Risk-Seeking Behavior and its Implications for the Optimal Decision Making of Annuity Insurers

2021 ◽  
Author(s):  
Cuixia Chen ◽  
Yijia Lin ◽  
Ming Zhou
Keyword(s):  
Decision Making ◽  
Optimal Decision ◽  
Risk Seeking ◽  
Seeking Behavior ◽  
Optimal Decision Making

scholarly journals Optimizing motor decision-making through competition with opponents

2018 ◽  
Author(s):  
Keiji Ota ◽  
Mamoru Tanae ◽  
Kotaro Ishii ◽  
Ken Takiyama
Keyword(s):  
Decision Making ◽  
Optimal Solution ◽  
Optimal Decision ◽  
Fine Motor ◽  
Risk Averse ◽  
Risk Seeking ◽  
Competitive Game ◽  
Ski Jumping ◽  
Human Motor ◽  
Optimal Decision Making

AbstractAlthough optimal decision-making is essential for sports performance and fine motor control, it has been repeatedly confirmed that humans show a strong risk-seeking bias, selecting a risky strategy over an optimal solution. Despite such evidence, the ideal method to promote optimal decision-making remains unclear. Here, we propose that interactions with other people can influence motor decision-making and improve risk-seeking bias. We developed a competitive reaching game (a variant of the “chicken game”) in which aiming for greater rewards increased the risk of no reward and subjects competed for the total reward with their opponent. The game resembles situations in sports, such as a penalty kick in soccer, service in tennis, the strike zone in baseball, or take-off in ski jumping. In five different experiments, we demonstrated that, at the beginning of the competitive game, the subjects robustly switched their risk-seeking strategy to a risk-averse strategy. Following the reversal of the strategy, the subjects achieved optimal decision-making when competing with risk-averse opponents. This optimality was achieved by a non-linear influence of an opponent’s decisions on a subject’s decisions. These results suggest that interactions with others can alter human motor decision strategies and that competition with a risk-averse opponent is key for optimizing motor decision-making.

scholarly journals GEAR: On Optimal Decision Making with Auxiliary Data

Stat ◽  
2021 ◽  
Author(s):  
Hengrui Cai ◽  
Rui Song ◽  
Wenbin Lu
Keyword(s):  
Decision Making ◽  
Optimal Decision ◽  
Auxiliary Data ◽  
Optimal Decision Making

Operation decision of logistics service supply chain: considering interruption probability in emergencies

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guangsheng Zhang ◽  
Xiao Wang ◽  
Zhiqing Meng ◽  
Qirui Zhang ◽  
Kexin Wu
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Evolutionary Game ◽  
Optimal Strategies ◽  
Optimal Decision ◽  
Content Type ◽  
Logistics Service ◽  
Social Reputation ◽  
Punishment Intensity ◽  
Optimal Decision Making

PurposeTo remedy the inherent defect in current research that focuses only on a single type of participants, this paper endeavors to look into the situation as an evolutionary game between a representative Logistics Service Integrator (LSI) and a representative Functional Logistics Service Provider (FLSP) in an environment with sudden crisis and tries to analyze how LSI supervises FLSP's operations and how FLSP responds in a recurrent pattern with different interruption probabilities.Design/methodology/approachRegarding the risks of supply chain interruption in emergencies, this paper develops a two-level model of single LSI and single FLSP, using Evolutionary Game theory to analyze their optimal decision-making, as well as their strategic behaviors on different risk levels regarding the interruption probability to achieve the optimal return with bounded rationality.FindingsThe results show that on a low-risk level, if LSI increases the degree of punishment, it will fail to enhance FLSP's operational activeness in the long term; when the risk rises to an intermediate level, a circular game occurs between LSI and FLSP; and on a high level of risk, FLSP will actively take actions, and its functional probability further impacts LSI's strategic choices. Finally, this paper analyzes the moderating impact of punishment intensity and social reputation loss on the evolutionary model in emergencies and provides relevant managerial implications.Originality/valueFirst, by taking both interruption probability and emergencies into consideration, this paper explores the interactions among the factors relevant to LSI's and FLSP's optimal decision-making. Second, this paper analyzes the optimal evolutionary game strategies of LSI and FLSP with different interruption probability and the range of their optimal strategies. Third, the findings of this paper provide valuable implications for relevant practices, such that the punishment intensity and social reputation loss determine the optimal strategies of LSI and FLSP, and thus it is an effective vehicle for LSSC system administrator to achieve the maximum efficiency of the system.

Blockchain Based Optimal Decision Making Of Dispatchable Units In Smart Grids Considering The High Uncertainty Effects

2021 ◽  
pp. 103418
Author(s):  
Xiangqian Zhu ◽  
Wenfeng Wang ◽  
Suhong Pang ◽  
Chaoyin An ◽  
Xiaoliang Yang ◽  
...  
Keyword(s):  
Decision Making ◽  
Smart Grids ◽  
Optimal Decision ◽  
Optimal Decision Making ◽  
High Uncertainty
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