Assessing Risk‐Based Upper Limits of Melamine Migration from Food Containers

Melamine contamination of food has become a major food safety issue because of incidents of infant disease caused by exposure to this chemical. This study was aimed at establishing a safety limit in Taiwan for the degree of melamine migration from food containers. Health risk assessment was performed for three exposure groups (preschool children, individuals who dine out, and elderly residents of nursing homes). Selected values of tolerable daily intake (TDI) for melamine were used to calculate the reference migration concentration limit (RMCL) or reference specific migration limit (RSML) for melamine food containers. The only existing values of these limits for international standards today are 1.2 mg/L (0.2 mg/dm²) in China and 30 mg/L (5 mg/dm²) in the European Union. The factors used in the calculations included the specific surface area of food containers, daily food consumption rate, body weight, TDI, and the percentile of the population protected at a given migration concentration limit (MCL). The results indicate that children are indeed at higher risk of melamine exposure at toxic levels than are other groups and that the 95th percentile of MCL (specific surface area = 5) for children aged 1–6 years should be the RMCL (0.07 mg/dm²) for protecting the sensitive and general population.     

Sensitivity,uncertainty, and decision analyses in the prioritization of research

The evaluation of hazards from complex, large scale, technologically advanced systems often requires the construction of computer implemented mathematical models. These models are used to evaluate the safety of the systems and to evaluate the consequences of modifications to the systems. These evaluations, however, are normally surrounded by significant uncertainties related to the uncertainty inherent in natural phenomena such as the weather and those related to uncertainties in the parameters and models used in the evaluation.

Another use of these models is to evaluate strategies for improving information used in the modeling process itself. While sensitivity analysis is useful in defining variables in the model that are important, uncertainty analysis provides a tool for assessing the importance of uncertainty about these variables. A third complementary technique, is decision analysis. It provides a methodology for explicitly evaluating and ranking potential improvements to the model. Its use in the development of information gathering strategies for a nuclear waste repository are discussed in this paper.     

Moment‐Independent Sensitivity Analysis Using Copula

In risk assessment, the moment‐independent sensitivity analysis (SA) technique for reducing the model uncertainty has attracted a great deal of attention from analysts and practitioners. It aims at measuring the relative importance of an individual input, or a set of inputs, in determining the uncertainty of model output by looking at the entire distribution range of model output. In this article, along the lines of Plischke et al., we point out that the original moment‐independent SA index (also called delta index) can also be interpreted as the dependence measure between model output and input variables, and introduce another moment‐independent SA index (called extended delta index) based on copula. Then, nonparametric methods for estimating the delta and extended delta indices are proposed. Both methods need only a set of samples to compute all the indices; thus, they conquer the problem of the “curse of dimensionality.” At last, an analytical test example, a risk assessment model, and the levelE model are employed for comparing the delta and the extended delta indices and testing the two calculation methods. Results show that the delta and the extended delta indices produce the same importance ranking in these three test examples. It is also shown that these two proposed calculation methods dramatically reduce the computational burden.     

煤矿瓦斯爆炸事故单危险源风险度量模型研究

本文研究了煤矿瓦斯爆炸事故危险源的分类,把危险源划分为人的不安全行为、机器设备不安全状态、环境不安全特征和管理缺陷四大类,并根据煤矿现场调查各类危险源的数据以及相应数学方法的特点,提出煤矿瓦斯爆炸事故人、机器设备(物)、环境、管理四类危险源的风险度量方法,在此基础上构建四类危险源的风险度量模型。研究表明,危险源的风险度量模型由风险发生的可能性、危险源重要度以及事故导致的损失构成;危险源风险发生的可能性,在具体应用中可以采用各类危险源的不可靠度、故障率等来衡量;危险源在事故中的重要度可以通过分析事故故障树种要素结构重要性获取。根据风险评价的结果,可以对危险源进行分级排序,从而为煤矿事故单危险源的控制提供依据。     

Improving Risk Management: From Lame Excuses to Principled Practice

The three classic pillars of risk analysis are risk assessment (how big is the risk and how sure can we be?), risk management (what shall we do about it?), and risk communication (what shall we say about it, to whom, when, and how?). We propose two complements as important parts of these three bases: risk attribution (who or what addressable conditions actually caused an accident or loss?) and learning from experience about risk reduction (what works, and how well?). Failures in complex systems usually evoke blame, often with insufficient attention to root causes of failure, including some aspects of the situation, design decisions, or social norms and culture. Focusing on blame, however, can inhibit effective learning, instead eliciting excuses to deflect attention and perceived culpability. Productive understanding of what went wrong, and how to do better, thus requires moving past recrimination and excuses. This article identifies common blame‐shifting “lame excuses” for poor risk management. These generally contribute little to effective improvements and may leave real risks and preventable causes unaddressed. We propose principles from risk and decision sciences and organizational design to improve results. These start with organizational leadership. More specifically, they include: deliberate testing and learning—especially from near‐misses and accident precursors; careful causal analysis of accidents; risk quantification; candid expression of uncertainties about costs and benefits of risk‐reduction options; optimization of tradeoffs between gathering additional information and immediate action; promotion of safety culture; and mindful allocation of people, responsibilities, and resources to reduce risks. We propose that these principles provide sound foundations for improving successful risk management.     

How to Evaluate Government Performance while Building a Rule of Law Government in China*

Building a law-based government is a central element of the comprehensive framework for promoting the rule of law in China, while using evaluation to catalyze growth is in line with the incentive principle of management studies. Since China started to implement reform and opening up over thirty years ago, rule of law development and organizational evaluation have gone through several stages, each with different characteristics. Efforts to build a law-based government have met with success, but what the country now has is essentially still goal-oriented assessment. At present, this suffers from the lack of a clear goal orientation or definition of functions, an imperfect technical system and unsound motivation mechanisms, not to mention the practical problems of each government department going its own way, duplicating evaluations or being left rudderless. Drawing on a combination of value rationality and instrumental rationality and using government performance evaluation to promote the building of a law-based government not only conforms to the spirit of the rule of law and value rationality in government performance, but also strengthens the role of evaluation as an instrument for organizational management. Therefore, we need to create new evaluation theories, expand public participation, introducing diversified evaluating entities, improve technical systems, strengthen institutional buildup, and foster a performance-based culture. In addition, replacing goal-oriented assessment with performance evaluation will help the emergence of a new discipline—the performance evaluation of rule of law government, thus promoting multidisciplinary efforts to integrate and create new public administration theories in China.     

Practical procedures to deal with common support problems in matching estimation

This paper assesses the performance of common estimators adjusting for differences in covariates, such as matching and regression, when faced with the so-called common support problems. It also shows how different procedures suggested in the literature affect the properties of such estimators. Based on an empirical Monte Carlo simulation design, a lack of common support is found to increase the root-mean-squared error of all investigated parametric and semiparametric estimators. Dropping observations that are off support usually improves their performance, although the magnitude of the improvement depends on the particular method used.     

Application of a QMRA Framework to Inform Selection of Drinking Water Interventions in the Developing Context

The aim of this study was to develop a modified quantitative microbial risk assessment (QMRA) framework that could be applied as a decision support tool to choose between alternative drinking water interventions in the developing context. The impact of different household water treatment (HWT) interventions on the overall incidence of diarrheal disease and disability adjusted life years (DALYs) was estimated, without relying on source water pathogen concentration as the starting point for the analysis. A framework was developed and a software tool constructed and then implemented for an illustrative case study for Nepal based on published scientific data. Coagulation combined with free chlorine disinfection provided the greatest estimated health gains in the short term; however, when long‐term compliance was incorporated into the calculations, the preferred intervention was porous ceramic filtration. The model demonstrates how the QMRA framework can be used to integrate evidence from different studies to inform management decisions, and in particular to prioritize the next best intervention with respect to estimated reduction in diarrheal incidence. This study only considered HWT interventions; it is recognized that a systematic consideration of sanitation, recreation, and drinking water pathways is important for effective management of waterborne transmission of pathogens, and the approach could be expanded to consider the broader water‐related context.     

Work performance and tax compliance in flat and progressive tax systems

Different tax systems, and their impact on work motivation and tax compliance are significant issues in contemporary political and economic debates. The proportional feature of a flat tax system is assumed to lead to higher performance, while the fairness of the redistributive progressive tax system is assumed to result in higher tax compliance. However, empirical findings on the topic are inconclusive. Both work performance and tax compliance under different tax systems were examined in an experiment, with special attention devoted to the effect of a change in tax systems. A flat tax system was supposed to induce greater work performance, whereas a progressive tax system was expected to increase tax compliance based on fairness perceptions, allowing for the opposite effect due to higher complexity. Furthermore, it was assumed that performance and tax payments would be influenced by motives of self-interest. The design included 20 rounds with a real-effort task in each round, determining participants’ experimental income. Participants (N = 191) made decisions about their tax payments from round-to-round in four different experimental conditions: (1) a flat tax system, (2) a progressive tax system, (3) starting with a flat and changing to a progressive, and (4) starting with a progressive and changing to a flat tax system. Results indicate higher work performance in a progressive system. However, a change from a progressive tax system to a flat system led to increased tax compliance.     

Stakeholder Performance Measurement in Nonprofit Organizations

According to recent findings, nonprofit organizations should address the relationships of nonprofit service quality, satisfaction, loyalty, and organizational identification when planning and evaluating donor surveys. This article presents a donor satisfaction barometer that can be used to gain insights into the strength of these key relationships and thereby establish a basis for calculated relevant indices. With such indices, nonprofit organizations can compare stakeholder performance over time and benchmark themselves against other organizations. Data from 2,599 blood donors to one section of the German Red Cross, collected through the proposed donor satisfaction barometer, show that service quality drives satisfaction, and donor satisfaction and organizational identification both exert significant positive effects on donor loyalty. Therefore, nonprofit organizations should use a combined strategic approach that improves both donor satisfaction and organizational identification to increase donor loyalty. The successful application of the donor satisfaction barometer also suggests its value for other nonprofit industries and offers important insights for managers.