A Human-centered Perspective on Interactive Optimization for Extreme Event Decision Making

Author(s):  
Daniel Alejandro Gonzalez Rueda ◽  
David Mendonca
Author(s):  
Georgios Tsaples ◽  
Theodore Tarnanidis

The objective of this chapter is the development of a System Dynamics model for the study of the milk supply chain and how an extreme event can affect its behavior. A simple interface is developed that can be used to increase the ease of communication and provide an interactive approach to the decision-making process. The model contains three echelons: farmers, processors and retailers. The main results show that under normal circumstances, the behavior of the system reaches equilibrium after a few oscillations. However, these oscillations can be smoothed out if the adjustment time of the order placement is increased. Under an extreme event that reduces the demand for milk, behavior changes and the system remains in dis-equilibrium for the entire simulation. Once again, adjustment times remain the leverages that can influence and mitigate those negative effects. Finally, a more robust and collaborative decision-making process among the actors of the chain could be beneficial for all not only under normal circumstances, but also in the presence of extreme uncertainty.


2017 ◽  
Vol 9 (2) ◽  
pp. 227-233 ◽  
Author(s):  
Duzgun Agdas ◽  
Forrest J. Masters ◽  
Gregory D. Webster

Abstract Extreme event perception drives personal risks and, consequently, dictates household decision-making before, during, and after extreme events. Given this, increasing the extreme event perception accuracy of the public is important to improving decision-making in extreme event scenarios; however, limited research has been done on this subject. Results of a laboratory experiment, in which 76 human participants were exposed to hurricane-strength weather conditions and asked to estimate their intensities and associated personal risks, are presented in this article. Participants were exposed to a range of identical wind speeds [20, 40, 60 mph (1 mph = 1.61 km h−1)] with [8 in. h−1 (1 in. = 2.54 cm)] and without rain. They then provided estimates of the perceived wind and rain (when present) speeds, and associated personal risks on a nominal scale of 0 to 10. Improvements in the accuracy of wind speed perception at higher speeds were observed when rain was present in the wind field (41.5 and 69.1 mph) than when it was not (45.2 and 75.8 mph) for 40- and 60-mph wind speed exposures, respectively. In contrast, risk perceptions were similar for both rain and nonrain conditions. This is particularly interesting because participants failed to estimate rain intensities (both horizontal and wind-driven rain) by a significant margin. The possible implications of rain as a perception aid to wind and the viability of using perception aids to better convey extreme weather risks are discussed. The article concludes by revisiting discussions about the implications of past hurricane experience on wind intensity perception, personal risk assessment, and future directions in extreme weather risk perception research.


Author(s):  
Georgios Tsaples ◽  
Theodore Tarnanidis

The objective of this chapter is the development of a System Dynamics model for the study of the milk supply chain and how an extreme event can affect its behavior. A simple interface is developed that can be used to increase the ease of communication and provide an interactive approach to the decision-making process. The model contains three echelons: farmers, processors and retailers. The main results show that under normal circumstances, the behavior of the system reaches equilibrium after a few oscillations. However, these oscillations can be smoothed out if the adjustment time of the order placement is increased. Under an extreme event that reduces the demand for milk, behavior changes and the system remains in dis-equilibrium for the entire simulation. Once again, adjustment times remain the leverages that can influence and mitigate those negative effects. Finally, a more robust and collaborative decision-making process among the actors of the chain could be beneficial for all not only under normal circumstances, but also in the presence of extreme uncertainty.


2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.


2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.


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

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