Indecisiveness is an individual difference measure of chronic difficulty and delay in decision making. Indecisiveness is associated with low decisional confidence and distinct patterns of pre-choice information search behavior. The present study explored whether the confidence levels and search behaviors associated with individual indecisiveness also emerge in group decision making contexts. In this study, 97 decisive and indecisive participants were assigned to make a decision individually or in a homogenous three-person group. Indecisiveness score was found to predict participant decisional confidence in the individual condition but not in the group condition, with group participants being overall more confident than individuals. Similar results were obtained for other related measures of participants’ perceptions of the decision task. Surprisingly, no indecisiveness-related differences in information search were found, suggesting that other aspects of the group process contribute to increased confidence. The results provide initial evidence that indecisiveness does not influence group decision making and that, especially for indecisive individuals, working in groups may be a way to boost decisional confidence.

This series of four studies was designed to clarify the underlying dimensionality and psychological well-being correlates of the major extant measures of the maximization tendency: the Maximization Scale (MS; Schwarz et al., 2002) and the Maximization Tendency Scale (MTS; Diab et al., 2008). Four studies using psychometric and factor analysis, item response theory (IRT), and an experimental manipulation all supported the following conclusions. The MS does measure three separate factors as postulated by its authors, but only two of them (alternative search and decisional difficulty) are correlated with each other and (negatively) with indices of well-being as postulated by the scale authors; high standards, the third factor, correlated strongly with the MTS, and both of these were strongly correlated with positive indices of well-being (optimism and happiness) and functioning (e.g., self-esteem and self-efficacy). The high standards subscale and MTS were related to analytical decision making style, while alternative search and decision difficulty were related to the regret-based decision making style and to procrastination. The IRT analysis indicated serious weaknesses in the measurement capabilities of existing scales, and the findings of the experimental study confirmed that alternative search and decision difficulty are related to the maximization tendency while high standards and MTS are not.Implications for further research and scale development are discussed.

The history of judgment and decision making is defined by a trend toward increasingly nuanced explanations of the decision making process. Recently, process models have become incredibly sophisticated, yet the tools available to directly test these models have not kept pace. These increasingly complex process models require increasingly complex process data by which they can be adequately tested. We propose a new class of data collection that will facilitate evaluation of sophisticated process models. Tracking mouse paths during a continuous response provides an implicit measure of the growth of preference that produces a choice—rather than the current practice of recording just the button press that indicates that choice itself. Recent research in cognitive science (Spivey & Dale, 2006) has shown that cognitive processing can be revealed in these dynamic motor responses. Unlike current process methodologies, these response dynamics studies can demonstrate continuous competition between choice options and even online preference reversals. Here, in order to demonstrate the mechanics and utility of the methodology, we present an example response dynamics experiment utilizing a common multi-alternative decision task.

When faced with a choice, people can normally select no option, i.e., defer choice. Previous research has investigated when and why individuals defer choice, but has almost never looked at these questions when groups of people make choices. Separate reasons predict that groups may be equally likely, more likely, or less likely than individuals to defer choice. We re-analyzed some previously published data and conducted a new experiment to address this question. We found that small groups of people tended to defer choice more often than their members would. Assuming that the groups used a plurality rule but gave additional weight to individual preferences to defer choice allowed the groups’ responses to be predicted quite well. We discuss several possible explanations of these findings.

Very small but cumulated decreases in food intake may be sufficient to erase obesity over a period of years. We examine the effect of slight changes in the accessibility of different foods in a pay-by-weight-of-food salad bar in a cafeteria serving adults for the lunch period. Making a food slightly more difficult to reach (by varying its proximity by about 10 inches) or changing the serving utensil (spoon or tongs) modestly but reliably reduces intake, in the range of 8–16%. Given this effect, it is possible that making calorie-dense foods less accessible and low-calorie foods more accessible over an extended period of time would result in significant weight loss.

The recognition heuristic models the adaptive use and dominant role of recognition knowledge in judgment under uncertainty. Of the several predictions that the heuristic makes, empirical tests have predominantly focused on the proposed noncompensatory processing of recognition. Some authors have emphasized that the heuristic needs to be scrutinized based on precise tests of the exclusive use of recognition. Although precise tests have clear merits, I critically evaluate the value of such tests as they are currently employed. First, I argue that using precise measures of the exclusive use of recognition has to go beyond showing that the recognition heuristic—like every model—cannot capture reality completely. Second, I illustrate how precise tests based on response times can lead to unsubstantiated conclusions if the fact that the recognition heuristic does not model the recognition judgment itself is ignored. Finally, I highlight two key but so far neglected aspects of the recognition heuristic: (a) the connection between recognition memory and the recognition heuristic; and (b) the mechanisms underlying the adaptive use of recognition.

Donation requests often convey numerical information about the people in need. In two studies we investigated the effects of numeracy and presentation format on the underlying affective and cognitive mechanisms of donation decisions. In Study 1, participants were presented with information about a victim in need, either in a frequency format or in a percentage format. In Study 2, we manipulated the identifiability and number of target victims. Our results demonstrate that donations of individuals lower in numeracy were more susceptible to changes in numeric presentation format than those higher in numeracy. Importantly, the underlying mechanisms for donations differed by numeracy. Whereas the mental image of the victim influenced donation decisions of less numerate people only, the estimated impact of a donation was positively correlated with donation amounts for both more and less numerate individuals.

We investigated the extent to which the human capacity for recognition helps to forecast political elections: We compared naïve recognition-based election forecasts computed from convenience samples of citizens’ recognition of party names to (i) standard polling forecasts computed from representative samples of citizens’ voting intentions, and to (ii) simple—and typically very accurate—wisdom-of-crowds-forecasts computed from the same convenience samples of citizens’ aggregated hunches about election results. Results from four major German elections show that mere recognition of party names forecast the parties’ electoral success fairly well. Recognition-based forecasts were most competitive with the other models when forecasting the smaller parties’ success and for small sample sizes. However, wisdom-of-crowds-forecasts outperformed recognition-based forecasts in most cases. It seems that wisdom-of-crowds-forecasts are able to draw on the benefits of recognition while at the same time avoiding its downsides, such as lack of discrimination among very famous parties or recognition caused by factors unrelated to electoral success. Yet it seems that a simple extension of the recognition-based forecasts—asking people what proportion of the population would recognize a party instead of whether they themselves recognize it—is also able to eliminate these downsides.

The recognition heuristic assumes that people make inferences based on the output of recognition memory. While much work has been devoted to establishing the recognition heuristic as a viable description of how people make inferences, more work is needed to fully integrate research on the recognition heuristic with research from the broader cognitive psychology literature. In this article, we outline four challenges that should be met for this integration to take place, and close with a call to address these four challenges collectively, rather than piecemeal.

We used a diffusion model to examine the effects of response-bias manipulations on response time (RT) and accuracy data collected in two experiments involving a two-choice decision making task. We asked 18 subjects to respond “low” or “high” to the number of asterisks in a 10×10 grid, based on an experimenter-determined decision cutoff. In the model, evidence is accumulated until either a “low” or “high” decision criterion is reached, and this, in turn, initiates a response. We performed two experiments with four experimental conditions. In conditions 1 and 2, the decision cutoff between low and high judgments was fixed at 50. In condition 1, we manipulated the frequency with which low- and high-stimuli were presented. In condition 2, we used payoff structures that mimicked the frequency manipulation. We found that manipulating stimulus frequency resulted in a larger effect on RT and accuracy than did manipulating payoff structure. In the model, we found that manipulating stimulus frequency produced greater changes in the starting point of the evidence accumulation process than did manipulating payoff structure. In conditions 3 and 4, we set the decision cutoff at 40, 50, or 60 (Experiment 1) and at 45 or 55 (Experiment 2). In condition 3, there was an equal number of low- and high-stimuli, whereas in condition 4 there were unequal proportions of low- and high-stimuli. The model analyses showed that starting-point changes accounted for biases produced by changes in stimulus proportions, whereas evidence biases accounted for changes in the decision cutoff.

The two most influential models in delay discounting research have been the exponential (E) and hyperbolic (H) models. We develop a new methodology to design binary choice questions such that exponential and hyperbolic discount rates can be purposefully manipulated to make their rate parameters orthogonal (Pearson’s R = 0), negatively correlated (R = –1), positively correlated (R = +1), or to hold one rate constant while allowing the other to vary. Then we extend the method to similarly contrast different versions of the hyperboloid model. The arithmetic discounting model (A), which is based on differences between present and future rewards rather than their ratios, may easily be made orthogonal to any other pair of models. Our procedure makes it possible to design choice stimuli that precisely vary the relationship between different discount rates. However, the additional control over the correlation between different discount rate parameters may require the researcher to either restrict the range that those rate parameters can take, or to expand the range of times the participant must wait for future rewards.

“Very small but cumulated decreases in food intake may be sufficient to have significant effects, even erasing obesity over a period of years” (Rozin et al., 2011). In two studies, one a lab study and the other a real-world study, we examine the effect of manipulating the position of different foods on a restaurant menu. Items placed at the beginning or the end of the list of their category options were up to twice as popular as when they were placed in the center of the list. Given this effect, placing healthier menu items at the top or bottom of item lists and less healthy ones in their center (e.g., sugared drinks vs. calorie-free drinks) should result in some increase in favor of healthier food choices.

Individual differences in decision making are a topic of longstanding interest, but often yield inconsistent and contradictory results. After providing an overview of individual difference measures that have commonly been used in judgment and decision-making (JDM) research, we suggest that our understanding of individual difference effects in JDM may be improved by amending our approach to studying them. We propose four recommendations for improving the pursuit of individual differences in JDM research: a more systematic approach; more theory-driven selection of measures; a reduced emphasis on main effects in favor of interactions between individual differences and decision features, situational factors, and other individual differences; and more extensive communication of results (whether significant or null, published or unpublished). As a first step, we offer our database—the Decision Making Individual Differences Inventory (DMIDI; http://html://www.sjdm.org/dmidi), a free, public resource that categorizes and describes the most common individual difference measures used in JDM research.

The article shows that when people consider differentiated goods or services that differ in price and quality, they exhibit a decision-making bias of “relative thinking”: relative price differences affect them even when economic theory suggests that only absolute price differences matter. This result is obtained in four different consumption categories. Sometimes subjects are affected only by relative price differences (“full relative thinking”) and sometimes also by absolute price differences (“partial relative thinking”). This behavior has implications for various disciplines, and it is particularly relevant in models dealing with horizontal or vertical differentiation, optimal pricing, competitive strategy, or advertising.

I describe and discuss the sometimes heated controversy surrounding the recognition heuristic (RH) as a model of inferential decision making. After briefly recapitulating the history of the RH up to its current version, I critically evaluate several specific assumptions and predictions of the RH and its surrounding framework: recognition as a memory-based process; the RH as a cognitive process model; proper conditions of testing the RH; measures of using the RH; reasons for not using the RH; the RH as a non-compensatory strategy; evidence for a Less-is-more effect (LIME); and the RH as part of the toolbox. The collection of these controversial issues may help to better understand the debate, to further sharpen the RH theory, and to develop ideas for future research.

We conducted three studies to investigate how well pictographs communicate medical screening information to persons with higher and lower numeracy skills. In Study 1, we conducted a 2 (probability level: higher vs. lower) × 2 (reference information: yes vs. no) × 2 (subjective numeracy: higher vs. lower) between-subjects design. Persons with higher numeracy skills were influenced by probability level but not by reference information. Persons with lower numeracy tended to differentiate between a higher and a lower probability when there was no reference information. Study 2 consisted of interviews about the mental processing of pictographs. Higher numeracy was associated with counting the icons and relying on numbers depicted in the graph. Study 3 was an experiment with the same design as in Study 1, but, rather than using reference information, we varied the sequence of task type (counting first vs. non-counting first) to explore the role of the focus on numerical information. Persons with lower numeracy differentiated between higher and lower risk only when they were in the non-counting first condition. Task sequence did not influence the risk perceptions of persons with higher numeracy. In sum, our results suggest that pictographs may be useful for persons with higher and lower numeracy. However, these groups seem to process the graph differently. Persons with higher numeracy rely more on the numerical information depicted in the graph, whereas persons with lower numeracy seem to be confused when they are guided towards these numbers.

The tempting fate effect is that the probability of a fateful outcome is deemed higher following an action that “tempts” the outcome than in the absence of such an action. In this paper we evaluate the hypothesis that the effect is due to an illusion of control induced by a causal framing of the situation. Causal frames require that the action make a difference to an outcome and that the action precedes the outcome. If an illusion of control modulates the reluctance to tempt fate, then actions that make a difference to well-being and that occur prior to the outcome should tempt fate most strongly. In Experiments 1–3 we varied whether the action makes a difference and the temporal order of action and outcome. In Experiment 4 we tested whether an action can tempt fate if all outcomes are negative. The results of all four experiments supported our hypothesis that the tempting fate effect depends on a causal construal that gives rise to a false sense of control.

In the current paper we investigate how feedback over decision outcomes may affect future decisions. In an experimental study we demonstrate that if people receive feedback over the outcomes they obtained (“factual outcomes”) and the outcomes they would have obtained had they decided differently (“counterfactual outcomes”), they become regret-averse in subsequent decisions. This effect is not only observed when this feedback evoked regret (with counterfactual outcomes being higher than factual outcomes), but even when the feedback evoked no regret (with factual outcomes being equal to counterfactual outcomes). The findings suggest that this effect on subsequent decisions is at least partly due to the transfer of a comparison mind-set triggered in the prior choice.

The recognition heuristic exploits the basic psychological capacity for recognition in order to make inferences about unknown quantities in the world. In this article, we review and clarify issues that emerged from our initial work (Goldstein & Gigerenzer, 1999, 2002), including the distinction between a recognition and an evaluation process. There is now considerable evidence that (i) the recognition heuristic predicts the inferences of a substantial proportion of individuals consistently, even in the presence of one or more contradicting cues, (ii) people are adaptive decision makers in that accordance increases with larger recognition validity and decreases in situations when the validity is low or wholly indeterminable, and (iii) in the presence of contradicting cues, some individuals appear to select different strategies. Little is known about these individual differences, or how to precisely model the alternative strategies. Although some researchers have attributed judgments inconsistent with the use of the recognition heuristic to compensatory processing, little research on such compensatory models has been reported. We discuss extensions of the recognition model, open questions, unanticipated results, and the surprising predictive power of recognition in forecasting.