Reliability (or "lack thereof") of on-line preference revelation: A controlled experimental analysis

Networks permitting anonymous contributions continue to expand and flourish. In some networks, the reliability of a contribution is not of particular importance. In other settings, however, the development of a network is driven by specific purposes which make the reliability of information exchanged of significant importance. One such situation involves the use of information markets for aggregating individuals' preferences on new or emerging technologies. At this point, there remains skepticism concerning the reliability of the preference revelations in such markets and thus the resulting preference aggregations and rankings of emerging technologies. In this paper, we study the reliability of on-line preference revelation using a series of controlled laboratory experiments. Our analysis includes individuals' pre- and post-experiment rankings of technologies, individual trading and accumulation activities during an electronics market experiment, the final experimental market outcomes, and a ranking of the same technologies by a panel of experts from a Fortune 5 company. In addition, as a final step, we allowed each participant to actually select and keep a unit of one of the technologies at zero price (free). That is, we were able to observe each participant's actual final true preference from the set of technologies. Outcome from information market is much consistent with expert panel.Information market does influence individual preferences.There is considerable inconsistency between survey and individual true preferences.

[1]  V. Smith.  Papers in experimental economics , 1991 .

[2]  James R. Marsden,et al.  The design and use of laboratory experiments for DSS evaluation , 1993, Decis. Support Syst..

[3]  Thomas S. Gruca,et al.  The Effect of Electronic Markets on Forecasts of New Product Success , 2003, Inf. Syst. Frontiers.

[4]  Martin Spann,et al.  Internet-Based Virtual Stock Markets for Business Forecasting , 2003, Manag. Sci..

[5]  James R. Marsden,et al.  The Use of Information System Technology to Develop Tests on Insider Trading and Asymmetric Information , 1999 .

[6]  Tomaso Poggio,et al.  Securities Trading of Concepts (STOC) , 2011 .

[7]  Bartel Van de Walle,et al.  Fuzzy relations for the analysis of traders' preferences in an information market game , 2009, Eur. J. Oper. Res..

[8]  Chao-Hsien Chu,et al.  PREDICTING UNCERTAIN OUTCOMES USING INFORMATION MARKETS: TRADER BEHAVIOR AND INFORMATION AGGREGATION , 2006 .

[9]  James R. Marsden,et al.  Decision making under time pressure with different information sources and performance-based financial incentives - Part 1 , 2002, Decis. Support Syst..

[10]  Christina Ann LaComb,et al.  The imagination market , 2007, Inf. Syst. Frontiers.

[11]  Li Chen,et al.  Design and Use of Preference Markets for Evaluation of Early Stage Technologies , 2009, J. Manag. Inf. Syst..

[12]  V. Smith.  Microeconomic Systems as an Experimental Science , 1982 .

[13]  Martin Spann,et al.  New Product Development 2.0: Preference Markets—How Scalable Securities Markets Identify Winning Product Concepts and Attributes* , 2010 .