We investigate how the selection process of a leader affects team performance with respect to social learning. We use a laboratory experiment in which an incentivized guessing task is repeated in a star network with the leader at the center. Leader selection is either based on competence, on self-confidence, or made at random. In our setting, teams with random leaders do not underperform. They even outperform teams with leaders selected on self-confidence. Hence, self-confidence can be a dangerous proxy for competence of a leader. We show that it is the declaration of the selection procedure which makes non-random leaders overly influential. To investigate the opinion dynamics, we set up a horse race between several rational and naïve models of social learning. The prevalent conservatism in updating, together with the strong influence of the team leader, imply an information loss since the other team members’ knowledge is not sufficiently integrated.

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.