:10.1007_s10614-016-9614-z
    DOI: 10.1007/s10614-016-9614-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-016-9614-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-016-9614-z?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Simone Pigolotti & Sebastian Bernhardsson & Jeppe Juul & Gorm Galster & Pierpaolo Vivo, 2011. "Equilibrium strategy and population-size effects in lowest unique bid auctions," Papers 1105.0819, arXiv.org, revised Feb 2012.
    2. Krishna, Vijay, 2009. "Auction Theory," Elsevier Monographs, Elsevier, edition 2, number 9780123745071.
    3. Cancan Zhou & Hongguang Dong & Rui Hu & Qinghua Chen, 2015. "Smarter than Others? Conjectures in Lowest Unique Bid Auctions," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-13, April.
    4. Harold Houba & Dinard Laan & Dirk Veldhuizen, 2011. "Endogenous entry in lowest-unique sealed-bid auctions," Theory and Decision, Springer, vol. 71(2), pages 269-295, August.
    5. Ho, William & Xu, Xiaowei & Dey, Prasanta K., 2010. "Multi-criteria decision making approaches for supplier evaluation and selection: A literature review," European Journal of Operational Research, Elsevier, vol. 202(1), pages 16-24, April.
    6. Diehl, Ernst & Sterman, John D., 1995. "Effects of Feedback Complexity on Dynamic Decision Making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 62(2), pages 198-215, May.
    7. Robert Östling & Joseph Tao-yi Wang & Eileen Y. Chou & Colin F. Camerer, 2011. "Testing Game Theory in the Field: Swedish LUPI Lottery Games," American Economic Journal: Microeconomics, American Economic Association, vol. 3(3), pages 1-33, August.
    8. Yinan Zhao & Qinghua Chen & Yougui Wang, 2014. "Bid distribution derived from consistent mixed strategy in lowest unique bid auction," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(05), pages 1-10.
    9. Zhang, Jianhua & Chen, Qinghua & Wang, Yougui, 2009. "Zipf distribution in top Chinese firms and an economic explanation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(10), pages 2020-2024.
    10. Simone Pigolotti & Sebastian Bernhardsson & Jeppe Juul & Gorm Galster & Pierpaolo Vivo, 2012. "Equilibrium strategy and population-size effects in lowest unique bid auctions," Post-Print hal-00681002, HAL.
    11. Ariely, Dan, 2000. "Controlling the Information Flow: Effects on Consumers' Decision Making and Preferences," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(2), pages 233-248, September.
    12. Rapoport, Amnon & Otsubo, Hironori & Kim, Bora & Stein, William E., 2007. "Unique bid auctions: Equilibrium solutions and experimental evidence," MPRA Paper 4185, University Library of Munich, Germany, revised 17 Jul 2007.
    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. Yamada, Takashi & Hanaki, Nobuyuki, 2016. "An experiment on Lowest Unique Integer Games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 88-102.
    2. Nadir Altinok & Abdurrahman Aydemir, 2015. "The Unfolding of Gender Gap in Education," Working Papers 934, Economic Research Forum, revised Aug 2015.
    3. Cancan Zhou & Hongguang Dong & Rui Hu & Qinghua Chen, 2015. "Smarter than Others? Conjectures in Lowest Unique Bid Auctions," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-13, April.
    4. Mohlin, Erik & Östling, Robert & Wang, Joseph Tao-yi, 2015. "Lowest unique bid auctions with population uncertainty," Economics Letters, Elsevier, vol. 134(C), pages 53-57.
    5. Mohlin, Erik & Östling, Robert & Wang, Joseph Tao-yi, 2020. "Learning by similarity-weighted imitation in winner-takes-all games," Games and Economic Behavior, Elsevier, vol. 120(C), pages 225-245.
    6. Berger, Ulrich & De Silva, Hannelore & Fellner-Röhling, Gerlinde, 2016. "Cognitive hierarchies in the minimizer game," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 337-348.
    7. Wang, Zhongmin & Xu, Minbo, 2016. "Selling a dollar for more than a dollar? Evidence from online penny auctions," Information Economics and Policy, Elsevier, vol. 36(C), pages 53-68.
    8. Wang, Zhongmin & Xu, Minbo, 2013. "Selling a Dollar for More Than a Dollar? Evidence from Online Penny Auctions," RFF Working Paper Series dp-13-15, Resources for the Future.
    9. Erik Mohlin & Robert Ostling & Joseph Tao-yi Wang, 2014. "Learning by Imitation in Games: Theory, Field, and Laboratory," Economics Series Working Papers 734, University of Oxford, Department of Economics.
    10. Eichberger, Jürgen & Vinogradov, Dmitri, 2016. "Efficiency of Lowest-Unmatched Price Auctions," Economics Letters, Elsevier, vol. 141(C), pages 98-102.
    11. Andrea Gallice, 2010. "Price Reveal Auctions on the Internet," Carlo Alberto Notebooks 147, Collegio Carlo Alberto.
    12. Andrea Gallice & Giuseppe Sorrenti, 2022. "Curious about the price? Consumers’ behavior in price reveal auctions," Applied Economics Letters, Taylor & Francis Journals, vol. 29(9), pages 831-834, May.
    13. Toomas Hinnosaar, 2013. "Penny Auctions are Unpredictable," Carlo Alberto Notebooks 305, Collegio Carlo Alberto.
    14. Andrea Gallice, 2008. "Lowest Unique Bid Auctions over the Internet: Ability, Lottery or Scam?," Department of Economic Policy, Finance and Development (DEPFID) University of Siena 0608, Department of Economic Policy, Finance and Development (DEPFID), University of Siena.
    15. Harold Houba & Dinard Laan & Dirk Veldhuizen, 2011. "Endogenous entry in lowest-unique sealed-bid auctions," Theory and Decision, Springer, vol. 71(2), pages 269-295, August.
    16. Costa-Gomes, Miguel A. & Shimoji, Makoto, 2014. "Theoretical approaches to lowest unique bid auctions," Journal of Mathematical Economics, Elsevier, vol. 52(C), pages 16-24.
    17. Pierre Bernhard & Marc Deschamps, 2017. "On Dynamic Games with Randomly Arriving Players," Dynamic Games and Applications, Springer, vol. 7(3), pages 360-385, September.
    18. Laurent Lamy, 2013. "“Upping the ante”: how to design efficient auctions with entry?," RAND Journal of Economics, RAND Corporation, vol. 44(2), pages 194-214, June.
    19. Petra Štamfestová & Lukáš Sobíšek & Jiří Hnilica, 2023. "Firm Size Distribution in the Central European Context," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 151-175.
    20. Jianxiong Zhang & Lin Feng & Wansheng Tang, 2014. "Optimal Contract Design of Supplier-Led Outsourcing Based on Pontryagin Maximum Principle," Journal of Optimization Theory and Applications, Springer, vol. 161(2), pages 592-607, May.

    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:kap:compec:v:50:y:2017:i:4:d:10.1007_s10614-016-9614-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.