Abstract
The FAZ.NET-Orakel is a crowd forecasting tool, made available to readers of the German-based Frankfurter Allgemeine Zeitung. Its main component is a prediction market used for forecasting economic indices as well as current political events. A shortcoming of prediction markets is their inability to exchange qualitative information. Therefore, we elaborate the combination of prediction markets with the Real-time Delphi method. We argue that several synergy effects may be achieved by this approach: First, prediction markets can be used to select experts for the Delphi survey. Second, valuable information and debates, which may be of interest, can be collected qualitatively. Third, the gamified approach of the prediction markets can raise commitment to the survey.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Atanasov, P., Rescober, P., Stone, E., Swift, S.A., Servan-Schreiber, E., Tetlock, P., Ungar, L., Mellers, B.: Distilling the wisdom of crowds: prediction markets vs. prediction polls. Manag. Sci., April 2016. http://dx.doi.org/10.1287/mnsc.2015.2374
Buckley, P.: Harnessing the wisdom of crowds: decision spaces for prediction markets. Bus. Horiz. 59(1), 85–94 (2016). http://www.sciencedirect.com/science/article/pii/S0007681315001172
Chen, W., Li, X., Zeng, D.D.: Simple is beautiful: toward light prediction markets. IEEE Intell. Syst. 30(3), 76–80 (2015). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7111878
Graefe, A.: German election forecasting: comparing and combining methods for 2013. Ger. Polit. 24(2), 195–204 (2015). http://dx.doi.org/10.1080/09644008.2015.1024240
Hayek, F.A.: The use of knowledge in society. Am. Econ. Rev. 35(4), 519–530 (1945)
Hevner, A.R.: A three cycle view of design science research. Scand. J. Inf. Syst. 19(2), 4 (2007)
Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS Q. 28(1), 75–105 (2004). http://www.jstor.org/stable/25148625
Kaye, A.: Learning together apart. In: Kaye, A.R. (ed.) Collaborative Learning Through Computer Conferencing. NATO ASI Series (Series F: Computer and Systems Sciences), vol. 90, pp. 1–24. Springer, Heidelberg (1992). doi:10.1007/978-3-642-77684-7_1
Klein, M., Garcia, A.C.B.: High-speed idea filtering with the bag of lemons. Decis. Support Syst. 78, 39–50 (2015). http://www.sciencedirect.com/science/article/pii/S0167923615001190
Kloker, S., Kranz, T.T., Straub, T., Weinhardt, C.: Shouldn’t collaboration be social? - proposal of a social real-time delphi. In: Proceedings of the Second Karlsruhe Service Summit Research Workshop (2016). http://service-summit.ksri.kit.edu/downloads/Session_3B2_KSS_2016_paper_19.pdf
Linstone, H.A., Turoff, M.: Introduction. In: The Delphi Method: Techniques and Applications, chap. 1, pp. 3–12. Addison-Wesley Educational Publishers Inc. (2002)
Prokesch, T., von der Gracht, H.A., Wohlenberg, H.: Integrating prediction market and delphi methodology into a foresight support system - insights from an online game. Technol. Forecast. Soc. Change 97, 47–64 (2015). http://www.sciencedirect.com/science/article/pii/S0040162514000857
Scheiner, C.W., Haas, P., Leicht, N., Voigt, K.I.: Accessing knowledge with a game - a meta-analysis of prediction markets (2013)
Teschner, F.: Forecasting economic indices: design, performance, and learning in prediction markets. Karlsruhe Institute of Technology (KIT) (2012). http://digbib.ubka.uni-karlsruhe.de/volltexte/1000029512
Tetlock, P.E., Mellers, B.A., Scoblic, J.P.: Bringing probability judgments into policy debates via forecasting tournaments. Science 355(6324), 481–483 (2017). http://science.sciencemag.org/content/355/6324/481.abstract
Wagner, C., Back, A.: Group wisdom support systems: aggregating the insights of many trough information technology. Issues Inf. Syst. (IIS) 9(2), 343–350 (2008). http://iacis.org/iis/2008/S2008_992.pdf
Welty, G.: Problems of selecting experts for delphi exercises. Acad. Manag. J. 15(1), 121–124 (1972)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Kloker, S., Straub, T., Weinhardt, C. (2017). Designing a Crowd Forecasting Tool to Combine Prediction Markets and Real-Time Delphi. In: Maedche, A., vom Brocke, J., Hevner, A. (eds) Designing the Digital Transformation. DESRIST 2017. Lecture Notes in Computer Science(), vol 10243. Springer, Cham. https://doi.org/10.1007/978-3-319-59144-5_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-59144-5_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59143-8
Online ISBN: 978-3-319-59144-5
eBook Packages: Computer ScienceComputer Science (R0)