ABSTRACT-When people have access to information sources such as newspaper weather forecasts, drug-package inserts, and mutual-fund brochures, all of which provide convenient descriptions of risky prospects, they can make decisions from description. When people must decide whether to back up their computer's hard drive, cross a busy street, or go out on a date, however, they typically do not have any summary description of the possible outcomes or their likelihoods. For such decisions, people can call only on their own encounters with such prospects, making decisions from experience. Decisions from experience and decisions from description can lead to dramatically different choice behavior. In the case of decisions from description, people make choices as if they overweight the probability of rare events, as described by prospect theory. We found that in the case of decisions from experience, in contrast, people make choices as if they underweight the probability of rare events, and we explored the impact of two possible causes of this underweighting-reliance on relatively small samples of information and overweighting of recently sampled information. We conclude with a call for two different theories of risky choice.
According to a common conception in behavioral decision research, two cognitive processes-overestimation and overweighting-operate to increase the impact of rare events on people's choices. Supportive findings stem primarily from investigations in which people learn about options via descriptions thereof. Recently, a number of researchers have begun to investigate risky choice in settings in which people learn about options by experiential sampling over time. This article reviews work across three experiential paradigms. Converging findings show that when people make decisions based on experience, rare events tend to have less impact than they deserve according to their objective probabilities. Striking similarities in human and animal experience-based choices, ways of modeling these choices, and their implications for risk and precautionary behavior are discussed.
Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, the authors generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (a) the Allais paradox, (b) risk aversion for gains if probabilities are high, (c) risk seeking for gains if probabilities are low (e.g., lottery tickets), (d) risk aversion for losses if probabilities are low (e.g., buying insurance), (e) risk seeking for losses if probabilities are high, (f) the certainty effect, (g) the possibility effect, and (h) intransitivities. The authors test how accurately the heuristic predicts people's choices, compared with previously proposed heuristics and 3 modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attentionexchange model, and cumulative prospect theory.Keywords: risky choice, heuristics, decision making, frugality, choice process Conventional wisdom tells us that making decisions becomes difficult whenever multiple priorities, appetites, goals, values, or simply the attributes of the alternative options are in conflict. Should one undergo a medical treatment that has some chance of curing a life-threatening illness but comes with the risk of debilitating side effects? Should one report a crime committed by a friend? Should one buy an expensive, high-quality camera or an inexpensive, low-quality camera? How do people resolve conflicts, ranging from the prosaic to the profound?The common denominator of many theories of human behavior is the premise that conflicts are mastered by making trade-offs. Since the Enlightenment, it has been believed that weighting and summing are the processes by which such trade-offs can be made in a rational way. Numerous theories of human behavior-including expected value theory, expected utility theory, prospect theory, Benjamin Franklin's moral algebra, theories of moral sense such as utilitarianism and consequentionalism (Gigerenzer, 2004), theories of risk taking (e.g., Wigfield & Eccles, 1992), motivational theories of achievement (Atkinson, 1957) and work behavior (e.g., Vroom, 1964), theories of social learning (Rotter, 1954), theories of attitude formation (e.g., Fishbein & Ajzen, 1975), and theories of health behavior (e.g., Becker, 1974; for a review see Heckhausen, 1991)-rest on these two processes. Take how expected utility theory would account for the choice between two investment plans as an example. The reasons for choosing are often negatively correlated with one another. High returns go with low probabilities, and low returns go with high probabilities. According to a common argument, negative correlations between reasons cause people to experience conflict, leading them to make tradeoffs (Shanteau & Thomas, 2000). In terms of expected utility, the trade-off between investment plans is performed by weighting the utility of the respective ...
On the basis of 39 risk-taking measures, this study finds evidence for a general and stable factor of risk preference.
Does risk taking change as a function of age? We conducted a systematic literature search and found 29 comparisons between younger and older adults on behavioral tasks thought to measure risk taking (N =4,093). The reports relied on various tasks differing in several respects, such as the amount of learning required or the choice framing (gains vs. losses). The results suggest that age-related differences vary considerably as a function of task characteristics, in particular the learning requirements of the task. In decisions from experience, age-related differences in risk taking were a function of decreased learning performance: older adults were more risk seeking compared to younger adults when learning led to risk-avoidant behavior, but were more risk averse when learning led to risk-seeking behavior. In decisions from description, younger adults and older adults showed similar risk-taking behavior for the majority of the tasks, and there were no clear age-related differences as a function of gain/loss framing. We discuss limitations and strengths of past research and provide suggestions for future work on age-related differences in risk taking.
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