Developing an analytical framework to assess the uncertainty and flexibility mismatches across the supply chain

Purpose: The purpose of this paper is to discuss how decisions regarding organisational flexibility can be improved through targeted resource allocation, by focusing on the supply chain's level of uncertainty exposure. Specifically, the issue of where and in what ways flexibility has been incorporated across the organisation's supply chain is addressed. Design/methodology/approach: A two-phase methodology design based on literature review and case study was used. Using 83 journal articles in the areas of uncertainty and flexibility an analytical process for assessing uncertainty-flexibility mismatches was developed. Furthermore, results from ten interviews with senior/middle managers within the Australian manufacturing sector were used to provide preliminary insights on the usefulness and importance of the analytical process and its relationship with organisational practice. Findings: The paper emphasises the importance of having a systematic and encompassing view of uncertainty-flexibility mismatches across the supply chain, as well as the significance of socio-technical engagement. The paper both conceptually and empirically illustrates how, using a structured analytical process, flexibility requirements across the supply, process, control and demand segments of a supply chain might be assessed. A four-step analytical process was accordingly developed and, its application, usefulness and importance discussed using empirical data. Practical implications: The analytical process presented in this paper can assist managers to obtain a comprehensive overview of supply chain flexibility when dealing with situations involving uncertainty. This can facilitate and improve their decision-making with respect to prioritising attention on identified flexibility gaps in order to ensure stability of their performance. Originality/value: The paper presents a supply chain-wide discussion on the difficulties that uncertainty brings to organisations, and how organisational flexibility might serve to moderate those challenges for supply chain management. It discusses how to identify the flexibility gap and proposes an original analytical process for systematic assessment of uncertainty-flexibility mismatches. © Emerald Group Publishing Limited.

Communication of scientific uncertainty : international case studies on the development of folate and vitamin D Dietary Reference Values.

Transparent evidence-based decision making has been promoted worldwide to engender trust in science and policy making. Yet, little attention has been given to transparency implementation. The degree of transparency (focused on how uncertain evidence was handled) during the development of folate and vitamin D Dietary Reference Values was explored in three a priori defined areas: (i) value request; (ii) evidence evaluation; and (iii) final values.

Uncertainty handling using neural network-based prediction intervals for electrical load forecasting

The complexity and level of uncertainty present in operation of power systems have significantly grown due to penetration of renewable resources. These complexities warrant the need for advanced methods for load forecasting and quantifying uncertainties associated with forecasts. The objective of this study is to develop a framework for probabilistic forecasting of electricity load demands. The proposed probabilistic framework allows the analyst to construct PIs (prediction intervals) for uncertainty quantification. A newly introduced method, called LUBE (lower upper bound estimation), is applied and extended to develop PIs using NN (neural network) models. The primary problem for construction of intervals is firstly formulated as a constrained single-objective problem. The sharpness of PIs is treated as the key objective and their calibration is considered as the constraint. PSO (particle swarm optimization) enhanced by the mutation operator is then used to optimally tune NN parameters subject to constraints set on the quality of PIs. Historical load datasets from Singapore, Ottawa (Canada) and Texas (USA) are used to examine performance of the proposed PSO-based LUBE method. According to obtained results, the proposed probabilistic forecasting method generates well-calibrated and informative PIs. Furthermore, comparative results demonstrate that the proposed PI construction method greatly outperforms three widely used benchmark methods. © 2014 Elsevier Ltd.

An optimized mean variance estimation method for uncertainty quantification of wind power forecasts

A statistical optimized technique for rapid development of reliable prediction intervals (PIs) is presented in this study. The mean-variance estimation (MVE) technique is employed here for quantification of uncertainties related with wind power predictions. In this method, two separate neural network models are used for estimation of wind power generation and its variance. A novel PI-based training algorithm is also presented to enhance the performance of the MVE method and improve the quality of PIs. For an in-depth analysis, comprehensive experiments are conducted with seasonal datasets taken from three geographically dispersed wind farms in Australia. Five confidence levels of PIs are between 50% and 90%. Obtained results show while both traditional and optimized PIs are hypothetically valid, the optimized PIs are much more informative than the traditional MVE PIs. The informativeness of these PIs paves the way for their application in trouble-free operation and smooth integration of wind farms into energy systems. © 2014 Elsevier Ltd. All rights reserved.

Quantification of spatial and thematic uncertainty in the application of underwater video for benthic habitat mapping

This study presents an analysis of the application of underwater video data collected for training and validating benthic habitat distribution models. Specifically, we quantify the two major sources of error pertaining to collection of this type of reference data. A theoretical spatial error budget is developed for a positioning system used to co-register video frames to their corresponding locations at the seafloor. Second, we compare interpretation variability among trained operators assessing the same video frames between times over three hierarchical levels of a benthic classification scheme. Propagated error in the positioning system described was found to be highly correlated with depth of operation and varies from 1.5m near the surface to 5.7m in 100m of water. In order of decreasing classification hierarchy, mean overall observer agreement was found to be 98% (range 6%), 82% (range 12%) and 75% (range 17%) for the 2, 4, and 6 class levels of the scheme, respectively. Patterns in between-observer variation are related to the level of detail imposed by each hierarchical level of the classification scheme, the feature of interest, and to the amount of observer experience. © 2014 Copyright © Taylor & Francis Group, LLC.

Extending scheduling algorithms to minimise the impact of bounded uncertainty using interval programming

 This research proposed a new methodology to extend algorithms to accept interval-based uncertain parameters. The methodology is applied on scheduling algorithms, including heuristic and meta-heuristic algorithms and produced optimal results with higher accuracy. The research outcomes are effective for decision making process using uncertain or predicted data.

A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources

The penetration of intermittent renewable energy sources (IRESs) into power grids has increased in the last decade. Integration of wind farms and solar systems as the major IRESs have significantly boosted the level of uncertainty in operation of power systems. This paper proposes a comprehensive computational framework for quantification and integration of uncertainties in distributed power systems (DPSs) with IRESs. Different sources of uncertainties in DPSs such as electrical load, wind and solar power forecasts and generator outages are covered by the proposed framework. Load forecast uncertainty is assumed to follow a normal distribution. Wind and solar forecast are implemented by a list of prediction intervals (PIs) ranging from 5% to 95%. Their uncertainties are further represented as scenarios using a scenario generation method. Generator outage uncertainty is modeled as discrete scenarios. The integrated uncertainties are further incorporated into a stochastic security-constrained unit commitment (SCUC) problem and a heuristic genetic algorithm is utilized to solve this stochastic SCUC problem. To demonstrate the effectiveness of the proposed method, five deterministic and four stochastic case studies are implemented. Generation costs as well as different reserve strategies are discussed from the perspectives of system economics and reliability. Comparative results indicate that the planned generation costs and reserves are different from the realized ones. The stochastic models show better robustness than deterministic ones. Power systems run a higher level of risk during peak load hours.

Education in the age of uncertainty: an eagle's eye-view

 How are we to educate young people of, and for, these times in a way which takes into account the existential and moral dilemmas of our age? We argue that the current education system fails to address the full implications of historical change in relation to ethics and equity. In what follows, we offer some ways of describing and theorising contemporary life in an age of uncertainty. We offer it as a knowledge base from which teachers, principals and policy makers might draw in creating new morally and ethically sound policy discourses. We follow with some new frameworks for helping students to deal with the altered context of moral and political life.

Business strateBusiness strategies under conditions of uncertainty: The rise of mutual life insurers in colonial Australiagies under conditions of uncertainty

The early development of Australian life insurance was marked by the failure of stock companies to successfully establish a market presence. Mutual insurers emerged in the mid-nineteenth century in response to this gap in supply. The underlying rationale behind their establishment differed but the business model adopted proved remarkably successful. Mutual life insurers dominated the market for life insurance for nearly a century. This chapter investigates mutualism as a business strategy that addressed particular problems associated with doing business in a small and underdeveloped economy. Business and social networks were important facilitators of new business. In addition, most mutual life insurers had a social/philanthropic charter and they were able to utilize this to build business. An outcome of this mix was the emergence of a particular type of entrepreneurship that fostered innovative product development and cemented the role of mutual insurers as market leaders.. The Variety, Choice, Governance, and Regulation of Organizational Forms 2.

Accounting for uncertainty in volumes of seabed change measured with repeat multibeam sonar surveys

Seafloors of unconsolidated sediment are highly dynamic features; eroding or accumulating under the action of tides, waves and currents. Assessing which areas of the seafloor experienced change and measuring the corresponding volumes involved provide insights into these important active sedimentation processes. Computing the difference between Digital Elevation Models (DEMs) obtained from repeat Multibeam Echosounders (MBES) surveys has become a common technique to identify these areas, but the uncertainty in these datasets considerably affects the estimation of the volumes displaced. The two main techniques used to take into account uncertainty in volume estimations are the limitation of calculations to areas experiencing a change in depth beyond a chosen threshold, and the computation of volumetric confidence intervals. However, these techniques are still in their infancy and, as a result, are often crude, seldom used or poorly understood. In this article, we explored a number of possible methodological advances to address this issue, including: (1) using the uncertainty information provided by the MBES data processing algorithm CUBE, (2) adapting fluvial geomorphology techniques for volume calculations using spatially variable thresholds and (3) volumetric histograms. The nearshore seabed off Warrnambool harbour - located in the highly energetic southwest Victorian coast, Australia - was used as a test site. Four consecutive MBES surveys were carried out over a four-months period. The difference between consecutive DEMs revealed an area near the beach experiencing large sediment transfers - mostly erosion - and an area of reef experiencing increasing deposition from the advance of a nearby sediment sheet. The volumes of sediment displaced in these two areas were calculated using the techniques described above, both traditionally and using the suggested improvements. We compared the results and discussed the applicability of the new methodological improvements. We found that the spatially variable uncertainty derived from the CUBE algorithm provided the best results (i.e. smaller confidence intervals), but that similar results can be obtained using as a fixed uncertainty value derived from a reference area under a number of operational conditions.

Communication of scientific uncertainty: International case studies on the development of folate and vitamin D Dietary Reference Values

Objective Transparent evidence-based decision making has been promoted worldwide to engender trust in science and policy making. Yet, little attention has been given to transparency implementation. The degree of transparency (focused on how uncertain evidence was handled) during the development of folate and vitamin D Dietary Reference Values was explored in three a priori defined areas: (i) value request; (ii) evidence evaluation; and (iii) final values. Design Qualitative case studies (semi-structured interviews and desk research). A common protocol was used for data collection, interview thematic analysis and reporting. Results were coordinated via cross-case synthesis. Setting Australia and New Zealand, Netherlands, Nordic countries, Poland, Spain and UK. Subjects Twenty-one interviews were conducted in six case studies. Results Transparency of process was not universally observed across countries or areas of the recommendation setting process. Transparency practices were most commonly seen surrounding the request to develop reference values (e.g. access to risk manager/assessor problem formulation discussions) and evidence evaluation (e.g. disclosure of risk assessor data sourcing/evaluation protocols). Fewer transparency practices were observed to assist with handling uncertainty in the evidence base during the development of quantitative reference values. Conclusions Implementation of transparency policies may be limited by a lack of dedicated resources and best practice procedures, particularly to assist with the latter stages of reference value development. Challenges remain regarding the best practice for transparently communicating the influence of uncertain evidence on the final reference values. Resolving this issue may assist the evolution of nutrition risk assessment and better inform the recommendation setting process.

Making conservation decisions under uncertainty for the persistence of multiple species

Population models for multiple species provide one of the few means of assessing the impact of alternative management options on the persistence of biodiversity, but
they are inevitably uncertain. Is it possible to use population models in multiple-speciesconservation planning given the associated uncertainties? We use information-gap decision theory to explore the impact of parameter uncertainty on the conservation decision when planning for the persistence of multiple species. An information-gap approach seeks robust outcomes that are most immune from error. We assess the impact of uncertainty in key model parameters for three species, whose extinction risks under four alternative management scenarios are estimated using a metapopulation model. Three methods are described for making conservation decisions across the species, taking into account uncertainty. We find that decisions based on single species are relatively robust to uncertainty in parameters, although the estimates of extinction risk increase rapidly with uncertainty. When identifying the best conservation decision for the persistence of all species, the methods that rely on the rankings of the management options by each species result in decisions that are similarly robust to uncertainty. Methods that depend on absolute values of extinction risk are sensitive to uncertainty, as small changes in extinction risk can alter the ranking of the alternative scenarios. We discover that it is possible to make robust conservation decisions even when the uncertainties of the multiple-species problem appear overwhelming. However, the decision most robust to uncertainty is likely to differ from the best decision when uncertainty is ignored, illustrating the importance of incorporating uncertainty into the decision-making process.

Uncertainty and reluctance in teaching taboo language: a case study of an experienced teacher of English as an additional language

Despite its ubiquitous employment by users of English to achieve authentic communicative goals, taboo language has received little attention in the education literature. Even less focus has been placed on such language in English language teaching - specifically, in teaching English as an Additional Language (EAL). Given the multiplicity of communicative struggles experienced by EAL learners surrounding the use of taboo language in authentic communication, meaningful consideration of this aspect can be seen as crucial in EAL instruction. Classroom learning could prepare learners for navigation and negotiation of taboo language use they will inevitably encounter in social interactions in target language communities of practice. However, EAL teachers' uncertainty or reluctance to introduce taboo language in classroom instruction is a key impediment in developing learners' sociocultural knowledge regarding such language use. We foreground one case of such uncertainty and reluctance surrounding the introduction of taboo language in EAL instruction derived as interview data from an experienced EAL teacher.

Aggregate uncertainty in the citizen candidate model yields extremist parties

We extend the citizen candidate model of electoral competition with sincere voting to allow for k ≥ 2 states of aggregate uncertainty. We discuss and characterize the equilibrium set in this framework. We provide conditions for the existence of two-party equilibria when k = 2 and show that the policies of the two parties in any such equilibrium are not only divergent but that the parties are extremist: when the political mood is left-wing, the left-wing party wins decisively with a platform that is to the left of the left-wing median voter, while when the political mood is right-wing, the right-wing party wins decisively with a platform that is to the right of the right-wing median voter. We then provide conditions under which such equilibria remain robust for an arbitrary value of k.

Better the devil you know than a world you don't? Intolerance of uncertainty and worldview explanations for belief in conspiracy theories

Conspiracy Theory (CT) endorsers believe in an omnipresent, malevolent, and highly coordinated group that wields secret influence for personal gain, and credit this group with the responsibility for many noteworthy events. Two explanations for the emergence of CTs are that they result from social marginalisation and a lack of agency, or that they are due to a need-to-explain-the-unexplained. Furthermore, representativeness heuristics may form reasoning biases that make such beliefs more likely. Two related studies (N = 107; N = 120) examined the relationships between these social marginalisation, intolerance of uncertainty, heuristics and CT belief using a correlational design. Overall, intolerance of uncertainty did not link strongly to CT belief, but worldview variables did - particularly a sense of the world as (socially) threatening, non-random, and with no fixed morality. The use of both representative heuristics that were examined was heightened in those participants more likely to endorse CTs. These factors seem to contribute to the likelihood of whether the individual will endorse CTs generally, relating similarly to common CTs, CTs generally historically accepted as "true", and to the endorsement of fictional CTs that the individual would find novel. Implications are discussed.