Typology Of Uncertainty Research Articles

The uncertainty in mega-regional SEA and its coping methods in China's practice

Mega-regional strategic environmental assessment (RSEA) aims to provide decision-makers with scientific estimations and protective recommendations for regional development by taking inter-provincial space as work scopes, focalizing regional development as evaluation objects, and evaluating long-term ecological environmental impacts. Huge uncertainties inevitably exist in RSEA, affecting a reliable assessment. However, past literature offers limited guidance on how to systematically identify and address uncertainties in RSEAs. Thus, in light of uncertainty research in other environmental domains, an uncertainty typology of RSEA is constructed based on Simon's administrative model (1957) and Koernoev & Devuyst's decision situation (2016). Three uncertainty types including stochastic, epistemic, and technical uncertainties are developed to respectively interpret the variability-, knowledge-, and technic-related uncertainties. Various coping methods are identified, such as scenario analysis, modeling simulation, worst-case principles, adaptive management, etc. Then, practitioners' perception towards the uncertainty typology is investigated by a questionnaire survey, and the application of uncertainty coping approaches in RSEA practice is examined through case studies. Subsequently, the enlightenment of uncertainty handling in China's RSEA is proposed.

The role of governments in uncertainty orchestration in market formation for sustainability transitions

Market formation in sustainability transitions is characterised by deep and longstanding uncertainty. Albeit prior research provides a rich repertoire of theoretical frameworks on how incumbent firms and entrepreneurs deal with uncertainty, there is still scant literature on the role of the government in orchestrating uncertainty concerning market formation. By studying multiple cases involving an innovation agency and municipalities in Brazil, we propose a new framework composed of a distinguishing typology of uncertainties and patterns of actions regarding how the government can orchestrate the mitigation of these uncertainties in market formation in sustainability transitions. Government actors cope with configurational uncertainty through boundary experimentation, affiliation uncertainty by removing barriers, and interdependence uncertainty by setting long-term mechanisms (nurturing, facilitating and driving interdependence). Our framework suggests that government actors adopt strategies to increase their legitimacy in driving market formation under uncertainty and use epistemic regulation to mitigate hypes. Implications and opportunities for further research are also discussed.

Options for reducing uncertainty in impact classification for alien species

AbstractImpact assessment is an important and cost‐effective tool for assisting in the identification and prioritization of invasive alien species. With the number of alien and invasive alien species expected to increase, reliance on impact assessment tools for the identification of species that pose the greatest threats will continue to grow. Given the importance of such assessments for management and resource allocation, it is critical to understand the uncertainty involved and what effect this may have on the outcome. Using an uncertainty typology and insects as a model taxon, we identified and classified the causes and types of uncertainty when performing impact assessments on alien species. We assessed 100 alien insect species across two rounds of assessments with each species independently assessed by two assessors. Agreement between assessors was relatively low for all three impact classification components (mechanism, severity, and confidence) after the first round of assessments. For the second round, we revised guidelines and gave assessors access to each other’s assessments which improved agreement by between 20% and 30% for impact mechanism, severity, and confidence. Of the 12 potential reasons for assessment discrepancies identified a priori, 11 were found to occur. The most frequent causes (and types) of uncertainty (i.e., differences between assessment outcomes for the same species) were as follows: incomplete information searches (systematic error), unclear mechanism and/or extent of impact (subjective judgment due to a lack of knowledge), and limitations of the assessment framework (context dependence). In response to these findings, we identify actions that may reduce uncertainty in the impact assessment process, particularly for assessing speciose taxa with diverse life histories such as Insects. Evidence of environmental impact was available for most insect species, and (of the non‐random original subset of species assessed) 14 of those with evidence were identified as high impact species (with either major or massive impact). Although uncertainty in risk assessment, including impact assessments, can never be eliminated, identifying, and communicating its cause and variety is a first step toward its reduction and a more reliable assessment outcome, regardless of the taxa being assessed.

Uncertainty and trustworthiness in discussions of fracking: Exploring the views of academic scientists and local governmental representatives

Hydraulic fracturing has transformed how unconventional natural gas and oil resources are extracted across the globe, with much disagreement over its potential environmental impacts, as well as the likelihood of those impacts. Using in-depth interviews, this study examines the views of two stakeholder groups, academic scientists and local governmental representatives, who have been involved in the debate over hydraulic fracturing in Texas’s Dallas-Fort Worth region, fracking’s modern-day birthplace. I explore how individuals within these two groups discuss uncertainty, and how they think their uncertainty framing impacts the public’s perceptions of them. In addition, this study adds to previous research on how expert groups frame uncertainty by integrating Wynne’s (1992) expanded typology of uncertainty, which includes the concepts of risk, uncertainty, ignorance, and indeterminacy.

Uncertainty Types and Transitions in the Entrepreneurial Process

While judgment is typically viewed as a discrete decision process, we conceptualize it as a continuous and dynamic process of reassessment and revision. Adopting this approach, we revisit the nature of entrepreneurial decision-making under uncertainty. We begin with a novel typology of uncertainty that defines and delineates different types of uncertain contexts. We then examine the nature of decision-making within these distinct contexts, highlighting differences in how entrepreneurs make decisions within different types of uncertainty. We build these insights into a theory of the entrepreneurial process that highlights the transitory nature of uncertainty as entrepreneurs make certain judgments and revise those judgments over time. We discuss how uncertainty transitions throughout the judgment process, how the judgment process continues dynamically even after a judgment is made, and how the nature of uncertainty shifts over time due to endogenous and exogenous change.

Неопределенность, риск и принятие решений в междисциплинарном контексте

The article reflects the author’s methodological position that the phenomena of uncertainty and risk are considered within the context of decision-making problems. It is shown that the ability to quantify the probability of the occurrence of possible events makes it possible to fundamentally distinguish between risk situations and situations of uncertainty. Risk is the result of a decision and is always associated with a person who not only makes a choice, but also estimates the probabilities of possible outcomes and related losses. Risk is an integral indicator that combines estimates of both the probability of a decision and of the quantitative characteristics of its consequences. Every person has her own system of preferences, therefore there is no universal functional integrating estimates of probabilities and consequences. As a result, a person chooses the alternative that most closely matches her goals, assessments and value system. The typology of uncertainties in decision-making tasks, previously developed by the author, is supplemented.

A General Framework to Deal with Uncertainty in Expert Panel Risk Assessment

The importance of clarifying and disclosing uncertainties in risk assessment (RA) has been acknowledged for several decades. However, even today, these uncertainties do not receive the attention they deserve to well inform decision makers. To overcome this situation, diverse regulators, health and safety agencies, and other bodies involving in RA at national, European or international level have recently mobilized themselves by reasserting the need to integrate uncertainty analysis in the RA process and making practical recommendations. The French agency for food, environmental and occupational health and safety (Anses) is one of them. This work presents the general framework developed by the Anses Expert Working Group on Methodology in Risk Assessment. Two critical points were addressed: A typology of uncertainties and a homogenized approach to deal with uncertainty analysis in different areas (human health related to the environment, work and food, animal health and welfare, and plant health). The proposed typology is divided into four classes (Context, Corpus of knowledge, Assessment methodology and Communication), according to the logic of an expert appraisal process. A five-step iterative approach, systematically preceded by a stage for planning the assessment, was proposed as a generic approach of uncertainty analysis. Especially, the importance of considering the decision-making context of the assessment from the planning stage is stressed. The iterative approach was developed to be flexible enough to enable the assessors ensure the analysis is proportionate to and fit for purpose of the assessment As part of a testing stage, the general framework was applied to different case studies dealing with diverse areas (health RA in humans, animals and plants). This testing phase was carried out in collaboration with different expert panels. It concluded that the generic and flexible nature of the proposed framework should be able to harmonize the practices in RA.

Managing Uncertainty for Preventive Conservation

ABSTRACT This paper examines how conservators engage with uncertainty when creating preventive conservation strategies. It argues that by recognising contexts in which uncertainty will be encountered conservators can develop effective management strategies. A typology of uncertainty explores a range of categories of uncertainty, their experience in preventive conservation and identifies distinct approaches to manage them. Managing uncertainty may include acts of defining its parameters, exposing and resolving through communication or protecting from with contingency. Whatever approach is adopted it must be accepted that uncertainty cannot be avoided. It is important therefore to aim to live well with uncertainty and the paper advocates for preventive conservation applications of strategies recommended in health care for patients with life-threatening illnesses. These strategies include working on things that can be controlled, goal setting, acceptance and factoring in emotions. The ability to identify contexts in which uncertainty is inbuilt should trigger those concerned with preventive conservation to activate strategies developed for managing and living well with uncertainty.

Improving the link between the futures field and policymaking

Policymakers need to make policies for unknown and uncertain futures. Researchers in the futures field have a great deal to contribute to the policymaking process. But, futures research is often neglected as an element of policymaking. The aim of this paper is to improve the link between futures research and policymaking. More specifically, as Policy Analysis has a strong link with policymaking, this paper explores the possibility of linking Policy Analysis to the futures field through the use of an uncertainty typology applied in Policy Analysis. The typology can be used to structure the various forward-looking disciplines (or subfields) of the futures field according to the level of uncertainty that they address. This linkage can add significantly to the use of futures research in policymaking.

Uncertainty Types and Transitions in the Entrepreneurial Process

While judgment has hitherto typically been viewed as a discrete decision process, we propose that it be conceptualized instead as a continuous and dynamic process of reassessment and revision. Adopting this approach, we revisit the nature of entrepreneurial decision making under uncertainty. We begin with a novel typology of uncertainty that defines and delineates different types of uncertain contexts. We then examine the nature of decision making within these distinct contexts, highlighting differences in how entrepreneurs make decisions within different types of uncertainty. We build these insights into a theory of the entrepreneurial process that highlights the transitory nature of uncertainty as entrepreneurs make certain judgments and revise those judgments over time. We discuss how uncertainty transitions throughout the judgment process, how the judgment process continues dynamically even after a judgment is made, and how the nature of uncertainty shifts over time due to endogenous and exogenous change.

Typology of Uncertainty in Static Geolocated Graphs for Visualization.

Static geolocated graphs have nodes connected by edges, where both can have geographic location and associated attributes. For example, it can be uncertain exactly where a node is located or whether an edge between two nodes exists. Because source data is often incomplete or inexact, it is necessary to visualize this uncertainty to help users make appropriate decisions. The proposed typology of uncertainty extends related typologies with specific features needed for characterizing uncertainty in static geolocated graphs.

A Relational Sociological Study on the Effects of Uncertainties in the Case of Influenza in Turkey

Health issues, especially global health issues, are important subjects of study for many sociologists. For example, the spread of influenza as a pandemic affects a large number of people and their emotions in terms of fear, becoming a social problem instead of a psychological issue. Because of uncertainties, what is happening and what people should do during global threats is not clear for many people generally and during pandemics specifically. The primary aim of this paper is to show the construction process of fear and risk by conducting a systematic review of former studies about the influenza that occurred in Turkey during the last 10 years. It is assumed that a combination of relational sociology and the sociology of disaster and development will provide an appropriate theoretical framework. In other words, H. White and his uncertainty typology along with A.E. Collins’ classification are both used to define the construction process of fear as a culture, starting with uncertainty and moving to alienation and finally normalization. Findings from this study, which are supported by N. Elias’ and U. Beck’s methodological considerations, revealed that uncertainties may lead to negative consequences, such as alienation. Due to conflicting information, people find themselves in a dilemma and they stop following norms and rules in terms of normlessness. Normlessness, as a sub-division of alienation along with meaningless, might result in negative actions, such as not getting vaccinated. Liminality, turning points and footing are also used to describe the construction process of fear and risk. Results also showed that over a 10-year period many things are normalized and people no longer panic as easily.

Classificatory volatility and (in)consistency of racial inequality.

Monitoring racial inequalities, whether socioeconomic or health-related, assumes stability in racial classification. Otherwise, the dynamics of these inequalities could result from racial reclassification rather than from processes related to socioeconomic and health inequalities per se. The study proposes a typology of uncertainty in racial classification (contextual - temporal, geographic, procedural - and sampling) and draws on the literature and nationally representative secondary data to discuss the magnitude of racial variability in Brazil according to these five dimensions. The results show that at least two of these uncertainties - geographic and procedural - are substantial, but have little influence on the racial gap in income. We address the impacts of these results on the existence and extent of racial inequalities in health and conclude that the structure of inequalities between whites and blacks is consistent, although skin color classification is volatile.

A typology of uncertainty derived from an analysis of critical incidents in medical residents: A mixed methods study.

BackgroundMedical uncertainty is inherently related to the practice of the physician and generally affects his or her patient care, job satisfaction, continuing education, as well as the overall goals of the health care system. In this paper, some new types of uncertainty, which extend existing typologies, are identified and the contexts and strategies to deal with them are studied.MethodsWe carried out a mixed-methods study, consisting of a qualitative and a quantitative phase. For the qualitative study, 128 residents reported critical incidents in their clinical practice and described how they coped with the uncertainty in the situation. Each critical incident was analyzed and the most salient situations, 45 in total, were retained. In the quantitative phase, a distinct group of 120 medical residents indicated for each of these situations whether they have been involved in the described situations and, if so, which coping strategy they applied. The analysis examines the relation between characteristics of the situation and the coping strategies.ResultsFrom the qualitative study, a new typology of uncertainty was derived which distinguishes between technical, conceptual, communicational, systemic, and ethical uncertainty. The quantitative analysis showed that, independently of the type of uncertainty, critical incidents are most frequently resolved by consulting senior physicians (49 % overall), which underscores the importance of the hierarchical relationships in the hospital. The insights gained by this study are combined into an integrative model of uncertainty in medical residencies, which combines the type and perceived level of uncertainty, the strategies employed to deal with it, and context elements such as the actors present in the situation. The model considers the final resolution at each of three levels: the patient, the health system, and the physician’s personal level.ConclusionsThis study gives insight into how medical residents make decisions under different types of uncertainty, giving account of the context in which the interactions take place and of the strategies used to resolve the incidents. These insights may guide the development of organizational policies that reduce uncertainty and stress in residents during their clinical training.Electronic supplementary materialThe online version of this article (doi:10.1186/s12909-015-0459-2) contains supplementary material, which is available to authorized users.

Uncertainty in the availability of natural resources: Fossil fuels, critical metals and biomass

Energy policies are strongly influenced by resource availability and recoverability estimates. Yet these estimates are often highly uncertain, frequently incommensurable, and regularly contested. This paper explores how the uncertainties surrounding estimates of the availability of fossil fuels, biomass and critical metals are conceptualised and communicated. The contention is that a better understanding of the uncertainties surrounding resource estimates for both conventional and renewable energy resources can contribute to more effective policy decision making in the long term. Two complementary approaches for framing uncertainty are considered in detail: a descriptive typology of uncertainties and a framework that conceptualises uncertainty as alternative states of incomplete knowledge. Both have the potential to be useful analytical and communication tools. For the three resource types considered here we find that data limitations, inconsistent definitions and the use of incommensurable methodologies present a pervasive problem that impedes comparison. Many aspects of resource uncertainty are also not commonly captured in the conventional resource classification schemes. This highlights the need for considerable care when developing and comparing aggregate resource estimates and when using these to inform strategic energy policy decisions.

Identifying Uncertainty in Environmental Risk Assessments: The Development of a Novel Typology and Its Implications for Risk Characterization

ABSTRACT Environmental risk analysts need to draw from a clear typology of uncertainties when qualifying risk estimates and/or significance statements about risk. However, categorizations of uncertainty within existing typologies are largely overlapping, contradictory, and subjective, and many typologies are not designed with environmental risk assessments (ERAs) in mind. In an attempt to rectify these issues, this research provides a new categorization of uncertainties based, for the first time, on the appraisal of a large subset of ERAs, namely 171 peer-reviewed environmental weight-of-evidence assessments. Using this dataset, a defensible typology consisting of seven types of uncertainty (data, language, system, extrapolation, variability, model, and decision) and 20 related sub-types is developed. Relationships between uncertainties and the techniques used to manage them are also identified and statistically evaluated. A highly preferred uncertainty management option is to take no action when faced with uncertainty, although where techniques are applied they are commensurate with the uncertainty in question. Key observations are applied in the form of guidance for dealing with uncertainty, demonstrated through ERAs of genetically modified higher plants in the European Union. The presented typology and accompanying guidance will have positive implications for the identification, prioritization, and management of uncertainty during risk characterization.

Managing uncertainty through supply chain flexibility: reactive vs. proactive approaches

The purpose of this paper is to obtain insights into the typology of uncertainty and relevant strategies adopted by manufacturing companies to achieve better supply chain flexibility. Strategies are classified into reactive (buffering) and proactive (redesigning). We develop a framework that links supply chain uncertainty, the two types of strategies for achieving supply chain flexibility and the relevant objectives to be achieved. Four case studies are compared in terms of uncertainty typology and strategies being adopted to improve supply chain flexibility. We present three propositions as a result of the study. First, to achieve better flexibility, companies have been focusing more on buffering than on proactive or redesign strategies. Second, companies tend to focus on internal operations rather than collaborating with external parties, and third, the power structure in a supply chain governs the type and configuration of supply chain flexibility.

Uncertainty of Population Risk Estimates for Pathogens Based on QMRA or Epidemiology: A Case Study of Campylobacter in the Netherlands

Epidemiology and quantitative microbiological risk assessment are disciplines in which the same public health measures are estimated, but results differ frequently. If large, these differences can confuse public health policymakers. This article aims to identify uncertainty sources that explain apparent differences in estimates for Campylobacter spp. incidence and attribution in the Netherlands, based on four previous studies (two for each discipline). An uncertainty typology was used to identify uncertainty sources and the NUSAP method was applied to characterize the uncertainty and its influence on estimates. Model outcomes were subsequently calculated for alternative scenarios that simulated very different but realistic alternatives in parameter estimates, modeling, data handling, or analysis to obtain impressions of the total uncertainty. For the epidemiological assessment, 32 uncertainty sources were identified and for QMRA 67. Definitions (e.g., of a case) and study boundaries (e.g., of the studied pathogen) were identified as important drivers for the differences between the estimates of the original studies. The range in alternatively calculated estimates usually overlapped between disciplines, showing that proper appreciation of uncertainty can explain apparent differences between the initial estimates from both disciplines. Uncertainty was not estimated in the original QMRA studies and underestimated in the epidemiological studies. We advise to give appropriate attention to uncertainty in QMRA and epidemiological studies, even if only qualitatively, so that scientists and policymakers can interpret reported outcomes more correctly. Ideally, both disciplines are joined by merging their strong respective properties, leading to unified public health measures.

수도권 대기 중 입자상 물질로 인한 건강부담 추정과 불확실성

It is well known that exposure to high level of PM (particulate matter) can adversely affect human health. However, little is known about health burden of PM considering the relationship, exposed level of PM, and health level in local communities. And, there is scarcely methodical assessment of uncertainty for application to policies of these assessment results. The scope of this study is divided into two parts: firstly to estimate the death burden of PM10 (particulate matter less then <TEX>$10{\mu}m$</TEX> in diameter) in Seoul metropolitan region, and secondly to evaluate potential uncertainties in these estimates. To estimate the death burden of PM10 in Seoul metropolitan region from 2005~2010, we firstly assessed the relationship between daily mean PM10 and daily death counts in Seoul from 2000~2010, and calculated the death burden of PM10 using BenMAP (Environmental Benefits Mapping and Analysis Program). After that, we identified and characterized uncertainties to substantially influence the results of death burden. The daily mortality risk was increased 1.000227 times (p-value/0.001) associated with <TEX>$1{\mu}g/m^3$</TEX> increase of daily mean PM10 for all ages population, Seoul. And, death burdens of PM10 in Seoul metropolitan region were estimated from 5.51 in 2005 to 5.12 in 2010 per 100,000 people. Finally, we categorized context, model, and input uncertainty and characterized these uncertainties in three dimensions (i.e. location, level, and nature) using uncertainty typology. In our study, we argue that uncertainties need to be identified, assessed, reported and interpreted in order for assessment results to adequately support decision making, such as the establishment of air quality standards based on health burden of air quality.

Uncertainty in developing supervisory demand-side controls in buildings: A framework and guidance

Successful demand-side control depends on the accuracy of the prediction of the power demand. This prediction should express margins of expected ranges of the power demand. Therefore, uncertainty is an unavoidable ingredient that has to be explicitly considered when evaluating performance of demand-side control. However, there is at present neither serious attention to system uncertainty nor to human-introduced uncertainty in developing the supervisory controls of building and HVAC&R systems. There is, in fact, neither a commonly shared terminology nor an agreement on a generic typology of uncertainty. Apart from introducing a common terminology and typology of uncertainty, this study provides a conceptual framework for systemic management of uncertainty, along with a process of developing the supervisory demand-side controls. This study reviews relevant uncertainty sources. Surveyed sources are classified according to the typology, and then encoded into the uncertainty matrix as part of the framework. The uncertainty matrix is used for a priori uncertainty assessment that enables model developers to identify, articulate, and prioritize critical uncertainty; it is a crucial step for gathering more adequate identification and for proper treatment of uncertainty before developing a significant model. The a priori uncertainty assessment identified that heuristic uncertainty and scenario uncertainty tend to introduce higher risks for the demand-side control in meeting its objectives. Upon this assessment, this study suggests a theoretical guide to manage and reduce risks due to uncertainty: heuristic uncertainty can be preventable if models are constructed through the formal modeling framework; physical uncertainty including both scenario uncertainty and statistical uncertainty can be compiled into model in order to render the model immune to uncertainty. • Uncertainty is an unavoidable complication for performance of the demand-side control. • Neither a commonly shared terminology nor typology of uncertainty is available. • A priori uncertainty assessment gathers more adequate identification of uncertainty. • A priori uncertainty assessment also suggests proper treatment of uncertainty. • This study presents a general guide to manage and reduce the risk due to uncertainty.