This repeated decision framework means that small statistical improvements in decisions will, over time, contribute to significant value.
In contrast to the simple single variable/single repeated decision setting of this case study, there are situations when multi-factor forecast information may be valuable for tactical, operational and strategic decisions.
"It's never a coincidence when a public official makes repeated decisions against sexual assault victims.
The regulation in question is quite as great an interference as a tax of the kind that repeated decisions have held void.
In order to derive a condition for switching between the expert and aggregated rules for repeated decisions, we first make the following assumption: For each decision, a group uses the expert rule if its optimality condition (equation 2, Model 1) is satisfied; and switch to the aggregated rule if the condition is violated.
Interestingly, for one-shot decisions, groups should use the information of the most informed individual – the expert – but for repeated decisions it pays to adopt an aggregated rule, as on average, it performs better (see Supplementary Files S1 and S2 for full model outputs).
With a former student, Yuh-Jia Chen, I have been investigating how people make repeated decisions, and the role of learning in shaping decision behavior in such contexts.
Blowing off dinner with a significant other may seem less consequential in the present day than not meeting the client's deadline (a potential immediate firing), but the long-term consequences of these repeated decisions are often unaccounted for -- until it's too late.
With another former student, Jie Gao, I have been investigating a longstanding puzzle in decision-making research: why people fail to choose optimally in repeated decisions, and instead "probability match".
These principles have been established by repeated decisions.
This would seem to be sufficiently set at rest by repeated decisions.
