scholarly journals COVID-19 Enhanced Diminishing Sensitivity in Prospect-Theory Risk Preferences: A Panel Analysis

2020 ◽  
Author(s):  
Shinsuke Ikeda ◽  
Eiji Yamamura ◽  
Yoshiro Tsutsui
1991 ◽  
Vol 73 (2) ◽  
pp. 429-435 ◽  
Author(s):  
Alan Collins ◽  
Wesley N. Musser ◽  
Robert Mason

1996 ◽  
Vol 11 (4) ◽  
pp. 287-295
Author(s):  
Thomas W. Lauer

A questionnaire was administered to 68 software project managers (SPMs). Questions were designed to test whether SPMs’ risky judgments were more consistent with Expected Utility Theory or Prospect Theory. Although the results were more consistent with Prospect Theory, they differed in important ways showing SPMs’ judgments to be less homogeneous than is assumed by either theory. These results highlight the potential importance of SPMs’ judgments to the outcome of software development projects.


2018 ◽  
Vol 20 (2) ◽  
pp. 177-197 ◽  
Author(s):  
Joel Maxcy ◽  
Pamela Wicker ◽  
Joachim Prinz

This study applies prospect theory to an assessment of actual behavior. Loss aversion, reference dependence, and diminishing sensitivity are conceptualized through survey respondents’ perceptions of physical and mental torture during training for and competition in long-distance triathlons. Regression results show that frequent thoughts of giving up during the race negatively affect happiness after the race, while mental torture during training and race is negatively associated with happiness in the weeks after the race. Satisfaction with race outcome positively affects happiness, suggesting that achieving individual goals is more important than absolute performance in terms of finishing times and ranks.


Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 125
Author(s):  
Jianwei Gao ◽  
Yu Yang ◽  
Fangjie Gao ◽  
Haoyu Wu

With the implementation of the carbon neutral policy, the number of electric vehicles (EVs) is increasing. Thus, it is urgently needed to manage the charging and discharging behavior of EVs scientifically. In this paper, EVs are regarded as agents, and a multiagent cooperative optimization scheduling model based on Roth–Erev (RE) algorithm is proposed. The charging and discharging behaviors of EVs will influence each other. The charging and discharging strategy of one EV owner will affect the choice of others. Therefore, the RE algorithm is selected to obtain the optimal charging and discharging strategy of the EV group, with the utility function of the prospect theory proposed to describe EV owners’ different risk preferences. The utility function of the prospect theory has superior effectiveness in describing consumers’ utility. Finally, in the case of residential electricity, the effectiveness of the proposed method is verified. Compared with that of random charging, this method reduces the total EV group cost of EVs by 52.4%, with the load variance reduced by 26.4%.


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