The Role of Aspiration Level in Risky Choice: A Comparison of Cumulative Prospect Theory and SP/A Theory

Lopes, Lola L.; Oden, Gregg C.

doi:10.1006/jmps.1999.1259

Cited by 312 publications

(252 citation statements)

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“…We tested the priority heuristic in four different sets of choice problems (Erev et al, 2002;Kahneman & Tversky, 1979;Lopes & Oden, 1999;Tversky & Kahneman, 1992). Two of these sets of problems were designed to test prospect theory and cumulative prospect theory, and one was designed to test security-potential/ aspiration theory (Lopes & Oden, 1999); none, of course, were designed to test the priority heuristic. The contestants used were three modifications of expected utility theory: cumulative prospect theory, security-potential/aspiration theory, and the transfer of attention exchange model (Birnbaum & Chavez, 1997).…”

Section: Problems?mentioning

confidence: 99%

“…To avoid this problem, we used the fitted parameter estimates from one set of choice problems to predict the choices in a different one. For cumulative prospect theory, we used three sets of parameter estimates derived from Erev et al (2002), Oden (1999), andKahneman (1992). For the choice problems by Kahneman and Tversky (1979), no such parameter estimates exist.…”

Section: The Contestantsmentioning

confidence: 99%

“…We used the same parameter estimates as in the four contests. For cumulative prospect theory, Figure 8 shows the mean performance across the three analyses using the parameter estimates from Erev et al (2002), Oden (1999), andKahneman (1992). Problem representation-A final potential limitation refers to the impact of different representations of the same decision problems on people's choices.…”

Section: Discrepant Expected Values-anothermentioning

confidence: 99%

“…No parameters for overweighting small probabilities and underweighting large probabilities or for the value function are built in. Can this simple model account for people's choices as well as multiparameter outcome models can?To answer this question, we test whether the priority heuristic(1) can account for evidence at variance with EU theory, namely (i) the Allais paradox, (ii) risk aversion for gains if probabilities are high, (iii) risk seeking for gains if probabilities are low (e.g., lottery tickets), (iv) risk aversion for losses if probabilities are low (e.g., buying insurance), (v) risk seeking for losses if probabilities are high, (vi) the certainty effect, (vii) the possibility effect, and (viii) intransitivities; and (2) can predict the empirical choices in four classes of gambles: (i) simple choice problems (no more than two nonzero outcomes; Kahneman & Tversky, 1979), (ii) multiple-outcome gambles (Lopes & Oden, 1999), (iii) gambles inferred from certainty equivalents (Tversky & Kahneman, 1992), and (iv) randomly sampled gambles (Erev et al, 2002). …”

mentioning

confidence: 99%

“…How does it fare when tested against a larger set of problems? We tested the priority heuristic in four different sets of choice problems (Erev et al, 2002;Kahneman & Tversky, 1979;Lopes & Oden, 1999;Tversky & Kahneman, 1992). Two of these sets of problems were designed to test prospect theory and cumulative prospect theory, and one was designed to test security-potential/ aspiration theory (Lopes & Oden, 1999); none, of course, were designed to test the priority heuristic.…”

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confidence: 99%

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The Priority Heuristic: Making Choices Without Trade-offs

Brandstätter¹,

Gigerenzer²,

Hertwig³

2011

Heuristics

100

182

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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, we generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (i) Allais' paradox, (ii) risk aversion for gains if probabilities are high, (iii) risk seeking for gains if probabilities are low (lottery tickets), (iv) risk aversion for losses if probabilities are low (buying insurance), (v) risk seeking for losses if probabilities are high, (vi) certainty effect, (vii) possibility effect, and (viii) intransitivities. We test how accurately the heuristic predicts people's choices, compared to previously proposed heuristics and three modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory.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 lifethreatening 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 trade-offs (Shanteau & Thomas, 2000). Europe PMC Funders Author ManuscriptsEurope PMC Funders Author Manuscripts utility, the trade-off between investment plans is performed by weighting the utility of the respective monetary outcomes by their probabilities and...

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Section: Problems?mentioning

confidence: 99%

Section: The Contestantsmentioning

confidence: 99%

Section: Discrepant Expected Values-anothermentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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The Priority Heuristic: Making Choices Without Trade-offs

Brandstätter¹,

Gigerenzer²,

Hertwig³

2011

Heuristics

100

182

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Decision Making

Markman¹,

Medin²

2002

Stevens' Handbook of Experimental Psychology

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For much of the 20th century, decision making research was strongly influenced by theories in economics. Economic models predict that people strive to make optimal decisions. True optimality is impossible to achieve given limitations in processing ability, and so much research examined the heuristics that people use to make good decisions in most natural situations. We begin by reviewing this work. However, there has been growing interest in the relationship between decision making and other aspects of psychological processing. The core areas of this emerging research are discussed in the second half of this chapter. First, we present research relating goals, motivation, and emotion to decision making. Then, we consider the role of expertise, analogical comparison and problem solving strategies in choice. Finally, we explore the types of choices people make and how those choices are influenced by culture. In this way, we examine the ways that decision making research has gone beyond its roots in economic models of choice.

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Behavioral Portfolio Selection

Shefrin

2010

Encyclopedia of Quantitative Finance

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Portfolios satisfy both financial needs and psychological needs. Behavioral portfolio selection is a framework for understanding how psychology impacts investors' portfolios. Whereas risk and return are the central variables in neoclassical portfolio selection, the behavioral approach emphasizes the roles of emotions such as hope and fear, aspirations, the framing of outcomes as gains or losses relative to reference points, regret aversion, self‐control, and judgmental biases.

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The Role of Aspiration Level in Risky Choice: A Comparison of Cumulative Prospect Theory and SP/A Theory

Cited by 312 publications

References 35 publications

The Priority Heuristic: Making Choices Without Trade-offs

The Priority Heuristic: Making Choices Without Trade-offs

Decision Making

Behavioral Portfolio Selection

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