Standard economic models assume people are self-interested and seek to maximize their monetary pay-offs in social interactions. However, people exhibit social preferences; that is, they base their choices partly on the outcomes others obtain in a social interaction and on what others belief about them. People care about fairness, and reciprocity affects behavior. For example, people give gratuity to a waiter although they may be unlikely to ever return to the restaurant. On the negative side, customers who suspect a supplier treats them unfairly are likely to feel angry and may search for (possibly more costly) alternatives. People trust others and cooperate even though they risk losing monetary payoffs.
In our lab we study the interplay between the intuitive emotional system (System 1) and the deliberative rational system (System 2) in social preferences such as trust, honesty, reciprocity and cooperation. Most previous research on the role of cognitive resources in individual decision making showed that when people are less able to use self-control, they are less rational and more prone to biases in decision making. Findings are less clear regarding decisions in social contexts. Using knowledge from psychology about automaticity, self-control, emotion regulation and paradigms from behavioral economics such as the ultimatum game, the trust game and prisoner's dilemma we examine the automaticity of social preferences such as reciprocity, trust and altruism. We also examine the changes in social preferences with age and with learning.
Köbis, N. , Verschuere, B., Bereby-Meyer, Y., Rand, D. & Shalvi, S., (2019).
Intuitive Honesty Versus Dishonesty: Meta-Analytic Evidence
Perspectives on Psychological Science, online fir. | http://doi.org/10.1177/1745691619851778
Gordon-Hecker, T., Rosensaft, D., Pittarello, A., Shalvi, S., & Bereby-Meyer, Y. (2017).
Not Taking responsibility: Equity trumps efficiency in allocation decisions
Journal of Experimental Psychology: General, 146, 771-775 | https://doi.org/10.1037/xge0000273
Halali, E., Bereby-Meyer, Y., & Meiran, N. (2014).
Between rationality and reciprocity: The social bright side of self-control failure
Journal of Experimental Psychology: General. 143, 745-754 | https://doi.org/10.1037/a0033824
Passive risks are risks brought on, or magnified, by inaction (e.g., not reading the “fine print” before signing an agreement, not saving for pension). They differ from active risks, which are incurred by actions people take that put them at risk (e.g., smoking, driving above the speed limit). In our lab we developed the PRT scale to measure these type of risks. We have demonstrated passive risk taking is not linked to classic risk correlates such as sensation seeking, but shows ties to inaction-oriented tendencies such as procrastination and avoidance — variables previously not regarded as relevant to risk taking.
Thus, passive risk taking may be considered a unique domain of risk taking. We are currently examining other individual differences such as self-control, time perspective and anxiety that differentiate between passive and active risks tendency. Additionally, we examine the application of passive risks tendency to real world risks, such as Cyber or health risks.
Idan, T., Keinan, R., & Bereby-Meyer, Y.
Differentiating Passive from Active Risk-Taking: The role of self-control and time perspective
(submitted for publication)
Keinan, R. & Bereby-Meyer, YI. (2012).
"Leaving it to chance" – Passive risk taking in everyday life
Judgment and Decision Making, 7, 705-715 | https://search.proquest.com/docview/1221558568?accountid=14484
Keinan, R. & Bereby-Meyer, Y. (2017).
Perceptions of Active versus Passive Risks, and the Effect of Personal Responsibility
Personality and Social Psychology Bulletin, 43, 1000-1017 | https://doi.org/10.1177/0146167217703079
We often need to predict the future to make decisions. For example, one may want to predict the chances of getting into a prestigious program, or an employer may want to predict the suitability of a candidate for a specific position. In our lab we examine how people make such predictions intuitively, and whether people can overcome biases in predictions. We currently work on the intuitive understanding of suppressor variables in selection decisions. Specifically, we examine whether people are able to consider irrelevant information that contaminates their predictors.