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Market-Based Collective Intelligence in Enterprise 2.0 Decision Making

Title data

Gimpel, Henner ; Teschner, Florian:
Market-Based Collective Intelligence in Enterprise 2.0 Decision Making.
2014
Event: Collective Intelligence 2014 , June 10-12, 2014 , Boston, MA, USA.
(Conference item: Conference , Paper )

Official URL: Volltext

Abstract in another language

In the context of Enterprise 2.0 collective intelligence approaches, we explore the usage of prediction markets as organizational decision support tool. Such markets typically involve market participants (i.e. experts) with a vested interest in the decision. Simply carrying over knowledge on prediction markets to the design of such decision markets might be premature. To back this hypothesis, we build on theory and evidence on prediction markets, decision markets, and market manipulation, and test the key theoretical predictions in a lab experiment.

Our data suggest that indeed, people who have a stake in the decision manipulate the market and partially corrupt information aggregation. More precisely, we show how different designs of the principal’s decision rule affect manipulation, information aggregation, and decision quality. In a nutshell, we find that the common practice is better than random but worse than an alternative design.

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Keywords: prediction markets; electronic markets; information aggregation; manipulation; experiments
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 14 Sep 2018 06:57
Last Modified: 14 Sep 2018 06:57
URI: https://eref.uni-bayreuth.de/id/eprint/45787