In optimal stopping problems, decision makers are assumed to search randomly to learn the utility of alternatives; in contrast, in one-shot multi-attribute utility optimization, decision makers are assumed to have perfect knowledge of utilities. We point out that these two contexts represent the boundaries of a continuum, of which the middle remains uncharted: How should people search intelligently when they possess imperfect information about the alternatives? We assume that decision makers first estimate the utility of each available alternative and then search the alternatives in order of their estimated utility until expected benefits are outweighed by search costs. We considered three well-known models for estimating utility: (i) a linear multi-attribute model, (ii) equal weighting of attributes, and (iii) a single-attribute heuristic. We used 12 real-world decision problems, ranging from consumer choice to industrial experimentation, to measure the performance of the three models. The full model (i) performed best on average but its simplifications (ii and iii) also had regions of superior performance. We explain the results by analyzing the impact of the models’ utility order and estimation error.

When people predict their future behavior, they tend to place too much weight on their current intentions, which produces an optimistic bias for behaviors associated with currently strong intentions. More realistic self-predictions require greater sensitivity to situational barriers, such as obstacles or competing demands, that may interfere with the translation of current intentions into future behavior. We consider three reasons why people may not adjust sufficiently for such barriers. First, self-predictions may focus exclusively on current intentions, ignoring potential barriers altogether. We test this possibility, in three studies, with manipulations that draw greater attention to barriers. Second, barriers may be discounted in the self-prediction process. We test this possibility by comparing prospective and retrospective ratings of the impact of barriers on the target behavior. Neither possibility was supported in these tests, or in a further test examining whether an optimally weighted statistical model could improve on the accuracy of self-predictions by placing greater weight on anticipated situational barriers. Instead, the evidence supports a third possibility: Even when they acknowledge that situational factors can affect the likelihood of carrying out an intended behavior, people do not adequately moderate the weight placed on their current intentions when predicting their future behavior.

We report two studies on the perceived responsibility of opponents competing for a goal that can be attained by only one of them. Responsibility judgments were collected in seven samples of lay people and experts before, during, and after the World Chess Championship in 2013. Participants assessed the responsibility of the two players, their supporting teams, local conditions, and chance factors for four hypothetical outcomes (large and small loss/win for each player), along with probabilities for these outcomes, demonstrating subadditivity (sums exceeding 100%) in all samples, even among chess experts. The winner was consistently perceived to be more responsible than the loser, and more for outcomes with large than small margins. There was also an effect of focal player, as Carlsen was given more responsibility both for losses and wins than Anand, by the present (Norwegian) pro-Carlsen samples. However, this effect could be modified by describing the outcomes as Anand’s (rather than Carlsen’s) wins and losses. Thus the study adds to the valence framing literature by showing how responsibility judgments are affected by the way outcomes are framed.

One prominent model in the realm of memory-based judgments and decisions is the recognition heuristic. Under certain preconditions, it presumes that choices are based on recognition in a one-cue non-compensatory manner and that other information is ignored. This claim has been studied widely—and received, at best, mixed support—in probabilistic inferences. By contrast, only a small number of recent investigations have taken the RH to the realm of preferential decisions (i.e. consumer choice). So far, the conclusion has been that the RH cannot satisfactorily account for aggregate data patterns, but no fully specified alternative model has been demonstrated to provide a better account. Herein, the data from a recent consumer-choice study (Thoma & Williams, 2013) are re-analyzed with the outcome-based maximum-likelihood strategy classification method, thus testing several competing models on individual data. Results revealed that an alternative compensatory model (an equal weights strategy) accounted best for a larger number of datasets than the RH. Thereby, the findings further specify prior results and answer the call for comparative model testing on individual data that has been voiced repeatedly.

Four laboratory studies were conducted to test the hypothesis that correct Bayesian reasoning can be predicted by two factors of task complexity — the number of mental steps required to reach the normative solution, and the compatibility between the framing of data presented and the framing of the question posed. The findings show that participants performed better on frequency format questions only when one mental step was required to solve the task and when the data were in a compatible frequency format. By contrast, participants performed more poorly on more complicated tasks which required more mental steps (in a compatible frequency or probability format) or when the data and question formats were incompatible (Studies 1 and 2). Incompatibility between data and question formats was also associated with higher reaction times (Study 2b). Furthermore, on problems that incorporated incompatibility between the data sample size and the target (question) sample size, participants performed better on the probability question than the frequency question, regardless of data format (Study 3). The latter findings highlight the ecological advantage of translating data into probability terms, which are normalized in a range between 0 and 1, and thus can be transferred from one situation to another.

Three studies tested whether people use cues about the way other people think—for example, whether others respond fast vs. slow—to infer what responses other people might give to reasoning problems. People who solve reasoning problems using deliberative thinking have better insight than intuitive problem-solvers into the responses that other people might give to the same problems. Presumably because deliberative responders think of intuitive responses before they think of deliberative responses, they are aware that others might respond intuitively, particularly in circumstances that hinder deliberative thinking (e.g., fast responding). Intuitive responders, on the other hand, are less aware of alternative responses to theirs, so they infer that other people respond as they do, regardless of the way others respond.

Are people honest about the extent to which they engage in unethical behaviors? We report an experiment examining the relation between self-reported risky unethical tendencies and actual dishonest behavior. Participants’ self-reported risk taking tendencies were assessed using the Domain-Specific Risk-Taking (DOSPERT) questionnaire, while actual self-serving dishonesty was assessed using a private coin tossing task. In this task, participants predicted the outcome of coin tosses, held the predictions in mind, and reported whether their predictions were correct. Thus, the task allowed participants to lie about whether their predictions were correct. We manipulated whether reporting higher correct scores increased (vs. not) participants monetary payoff. Results revealed a positive relation between self-reported unethical risky tendencies and actual dishonesty. The effect was limited to the condition in which dishonesty was self-serving. Our results suggest liars are aware of their dishonest tendencies and are potentially not ashamed of them.

The influence of numeracy on information processing of two risk communication formats (percentage and pictograph) was examined using an eye tracker. A sample from the general population (N = 159) was used. In intuitive and deliberative decision conditions, the participants were presented with a hypothetical scenario presenting a test result. The participants indicated their feelings and their perceived risk, evoked by a 17% risk level. In the intuitive decision condition, a significant correlation (r = .30) between numeracy and the order of information processing was found: the higher the numeracy, the earlier the processing of the percentage, and the lower the numeracy, the earlier the processing of the pictograph. This intuitive, initial focus on a format prevailed over the first half of the intuitive decision-making process. In the deliberative decision condition, the correlation between numeracy and order of information processing was not significant. In both decision conditions, high and low numerates processed pictograph and percentage formats with similar depths and derived similar meanings from them in terms of feelings and perceived risk. In both conditions numeracy had no effects on the degree of attention on the percentage or the pictograph (number of fixations on formats and transitions between them). The results suggest that pictographs attract low numerates’ attention, and percentages attract high numerates’ attention in the first, intuitive, phase of numeric information processing. Pictographs thus ensure low numerates’ further elaboration on numeric risk information, which is an important precondition of risk understanding and decision making.

Decision makers have been found to bias their interpretation of incoming information to support an emerging judgment (predecisional information distortion). This is a robust finding in human judgment, and was recently also established and measured in physicians’ diagnostic judgments (Kostopoulou et al. 2012). The two studies reported here extend this work by addressing the constituent modes of distortion in physicians. Specifically, we studied whether and to what extent physicians distort information to strengthen their leading diagnosis and/or to weaken a competing diagnosis. We used the “stepwise evolution of preference” method with three clinical scenarios, and measured distortion on separate rating scales, one for each of the two competing diagnoses per scenario.

In Study 1, distortion in an experimental group was measured against the responses of a separate control group. In Study 2, distortion in a new experimental group was measured against participants’ own, personal responses provided under control conditions, with the two response conditions separated by a month. The two studies produced consistent results. On average, we found considerable distortion of information to weaken the trailing diagnosis but little distortion to strengthen the leading diagnosis. We also found individual differences in the tendency to engage in either mode of distortion. Given that two recent studies found both modes of distortion in lay preference (Blanchard, Carlson & Meloy, 2014; DeKay, Miller, Schley & Erford, 2014), we suggest that predecisional information distortion is affected by participant and task characteristics. Our findings contribute to the growing research on the different modes of predecisional distortion and their stability to methodological variation.

We asked whether behavioral biases are related to cognitive abilities of Malaysian youth. Frederick’s three-item Cognitive Reflection Test was used to understand the role of behavioral biases concerning behavioral economics and finance. The sample (n = 880) comprised of university students from different parts of Malaysia. We found significant CRT differences as a function of gender, race and age groups. In addition, lower scores on the CRT are correlated positively with time preference and conservatism, but not with risk preference or the conjunction fallacy.

Decisions that consumers make often rest on evaluations of attributes, such as how large, expensive, good, or fattening an option seems. Extant research has demonstrated that these evaluations in turn depend upon the recently experienced distribution of attribute values (e.g., positively or negatively skewed). In many situations decisions rely on recalling the attribute values of each option, a process that has been neglected in much of the previous literature. In two experiments, participants learned attribute information for labeled stimuli presented within either a positively or negatively skewed distribution and then they recalled values from labels after approximately one minute. The results demonstrated effects that are inconsistent with predictions of the category-adjustment model (Duffy, Huttenlocher, Hedges & Crawford, 2010) that recalled values would shift toward the mean of the distribution of values presented. Instead, results were consistent with predictions of the comparison-induced distortion model (Choplin & Hummel, 2002) that remembered values would depend on the density of stimuli within the attribute range. Reasons for these results, alternative models, and implications for decision-making are discussed.

A positive test result for BRCA1/2 gene mutation is a substantial risk factor for breast and ovarian cancer. However, testing is not always covered by insurance, even for high risk women. Variables affecting willingness to pay (WTP) have implications for clinic-based and direct-to-consumer testing. The relative impact of objective and subjective numeracy on WTP, in the context of worry, perceived risk (of having the mutation and developing breast cancer) and family history, was examined in 299 high-risk women, not previously tested for BRCA1/2. Objective and subjective numeracy correlated positively with one another, yet only subjective numeracy correlated (positively) with WTP. This could not be explained by educational level or worry. In line with the numeracy result, other objective factors including family history, age, and Ashkenazi descent were not correlated with WTP. Perceived risk of having a mutation was also correlated with WTP, though perceived risk of developing breast cancer was not, perhaps because it lacks direct connection with testing. Thus, subjective confidence in the ability to interpret test results and perceived risk of a positive test result are more important drivers in paying for BRCA1/2 testing than factors more objective and/or further removed from the testing itself (e.g., perceived risk of developing cancer, family history). Findings underscore the need for genetic counselling that makes probabilistic information accessible and intelligible, so as to build confidence and promote accurate perception of mutation risk and ultimately better decision-making.

Trolley problems have been used in the development of moral theory and the psychological study of moral judgments and behavior. Most of this research has focused on people from the West, with implicit assumptions that moral intuitions should generalize and that moral psychology is universal. However, cultural differences may be associated with differences in moral judgments and behavior. We operationalized a trolley problem in the laboratory, with economic incentives and real-life consequences, and compared British and Chinese samples on moral behavior and judgment. We found that Chinese participants were less willing to sacrifice one person to save five others, and less likely to consider such an action to be right. In a second study using three scenarios, including the standard scenario where lives are threatened by an on-coming train, fewer Chinese than British participants were willing to take action and sacrifice one to save five, and this cultural difference was more pronounced when the consequences were less severe than death.

Previous research has found that people consult closeness or proximity cues when they evaluate the plausibility or likelihood of a counterfactual alternative to reality. In this paper we asked whether the plausibility of counterfactuals extends to dynamic proximity cues that signal a sense of propensity or acceleration in the lead-up to an outcome. Subjects gambled on obtaining either three heads or three tails from three coin-flips. When they lost the gamble they thought it was more likely that they could have won if they had lost on the third coin-flip that was revealed rather than the first or second coin-flip. We discuss how the sense of propensity was raised prior to the revelation of the final decisive losing coin-flip which created a perception of psychological momentum towards winning. Moreover, the consequence of this propensity effect was to positively bias perceptions of the likelihood of the counterfactual winning outcome.

Past research has shown that people consistently believe that others are more easily manipulated by external influences than they themselves are—a phenomenon called the “third-person effect” (Davison, 1983). The present research investigates whether support for public policies aimed at changing behavior using incentives and other decision “nudges” is affected by this bias. Across two studies, we phrased justification for public policy initiatives using either the second- or third-person plural. In Study 1, we found that support for policies is higher when their justification points to people in general rather than the general “you”, and in Study 2 we found that this former phrasing also improves support compared to a no-justification control condition. Policy support is mediated by beliefs about the likelihood of success of the policies (as opposed to beliefs about the policies’ unintended consequences), and, in the second-person condition, is inversely related to a sense of personal agency. These effects suggest that the third-person effect holds true for nudge-type and incentive-based public policies, with implications for their popular support.

We report a series of experiments investigating the influence of feeling lucky or unlucky on people’s choice of known-risk or ambiguous options using the traditional Ellsberg Urns decision-making task. We induced a state of feeling lucky or unlucky in subjects by using a rigged wheel-of-fortune game, which just missed either the bankrupt or the jackpot outcome. In the first experiment a large reversal of the usual ambiguity aversion effect was shown, indicating that feeling lucky made subjects significantly more ambiguity seeking than usual. However, this effect failed to replicate in five refined and larger follow-up experiments. Thus we conclude that there is no evidence that feeling lucky reliably influences ambiguity aversion. Men were less ambiguity averse than women when there were potential gains to be had, but there were no gender differences when the task was negatively framed in terms of losses.

Previous research has demonstrated that consumers’ decisions regarding supplementary pensions could be affected by biases. Bernatzi and Thaler’s experiment demonstrated that menu design can influence pension fund enrollment decisions, in that participants appear to adopt a naïve heuristic, i.e., “extremeness aversion”. Using a database of 27 occupational pension funds from 2007 to 2011, representing 1,732,530 employees, this study asked whether menu design affected Italian workers’ choices regarding the supplementary pension system as a result of the new rules enacted by the regulator in 2007. Most enrolled workers opted for the median investment line. I discuss the possible relevance of this result to public policy, in particular the possibility of including these preferences in the regulations, with the aim of benefiting employees.

This paper explored how frames influence people’s evaluation of others’ probabilistic predictions in light of the outcomes of binary events. Most probabilistic predictions (e.g., “there is a 75% chance that Denver will win the Super Bowl”) can be partitioned into two components: A qualitative component that describes the predicted outcome (“Denver will win the Super Bowl”), and a quantitative component that represents the chance of the outcome occurring (“75% chance”). Various logically equivalent variations of a single prediction can be created through different combinations of these components and their logical or numerical complements (e.g., “25% chance that Denver will lose the Super Bowl”, “75% chance that Seattle will lose the Super Bowl”). Based on the outcome of the predicted event, these logically equivalent predictions can be categorized into two classes: Congruently framed predictions, in which the qualitative component matches the outcome, and incongruently framed predictions, in which it does not. Although the two classes of predictions are logically equivalent, we hypothesize that people would judge congruently framed predictions to be more accurate. The paper tested this hypothesis in seven experiments and found supporting evidence across a number of domains and experimental manipulations, and even when the congruently framed prediction was logically inferior. It also found that this effect held even for subjects who saw both congruently framed and incongruently framed versions of a prediction and judged the two to be logically equivalent.

We demonstrate the usefulness of cognitive models for combining human estimates of probabilities in two experiments. The first experiment involves people’s estimates of probabilities for general knowledge questions such as “What percentage of the world’s population speaks English as a first language?” The second experiment involves people’s estimates of probabilities in football (soccer) games, such as “What is the probability a team leading 1–0 at half time will win the game?”, with ground truths based on analysis of large corpus of games played in the past decade. In both experiments, we collect people’s probability estimates, and develop a cognitive model of the estimation process, including assumptions about the calibration of probabilities and individual differences. We show that the cognitive model approach outperforms standard statistical aggregation methods like the mean and the median for both experiments and, unlike most previous related work, is able to make good predictions in a fully unsupervised setting. We also show that the parameters inferred as part of the cognitive modeling, involving calibration and expertise, provide useful measures of the cognitive characteristics of individuals. We argue that the cognitive approach has the advantage of aggregating over latent human knowledge rather than observed estimates, and emphasize that it can be applied in predictive settings where answers are not yet available.

Pie charts are often used to communicate risk, such as the risk of driving. In the foreground-background salience effect (FBSE), foreground (probability of bad event) has greater salience than background (no bad event) in such a chart. Experiment 1 confirmed that the displays format of pie charts showed a typical FBSE. Experiment 2 showed that the FBSE resulted from a difference in cognitive efforts in processing the messages and that a foreground-emphasizing display was easier to process. Experiment 3 manipulated subjects’ information processing mindset and explored the interaction between displays format and information processing mindset. In the default mindset, careless subjects displayed a typical FBSE, while those who were instructed to be careful reported similar risk-avoidant behavior preference reading both charts. Suggestions for improving risk communication are discussed.