Change of Decision-Making Processes in Repeated Risk-Taking Behavior in Complex Dynamic Situations

The purpose of this study is to examine how decision-making processes change in repeated risk-taking behavior in complex dynamic situations. Repeated risk-taking behavior is defined as behavior in which people repeat risk-taking behavior in a complex dynamic situation. For example, in a gambling game people make a bet according to the amount of money they have, and win or loss in a game influences the complex dynamic situation (e.g., total money), and affects the next bet. We limit the discussion to personal decision-making processes. Therefore, we are not concerned here with decision-making processes in a group (e.g., a company and a government) or in an emergency (the scene of a fire or an earthquake). There are three approaches to explaining individual differences in risk-taking behaviors. The first is the "personality factors approach". For instance, Zuckerman (1994) indicated that sensation seekers prefer physical risk-taking behaviors (e.g., skydiving, smoking, and drugs). The second is the "situational factors approach". Tversky & Kahneman (1986) indicated that in gain situations people prefer risk-averse options, but on the contrary, in loss situations people prefer risk-taking options. The third is the interaction approach explained by personality, situational, and cognitive factors. Bromiley & Curley (1992) divided the kinds of risk-situation into physical sensation, gambling and lotteries, everyday life experiences, and business and finance. They examined which personality and cognitive factors influenced risk-taking behaviors. To make the decision-making processes clear, Ueichi & Kusumi (1998a, b) examined the relationship between personality factors (e.g., Five Factor Model, sensation seeking, and optimism), cognitive factors (risk perception, own perceived competence, and perceive a cost and benefit), and risk-taking behaviors in four situations: personal, social, gain-loss, and loss situations. Covariance structure analysis showed two processes: firstly, neuroticism (Five Factor Model) affected risk significance, risk significance affected perceived benefit, and perceived benefit affected risk-taking behavior; secondly, openness affected own perceived competence, own perceived competence affected risk perception, risk perception affected risk-taking behavior. Schunn & Reder (1997) used the Kanfer-Ackerman Air Traffic Controller Task as a complex dynamic situation. They examined the relationship between general intelligence, adaptivity of strategy, and performance. The results indicated that general intelligence affected adaptivity of strategy and performance. The previous researches, however, have not clearly shown the relationship between personality factors, cognitive factors, and risk-taking behavior in repeated risk-taking behavior. In other words, it is not obvious how the decision-making processes of people change in repeated risk-taking behavior in complex dynamic situations. Therefore, the present study uses TV games as a device for reproducing personal, gain-loss, and complex dynamic situations (skiing and gambling) and measures the cognitive factors and preferences of people regarding the level of risk-taking behavior in repeated risk-taking behavior. To make clear the change in decision-making processes, we examine the change of relationship between (1) personality factors and cognitive factors, (2) cognitive factors, and (3) cognitive factors and risk-taking behavior in repeated risk-taking behavior. EXPERIMENTEXPERIMENT METHOD Subjects. Subjects were 25 graduate students (10 males, 15 females). Apparatus.Apparatus. We used a skiing game (SONY PlayStation software: DOWNHILL SNOW, PACK-IN-SOFT Victor Interactive software Inc.) as a physical risk-taking situation and a pachinko game (SANKYO FEVER real machines' simulation Vol.2, T･E･N laboratory) as a gambling situation to measure the preference of subjects regarding the level of risk-taking behavior. Task. Physical risk-taking situation (ski game) Subjects had to reach a goal as fast as possible within a time limit and without falling down. There were two options: the high-risk and high-return course for experts (high-risk course) and the low-risk and low-return course for beginners (low-risk course). Subjects chose one of the courses in each trial. The trial was repeated three times. We instructed subjects that they should think that they were really skiing. Gambling situation (pachinko game) A pachinko game is much the same as a slot machine. Subjects had to get as much money as possible. There were two options: high-risk and high-return machine (high-risk machine) and low-risk and low-return machine (low-risk machine).