Over the last decades, modeling and simulation have become central methods in engineering design. Today’s technologies enable previously unachievable levels of sophistication and accuracy. However, if decision-makers are unaware of the confidence they can place in models and simulations (M&S), they either fail to leverage their potential by not involving them in processes or make judgments based on unreliable results. Assessments to evaluate M&S exist, but factors that enable decision-makers to have confidence and improve acceptance of using M&S need to be researched in more detail. Therefore, a literature review analyzing design requirements and an online survey to measure factors associated with confidence were conducted. As a result, the survey identified nine predictors of confidence: (1) capability, (2) history, (3) validity, (4) reliability and (5) accessibility of the model. Further, (6) integrity and (7) competence of the modeler, as well as (8) trusting nature and (9) risk awareness of the stakeholder were identified. Having confidence in M&S results significantly increases the reliance on them and leads to better-informed decision-making. Therefore, based on the findings, a framework and an initial application model were developed. The results were initially evaluated and are described.

Combining experts’ subjective probability estimates is a fundamental task with broad applicability in domains ranging from finance to public health. However, it is still an open question how to combine such estimates optimally. Since the beta distribution is a common choice for modeling uncertainty about probabilities, here we propose a family of normative Bayesian models for aggregating probability estimates based on beta distributions. We systematically derive and compare different variants, including hierarchical and non-hierarchical as well as asymmetric and symmetric beta fusion models. Using these models, we show how the beta calibration function naturally arises in this normative framework and how it is related to the widely used Linear-in-Log-Odds calibration function. For evaluation, we provide the new Knowledge Test Confidence data set consisting of subjective probability estimates of 85 forecasters on 180 queries. On this and another data set, we show that the hierarchical symmetric beta fusion model performs best of all beta fusion models and outperforms related Bayesian fusion models in terms of mean absolute error.

Based on a reading of Joseph O'Neill's 2008 novel Netherland, this article discusses the relationship between cricket and finance capitalism from the perspective of time and temporality. Despite its function as a global commodity, cricket inserts a flow of postcolonial time into the temporal streams of transnational market culture, neoliberalism, and the increasing financialization of the world. Set in the aftermath of 9/11 and before the financial crisis of 2008, Netherland juxtaposes the deviant temporal power of cricket with the time structures of finance capitalism to illustrate how the conduct of Wall Street before the crisis can be understood as a colonial appropriation. In O'Neill's novel, this conflict is embodied in the precarious friendship of a cosmopolitan Dutch financial analyst and a Trinidadian version of Jay Gatsby.

This article presents self-validation theory (SVT) as a framework predicting when mental contents guide performance. First, we illustrate how confidence can validate people’s thoughts (goals, beliefs, identity) increasing and decreasing performance, depending on what thoughts are validated. This first section reviews examples of validation processes in guiding intellectual performance in academic settings, sport performance in athletes, as well as performance on diverse social tasks. SVT specifies moderating conditions for validation processes to operate. Therefore, in the second section of this review, we identify unique and testable moderators for metacognitive processes demonstrating when and for whom validation processes are more likely to occur. A third section calls for future research identifying new validating variables (e.g., preparation, courage) capable of increasing usage of unexplored thoughts relevant to performance (e.g., expectations). This final section examines new domains for validation (e.g., group performance, cheating in performance), discusses to what extent people can use self-validation strategies deliberatively to improve their performance and addresses when performance can be impaired by invalidation (e.g., due to identity threat).

The legitimacy of welfare state institutions is a key question in public policy research. In this study we examine population’s confidence in child protection systems, the role of institutional context and moral alignment. Analysing representative samples of survey data (N=6,043) of citizens in six European countries (Czechia, England, Finland, Norway, Poland and Romania), we find that overall people express confidence in their child protection system. Differences between populations are correlated with institutional context, i.e. the type of child protection system in place – that is, if people live in a country with a risk-oriented system or a family service-oriented system. People’s view on their moral alignment with the system (or not) only shows minor differences in support of interventions. However, a tendency towards polarisation is detected in Finland and Norway with clear differences in support of interventions that restrict parental rights: individuals who state they are in alignment with the system favour stronger interventions than those who say they are not.

Six experiments investigated how the distance between one’s initial opinion and advice relates to advice utilization. Going beyond previous research, we relate advice distance to both relative adjustments and absolute adjustments towards the advice, and we also investigate a second mode of advice utilization, namely confidence shifts due to social validation.Whereas previous research suggests that advice is weighted less the more it differs from one’s initial opinion, we consistently find evidence of a curvilinear pattern. Advice is weighted less when advice distance is low and when it is high. This is in particular because individuals are much more likely to retain their initial opinions in the light of near advice. Also, absolute opinion adjustments towards the advice increases in a monotone fashion as advice distance increases. This finding is in contrast to the predictions of the theoretical framework previous studies on advice distance are based on, social judgment theory. Instead, they data are more in line with a simple stimulus-response model suggesting that absolute adjustments towards the advice increase with advice distance but—potentially—with diminished sensitivity. Finally, our data show that advice can be utilized even when it receives zero weight during belief revision. The closer advice was to the initial opinions, the more it served as a means for social validation, increasing decision-makers’ confidence in the accuracy of their final opinions. Thus, our findings suggest that advice utilization is a more complex function of advice distance than previously assumed.

Glöckner and Bröder (2011) have shown that for 77.5% of their participants’ decision making behavior in decisions involving recognition information and explicitly provided additional cues could be better described by weighted-compensatory Parallel Constraint Satisfaction (PCS) Models than by non-compensatory strategies such as recognition heuristic (RH) or Take the Best (TTB). We investigate whether this predominance of PCS models also holds in memory-based decisions in which information retrieval is effortful and cognitively demanding. Decision strategies were analyzed using a maximum-likelihood strategy classification method, taking into account choices, response times and confidence ratings simultaneously. In contrast to the memory-based-RH hypothesis, results show that also in memory-based decisions for 62% of the participants behavior is best explained by a compensatory PCS model. There is, however, a slight increase in participants classified as users of the non-compensatory strategies RH and TTB (32%) compared to the previous study, mirroring other studies suggesting effects of costly retrieval.

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.

We investigated the relations between numeracy and superior judgment and decision making in two large community outreach studies in Holland (n=5408). In these very highly educated samples (e.g., 30–50% held graduate degrees), the Berlin Numeracy Test was a robust predictor of financial, medical, and metacognitive task performance (i.e., lotteries, intertemporal choice, denominator neglect, and confidence judgments), independent of education, gender, age, and another numeracy assessment. Metacognitive processes partially mediated the link between numeracy and superior performance. More numerate participants performed better because they deliberated more during decision making and more accurately evaluated their judgments (e.g., less overconfidence). Results suggest that well-designed numeracy tests tend to be robust predictors of superior judgment and decision making because they simultaneously assess (1) mathematical competency and (2) metacognitive and self-regulated learning skills.

Research on the processing of recognition information has focused on testing the recognition heuristic (RH). On the aggregate, the noncompensatory use of recognition information postulated by the RH was rejected in several studies, while RH could still account for a considerable proportion of choices. These results can be explained if either a) a part of the subjects used RH or b) nobody used it but its choice predictions were accidentally in line with predictions of the strategy used. In the current study, which exemplifies a new approach to model testing, we determined individuals’ decision strategies based on a maximum-likelihood classification method, taking into account choices, response times and confidence ratings simultaneously. Unlike most previous studies of the RH, our study tested the RH under conditions in which we provided information about cue values of unrecognized objects (which we argue is fairly common and thus of some interest). For 77.5% of the subjects, overall behavior was best explained by a compensatory parallel constraint satisfaction (PCS) strategy. The proportion of subjects using an enhanced RH heuristic (RHe) was negligible (up to 7.5%); 15% of the subjects seemed to use a take the best strategy (TTB). A more-fine grained analysis of the supplemental behavioral parameters conditional on strategy use supports PCS but calls into question process assumptions for apparent users of RH, RHe, and TTB within our experimental context. Our results are consistent with previous literature highlighting the importance of individual strategy classification as compared to aggregated analyses.

People often use tools for tasks, and sometimes there is uncertainty about whether a given task can be completed with a given tool. This project explored whether, when, and how people’s optimism about successfully completing a task with a given tool is affected by the contextual salience of a better or worse tool. In six studies, participants were faced with novel tasks. For each task, they were assigned a tool but also exposed to a comparison tool that was better or worse in utility (or sometimes similar in utility). In some studies, the tool comparisons were essentially social comparisons, because the tool was assigned to another person. In other studies, the tool comparisons were merely counterfactual rather than social. The studies revealed contrast effects on optimism, and the effect worked in both directions. That is, worse comparison tools boosted optimism and better tools depressed optimism. The contrast effects were observed regardless of the general type of comparison (e.g., social, counterfactual). The comparisons also influenced discrete decisions about which task to attempt (for a prize), which is an important finding for ruling out superficial scaling explanations for the contrast effects. It appears that people fail to exclude irrelevant tool-comparison information from consideration when assessing their likelihood of success on a task, resulting in biased optimism and decisions.