IDEAS home Printed from https://ideas.repec.org/a/aml/intbrm/v3y2012i3p133-143.html
   My bibliography  Save this article

Using Information Aggregation Markets for Decision Support

Author

Listed:
  • Patrick Buckley

    (University of Limerick, Ireland)

Abstract

Information Aggregation Markets, often referred to as prediction markets, are markets that are designed to aggregate information from a disparate pool of human individuals to make predictions about the likely outcome of future uncertain events. This paper looks at how Information Aggregation Markets can be incorporated into the standard body of decision making theory. It examines how Information Aggregation Markets can be used as decision support systems, and provides empirical evidence from a wide variety of sources as to the effectiveness and practicality of Information Aggregation Markets. Finally, this paper details some future research questions to be addressed in the area of Information Aggregation Markets.

Suggested Citation

  • Patrick Buckley, 2012. "Using Information Aggregation Markets for Decision Support," International Journal of Business Research and Management (IJBRM), Computer Science Journals (CSC Journals), vol. 3(3), pages 133-143, June.
  • Handle: RePEc:aml:intbrm:v:3:y:2012:i:3:p:133-143
    as

    Download full text from publisher

    File URL: https://www.cscjournals.org/manuscript/Journals/IJBRM/Volume3/Issue3/IJBRM-92.pdf
    Download Restriction: no

    File URL: https://www.cscjournals.org/library/manuscriptinfo.php?mc=IJBRM-92
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kay-Yut Chen & Leslie R. Fine & Bernardo A. Huberman, 2003. "Predicting the Future," Information Systems Frontiers, Springer, vol. 5(1), pages 47-61, January.
    2. Martin Spann & Bernd Skiera, 2003. "Internet-Based Virtual Stock Markets for Business Forecasting," Management Science, INFORMS, vol. 49(10), pages 1310-1326, October.
    3. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    4. Georgios Tziralis & Ilias Tatsiopoulos, 2007. "Prediction Markets: An Extended Literature Review," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 75-91, February.
    5. Burton G. Malkiel, 2005. "Reflections on the Efficient Market Hypothesis: 30 Years Later," The Financial Review, Eastern Finance Association, vol. 40(1), pages 1-9, February.
    6. Boyle, Glenn & Videbeck, Steen, 2005. "A Primer on Information Markets," Working Paper Series 3853, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    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. Matteo Cristofaro & Pier Luigi Giardino & Luna Leoni, 2021. "Back to the Future: A Review and Editorial Agenda of the International Journal of Business Research and Management," International Journal of Business Research and Management (IJBRM), Computer Science Journals (CSC Journals), vol. 12(1), pages 16-33, February.
    2. Wolfgang Ossadnik & Ralf H. Kaspar & Stefanie Schinke, 2013. "Constructing a Tailor-made Performance Management System Supported by Knowledge Elicitation Tools and Dynamic Modeling," International Journal of Business Research and Management (IJBRM), Computer Science Journals (CSC Journals), vol. 4(4), pages 75-98, November.

    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. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
    2. Patrick Buckley & Fergal O’Brien, 2017. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 19(3), pages 611-623, June.
    3. Ledyard, John & Hanson, Robin & Ishikida, Takashi, 2009. "An experimental test of combinatorial information markets," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 182-189, February.
    4. Buckley, Patrick, 2016. "Harnessing the wisdom of crowds: Decision spaces for prediction markets," Business Horizons, Elsevier, vol. 59(1), pages 85-94.
    5. van Bruggen, G.H. & Spann, M. & Lilien, G.L. & Skiera, B., 2006. "Institutional Forecasting: The Performance of Thin Virtual Stock Markets," ERIM Report Series Research in Management ERS-2006-028-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Siemroth, Christoph, 2014. "Why prediction markets work : The role of information acquisition and endogenous weighting," Working Papers 14-02, University of Mannheim, Department of Economics.
    7. McKenzie, Jordi, 2013. "Predicting box office with and without markets: Do internet users know anything?," Information Economics and Policy, Elsevier, vol. 25(2), pages 70-80.
    8. Lennart Sjöberg, 2009. "Are all crowds equally wise? a comparison of political election forecasts by experts and the public," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 1-18.
    9. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    10. Green, Lawrence & Sung, Ming-Chien & Ma, Tiejun & Johnson, Johnnie E. V., 2019. "To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market," European Journal of Operational Research, Elsevier, vol. 278(1), pages 226-239.
    11. Mikuláš Gangur & Miroslav Plevný, 2014. "Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(36), pages 578-578, May.
    12. Dai, Min & Jia, Yanwei & Kou, Steven, 2021. "The wisdom of the crowd and prediction markets," Journal of Econometrics, Elsevier, vol. 222(1), pages 561-578.
    13. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
    14. Elberse, Anita & Anand, Bharat, 2007. "The effectiveness of pre-release advertising for motion pictures: An empirical investigation using a simulated market," Information Economics and Policy, Elsevier, vol. 19(3-4), pages 319-343, October.
    15. Khan, Urmee & Lieli, Robert P., 2018. "Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries," International Journal of Forecasting, Elsevier, vol. 34(4), pages 696-710.
    16. Victor Tiberius & Christoph Rasche, 2011. "Prognosemärkte," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 21(4), pages 467-472, April.
    17. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    18. Franck, Egon & Verbeek, Erwin & Nüesch, Stephan, 2010. "Prediction accuracy of different market structures -- bookmakers versus a betting exchange," International Journal of Forecasting, Elsevier, vol. 26(3), pages 448-459, July.
    19. Schadner, Wolfgang, 2022. "U.S. Politics from a multifractal perspective," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    20. Hedtrich, F. & Loy, J.-P. & Müller, R.A.E., 2010. "Prognosen auf Agrarmärkten: Prediction Markets – eine innovative Prognosemethode auch für die Landwirtschaft?," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 45, March.

    More about this item

    Keywords

    Information Aggregation Markets; Decision Making; Decision Support Systems;
    All these keywords.

    JEL classification:

    • M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General

    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:aml:intbrm:v:3:y:2012:i:3:p:133-143. 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: Nabeel Tahir (email available below). General contact details of provider: .

    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.