This paper examines how credit constraints shape the transmission of uncertainty shocks in business cycles. Standard models struggle to capture the simultaneous declines in output, consumption, investment, and labor hours during uncertainty spikes. We introduce collateral-based credit constraints for impatient households and entrepreneurs, linking their borrowing capacity to asset values. As uncertainty rises, higher risk premia reduce the demand for collateral assets, prompting impatient households to cut labor supply, leading to an output decline. Our model generates macroeconomic co-movements without relying on nominal rigidities. Lowering the loan-to-value (LTV) ratio, particularly for households, helps mitigate these adverse effects.

This study revisits the relationship between household consumption and its economic (income, wealth, and interest rates) and behavioural drivers. We specify this relationship while allowing for a threshold effect and a switching regime, which help capture further asymmetry, time-variation, and nonlinearity in this relationship. To this end, we specify a vector logistic smooth transition regression (VLSTR) model, which allows modelling the consumption–income relationship in a nonlinear system and provides more concise estimators. We obtain two interesting results. First, the consumption–income relationship is time-varying, regime-dependent, and it exhibits asymmetry and nonlinearity. Second, while household consumption remains driven by usual factors (income, financial wealth, interest rate, and exchange rate), it is also statistically sensitive to factors (consumer sentiment), and this sensitivity is regime-dependent.

This study explores the experiences of Russian relocants in Turkey, focusing on their migration trajectories through overlapping waves of shock, relocation, and partial mobilization, following the Russian invasion of Ukraine in 2022. Initially, Turkey was an attractive destination due to its visa-free access, air connectivity, affordable cost of living, and established post-Soviet community. However, among the nearly one million people who fled Russia, many relocants – primarily young, educated, and entrepreneurial individuals from the information technology sector and oppositional groups – face various uncertainties in Turkey. Drawing on findings from a qualitative study, this research first examines the migration journeys of Russian relocants through their self-narratives, tracing the waves of the exodus in 2022. It then critically analyzes the legal, economic, and social uncertainties they encounter in Turkey. Finally, it explores how the physical and virtual “bubbles” formed in İstanbul function as coping mechanisms to navigate these challenges. Blending staying and returning, bubbles function as temporary “in-between” spaces, allowing Russian relocants to encounter Turkey’s novelties, while maintaining a “transnational double presence” through ongoing ties to their homeland, resulting in a form of “functional adaptation.”

Human-centric uncertainty remains one of the most persistent yet least quantified sources of risk in aviation maintenance. Although established safety frameworks such as SMS (safety management system), STAMP (Systems-Theoretic Accident Model and Processes), and FRAM (Functional Resonance Analysis Method) have advanced systemic oversight, they fall short in capturing the dynamic, context-dependent variability of human performance in real time. This study introduces the uncertainty quantification in aircraft maintenance (UQAM) framework – a novel, predictive safety tool designed to measure and manage operational uncertainty at the task level. The integrated uncertainty equation (IUE) is central to the model, a mathematical formulation that synthesises eight empirically derived uncertainty factors into a single, actionable score. Using a mixed-methods design, the research draws on thematic analysis of 49 semi-structured interviews with licensed maintenance engineers, followed by a 12-month field validation across four distinct maintenance tasks. Results demonstrate that the IUE effectively distinguishes between low, moderate and high-risk scenarios while remaining sensitive to procedural anomalies, diagnostic ambiguity and environmental complexity. Heatmap visualisations further enable supervisory teams to identify dominant uncertainty drivers and implement targeted interventions. UQAM enhances predictive governance, supports real-time decision-making and advances the evolution of next-generation safety systems in high-reliability aviation environments by embedding quantitative uncertainty metrics into existing safety architectures.

Increasing senior leadership diversity and decentralizing decision-making have become imperatives for many organizations, supported by a growing normative literature. However, mixed empirical evidence suggests that these may hinder the decision-making processes required to deliver value to firms and their stakeholders. We argue that diversity and decentralization should instead be viewed as means of organizing towards these ends, and theorize the conditions under which they may harm performance – specifically, the nature of the knowledge problems faced by leaders. Analyzing a 19-year panel of 922 U.S. firms, we find that diversity and decentralization are associated with stronger financial and market performance in uncertain environments but become liabilities under ambiguity, where speed and strategic clarity are critical and homogeneous, centralized leadership is more effective. Stakeholder outcomes are similarly affected, particularly employee wellbeing and ethical political activity. These findings challenge normative claims, with implications for theory, proscriptions, and practice.

This paper explores the employment implications of integrating service robots in waste management. Using the scenario technique method, 14 critical influencing factors were identified and analyzed to develop a Best-Case, Worst-Case, and Trend scenario. A SWOT analysis was used to identify implications and develop measures. The findings indicate that service robots can enhance working conditions and enable service expansion but pose risks like job displacement without proper education and reskilling. The study underscores the need for regulatory frameworks, workforce adaptation, and education to ensure socially sustainable robotic integration.

Current quantitative methods for estimating product-related environmental emissions face limitations in supporting sustainable design, particularly in second-life product strategies. This paper highlights challenges in accurately assessing emissions and environmental impacts under existing regulations, which often fail to reward designs enabling circularity. Through examples of current practices, it underscores methodological ambiguities and regulatory gaps, proposing a research agenda for improved tools and frameworks. These advancements aim to better support the design, production, and certification of sustainable, second-life-ready solutions, fostering more effective environmental impact reduction. Additionally, the paper emphasizes the need for regulatory adaptation to incentivize circular design practices, ensuring a fair evaluation of products conceived for second-life applications

Uncertainty in coping with sustainability demands poses a challenge to decision makers concerned with manufacturing companies’ product engineering. Therefore, our paper reports on a newly developed guide to address their uncertainty and support them in initiating targeted sustainability action. The guide, based on an interview study (n = 25; 4 company cases and 1 consultancy) and a systematic literature review, addresses decision makers in product engineering and beyond. It was initially applied and evaluated in company workshops. The guide provides success criteria and reflection questions for each step toward targeted sustainability action: understanding, operationalizing, and implementing. This paper outlines the main concepts behind the guide and contributes to the literature by suggesting a novel approach to sustainability action in product engineering by addressing uncertainty.

Policy making in areas of scientific uncertainty may be shaped by the public’s stated preferences (SP). SP surveys provide respondents with information about the scenario, typically from expert sources. Here, we tested whether respondents’ pre-existing confidence in the ability of experts in general to provide reliable information was associated with (a) status quo bias, (b) response certainty and (c) willingness to pay (WTP) estimates. Using 670 responses to a 2020 choice experiment on microplastic restrictions in the UK, we show that being ex ante more confident was significantly related to less frequent status quo choices and higher response certainty. However, we only observed differences in mean WTP for our ‘microplastics released’ attribute. Our findings suggest that confidence in expert-provided information shapes how respondents engage with SP surveys, particularly in contexts of scientific uncertainty. Future work to further understand determinants and consequences of perceived expert trustworthiness would be insightful.

People’s decisions may change when made in a foreign language (FL). Research testing this foreign language effect (FLE) has mostly used scenarios where uncertainty is expunged or reduced to a form of risk, whereas real-life decisions are usually characterized by uncertainty around outcome likelihood. In the current work, we aimed to investigate whether the FLE on decision-making extends to uncertain scenarios. Moreover, as it is still unclear what linguistic and psychological factors contribute to the FLE, we tested the effects of participants’ FL background, cognitive style and risk-taking attitude on decision processes under certain and uncertain conditions. Overall, we report null effects of language context (native versus foreign language) and problem condition (certain versus uncertain prospects) on participants’ choices. In addition, we found that both FL background and decision makers’ traits modulated participants’ choices in a FL, without emerging into the ‘classic’ FLE on decision-making. However, the direction of such effects was complex, and not always compatible with previous FLE theories. In light of these results, our study highlights the need to reconceptualize the FLE and its implications on decision-making.