scholarly journals The Role of Risk Aversion in Non-Conscious Decision Making

2012 ◽  
Vol 3 ◽  
Author(s):  
Shuo Wang ◽  
Ian Krajbich ◽  
Ralph Adolphs ◽  
Naotsugu Tsuchiya
2017 ◽  
Author(s):  
John R. Nofsinger ◽  
Fernando Patterson ◽  
Corey A. Shank ◽  
Robert T. Daigler

Author(s):  
James C. Engle Warnick ◽  
Javier Escobal ◽  
Sonia C. Laszlo

Abstract While the effect of risk aversion on farmers' decision-making has long been documented, far less is known about the effect of ambiguity aversion. We argue that ambiguity aversion is just as relevant to their decision-making process because they are uncertain about the yield distributions generated by new technologies. By experimentally measuring risk and ambiguity aversion in rural Peru, we provide new evidence on the role of ambiguity aversion on farm decisions in developing countries: ambiguity aversion, not risk aversion, reduces the likelihood that farmers plant more than one variety of their main crop.


2018 ◽  
Vol 10 (8) ◽  
pp. 1
Author(s):  
Fan Liu

Risk and time preferences influence the insurance purchase decisions under uncertainty. Accident forgiveness, often considered as “premium insurance,” protects policyholders against a premium increase in the next period if an at-fault accident occurs. In this paper, by conducting a unique experiment in the controlled laboratory conditions, we examine the role of risk and time preferences in accident forgiveness purchase decisions. We find that individual discount rates and product price significantly affect premium insurance purchase decision. Interestingly, we also find evidence that less risk averse policyholders in general behave more like risk neutral when making insurance decision. Risk attitudes affect insurance decision-making only among those who have relatively high degree of risk aversion.


2021 ◽  
Author(s):  
Carsten Bogler ◽  
Bojana Grujičić ◽  
John-Dylan Haynes

Experiments on choice-predictive brain signals have played an important role in the debate on free will. In a seminal study, Benjamin Libet and colleagues found that a negative-going EEG signal, the readiness potential (RP), can be observed over motor-related brain regions already a few hundred ms before a participant makes a conscious decision to move. If the onset of the readiness potential is taken as an indicator of the "brain's decision to move" this could mean that this decision to move is made early, by unconscious brain activity, rather than later, at the time when the subject believes to be deciding. However, an alternative interpretation has recently been discussed, the stochastic decision model (SDM), that takes its inspiration from models of perceptual decision making. It suggests that the RP originates from an accumulation of stochastic internal fluctuations. In this view the decision happens only at a much later stage when an accumulated noise signal reaches a threshold. Here we address a number of confusions regarding both the evidence for the stochastic decision model as well as its interpretation. We will show: (a) that the evidence for the role of stochastic fluctuations is highly indirect; (b) that there is little direct support for the SDM from animal studies; (c) that deterministic (non-random) processes can explain the data in a similar way; (d) that the relative components of the model have been mischaracterized leading to an over-emphasis on the role of random fluctuations and an under-emphasis of deterministic aspects of the model; (e) that there is confusion regarding the role of "urgency" and "evidence" in the SDM and its link to perceptual decision making; (f) that the question whether the decision happens early or late depends on the nature of the noise fluctuations, specifically, whether they reflect "absolute" or "epistemic" randomness; (g) finally, that the model does not explain the temporal relationship between conscious decision and neural decision. Our aim is not to rehabilitate the role of RPs in the free will debate. Rather we aim to address some confusions and premature conclusions regarding the evidence for accumulators playing a role in these preparatory brain processes.


2018 ◽  
Vol 29 ◽  
pp. 1-16 ◽  
Author(s):  
John R. Nofsinger ◽  
Fernando M. Patterson ◽  
Corey A. Shank

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.


2014 ◽  
Vol 38 (01) ◽  
pp. 46
Author(s):  
David R. Shanks ◽  
Ben R. Newell

2014 ◽  
Vol 38 (01) ◽  
pp. 48
Author(s):  
David R. Shanks ◽  
Ben R. Newell

2014 ◽  
Vol 21 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Helen Pryce ◽  
Amanda Hall

Shared decision-making (SDM), a component of patient-centered care, is the process in which the clinician and patient both participate in decision-making about treatment; information is shared between the parties and both agree with the decision. Shared decision-making is appropriate for health care conditions in which there is more than one evidence-based treatment or management option that have different benefits and risks. The patient's involvement ensures that the decisions regarding treatment are sensitive to the patient's values and preferences. Audiologic rehabilitation requires substantial behavior changes on the part of patients and includes benefits to their communication as well as compromises and potential risks. This article identifies the importance of shared decision-making in audiologic rehabilitation and the changes required to implement it effectively.


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