Dimensions Of Uncertainty Research Articles

Exploring the interaction of design variability and stochastic operational uncertainties in software-intensive systems through the lens of modeling

AbstractIn software-intensive systems, navigating the complexities that emerge from the interaction of design variability and stochastic operational uncertainties presents a daunting challenge. This paper delves into the dynamics between these two dimensions of uncertainty, offering novel insights about how modeling can contribute to the analysis of their combined impact upon system properties. By elevating the abstraction level at which probabilistic models are conceptualized, our approach enables an integrated analysis framework that considers both structural and quantitative dimensions of design spaces. Through the introduction of novel language constructs, our methodology facilitates the direct referencing of structural relationships within probabilistic behavioral specifications. Furthermore, the adoption of novel quantifiers in probabilistic temporal logic enables evaluating complex properties across diverse design variants, thereby streamlining the assessment of guarantees within the solution space. We demonstrate the feasibility of this approach on four case studies, showcasing its potential to offer comprehensive insights into the trade-offs and decision-making processes inherent in managing different types of structural design variability and operational uncertainties in software-intensive systems.

Intolerance of uncertainty dimensions and alcohol problems: The effects of coping motives and heavy drinking

AbstractThis study explored the roles of coping motives and frequency of heavy drinking episodes on the association between intolerance of uncertainty (IU) dimensions (i.e., prospective IU and inhibitory IU) and alcohol problems in a crowdsourced sample of adults (N = 375) of current drinkers. Serial mediation results indicated that there was a significant positive indirect effect of inhibitory IU on alcohol problems via coping motives and heavy drinking episodes. Unexpectedly, prospective IU had significant negative effects on frequency of heavy drinking episodes and alcohol problems. Implications of the study findings are discussed.

The dimensions of uncertainty and ambiguity in adolescents and young adults' romantic relationships: A systematic review

Contemporary romantic relationships in adolescence and young adulthood no longer follow a linear trajectory but come to be increasingly characterized by high heterogeneity. Social networks have also constituted a new context for interaction, which has given rise to the tendency to enact behaviors characterized by uncertainty and ambiguity. This study aims at providing a framework of the existing literature contributions on the dimensions of relational uncertainty and relational ambiguity in adolescents and young adults' romantic relationships. A state-of-art systematic review was performed on PsycInfo, Google Scholar, Scopus, and Science Direct, adopting the PRISMA statement. Through a qualitative analysis, four themes emerged from the 23 included articles: (a) the definitions of relational uncertainty and relational ambiguity, (b) the impact on the quality of the romantic relationship, (c) communicative and individual outcomes, and (d) coping strategies.

Unveiling the spatial dynamics of climate impact on rice yield in India

Climate change has added new dimensions of uncertainty associated with India's rice production. Previous research has explored the impact of climate variation on production and noted the interdependence among neighbouring regions. Using district-level data, we investigate two categories of spatial dynamics associated with the climate sensitivity of rice yield. First, we find evidence that supports previous research that yield is significantly influenced by the direct effects of monsoon maximum temperature and rainfall. The second category, capturing indirect effects, is novel because it provides additional insights into formal and informal networks that underpin the information flow on climate adaptation. Empirical evidence of spatial interdependence arising from information spillovers provides insights into the development of spatially targeted policies that offer the potential for knowledge transfer that contributes to sustaining and increasing rice yields. Policy objectives should therefore focus on advancing technology and promoting social networks that enhance information flow across regions.

A global study of climate uncertainty and carbon assurance

Measurement, verification, and reporting of carbon emissions is essential for climate management. However, research on carbon assurance is limited. To address this gap, we investigate the association between climate uncertainty and voluntary carbon assurance. We conceptualize and operationalize four dimensions of micro-level climate uncertainty: innovation, management and performance, supply chain, and managerial perception uncertainty. We find that all four proxies of climate uncertainty are positively associated with the adoption of voluntary carbon assurance and the positive associations are moderated by a country-level environmental, social, and governance reporting mandate and the industry. Finally, we document that voluntary carbon assurance impacts the valuation of certain dimensions of climate uncertainty. Overall, our study is among the first to document empirical evidence of the nature, characteristics, and dimensions of climate uncertainty and its impact on firms’ carbon assurance. The knowledge will help companies strengthen their capacity to manage the green transition toward carbon neutrality.

The effect of policy uncertainty on the volatility of bitcoin

PurposeThis paper aims to investigate the effect of the economic policy uncertainty (EPU), geopolitical risk (GPR) and climate policy uncertainty (CPU) of USA on Bitcoin volatility from August 2010 to August 2022.Design/methodology/approachIn this paper, the authors have adopted the empirical strategy of Yen and Cheng (2021), who modified volatility model of Wang and Yen (2019), and the authors use an OLS regression with Newey-West error term.FindingsThe results using OLS regression with Newey–West error term suggest that the cryptocurrency market could have hedge or safe-haven properties against EPU and geopolitical uncertainty. While the authors find that the CPU has a negative impact on the volatility of the bitcoin market. Hence, the authors expect climate and environmental changes, as well as indiscriminate energy consumption, to play a more important role in increasing Bitcoin price volatility, in the future.Originality/valueThis study has two implications. First, to the best of the authors’ knowledge, the study is the first to extend the discussion on the effect of dimensions of uncertainty on the volatility of Bitcoin. Second, in contrast to previous studies, this study can be considered as the first to examine the role of climate change in predicting the volatility of bitcoin. This paper contributes to the literature on volatility forecasting of cryptocurrency in two ways. First, the authors discuss volatility forecasting of Bitcoin using the effects of three dimensions of uncertainty of USA (EPU, GPR and CPU). Second, based on the empirical results, the authors show that cryptocurrency can be a good hedging tool against EPU and GPR risk. But the cryptocurrency cannot be a hedging tool against CPU risk, especially with the high risks and climatic changes that threaten the environment.

Asset Returns and Economic Uncertainty: A Cross-Country Analysis

This paper examines the effects of economic uncertainty (idiosyncratic vis-à-vis common uncertainty) on equity, bond and housing returns across both developed and developing countries. Building on International/Intertemporal Capital Asset Pricing Model (ICAPM), we find that economic uncertainty exerts negative effects on equity, bond and housing returns. When we decompose economic uncertainty into two parts: idiosyncratic and common economic uncertainty, we find that ‘idiosyncratic uncertainty’ affects equity, bond and housing returns more negative and pronounced than ‘common’ uncertainty, where investors do not demonstrate differences in responses to the different dimensions of uncertainty. Moreover, there are weak lagged effects of economic uncertainty on asset returns. Additionally, we find negative uncertainty premium for equity more persistently in bullish rather than bearish market conditions. Our results are also robust for low frequency data and inclusion of covid period in the analysis. Our findings have implications for policy makers in both developed and emerging markets regarding clear communication of economic policies.

Dispositional factors in the explanation of symptoms of depression, anxiety, health anxiety and COVID-19 Phobia.

Maladaptive personality, the motivational systems, and intolerance of uncertainty play important roles in the statistical explanation of depression and anxiety. Here, we notably examined for the first time whether symptoms of depression, anxiety, health anxiety, and fear of COVID-19 share similar associations (e.g., variance explained) with these important dispositional dimensions. For this cross-sectional study, data from 1001 participants recruited in Germany (50% women; mean age = 47.26) were collected. In separate models, we examined the cross-sectional associations of the symptoms of depression, anxiety, health anxiety, and fear of COVID-19 with the Personality Inventory for DSM Short Form Plus scales, the Behavioral Inhibition System / Flight-Fight-Freeze System / Behavioral Activation System scales, and Intolerance of Uncertainty scales. Relative weight analyses were used to determine the within-model importance of the different scales in the prediction of the symptoms. All in all, our study showed that maladaptive personality and intolerance of uncertainty dimensions are more important sets of predictors of the studied outcomes (with which depressive and anxious symptomatology feature very similar associations) than are the motivational system dimensions. Within predictor sets, the scales with the most important predictors were: Negative Affectivity, the Behavioral Inhibition System, and Burden due to Intolerance of Uncertainty. Our findings highlight the relevance of focusing behavioral targets of psychotherapy on these within-set traits and identify potential research priorities (maladaptive personality and intolerance of uncertainty) in relation to the symptoms of interest.

Aversion and ambiguity: On the robustness of the macroeconomic uncertainty measure framework

The economic literature has focused on the role of uncertainty in the real economy, employing both measures of risk aversion and ambiguity aversion in structural models. In this connection, concerns about the measures for VIX and EPU, have been raised about whether or not they both measure and identify similar type of uncertainty. Using a structural vector autoregressive (SVAR) approach, we examine the relationship between VIX and EPU, their impact on the real economy and whether, and under which conditions, they can be distinguished between measures of risk aversion and ambiguity aversion. Specifically, we analyse the impact of uncertainty shocks of VIX and EPU on the industrial production, unemployment, and consumer credit in the US. Our main finding is that given their fundamental differences, the two measures are capturing different dimensions of uncertainty, VIX is a measure of risk aversion and EPU is a measure of ambiguity aversion. As such, our results are very important in terms of trading decision strategies to be implemented by investors and portfolio managers as it may help explain the two central behavioral traits affecting economic lifecycle problems, such as production, unemployment and consummation.

Dynamic impacts of multidimensional uncertainty on the renminbi exchange rate: Insights from time-varying analysis

Using a time-varying model, this study investigates the dynamic impact of multidimensional uncertainty by considering data from the policy, finance, and energy markets on the renminbi (RMB) exchange rate from 2001 to 2022. It analyzes specific influence patterns during critical economic periods. We find that multiple dimensions of uncertainty influence the RMB exchange rate rapidly and that these influences exhibit notable temporal variation. (1) The dynamic impact of economic policy uncertainty (EPU) on the RMB exchange rate depends not only on the magnitude of EPU but also on the divergence between domestic and global EPU (also called relative uncertainty). When the domestic EPU is lower than its global counterpart, it can still promote RMB appreciation, even at high levels. (2) The dynamic effect of stock market uncertainty depends on the balance between asset substitutability and risk contagion. The dominance of asset substitutability triggers RMB appreciation during periods of stock market uncertainty. (3) The escalation of energy market uncertainty significantly increases the value of the RMB; this effect is especially pronounced after the financial crisis. Against the backdrop of heightened global economic uncertainty and the significant challenge of maintaining exchange rate stability, regulators should focus on the impact of relative uncertainty and prevent excessive spillovers from other markets. Fostering a risk-neutral mindset and effectively leveraging uncertainty is crucial for forming stable market expectations for exchange rates.

Underexplored Dimensions of Uncertainty and Risk in Human Development Policy Call for a New Paradigm

The human development paradigm like many other development policy domains, old and new, is being challenged by a fundamentally new context that has been described by many as a VUCA world meaning Volatile, Uncertain, Complex, and Ambiguous. These factors are of course not independent of each other, but interactive, thus making for a very difficult environment in which public policy must be made. The Human Development Report (HDR) made a wise and topical choice therefore in selecting uncertain unsettled lives as the theme for the 2021–2022 report. This paper first identifies some of the strengths of the current human development policy analysis but then proceeds to outline multiple concrete, though novel, ways of addressing the challenges of uncertain times and unsettled lives. These include the need for unpackaging the concept of uncertainty, highlighting both differences and linkages between risk and uncertainty, and further implications for policymaking. In addition, we discuss new and promising ways of thinking about uncertainty in policy issues around human development including complexity theory and complex adaptive systems thinking as well as quantum-like frameworks. Finally, we discuss applied spirituality which, in our opinion, can be of great value in engaging with unsettled lives. Ours is an attempt to call for a future paradigm in policy thinking, and social and human sciences as a whole.

The Role of Disgust Certainty in Intuitive Thought Processing: Electrophysiological Evidence.

The impact of emotions on intuitive and analytical thinking has been widely studied. Most research suggests that negative emotions enhance analytical processing. However, there are studies indicating that the sense of certainty associated with disgust can stimulate intuitive processing. Despite these findings, the neuroelectrophysiological evidence supporting the role of disgust in promoting intuitive processing remains unexplored. This study aimed to investigate the neuroelectrophysiological mechanisms by which disgust promotes intuitive processing. A total of 54 participants were recruited and randomly assigned to specific emotion groups. Emotional states were induced by exposing participants to disgust and fear videos designed to evoke specific dimensions of certainty and uncertainty. Event-related potentials (ERP) and the Cognitive Reflection Test (CRT) were utilized as experimental materials to measure participants' responses. The results demonstrated that disgust facilitated intuitive thinking, as evidenced by the lowest accuracy in behavioral outcomes. ERP findings showed that disgust led to smaller N2 and larger P3b amplitudes under conditions of conflict. These results suggest that disgust reduces individuals' conflict-detection ability, resulting in a stronger sense of certainty in intuitive but incorrect answers. This study provides neuroelectrophysiological evidence that disgust enhances intuitive thinking. The findings offer a new perspective on the influence of emotions on dual-process thinking, highlighting the role of disgust in shaping intuitive and analytical thought processes.

Money never sleeps: Capital flows under global risk and uncertainty

We employ various indexes, namely the geopolitical risk (GPR) index, economic policy uncertainty (EPU) index, and world uncertainty index (WUI), to comprehensively capture multiple dimensions of risk and uncertainty and investigate their influence on capital flows measured by different categories of mutual fund flows and IMF intercountry transaction flows. We find that GPR harms aggregate capital flows of both equity and bond funds, whereas rising EPU only significantly reduces the capital flows of equity funds. Additionally, WUI increases capital flowing into active bond funds, indicating a flight-to-safety effect. Besides, high GPR environments amplify the negative influence of EPU on capital flows of equity funds. Meanwhile, in more geopolitically stable conditions, bond markets may serve as a preferred shelter for navigating EPU. However, we find that the impacts of risk and uncertainty on transaction flows are marginal. Furthermore, we demonstrate that global risk or uncertainty (EPU and WUI) plays a more dominant role than country-specific ones in shaping capital flows. Therefore, this study offers novel insights into how different dimensions of risk and uncertainty can shape capital flows differently and whether the compounding effect of risk and uncertainty differs from that of a single risk or uncertainty.

How Do Uncertainties Affect Supply-Chain Resilience? The Moderating Role of Information Sharing for Sustainable Supply-Chain Management

Uncertainties caused by many internal and external factors can lead to supply-chain disruptions, increasing the vulnerability and cost of operations. In particular, the COVID-19 pandemic, whose worldwide emergence was not foreseen, has become a major threat to supply-chain resilience and has caused the disruption of global network connections. The purpose of this study is to examine in depth the impact of uncertainty on supply-chain resilience and to determine whether information sharing has a moderating effect on this interaction. The relationships proposed in the research model are tested through empirical analyses in SEM applied to 244 survey data points from internationally operating manufacturing firms in Turkey. The findings reveal several key insights. First, it is concluded that all dimensions of uncertainty, except technological uncertainty, negatively affect supply-chain resilience. Second, although no direct effect of technological uncertainty on supply-chain resilience is found, technological uncertainty has a negative effect on resilience when the moderating role of internal and supplier information sharing is taken into account. Low-level information sharing, as opposed to high-level, creates variation in the severity of supply-chain resilience at different levels of technological uncertainty. In addition, it is worth noting that a high level of information sharing with suppliers under high-uncertainty conditions negatively affects supply-chain resilience. The results of this study, conducted within the framework of the Contingent Resource-Based Theory, demonstrate compatibility with the theory. Based on all the findings, this study suggests that managers should adopt proactive strategies to maintain high supply-chain resilience, considering today’s highly uncertain conditions.

The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change

Abstract. Future sea-level rise projections are characterized by both quantifiable uncertainty and unquantifiable structural uncertainty. Thorough scientific assessment of sea-level rise projections requires analysis of both dimensions of uncertainty. Probabilistic sea-level rise projections evaluate the quantifiable dimension of uncertainty; comparison of alternative probabilistic methods provides an indication of structural uncertainty. Here we describe the Framework for Assessing Changes To Sea-level (FACTS), a modular platform for characterizing different probability distributions for the drivers of sea-level change and their consequences for global mean, regional, and extreme sea-level change. We demonstrate its application by generating seven alternative probability distributions under multiple emissions scenarios for both future global mean sea-level change and future relative and extreme sea-level change at New York City. These distributions, closely aligned with those presented in the Intergovernmental Panel on Climate Change Sixth Assessment Report, emphasize the role of the Antarctic and Greenland ice sheets as drivers of structural uncertainty in sea-level change projections.

The Welfare State: The Challenges of Sustainability

It is nothing new that ‘the welfare state’ faces serious challenges. Ever since the 1970s, Western welfare states have by many researchers been regarded as being in crisis, but despite many policy adjustments and important variations among Western welfare states, the overall scope of the welfare state, as measured by social expenditure per capita, has by and large increased. At the same time, we can observe a globalization of social policy and the emergence of a more active social role of the state in many parts of the world during recent decades. But new challenges due to a variety of new security issues and new dimensions of uncertainty have appeared, not least following the unanticipated Russian large-scale invasion of and war on Ukraine and concomitant international political developments. Political unease about the future of the welfare state and scope of social policies in different parts of the world has escalated. Welfare political priorities must compete with increased priorities for defense, cyber security, and issues related to energy, climate, food, and the environment. Motivations for state responsibility for citizen welfare and well-being – as well as for the type and scope of responsibility - vary. The fate of the welfare state and social policies is clearly a question of political and normative commitment to what kind of socially active state is desired. The paper addresses the following topics: Why should a state be socially active? What were historical reasons for developing welfare states? What are current motivations for developing and maintaining welfare states? What are the economic, political, and moral dimensions of welfare state sustainability? In addition to possible national political responses to social challenges, it is argued that in a globalized world reinforced international cooperation, coordination and regulation may be necessary to achieve sustainability of (national) welfare states.

Decomposing the Precipitation Response to Climate Change in Convection Allowing Simulations Over the Conterminous United States

AbstractExplicit representation of finer‐scale processes can affect the sign and magnitude of the precipitation response to climate change between convection‐permitting and convection‐parameterizing models. We compare precipitation across two 15‐year epochs, a historical (HIST) and an end‐of‐21st‐century (EoC85), between a set of dynamically downscaled regional climate simulations at 3.75 km grid spacing (WRF) and bias‐corrected Community Earth System Model (CESM) output used to initialize and force the lateral boundaries of the downscaled simulations. In the historical climate, the downscaled simulations demonstrate less overall error than CESM when compared to observations for most portions of the conterminous United States. Both sets of simulations overestimate the incidence of environments with moderate to high precipitable water while CESM generally simulates rainfall that is too frequent but less intense. Within both sets of simulations, EoC85 rainfall amounts decrease in low‐moisture environments due to reduced rainfall frequency and intensity while rainfall amounts increase in high‐moisture environments as they occur more often. Overall, reductions in rainfall are stronger in WRF than in CESM, particularly during the warm season. This reduced drying in CESM is attributed to relatively higher rainfall frequency in environments with high concentrations of precipitable water and weak vertical motion. As a result, an increase in the occurrence of high moisture environments in EoC85 naturally favors more rainfall in CESM than WRF. Our results present an in‐depth examination of the characteristics of changes in overall accumulated precipitation and highlight an extra dimension of uncertainty when comparing convection‐permitting models against convection‐parameterizing models.

Uncertainty in the production of Czech noun and verb forms

We examine the reactions of Czech native speakers to cues asking them to supply inflectional forms of nouns and verbs that are either canonical (non-variant), overabundant, or supposedly defective, to see what distinguishing characteristics these three conditions have for production. We find that respondents handle defective material differently from other conditions, producing different sorts of forms at different frequencies, and taking significantly longer to do so. Overabundant cells pattern at the individual level like canonical inflectional cells, but collectively display a significantly more varied and less focused spread of forms produced than our canonical cells. The individual dimension of uncertainty in production is thus limited to defective cells, but the collective dimension of uncertainty is evident between all three conditions.

Effects of target-amplitude and background-contrast uncertainty predicted by a normalized template-matching observer.

When detecting targets under natural conditions, the visual system almost always faces multiple, simultaneous, dimensions of extrinsic uncertainty. This study focused on the simultaneous uncertainty about target amplitude and background contrast. These dimensions have a large effect on detection and vary greatly in natural scenes. We measured the human performance for detecting a sine-wave target in white noise and natural-scene backgrounds for two levels of prior probability of the target being present. We derived and tested the ideal observer for white-noise backgrounds, a special case of a template-matching observer that dynamically moves its criterion with the background contrast (the DTM observer) and two simpler models with a fixed criterion: the template-matching (TM) observer and the normalized template-matching (NTM) observer that normalizes template response by background contrast. Simulations show that, when the target prior is low, the performance of the NTM observer is near optimal and the TM observer is near chance, suggesting that manipulating the target prior is valuable for distinguishing among models. Surprisingly, we found that the NTM and DTM observers better explain human performance than the TM observer for both target priors in both background types. We argue that the visual system most likely exploits contrast normalization, rather than dynamic criterion adjustment, to deal with simultaneous background contrast and target amplitude uncertainty. Finally, our findings show that the data collected under high levels of uncertainty have a rich structure capable of discriminating between models, providing an alternative approach for studying high dimensions of uncertainty.

Impact of consumer foresight on efficient overselling

AbstractOverselling is commonly adopted in the travel and hospitality sectors where a good or service is sold in excess of actual supply. We examine the impact of consumer foresight on efficient overselling when there are two dimensions of uncertainty, namely, early consumers are uncertain about their service valuations and the seller is uncertain about late demand arrival. We show that when consumers are naïve and have no foresight to anticipate future events, the seller resorts to the use of partial refunds and involuntary cancellation when the mandatory compensation for seller‐initiated cancellation is low, resulting in efficiency loss. When consumers are sophisticated and have perfect foresight on future events, efficiency is achieved when the seller sells the entire capacity in advance and relies solely on voluntary cancellation to re‐sell units when late demand warrants it. Refund complements overselling both by improving allocation efficiency in involuntary cancellation and by mitigating the cost of overselling when consumers have limited foresight. Unlike the social planner, the seller may suffer from consumer foresight. Our findings pinpoint the mandatory compensation in involuntary cancellation as a strategic tool for the social planner to tilt the seller's preference in the seller‐initiated cancellation policy to achieve efficient overselling.