Navigational safety is one of the important focuses of Maritime Education and Training (MET), and the quality of MET is the key to cultivating competent officers at sea. This study aims to understand better the effects of a rapid training method on ship handling and navigation in restricted waters, as well as decision-making skills under stressful situations. Tests were carried out in a simulator-based maritime training environment to explore the decision-making skills of maritime students in stressful situations under different training levels and methods. This study compares routine maritime training and task-aimed rapid training in improving manoeuvring and navigational and decision-making skills, and examines the training outcomes. The data used in this study is based on comparing the task performance and stress levels of the two groups of students using simulator-based training results from a designed scenario. The results analyse the training outcomes of decision-making skills and maritime operation performance by applying a specific decision-making model. In addition, the impact of students' stress levels was examined, both subjectively and objectively. The paper concludes with a set of recommendations for the design of future MET. The research helps enhance decision-making skills in maritime training programmes and understanding how learning in simulator-based maritime training environments can be improved.

Online experiments allow researchers to collect datasets at times not typical of laboratory studies. We recruit 2336 participants from Amazon Mechanical Turk to examine if participant characteristics and behaviors differ depending on whether the experiment is conducted during the day versus night, and on weekdays versus weekends. Participants make incentivized decisions involving prosociality, punishment, and discounting, and complete a demographic and personality survey. We find no time or day differences in behavior, but do find that participants at nights and on weekends are less experienced with online studies; on weekends are less reflective; and at night are less conscientious and more neurotic. These results are largely robust to finer-grained measures of time and day. We also find that those who participated earlier in the course of the study are more experienced, reflective, and agreeable, but less charitable than later participants.

This article presents a joint modeling framework of ordinal responses and response times (RTs) for the measurement of latent traits. We integrate cognitive theories of decision-making and confidence judgments with psychometric theories to model individual-level measurement processes. The model development starts with the sequential sampling framework which assumes that when an item is presented, a respondent accumulates noisy evidence over time to respond to the item. Several cognitive and psychometric theories are reviewed and integrated, leading us to three psychometric process models with different representations of the cognitive processes underlying the measurement. We provide simulation studies that examine parameter recovery and show the relationships between latent variables and data distributions. We further test the proposed models with empirical data measuring three traits related to motivation. The results show that all three models provide reasonably good descriptions of observed response proportions and RT distributions. Also, different traits favor different process models, which implies that psychological measurement processes may have heterogeneous structures across traits. Our process of model building and examination illustrates how cognitive theories can be incorporated into psychometric model development to shed light on the measurement process, which has had little attention in traditional psychometric models.

An observer is to make inference statements about a quantity p, called a propensity and bounded between 0 and 1, based on the observation that p does or does not exceed a constant c. The propensity p may have an interpretation as a proportion, as a long-run relative frequency, or as a personal probability held by some subject. Applications in medicine, engineering, political science, and, most especially, human decision making are indicated. Bayes solutions for the observer are obtained based on prior distributions in the mixture of beta distribution family; these are then specialized to power-function prior distributions. Inference about log p and log odds is considered. Multiple-action problems are considered in which the focus of inference shifts to the process generating the propensities p, both in the case of a process parameter π known to the subject and unknown. Empirical Bayes techniques are developed for observer inference about c when π is known to the subject. A Bayes rule, a minimax rule and a beta-minimax rule are constructed for the subject when he is uncertain about π.

When considering the implications of the shareholder-stakeholder debate in defining the purpose of a company, epistemological clarity is vital in this emerging theory of the firm. Such clarity can prevent recurrence based solely on rephrasing key terms. To understand how various stakeholders develop and interpret a shared purpose, I argue for the necessity of a pragmatist approach that is normative and process-oriented. Mental models play a crucial role in interpretive processes that define decision-making, where individual perspectives converge. The figures of Milton Friedman and Ed Freeman serve as “beacons,” as artefacts, in the transmission of knowledge through which we, as individuals, shape a shared understanding. In current societies, profound polarization obstructs solutions to grand challenges. Pragmatism starts by questioning the underlying values of everyone involved. It assumes that sound deliberative processes are the only way to reach real solutions—not only for the mind but, above all, for the heart.

Many populist leaders politicise disputes with external financial ‘elites’, but most are forced by economic pressures to fundamentally change their ‘people-versus-elite’ problem representations and ‘concede defeat’. Notable exceptions are Hungary’s Viktor Orbán, Argentina’s Cristina Kirchner, and Turkey’s Recep Tayyip Erdoğan, who sooner or later resisted strong push-back and defied the IMF or distressed-debt funds. These instances of prolonged populist defiance differ widely across commonly used structural and agential explanatory factors at international, domestic, and individual levels. To explain how Orbán, Kirchner, and Erdoğan managed to ‘beat the elite’, this paper clusters several root causes into a parsimonious framework of two intervening variables. The temporality of strong ‘elite’ push-back and the openness of advisory systems are theorised as shaping distinct cognitive mechanisms of representational continuity or change, through which ‘people-versus-elite’ input is either preserved until – or discarded before – feeding into decision outputs. As the two-by-two matrix of early/later external shocks and open/closed inner circles explains, Orbán did not move beyond marginal representational adjustments; Kirchner’s contingent representational fluidity benefited from opportune situational developments; and Erdoğan defied significant socio-economic cost with fundamental representational continuity. These insights highlight the potential of studying populism at the intersection of foreign policy analysis and international political economy.

The literature on emotion and risk-taking is large and heterogeneous. Whereas some studies have found that positive emotions increase risk-taking and negative emotions increase risk aversion, others have found just the opposite. In this study, we investigated this question in the context of a risky decision-making task with embedded high-resolution sampling of participants’ subjective emotional valence. Across two large-scale experiments (N = 329 and 524), we consistently found evidence for a negative association between self-reported emotional valence and risk-taking behaviors. That is, more negative subjective affect was associated with increased risk-seeking, and more positive subjective affect was associated with increased risk aversion. This effect was evident both when we compared participants with different levels of mean emotional valence as well as when we considered within-participant emotional fluctuations over the course of the task. Prospect-theoretic computational modeling analyses suggested that both between- and within-participant effects were driven by an effect of emotional valence on the curvature of the subjective utility function (i.e., increased risk tolerance in more negative emotional states), as well as by an effect of within-person emotion fluctuations on loss aversion. We interpret findings in terms of a tendency for participants in negative emotional states to choose high-risk, high-reward options in an attempt to improve their emotional state.

Our study aims to contribute to the existing body of research on age-related changes in decision-making by investigating susceptibility to the attraction effect across adulthood. Prior studies have produced inconsistent conclusions regarding the decision-making abilities of older individuals, with some portraying them as easily manipulated and risk-averse, while others suggest the opposite. To address this issue, we conducted two experiments using a novel paradigm of the roulette task: (1) in an online environment with 357 participants and (2) in a laboratory setting with 173 participants. The results were consistent and demonstrated the robustness of the attraction effect. However, no age differences in susceptibility to the attraction effect as a common decision bias were found. As predicted, older adults were more likely to commit simple decision-making mistakes, especially in the preliminary trials, which could have serious financial or societal consequences. Additionally, older adults exhibited more risk-seeking behaviours. Furthermore, we observed that the dynamics of decision competence (as indicated by a decrease in the selection of erroneous decoy options and an increase in decision fluency) were similar for both younger and older adults, suggesting preservation of the ability to optimise decision-making while becoming familiar with new tasks. These findings provide insight into the cognitive functioning of older adults and indicate that decision-making abilities in late adulthood may be more complex than commonly assumed.

This work presents a reflection on the meaning and significance of knowledge coproduction in the field of glaciology. We start by invoking the paradigm of Structure–Form–Environment Interplay (SFEI) to formulate a generalised definition of glaciology, which highlights the relevance of knowledge coproduction. The adoption of a relational view of glaciological knowledge leads us to identify five core dimensions of knowledge coproduction: purpose, ethics, ambiguity, inclusion/exclusion, and relationships. Based on those dimensions, we delve into the decisive methodological aspects of the coproduction process, namely the definition of its purpose, the identification of participants, the organisation of the process, the recognition of ambiguity in Ways of Knowing (WoKs), and the consideration of ethical implications. In addition to the already known three stages of knowledge coproduction process (codesign, codevelopment, and codelivery), we propose the inclusion of an additional preparation stage, which entails the acknowledgment of the identity and involvement of all human and nonhuman participants, their positionality, and means to ensure their cultural and ontological safety. We reason that knowledge coproduction does not replace the scientific method, but rather complements it, eliciting the possibility to unveil deeper insights that might be difficult to attain through unilateral means.

Critical space assets require continuous monitoring to prevent potential losses. Auxiliary satellites protect these assets by observing and tracking approaching targets. Although observation satellites can make rapid autonomous onboard decisions, they face challenges due to limited computational capacity. The two mainstream command and control methods currently available do not meet the demands of onboard decision-making. Highly procedural decision-making methods require extended decision times, while rapid-response intuitive or heuristic methods carry significant error risks. To address this, this paper proposes a multi-granularity decision-making method for optical space surveillance satellites. First, multi-granularity relative orbit determination algorithm models and multi-granularity impulsive orbit manoeuver algorithm models were developed. Based on these models, a granularity selection method for sequential three-way decisions is proposed. In non-emergency situations, fine-granularity models are preferred to conserve fuel, while in emergency situations, coarse-granularity models are used to enhance decision-making speed and reduce positional deviations caused by the manoeuvering game. In random multi-scenario tests, the proposed method demonstrates lower average terminal positional deviations and fuel consumption compared to single-granularity (highly procedural or rapid-response) and random-granularity methods.