Too Good to Be True – Individual and Collective Decision-Making with Misleading Signals

In many situations, an abundance of misleading evidence—such as fake customer reviews—can lead to false or deceptive conclusions. We experimentally investigate individual and collective decision-making in an information structure in which signals can be correlated, depending on the state of the world. In this setting, too much evidence pointing in one direction has the potential to mislead, necessitating a level of sophistication for rational decision-making. Overall, participants’ performance is poor with only small differences in collective and individual decision-making accuracy. Interestingly, the more complex environment tends to encourage greater honesty within heterogeneous groups than a benchmark setting with independent signals, thus corroborating a rather subtle game-theoretic prediction. This paper was accepted by Dorothea Kübler, behavioral economics and decision analysis. Funding: The authors received financial support from Tamkeen under NYU Abu Dhabi Research Institute Award CG005, from the Juniorprofessorenprogramm Baden-Württemberg, and from the Federal Ministry of Labour and Social Affairs (Germany) through the funding network Interdisciplinary Social Policy Research (BMAS-FIS). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06504 .

• 저널Management Science
• 토픽Mobile Crowdsensing and Crowdsourcing · Computer Science Applications
• DOI10.1287/mnsc.2024.06504
• 저자Sebastian Fehrler, Anna Hochleitner, Moritz Janas