An important open problem is how values are compared to make simple choices. A natural hypothesis is that the brain carries out the computations associated with the value comparisons in a manner consistent with the Drift Diffusion Model (DDM), since this model has been able to account for a large amount of data in other domains. We investigated the ability of four different versions of the DDM to explain the data in a real binary food choice task under conditions of high and low time pressure. We found that a seven-parameter version of the DDM can account for the choice and reaction time data with high-accuracy, in both the high and low time pressure conditions. The changes associated with the introduction of time pressure could be traced to changes in two key model parameters: the barrier height and the noise in the slope of the drift process.

The current study looks at the role working memory plays in risky-choice framing. Eighty-six participants took the Automatic OSPAN, a measurement of working memory; this was followed by a risky-choice framing task. Participants with high working memory capacities demonstrated well pronounced framing effects, while those with low working memory capacities did not. This pattern suggests that, in a typical risky-choice decision task, elaborative encoding of task information by those with high working memory capacity may lead them to a more biased decision compared to those with low working memory.

The sunk cost fallacy is the tendency to continue an endeavour once an investment in money, effort, or time has been made. We studied how people’s chronic orientation to cope with failing projects (i.e., action vs. state orientation) influences the occurrence of this sunk cost effect. We found that people with a state orientation, who have a tendency to ruminate about past events and have a hard time to let go of them, were especially prone to fall in the sunk cost trap. People with an action orientation, who more easily let go of past events, were not susceptible to the sunk cost effect. We discuss the implications of these results for the sunk cost fallacy literature.

Participants drank either regular root beer or sugar-free diet root beer before working on a probability-learning task in which they tried to predict which of two events would occur on each of 200 trials. One event (E1) randomly occurred on 140 trials, the other (E2) on 60. In each of the last two blocks of 50 trials, the regular group matched prediction and event frequencies. In contrast, the diet group predicted E1 more often in each of these blocks. After the task, participants were asked to write down rules they used for responding. Blind ratings of rule complexity were inversely related to E1 predictions in the final 50 trials. Participants also took longer to advance after incorrect predictions and before predicting E2, reflecting time for revising and consulting rules. These results support the hypothesis that an effortful controlled process of normative rule-generation produces matching in probability-learning experiments, and that this process is a function of glucose availability.

Often to the detriment of human decision making, people are prone to an impact bias when making affective forecasts, overestimating the emotional consequences of future events. The cognitive processes underlying the impact bias, and methods for correcting it, have been debated and warrant further exploration. In the present investigation, we examined both individual differences and contextual variables associated with cognitive processing in affective forecasting for an election. Results showed that the perceived importance of the event and working memory capacity were both associated with an increased impact bias for some participants, whereas retrieval interference had no relationship with bias. Additionally, an experimental manipulation effectively reduced biased forecasts, particularly among participants who were most distracted thinking about peripheral life events. These findings have theoretical implications for understanding the impact bias, highlight the importance of individual differences in affective forecasting, and have ramifications for future decision making research. The possible functional role of the impact bias is discussed within the context of evolutionary psychology.

In inductive inference, a strong prediction is the less-is-more effect: Less information can lead to more accuracy. For the task of inferring which one of two objects has a higher value on a numerical criterion, there exist necessary and sufficient conditions under which the effect is predicted, assuming that recognition memory is perfect. Based on a simple model of imperfect recognition memory, I derive a more general characterization of the less-is-more effect, which shows the important role of the probabilities of hits and false alarms for predicting the effect. From this characterization, it follows that the less-is-more effect can be predicted even if heuristics (enabled when little information is available) have relatively low accuracy; this result contradicts current explanations of the effect. A new effect, the below-chance less-is-more effect, is also predicted. Even though the less-is-more effect is predicted to occur frequently, its average magnitude is predicted to be small, as has been found empirically. Finally, I show that current empirical tests of less-is-more-effect predictions have methodological problems and propose a new method. I conclude by examining the assumptions of the imperfect-recognition-memory model used here and of other models in the literature, and by speculating about future research.

This article presents several studies that replicate and extend previous research on maximizing. A modified scale for measuring individual maximizing tendency is introduced. The scale has adequate psychometric properties and reflects maximizers’ aspirations for high standards and their preference for extensive alternative search, but not the decision difficulty aspect included in several previous studies. Based on this scale, maximizing is positively correlated with optimism, need for cognition, desire for consistency, risk aversion, intrinsic motivation, self-efficacy and perceived workload, whereas the association with regret is inconsistent. Analysis of correlates of the difficulty dimension suggests that decision difficulty should be conceptualized as a separate dimension rather than as a sub-dimension of maximizing. Opportunities for future research are suggested.

Several scholars have recognized the limitations of theories of moral reasoning in explaining moral behavior. They have argued that moral behavior may also be influenced by moral identity, or how central morality is to one’s sense of self. This idea has been supported by findings that people who exemplify moral behavior tend to place more importance on moral traits when defining their self-concepts (Colby & Damon, 1995). This paper takes the next step of examining individual variation in a construct highly associated with immoral behavior — psychopathy. In Study 1, we test the hypothesis that individuals with a greater degree of psychopathic traits have a weaker moral identity. Within a large online sample, we found that individuals who scored higher on a measure of psychopathic traits were less likely to base their self-concepts on moral traits. In Study 2, we test whether this reduced sense of moral identity can be attributed to differences in moral judgment, which is another factor that could influence immoral behavior. Our results indicated that the reduced sense of moral identity among more psychopathic individuals was independent of variation in moral judgment. These results suggest that individuals with psychopathic traits may display immoral behavior partially because they do not construe their personal identities in moral terms.

This paper explores the psychology of conflict of interest by investigating how conflicting interests affect both public statements and private judgments. The results suggest that judgments are easily influenced by affiliation with interested partisans, and that this influence extends to judgments made with clear incentives for objectivity. The consistency we observe between public and private judgments indicates that participants believed their biased assessments. Our results suggest that the psychology of conflict of interest is at odds with the way economists and policy makers routinely think about the problem. We conclude by exploring implications of this finding for professional conduct and public policy.

Economist Frank H. Knight (1885–1972) is commonly credited with defining the distinction between decisions under “risk” (known chance) and decisions under “uncertainty” (unmeasurable probability) in his 1921 book Risk, Uncertainty and Profit. A closer reading of Knight (1921) reveals a host of psychological insights beyond this risk-uncertainty distinction, many of which foreshadow revolutionary advances in psychological decision theory from the latter half of the 20th century. Knight’s description of economic decision making shared much with Simon’s (1955, 1956) notion of bounded rationality, whereby choice behavior is regulated by cognitive and environmental constraints. Knight described features of risky choice that were to become key components of prospect theory (Kahneman & Tversky, 1979): the reference dependent valuation of outcomes, and the non-linear weighting of probabilities. Knight also discussed several biases in human decision making, and pointed to two systems of reasoning: one quick, intuitive but error prone, and a slower, more deliberate, rule-based system. A discussion of Knight’s potential contribution to psychological decision theory emphasises the importance of a historical perspective on theory development, and the potential value of sourcing ideas from other disciplines or from earlier periods of time.

Difficulty making decisions is one of the symptoms of the depressive illness. Previous research suggests that depressed individuals may make decisions that differ from those made by the non-depressed, and that they use sub-optimal decision-making strategies. For this study we constructed an instrument that aims to measure a variety of decision-making styles as well as the respondent’s view of him or herself as a decision-maker (decisional self-esteem). These styles and estimates of decisional self-esteem were then related to depressive symptoms. Depressive symptomatology correlated negatively with perception of self as a decision-maker. Those with higher depression severity scores characterized themselves as being more anxious about decisions, and more likely to procrastinate. They also reported using fewer productive decision-making strategies, depending more on other people for help with decisions, and relying less on their own intuitions when making decisions. Further research is needed to determine the extent to which these decision-making styles are antecedents to depressive symptomatology or are instead products of, or aspects of, the phenomenology associated with depression.

Using a stochastic dominance approach in an international dataset of about 10,000 Catholic subjects, we show that incentives (based on absolute belief) play a crucial role in religious practice (church attendance and prayer). Furthermore, we find that when both positive (heaven) and negative (hell) incentives are available, the former have a much stronger effect than the latter. The results are confirmed using Kolmogorov-Smirnov tests.

Inferences consistent with “recognition-based” decision-making may be drawn for various reasons other than recognition alone. We demonstrate that, for 2-alternative forced-choice decision tasks, less-is-more effects (reduced performance with additional learning) are not restricted to recognition-based inference but can also be seen in circumstances where inference is knowledge-based but item knowledge is limited. One reason why such effects may not be observed more widely is the dependence of the effect on specific values for the validity of recognition and knowledge cues. We show that both recognition and knowledge validity may vary as a function of the number of items recognized. The implications of these findings for the special nature of recognition information, and for the investigation of recognition-based inference, are discussed.

Unbiased lotteries seem the least unfair and simplest procedures to allocate scarce indivisible resources to those with equal claims. But, when lotteries are repeated, it is not immediately obvious whether prior winners should be included or excluded. As in design questions surrounding single-shot lotteries, considerations of self-interest and distributive social preferences may interact. We investigate preferences for allowing participation of earlier winners in sequential lotteries. We found a strong preference for exclusion, both in settings where subjects were involved, and those where they were not. Subjects who answered questions about both settings did not differ in their tendency to prefer exclusion. Stated rationales significantly predicted choice but did not predict switching of choices between the two settings.

Genetic screening for BRCA1 and BRCA2 gives women the opportunity for early detection, surveillance, and intervention. One key feature of genetic testing and counseling is the provision of personal lifetime risk. However, little attention has been paid to how women interpret lifetime risk information, despite the fact that they base screening, treatment and family planning decisions on such information. To study this vital issue, we set out to test the ability of women to choose the most appropriate interpretation of National Cancer Institute’s (NCI) message about lifetime risk of developing cancer for a woman with altered BRCA1 and BRCA2 genes. Participants included 277 women who had not undergone genetic testing or had cancer and 207 women who had undergone genetic testing or had cancer. Over 50% of the women who had not undergone genetic testing or had cancer and 40% of those who had undergone genetic testing or had cancer misunderstood NCI’s information. Furthermore, in line with a growing body of research, we found that high numeracy level (objective or subjective) is positively associated with a woman’s ability to correctly interpret NCI’s message.

We investigated the role of individual differences in cognitive reflection in decision making. We measured the performance of 157 participants in the cognitive reflection test (Frederick, 2005) and a number of decision-making tasks. We examined the relation of cognitive reflection with performance in tasks that assess correspondence (as distinct from coherence), such as predicting the ratings of chess players. We found significant correlations between cognitive reflection and all the estimation measures in correspondence tasks. Our results suggest that cognitive reflection is a thinking disposition that includes more characteristics than originally proposed by Frederick (2005). We proposed that cognitive reflection is related to the concept of actively open-minded thinking (Baron, 1985, 2008). We concluded that cognitive reflection is a thinking disposition that interacts with knowledge, domain-specific heuristics and characteristics of the environment and that it may play an essential role in the adaptation of the decision maker to different environments and situations.

One major challenge to behavioral decision research is to identify the cognitive processes underlying judgment and decision making. Glöckner (2009) has argued that, compared to previous methods, process models can be more efficiently tested by simultaneously analyzing choices, decision times, and confidence judgments. The Multiple-Measure Maximum Likelihood (MM-ML) strategy classification method was developed for this purpose and implemented as a ready-to-use routine in STATA, a commercial package for statistical data analysis. In the present article, we describe the implementation of MM-ML in R, a free package for data analysis under the GNU general public license, and we provide a practical guide to application. We also provide MM-ML as an easy-to-use R function. Thus, prior knowledge of R programming is not necessary for those interested in using MM-ML.

Considerable research has pointed towards processing differences as a viable means for understanding the strength and likelihood of a framing effect. In the current study we explored how differences in processing may emerge through diurnal patters in circadian rhythm, which varies across individuals. We predicted that during circadian off-times, participants would exhibit stronger framing effects whereas framing effects would be relatively weaker during on-times. Six-hundred and eighty five individuals took part in the study; the findings supported our hypothesis, revealing a diurnal pattern of risk responding that varies across the 24-hour circadian cycle.

The gambler’s fallacy and the hot hand belief have been classified as two exemplars of human misperceptions of random sequential events. This article examines the times of pattern occurrences where a fair or biased coin is tossed repeatedly. We demonstrate that, due to different pattern composition, two different statistics (mean time and waiting time) can arise from the same independent Bernoulli trials. When the coin is fair, the mean time is equal for all patterns of the same length but the waiting time is the longest for streak patterns. When the coin is biased, both mean time and waiting time change more rapidly with the probability of heads for a streak pattern than for a non-streak pattern. These facts might provide a new insight for understanding why people view streak patterns as rare and remarkable. The statistics of waiting time may not justify the prediction by the gambler’s fallacy, but paying attention to streaks in the hot hand belief appears to be meaningful in detecting the changes in the underlying process.

The recognition heuristic (RH) — which predicts non-compensatory reliance on recognition in comparative judgments — has attracted much research and some disagreement, at times. Most studies have dealt with whether or under which conditions the RH is truly used in paired-comparisons. However, even though the RH is a precise descriptive model, there has been less attention concerning the precision of the methods applied to measure RH-use. In the current work, I provide an overview of different measures of RH-use tailored to the paradigm of natural recognition which has emerged as a preferred way of studying the RH. The measures are compared with respect to different criteria — with particular emphasis on how well they uncover true use of the RH. To this end, both simulations and a re-analysis of empirical data are presented. The results indicate that the adherence rate — which has been pervasively applied to measure RH-use — is a severely biased measure. As an alternative, a recently developed formal measurement model emerges as the recommended candidate for assessment of RH-use.