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How do people make everyday decisions in order to achieve the most successful outcome? Decision making research typically evaluates choices according to their expected utility. However, this research largely focuses on abstract or hypothetical tasks and rarely investigates whether the outcome is successful and satisfying for the decision maker. Instead, we use an everyday decision making task inwhich participants describe a personally meaningful decision they are currently facing. We investigate the decision processes used to make this decision, and evaluate how successful and satisfying the outcome of the decision is for them. We examine how well analytic, attribute-based processes explain everyday decision making and predict decision outcomes, and we compare these processes to associative processes elicited through free association. We also examine the characteristics of decisions and individuals that are associated with good decision outcomes. Across three experiments we found that: 1) an analytic decision analysis of everyday decisions is not superior to simpler attribute-based processes in predicting decision outcomes; 2) contrary to research linking associative cognition to biases, free association generates valid cues that predict choice and decision outcomes as effectively as attribute-based approaches; 3) contrary to research favouring either attribute-based or associative processes, combining both attribute-based and associates best explains everyday decisions and most accurately predicts decision outcomes; and 4) individuals with a tendency to attempt analytic thinking do not make more successful everyday decisions. Instead, frequency, simplicity, and knowledge of the decision predict success. We propose that attribute-based and associative processes, in combination, both explain everyday decision making and predict successful decision outcomes. [ABSTRACT FROM AUTHOR]

The use of gamification to motivate engagement has greatly increased the number of ways in which people compete. Many of these competitions allow individuals to see how they rank as a competition progresses. Our work aims to provide a better understanding of how individuals feel about different rank outcomes in competitions. We do this by applying the principles of expected utility theory to elicit utility curves for over 3,000 people across three studies using hypothetical competition scenarios. We find consistent support for the following generalizations: 1) individuals are risk-seeking when in second place, 2) they are risk-averse when in second-to-last place, and 3) the utility decrease going from first to second place is greater than their decrease going from second-to-last to last place. Our results suggest individuals are both last-place averse and first-place seeking, with an even stronger inclination towards the latter. [ABSTRACT FROM AUTHOR]

Sunk costs have been known to elicit violations of expected utility theory, in particular, the independence or cancellation axiom. Separately, violations of the stochastic dominance principle have been demonstrated in various settings despite the fact that descriptive models of choice favored in economics deem such violations irrational. However, it is currently unknown whether sunk costs also yield stochastic dominance violations. In two studies using a tri-colored roulette wheel choice task with non-equiprobable events yet equal payoffs, we observed that those who had sunk costs selected a stochastically dominated option significantly more than did those who had no costs. Moreover, a second study revealed that people chose a stochastically dominated option significantlymore when the expected value was low compared to high. Amodel comparison of psychological explanations demonstrated that theories that incorporate a reference shift of the status quo could predict these sunk cost-based violations of stochastic dominance whereas other models could not. [ABSTRACT FROM AUTHOR]

Risk attitudes implied by valuations of risk-increasing assets depart markedly from those implied by valuations of riskreducing assets. For instance, many are unwilling to pay the expected value for a risky asset or for its perfect hedge. Although nearly every theory of risk preference (and logic) demands a negative correlation between valuations of bets and hedges, we observe positive correlations. This inconsistency is difficult to expunge. [ABSTRACT FROM AUTHOR]

Birnbaum and Quispe-Torreblanca (2018) evaluated a set of six models developed under true-and-error theory against data in which people made choices in repeated gambles. They concluded the three models based on expected utility theory were inadequate accounts of the behavioral data, and argued in favor of the simplest of the remaining three more general models. To reach these conclusions, they used non-Bayesian statistical methods: frequentist point estimation of parameters, bootstrapped confidence intervals of parameters, and null hypothesis significance testing of models. We address the same research goals, based on the same models and the same data, using Bayesian methods. We implement the models as graphical models in JAGS to allow for computational Bayesian analysis. Our results are based on posterior distribution of parameters, posterior predictive checks of descriptive adequacy, and Bayes factors for model comparison. We compare the Bayesian results with those of Birnbaumand Quispe-Torreblanca (2018). We conclude that, while the very general conclusions of the two approaches agree, the Bayesian approach offers better detailed answers, especially for the key question of the evidence the data provide for and against the competing models. Finally, we discuss the conceptual and practical advantages of using Bayesian methods in judgment and decision making research highlighted by this case study. [ABSTRACT FROM AUTHOR]

True and Error Theory (TET) provides a method to separate the variability of behavior into components due to changing true policy and to random error. TET is a testable theory that can serve as a statistical model, allowing one to evaluate substantive theories as nested, special cases. TET is more accurate descriptively and has theoretical advantages over previous approaches. This paper presents a freely available computer program in R that can be used to fit and evaluate both TET and substantive theories that are special cases of it. The program performs Monte Carlo simulations to generate distributions of test statistics and bootstrapping to provide confidence intervals on parameter estimates. Use of the program is illustrated by a reanalysis of previously published data testing whether what appeared to be violations of Expected Utility (EU) theory (Allais paradoxes) by previous methods might actually be consistent with EU theory. [ABSTRACT FROM AUTHOR]

A new theory of decision-making under risk, the Opportunity-Threat Theory is proposed. Analysis of risk into opportunity and threat components allows description of behavior as a combination of opportunity seeking and threat aversion. Expected utility is a special case of this model. The final evaluation is an integration of the impacts of opportunity and threat with this expectation. The model can account for basic results as well as several "new paradoxes" that refuted cumulative prospect theory in favor of configural weight models. The discussion notes similarities and differences of this model to the configural weight TAX model, which can also account for the new paradoxes. [ABSTRACT FROM AUTHOR]

This paper provides a novel interpretation of focal point responses (0, 50, 100 percent) in terms of ambiguous beliefs dynamics that arise in new developments of decision theory such as Choquet expected utility theory. In particular, focal point responses that have been updated from nonfocal responses can be interpreted as non-additive beliefs that account for psychological bias. A focal point response of 100 that has been updated from a nonfocal response can be represented by a non-additive belief that has been updated according to the Overestimating Update Rule. A focal point response of zero that has been updated from a nonfocal response can be represented by a non-additive belief that has been updated according to the Underestimating Update Rule. Focal point responses given consistently over time are not subject to psychological bias, and can be represented by additive probability distributions. Estimation results show such a model to be a very good fit to the data. [ABSTRACT FROM AUTHOR]

In jurisdictions with two or more tiers of criminal courts, some defendants can choose the type of trial court to be tried in. This may involve a trade-off between the probability of acquittal/conviction and the estimated severity of sentence if convicted. For instance, in England and Wales, the lower courts have a higher conviction rate but limited sentencing powers, whereas the higher courts have a higher acquittal rate but greater sentencing powers. We examined 255 offenders' choice of trial court type using a hypothetical scenario where innocence and guilt was manipulated. Participants' choices were better predicted by a lexicographic than utility maximization model. A greater proportion of "guilty" participants chose the lower court compared to their "innocent" counterparts, and estimated sentence length was more important to the former than latter group. The present findings provide further support for heuristic decisionmaking in the criminal justice domain, and have implications for legal policy-making. [ABSTRACT FROM AUTHOR]

The body of literature on the relationship between risk aversion and wealth is extensive. However, little attention has been given to examining how future realizations of wealth might affect (current) risk decisions. Using paired lottery choice experiments and exposing subjects experimentally to imagined future wealth frames, I find that individuals are more risk-seeking if they are asked to imagine that they will be wealthy in the future. Yet I find that individuals are not significantly more risk-averse if they are asked to imagine that they will be poor in the future. I discuss theoretical and policy implications of these findings, including why savings rates are so low in the United States. [ABSTRACT FROM AUTHOR]