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The Effect of Electronic Markets on Forecasts of New Product Success

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  • Thomas S. Gruca

    (University of Iowa)

  • Joyce Berg

    (University of Iowa)

  • Michael Cipriano

    (University of Iowa)

Abstract

In this paper, we extend field experiments of real money prediction markets to the problem of forecasting the success of a new product. We collect forecasts using a traditional survey mechanism and a market mechanism. Our results suggest that market prices summarize the information contained in survey forecasts and improve those forecasts by reducing the variability of the forecast. However, we find no evidence of a “crystal ball” equilibrium. Our markets have considerable variability and predict only as well as the public signal provided by the HSX movie market game.

Suggested Citation

  • Thomas S. Gruca & Joyce Berg & Michael Cipriano, 2003. "The Effect of Electronic Markets on Forecasts of New Product Success," Information Systems Frontiers, Springer, vol. 5(1), pages 95-105, January.
    • Handle: RePEc:spr:infosf:v:5:y:2003:i:1:d:10.1023_a:1022054108164
    DOI: 10.1023/A:1022054108164
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    References listed on IDEAS

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    1. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-1161, December.
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    5. Jehoshua Eliashberg & Mohanbir S. Sawhney, 1994. "Modeling Goes to Hollywood: Predicting Individual Differences in Movie Enjoyment," Management Science, INFORMS, vol. 40(9), pages 1151-1173, September.
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    Cited by:

    1. Li Chen & Paulo Goes & Wynd Harris & James Marsden & John Zhang, 2010. "Preference Markets for Innovation Ranking and Selection," Interfaces, INFORMS, vol. 40(2), pages 144-153, April.
    2. Christina Ann LaComb & Janet Arlie Barnett & Qimei Pan, 2007. "The imagination market," Information Systems Frontiers, Springer, vol. 9(2), pages 245-256, July.
    3. Martin Spann & Bernd Skiera, 2009. "Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 55-72.
    4. Shan Wang & Shi Zheng & Lida Xu & Dezheng Li & Huan Meng, 2008. "A literature review of electronic marketplace research: Themes, theories and an integrative framework," Information Systems Frontiers, Springer, vol. 10(5), pages 555-571, November.
    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. Stefan Palan & Jürgen Huber & Larissa Senninger, 2020. "Aggregation mechanisms for crowd predictions," Experimental Economics, Springer;Economic Science Association, vol. 23(3), pages 788-814, September.
    7. repec:grz:wpsses:2019-01 is not listed on IDEAS

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