Probing the determinants of risky decision making in the wild

Risky decision making carries many of our behaviors in everyday life. Behavioral researchers have been perpetually probing risky decision making using a plethora of different measures and since over two hundred years, different models have been integrating the results of these measures. Despite this effort, it remains elusive how determinants of risk taking, probed in the enclosed space of the behavioral laboratory, map to actual everyday decisions in the wild. What is the structure of these determinants? Do people have stable preferences for risky decision making over various domains? And how is the perception of risk influencing the process of decision making?
This dissertation focuses on two major determinants of risky decision making; risk preferences, and risk perceptions. The first part includes two manuscripts focusing on quantifying risk preferences that are relevant in real-life. The second part of the dissertation investigates risk perceptions, which come into action especially when people do not have full information about decision-options, which defines most everyday-behavior. Manuscript one probes different existing and newly developed risk-preference measures in terms of retest-reliability and validity. The new measure builds advantages of various existing measures and proves to be more reliable than existing measures of its kind. In manuscript two, we provide an example of how specific and general risk-preference measures boost the predictive power of risky decision making in actual street crossing behavior. Finally, in part two, manuscript three quantifies risk perceptions in a sequential risk task and shows that when knowledge about decision options is incomplete, people rely strongly on their subjective probabilities to make decisions in the task. In turn, these subjective probabilities are very vulnerable to initial experience.
Harnessing decades of research on risky decision making, the results of this dissertation build on over 50 different risk measures to target the gap between decision-theory and everyday behavior. Results from these measures are evaluated using mathematical models of decision making, to make assumptions about the cognitive determinants of risky decision making in the wild.