
How do individuals process nondiagnostic information? According to Bayes’ theorem, signals that do not carry relevant information are treated as if no signal occurred. This paper provides evidence that individuals update their expectations even after observing uninformative signals. Importantly, the direction in which they update depends on the valence of the signal. Prior beliefs become more optimistic after desirable uninformative signals and more pessimistic after undesirable uninformative signals. Our results provide novel insights why individuals form and entertain false beliefs in environments in which potentially new information is easily accessible but costly to verify (e.g., online media). This paper was accepted by George Wu, behavioral economics and decision analysis. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03367 .
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| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
