Is the radon risk overestimated? Neglected doses in the estimation of the risk of lung cancer in uranium underground miners

Only the exposure to inhaled radon decay products is usually taken into account in the determination of the risk of radiogenic lung cancer in uranium miners. However, the elevated lung cancer risk in uranium miners is due to the total dose of radiation received by that organ, not to the dose from inhaled radon-222 decay products (222Rn D.P.) alone. Lung doses from sources other than 222Rn D.P. may reach 25% to 75% of total effective dose, absorbed dose or equivalent lung dose, are correlated to 222Rn D.P. doses and are quite variable between facilities. Therefore, to neglect these doses leads to a systematic overestimation of the risk of lung cancer per unit 222Rn D.P. exposure, both through dose underestimation and dose misclassification. Correction for neglected doses and dose misclassification would pull the risk per unit radon exposure downward by a factor of at least two or three and bring the overall dose-effect relationship towards the no-effect null hypothesis, thereby increasing the likelihood of thresholds for lung cancer risk at indoor and today's uranium mine exposures.     

Motor ability: protective or risk for school injuries?

The study aims were to assess the independent contribution of motor ability to the incidence of school injuries. The study included 2057 pupils in grades 3-6 of primary schools in a city in the north of Israel. A surveillance system gathered information about injuries that occurred on school premises or during school related activities and required medical treatment or caused limitation of usual activities. Children provided information on sensation seeking, self-appraisal of health, academic performance, physical activity, and dominant hand; anthropometric measurements and motor ability tests were performed.The incidence of injury events was 4% (95% CI=3.2-5.0). Injuries increased with increased balance and agility, but there were no differences according to reaction time. No other study variables were associated with the incidence of injuries. Our findings of an increase in the incidence of injuries with better motor ability may express differences in exposure to risk situations between children with better and poorer motor abilities.     

Mammographic screening: is the benefit worth the risk?

Justification of medical exposures is a fundamental principle of radiation protection. This principle applies to mammographic screening, both for the screened population and at an individual level. The benefit of mammographic screening may be considered to be the number of cancers detected or lives saved by breast screening. The risk is the hypothetical number of fatal cancers induced by the use of ionising radiation in screening mammography. Benefit can be deduced from the cancer detection rate in the NHS Breast Screening Programme. The number of additional lives saved by the intervention of a screening programme may be deduced from knowledge of the change in tumour size, stage and nodal status (and hence prognosis) in women with screening detected breast cancers compared with symptomatic women before screening. Calculations of benefit risk ratios to the UK population have been performed. It is concluded that breast screening is justified in radiation protection terms.     

‘Anticipatory batch insertion’ to mitigate perceived processing risk

Literature on lot-sizing models with random yields has been traditionally limited to random occurrences that cannot be anticipated in advance; for instance, day-to-day production errors and minor machine repairs. However, in reality, manufacturing processes are subject to other risks that are anticipatory, or non-random, in nature. One example would be yield loss resulting from non-random events such as process, product or material changes. Yield uncertainties of these types are temporary in nature with an impact that decays over time until the manufacturing system fully re-stabilises. One way of reducing the impact of such events is to split the lot and to process a small sub-batch in advance to stabilise the process, thus absorbing the risk associated with the change event. We refer to this approach as ‘anticipatory batch insertion’. This paper presents an exploratory study to analyse the performance of batch insertion under various scenarios related to product sensitivity, risk magnitude and schedule hardness. Results indicate that batch insertion is most advantageous whenever the production schedule is loose, multiple products are sensitive to the risk and the risk magnitude is high.     

Critical factors and paths influencing construction workers’ safety risk tolerances

While workers’ safety risk tolerances have been regarded as a main reason for their unsafe behaviors, little is known about why different people have different risk tolerances even when confronting the same situation. The aim of this research is to identify the critical factors and paths that influence workers’ safety risk tolerance and to explore how they contribute to accident causal model from a system thinking perceptive. A number of methods were carried out to analyze the data collected through interviews and questionnaire surveys. In the first and second steps of the research, factor identification, factor ranking and factor analysis were carried out, and the results show that workers’ safety risk tolerance can be influenced by four groups of factors, namely: (1) personal subjective perception; (2) work knowledge and experiences; (3) work characteristics; and (4) safety management. In the third step of the research, hypothetical influencing path model was developed and tested by using structural equation modeling (SEM). It is found that the effects of external factors (safety management and work characteristics) on risk tolerance are larger than that of internal factors (personal subjective perception and work knowledge & experiences). Specifically, safety management contributes the most to workers’ safety risk tolerance through its direct effect and indirect effect; while personal subjective perception comes the second and can act as an intermedia for work characteristics. This research provides an in-depth insight of workers’ unsafe behaviors by depicting the contributing factors as shown in the accident causal model developed in this research.     

Antecedents of proactive supply chain risk management – a contingency theory perspective

Since supplier insolvencies are a major source of supply chain disruptions, scholars have continuously suggested managing supply chain risk management (SCRM) proactively in order to avoid their occurrence. However, business practice seems to fail with this task. This paper investigates antecedents which foster proactive SCRM implementation from a contingency theory perspective. As a major contingency we choose past supplier insolvencies as an indicator for the level of vulnerability of organisations and investigate inter-organisational, intra-organisational, and individual antecedents. By consulting supply chain management and management accounting literature, hypotheses are developed and tested via content analysis in 63 interviews with representatives from the automotive industry. The findings demonstrate that a mechanistic management control system, a rational cognitive style and relational buyer–supplier relationships have positive impacts on proactively managing supplier insolvency risks. Furthermore, past experience with supplier insolvencies has a moderating, though not a direct, effect on proactiveness. This research suggests that a holistic risk management approach is required to proactively mitigate supplier insolvency risk.     

Are drivers aware of sleepiness and increasing crash risk while driving?

Drivers are advised to take breaks when they feel too tired to drive, but there is question over whether they are able to detect increasing fatigue and sleepiness sufficiently to decide when to take a break. The aim of this study was to investigate the extent to which drivers have access to cognitive information about their current state of sleepiness, likelihood of falling asleep, and the implications for driving performance and the likelihood of crashing. Ninety drivers were recruited to do a 2 h drive in a driving simulator. They were divided into three groups: one made ratings of their sleepiness, likelihood of falling asleep and likelihood of crashing over the next few minutes at prompts occurring at 200 s intervals throughout the drive, the second rated sleepiness and likelihood of falling asleep at prompts but pressed a button on the steering wheel at any time if they felt they were near to crashing and the third made no ratings and only used a button-press if they felt a crash was likely. Fatigue and sleepiness was encouraged by monotonous driving conditions, an imposed shorter than usual sleep on the night before and by afternoon testing. Drivers who reported that they were possibly, likely or very likely to fall asleep in the next few minutes, were more than four times more likely to crash subsequently. Those who rated themselves as sleepy or likely to fall asleep had a more than 9-fold increase in the hazards of a centerline crossing compared to those who rated themselves as alert. The research shows clearly that drivers can detect changes in their levels of sleepiness sufficiently to make a safe decision to stop driving due to sleepiness. Therefore, road safety policy needs to move from reminding drivers of the signs of sleepiness and focus on encouraging drivers to respond to obvious indicators of fatigue and sleepiness and consequent increased crash risk.     

Does exposure to residential radon increase the risk of lung cancer?

In assessing the risks of exposure to ionising radiation, it is important to neither overstate nor understate the effects of the hazard. These requirements are often difficult to satisfy, especially since much of our knowledge about the effects of low levels of radiation is subject to rather large uncertainties. Our participants have given their opinions about the risk of lung cancer induction resulting from exposure to radon in residences. Each agrees that exposures to high concentrations of radon are hazardous. However, as with low level exposures to other types of ionising radiation, quantifying relatively small risks is quite difficult. The national and international standards setting bodies have recommended a fairly conservative approach that may overestimate the 'true' magnitude of deleterious effects and their dependence upon exposure, but this is to be expected given the uncertainties in the data and the need to avoid underestimates. A conservative approach can have both positive and negative consequences, and it is also important to neither overstate nor understate these consequences.     

The accidental risk assessment methodology for industries (ARAMIS)/layer of protection analysis (LOPA) methodology: A step forward towards convergent practices in risk assessment?

In the last ten years, layer of protection analysis (LOPA) emerged as a simplified form of quantitative risk assessment (QRA). The European Commission funded project Accidental Risk Assessment Methodology for Industries in the context of the Seveso 2 Directive (ARAMIS) has recently been completed. ARAMIS has several modules which give a consistent simplified approach to risk assessment which does not approach the complexity or expense of full QRA. LOPA is potentially a means of carrying out the assessment of barriers required in ARAMIS. This paper attempts to explain the principles of LOPA and the means by which it can be used within ARAMIS.     

Developing a resilient supply chain through supplier flexibility and reliability assessment

In this study, we examine the optimal allocation of demand across a set of suppliers in a supply chain that is exposed to supply risk and environmental risk. A two-stage mixed-integer programming model is used to develop a flexible sourcing strategy under disruptions. Our model integrates supplier selection and demand allocation with transportation channel selection and provides contingency plans to mitigate the negative impacts of disruptions and minimise total network costs. Finally, a numerical example is presented to illustrate the model and provide insights. The findings suggest that developing contingency plans using flexibility in suppliers’ production capacity is an effective strategy for firms to mitigate the severity of disruptions. We also show that flexibility and reliability of the suppliers and regions play a significant role in determining contingency plans for during disruption. Findings generally show that highly flexible suppliers receive less allocation, and their flexible capacity is reserved for disruptions. For firms that do not incorporate risk management into supplier selection and allocation, the recommendation is to source from fewer, more reliable suppliers with less risk of disruption. Our findings also emphasise that the type of disruption has important implications for supplier selection and demand allocation. This study highlights the supply chain risk management strategy of regionalising as a means for minimising the impact of environmental disruptions.     

Using backup supply with responsive pricing to mitigate disruption risk for a risk-averse firm

We consider a risk-averse firm’s sourcing problem with two suppliers: a dedicated one and a backup one. The dedicated supplier charges a lower wholesale price, but faces potential disruption risk. The backup supplier is assumed to be perfectly reliable, but charges a higher wholesale price. To mitigate the disruption risk, the firm uses a joint backup supply and responsive pricing strategy. We consider three common backup strategies between the firm and the backup supplier: advance purchase, reservation and contingency purchase. We derive under what conditions each strategy could be optimal. The results show that the thresholds that determine the optimal backup supply strategy are affected by the risk aversion level. When the risk aversion level is not extremely high, the firm should choose among the three backup suppliers by considering the disruption probability and the reservation fee. Firms with a higher risk aversion level tend to rely more on ex-ante preventive efforts (i.e. reservation or advance purchase strategies). When the risk aversion level is extremely high, the firm never considers the contingency purchase strategy, even for a low-probability disruption event. Additionally, market conditions yield non-negligible influences on the firm’s strategic choices due to the existence of risk aversion.     

A portfolio approach to supply chain disruption management

A new, computationally efficient portfolio approach to supplier selection in the presence of supply chain disruption risks is proposed, where the selection of supply portfolios for parts is combined with production scheduling of finished products. Unlike most of reported research on the supply chain risk management which focuses on the risk mitigation decisions taken prior to a disruption, the proposed portfolio approach combines decisions made before, during and after the disruption. The two decision-making approaches are considered: an integrated approach with the perfect information about the future disruption scenarios, and a hierarchical approach with no such information available. In the integrated approach, which accounts for all potential disruption scenarios, the primary supply portfolio that will hedge against all scenarios is determined along with the recovery supply portfolio and production schedule for each scenario. In the hierarchical approach, first the primary supply portfolio is determined, and then, when a primary supplier is hit by a disruption, the recovery supply portfolio is selected. For the integrated and the hierarchical decision-making, mixed integer programming models are developed with the two risk-neutral conflicting objectives that account for both time and cost of recovery: minimising expected cost or maximising expected service level. The findings indicate that for both objectives, the integrated decision-making selects a more diversified primary supply portfolio than the hierarchical approach and when all primary suppliers are shutdown by disruption, a single sourcing recovery portfolio is usually selected.     

Multiobjective capital allocation for supplier development under risk

Supplier development is increasingly important due to the complexity of today’s supply chains and the globalisation of businesses. Since manufacturers have only limited resources, they need to make an informed decision about which suppliers to develop. Moreover, the returns from investment in supplier development are uncertain, so manufacturers have to take this risk into account when choosing their suppliers for development programmes. In this paper, we propose a multi-objective model for capital allocation for supplier development under risk. We apply it to an example of a global car manufacturer and support the decision-making process with data downloaded from the Bloomberg database. We use stock market returns and cost of capital of suppliers to assess their performance. Our model supports an informed decision, which is that tradeoffs exist between risk and cost of supplier development programme. Depending on the risk aversion of the manufacturer, we demonstrate different allocation schemes for supplier development.     

A dynamic sourcing strategy considering supply disruption risks

This study presents a formulation that supports decision-making by determining the optimal number of standby suppliers required to respond to supply failure risks. The problem of supply failure is modelled through a standby approach, in which failure is time-dependent. The probabilities of supply interruption, financial loss caused by supply failure, and operating cost of working with suppliers are modelled to yield the expected total cost, which enables organisations to determine the optimal number of suppliers. Two possible modes of substitution failure are considered in the standby model to enhance the analysis. A set of sensitivity analyses are performed for several input parameters to illustrate the model’s behaviour. The analysis provides an optimal sourcing strategy depending on a combination of supply risk, operational cost vs. loss ratio and length of the supply period. The proposed model indicates the benefits of cost savings, unlike other dynamic models that use multiple suppliers simultaneously.     

Modelling of outsourcing decisions in global supply chains. An empirical study on supplier management performance with different outsourcing strategies

Outsourcing decisions in global supply chains are critical to a business’ competitiveness. This study investigates and compares the supplier management in Taiwanese enterprises under different outsourcing strategies. Base on an empirical study through questionnaires, we investigate the supplier management and critical success factors of the Taiwanese enterprises. It is shown that different outsourcing strategies should be deployed by different types of industries, and a good working relationship with suppliers and customers are paramount to success. The important issues related to supplier management include supplier capability to deliver on time, long term contract strategy with suppliers, supplier evaluation, and quality of material from suppliers.     

Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.     

供应中断风险下供应链恢复能力投资决策及协调

摘要： 〖HTSS〗为了减缓供应商生产运营中断对制造商带来的供应中断风险,制造商需要在突发事件前优化供应链恢复能力投资水平。引入CVaR来刻画供应链在突发事件下的应急目标,建立了一定置信水平控制下的供应链恢复能力投资的决策模型,进而揭示了制造商风险规避程度对供应链最优恢复能力投资水平的影响。分权供应链下,制造商运用基于绩效的契约来激励供应商投资合适的恢复能力,以协调供应链。结论表明,CVaR可以恰当描述供应链恢复的能力投资行为,当风险规避程度越高,供应链最优恢复能力投资越多;当单位中断时间的惩罚系数的条件期望值等于单位中断时间的商誉成本的条件期望值时,供应链进入协调状态。     

A hybrid risks-informed approach for the selection of supplier portfolio

In conventional supplier selection approaches, cost consideration is usually emphasised and it renders a vulnerable supply chain with various risks. This article aims to develop a quantitative approach for modelling both supply chain operational risks and disruption risks to support decision-making with regard to order allocation and risk mitigation. We introduce two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Specifically, VaR is used to measure operational risks caused by improper selection and operations of a supplier portfolio to the stochastic demand, which may frequently occur but result in relatively small losses to supply chains; CVaR is used to evaluate disruption risks that are less frequent and tend to cause significant damage. After incorporating risk factors into a probability-based multi-criteria optimisation model, different methods and parameters are compared and tested to determine the factors that may influence the supplier selection process. Computational examples by simulation are presented to illustrate the approach and how decision-makers make trade-offs between costs and hybrid risks.     

A strategic decision framework for a value added supply chain

Supply chains are becoming increasingly complex. The structure of the supply chain and the suppliers who participate in it are critical decisions for managers. The supply chain is no longer simply a source of inputs or services but an integral source of value added. It is clear that in some cases strategic supply chain objectives may require trade-offs, for example, between cost and innovation capability or between managing risk and maximising flexibility. These decisions balancing trade-offs between desirable partner characteristics are critical and can make a significant contribution to business performance. A framework is outlined, based on the foundation of extant literature, within which firms can make strategic decisions on supply chain structure by categorising the characteristics they prioritise in their supply chain strategy. There is also a strong foundation in the literature on developing mathematical models that provide insight into the decision-making process. A mixed integer programming model is specified that incorporates the opportunity for diversification and provides a demand allocation decision. The model is robust enough to allow for single or diversified supplier strategies based not only on capacity constraints but also on risk pooling and minimum performance requirements for key characteristics that form the basis of the strategy. A Lagrangian relaxation is proposed and satisfactory performance results are provided.