Health-Based Screening Levels to Evaluate U.S. Geological Survey Ground water Quality Data

Federal and state drinking-water standards and guidelines do not exist for many contaminants analyzed by the U.S. Geological Survey's National Water-Quality Assessment Program, limiting the ability to evaluate the potential human-health relevance of water-quality findings. Health-based screening levels (HBSLs) were developed collaboratively to supplement existing drinking-water standards and guidelines as part of a six-year, multi-agency pilot study. The pilot study focused on ground water samples collected prior to treatment or blending in areas of New Jersey where groundwater is the principal source of drinking water. This article describes how HBSLs were developed and demonstrates the use of HBSLs as a tool for evaluating water-quality data in a human-health context. HBSLs were calculated using standard U.S. Environmental Protection Agency (USEPA) methodologies and toxicity information. New HBSLs were calculated for 12 of 32 contaminants without existing USEPA drinking-water standards or guidelines, increasing the number of unregulated contaminants (those without maximum contaminant levels (MCLs)) with human-health benchmarks. Concentrations of 70 of the 78 detected contaminants with human-health benchmarks were less than MCLs or HBSLs, including all 12 contaminants with new HBSLs, suggesting that most contaminant concentrations were not of potential human-health concern. HBSLs were applied to a state-scale groundwater data set in this study, but HBSLs also may be applied to regional and national evaluations of water-quality data. HBSLs fulfill a critical need for federal, state, and local agencies, water utilities, and others who seek tools for evaluating the occurrence of contaminants without drinking-water standards or guidelines.     

《萨班斯法案》对美国公司董事会影响的分析

2002年度美国出台的《萨班斯法案》全方位地对安然等事件暴露出来的问题作出相应的调整性规定,必将对公司治理产生深切的影响。《萨班斯法案》对审计委员会提出了修正性和提高性要求,本文选择外部董事、女性董事、财务专家、CEO兼任董事会主席、CEO在提名委员会任职等指标进行分析。实证分析结果说明:《萨班斯法案》有效消除了董事会和管理层任人唯亲的现象,董事会的独立性和专业性均有所提高。其实,《萨班斯法案》颁布之前就有加强公司治理的要求,公司治理就有改进的趋势,但《萨班斯法案》关于审计委员会方面的明文规定加速了公司董事会的变化,使得公司治理改革超越了法律的既定要求。     

An empirical analysis of innovation strategies of biotechnology firms in the U.S.

The paper explores the strategies of biotechnology firms in the U.S. through a mail questionnaire study. Based on the responses of 89 companies we have developed strategy archetypes of these firms in R&D, marketing, and technology acquisition. In R&D, we found the firms to follow either incremental or radical strategy. In marketing, the firms use either a defender or an innovator strategy. In technology acquisition, firms differ in terms of their emphasis on licensing or developing new technology. The interrelationship among the strategy groups is weak. The R&D and technology acquisition strategies are related in the sense that aggressive technology strategy dictates radical R&D behavior with emphasis on development of new technology. We have found that firms following aggressive technology strategy tend to follow conservative marketing strategy. This is consistent with an earlier study by of German firms where it was found that firms tend to balance their technical and marketing risks. The paper also provides additional information about the factors considered to be important in product decisions for various strategies.     

次贷危机前后国际原油市场与中美股票市场间的协动性研究

本文运用基于动态条件相关的多元GARCH(DCC-MVGARCH)模型,对美国次信贷危机发生前后国际原油市场和中、美股票市场间的协动性变化进行了研究。实证结果表明在次信贷危机发生后,国际原油市场与中、美股票市场间的协动性有了明显的增强,不同市场间的波动具有明显的传导作用。国际原油市场与美国股市的协动性相对于中国股市波动性更强,说明冲击在国际原油市场与美国股市间的传导更强烈,其协动性对冲击的反应更敏感。另外,运用偏最小二乘方法(PLS)对影响国际原油市场和中、美股票市场的诸多因素在次信贷危机爆发前后对协动性解释能力的变化进行了分析,结果发现次信贷危机对这些因素的解释能力有明显的影响。     

An Empirical Model of Perceived Mortality Risks for Selected U.S. Arsenic Hot Spots

Researchers have long recognized that subjective perceptions of risk are better predictors of choices over risky outcomes than science‐based or experts’ assessments of risk. More recent work suggests that uncertainty about risks also plays a role in predicting choices and behavior. In this article, we develop and estimate a formal model for an individual's perceived health risks associated with arsenic contamination of his or her drinking water. The modeling approach treats risk as a random variable, with an estimable probability distribution whose variance reflects uncertainty. The model we estimate uses data collected from a survey given to a sample of people living in arsenic‐prone areas in the United States. The findings from this article support the fact that scientific information is essential to explaining the mortality rate perceived by the individuals, but uncertainty about the probability remains significant.     

The Impact of Contract Manufacturing on Inventory Performance: An Examination of U.S. Manufacturing Industries

In recent years, a growing number of original equipment manufacturers (OEMs) have transferred their manufacturing processes to specialized firms, known as contract manufacturers. In so doing, contract manufacturers can reduce an OEM's production costs and provide OEMs with flexibility in the production process. We examine another potential reason for the use of contract manufacturing—the potential for efficiency gains from inventory reductions. Employing econometric models and data representing manufacturing industries in the USA, we provide statistical evidence that contract manufacturing can lead to lower industry‐wide inventory levels, after controlling for other relevant factors. Key managerial implications are derived from the analysis.     

Returns to scale vs. damages to scale in data envelopment analysis: An impact of U.S. clean air act on coal-fired power plants

This study proposes a use of Data Envelopment Analysis (DEA) to measure Returns to Scale (RTS) of US coal-fired power plants. The power plants produce not only desirable outputs (e.g., electricity) but also undesirable outputs (e.g., CO₂ and NO_x) as a result of their plant operations. Therefore, the proposed use of DEA also measures a new concept, or “DTS: Damages to Scale” (corresponding to RTS for undesirable outputs). Both scale measures discussed in this study are a quick-and-easy approach for assessing RTS and DTS, but not an exact method, because it does not consider a direct linkage between the two measures. This study applies the proposed approach to examine the legal validity of U.S. Clean Air Act (CAA). We find that the CAA has been legally effective and influential on the operation of coal-fired power plants in the United States because their plant operations belong to increasing RTS on a desirable output and increasing DTS on three undesirable outputs. The increasing DTS indicates a need for managerial improvement and/or engineering innovation such as advanced clean coal technology. This empirical result implies that U.S. federal and state governments need to expand the legal scope of CAA to the emission control of CO₂ because the current CAA excludes the regulation on CO₂ emission that is now considered as a main source of the global warming and climate change.     

Performance Impacts of Strategy,Information Technology Applications,and Business Process Outsourcing in U.S. Manufacturing Plants

This paper develops a conceptual model to study the role of outsourcing strategies and plant‐level information technology (IT) application infrastructure in the outsourcing of production and support business processes, as well as their subsequent impact on overall plant performance. We validate this model empirically using cross‐sectional survey data from U.S. manufacturing plants. We find that some IT applications are more effective at enabling the outsourcing of business processes than others. For example, the implementation of enterprise management systems is associated with the outsourcing of both production and support processes, whereas operations management systems are not associated with the outsourcing of plant processes. Plants with a low‐cost outsourcing strategy are more likely to outsource support processes than plants with a competency‐focused outsourcing strategy. However, both cost‐ and competency‐based strategies have a positive and similar impact on the outsourcing of production processes. In terms of implications for plant performance, our findings indicate that the outsourcing of production and support processes is associated with higher gross margins. Although plant IT infrastructure is positively associated with favorable on‐time delivery rates, there is no positive association between the incidence of plant outsourcing and on‐time delivery rates. These results have implications for crafting plant‐level outsourcing strategies and for investments in IT systems to facilitate the outsourcing of business processes for enhanced plant performance.     

Critical Radionuclide/Critical Pathway Analysis for the U.S. Department of Energy's Savannah River Site

Many different radionuclides have been released to the environment from the Savannah River Site (SRS) during the facility's operational history. However, as shown by this analysis, only a small number of the released radionuclides have been significant contributors to potential doses and risks to off-site people. This article documents the radiological critical contaminant/critical pathway analysis performed for SRS. If site missions and operations remain constant over the next 30 years, only tritium oxide releases are projected to exceed a maximally exposed individual (MEI) risk of 1.0E-06 for either the airborne or liquid pathways. The critical exposure pathways associated with site airborne releases are inhalation and vegetation consumption, whereas the critical exposure pathways associated with liquid releases are drinking water and fish consumption. For the SRS-specific, nontypical exposure pathways (i.e., recreational fishing and deer and hog hunting), cesium-137 is the critical radionuclide.     

A Comparative Analysis of Quality Practice in Manufacturing Firms in the U.S. and Taiwan*

The aim of this paper is to determine if there is a causal relationship between multivariate constructs for quality (i.e., customer satisfaction, employee satisfaction, and employee service quality) and organizational performance. The presence of such relationships, as well as the identification of key indicators within each quality construct for different types of firms, are explored in this empirical study on the perceptions of middle managers in Taiwan and the United States. The study found a significant causal relationship between the quality constructs and organizational performance. These relationships are different, however, for the four types of firms based on age and size. Also, within the same firm types, there are differences among countries. For example, for older firms, Taiwanese managers tend to perceive customer satisfaction as the most important quality construct in improving organizational performance, while U.S. managers tend to perceive employee satisfaction as the most important. For younger firms, U.S. managers perceive customer satisfaction as influencing organizational performance, while Taiwanese managers perceive both customer satisfaction and employee satisfaction as doing so. A further breakdown of the quality constructs identified the key indicators within each construct that separates “better performers'’from “lesser performers'’in both countries for the four types of firms. These indicators are dissimilar, thus suggesting that focus on quality constructs may lead to improvements in organizational performance by focusing on different indicators in different environments. These results have implications for the adoption and implementation of quality practices in different countries.     

Multi-Stage Model Estimates of Lung Cancer Risk from Exposure to Diesel Exhaust, Based on a U.S. Railroad Worker Cohort

A California Environmental Protection Agency (Cal/EPA) report concluded that a reasonable and likely explanation for the increased lung cancer rates in numerous epidemiological studies is a causal association between diesel exhaust exposure and lung cancer. A version of the present analysis, based on a retrospective study of a U.S. railroad worker cohort, provided the Cal/EPA report with some of its estimates of lung cancer risk associated with diesel exhaust. The individual data for that cohort study furnish information on age, employment, and mortality for 56,000 workers over 22 years. Related studies provide information on exposure concentrations. Other analyses of the original cohort data reported finding no relation between measures of diesel exhaust and lung cancer mortality, while a Health Effects Institute report found the data unsuitable for quantitative risk assessment. None of those three works used multistage models, which this article uses in finding a likely quantitative, positive relations between lung cancer and diesel exhaust. A seven-stage model that has the last or next-to-last stage sensitive to diesel exhaust provides best estimates of increase in annual mortality rate due to each unit of concentration, for bracketing assumptions on exposure. Using relative increases of risk and multiplying by the background lung cancer mortality rates for California, the 95% upper confidence limit of the 70-year unit risks for lung cancer is estimated to be in the range 2.1 x 10(-4) (microg/m3)(-1) to 5.5 x 10(-4) (microg/m3)(-1). These risks constitute the low end of those in the Cal/EPA report and are below those reported by previous investigators whose estimates were positive using human data.     

The Impact of Mega‐Catastrophes on Insurers: An Exposure‐Based Analysis of the U.S. Homeowners’ Insurance Market

Insurance is a key risk‐sharing mechanism that protects citizens and governments from the losses caused by natural catastrophes. Given the increase in the frequency and intensity of natural catastrophes over recent years, this article analyzes the performance effects of mega‐catastrophes for U.S. insurance firms using a measure of market expectations. Specifically, we analyze the share price losses of insurance firms in response to catastrophe events to ascertain whether mega‐catastrophes significantly damage the performance of insurers and whether different types of mega‐catastrophes have different impacts. The main message from our analysis is that the impact of mega‐catastrophes on insurers has not been too damaging. While the exact impact of catastrophes depends on the nature of the event and the degree of competition within the relevant insurance market (less competition allows insurers to recoup catastrophe losses through adjustments to premiums), our overall results suggest that U.S. insurance firms can adequately manage the risks and costs of mega‐catastrophes. From a public policy perspective, our results show that insurance provides a robust means of sharing catastrophe losses to help reduce the financial consequences of a catastrophe event.     

Evaluation of Two Approaches to Defining Extinction Risk under the U.S. Endangered Species Act

The predominant definition of extinction risk in conservation biology involves evaluating the cumulative distribution function (CDF) of extinction time at a particular point (the “time horizon”). Using the principles of decision theory, this article develops an alternative definition of extinction risk as the expected loss (EL) to society resulting from eventual extinction of a species. Distinct roles are identified for time preference and risk aversion. Ranges of tentative values for the parameters of the two approaches are proposed, and the performances of the two approaches are compared and contrasted for a small set of real‐world species with published extinction time distributions and a large set of hypothetical extinction time distributions. Potential issues with each approach are evaluated, and the EL approach is recommended as the better of the two. The CDF approach suffers from the fact that extinctions that occur at any time before the specified time horizon are weighted equally, while extinctions that occur beyond the specified time horizon receive no weight at all. It also suffers from the fact that the time horizon does not correspond to any natural phenomenon, and so is impossible to specify nonarbitrarily; yet the results can depend critically on the specified value. In contrast, the EL approach has the advantage of weighting extinction time continuously, with no artificial time horizon, and the parameters of the approach (the rates of time preference and risk aversion) do correspond to natural phenomena, and so can be specified nonarbitrarily.     

The Impact of Process Variation on Customer Dissatisfaction: Evidence from the U.S. Domestic Airline Industry

This paper investigates how process variation reduction affects customer dissatisfaction in the context of the U.S. domestic airline industry. We use quarterly data on all major carriers, available since the introduction of required reporting of service indicators to the U.S. Department of Transportation (DOT). Specifically, we investigate how both average performance and variation performance (consistency) of certain processes affect customer dissatisfaction. Our empirical results show that the relationship between process variation and customer dissatisfaction is contingent upon a company's average performance with regard to each process. Consistency is at least as important as average performance for high performers, while it has limited impact for low performers.     

Use of Markov Chain Monte Carlo Analysis with a Physiologically-Based Pharmacokinetic Model of Methylmercury to Estimate Exposures in U.S. Women of Childbearing Age

A Bayesian approach, implemented using Markov Chain Monte Carlo (MCMC) analysis, was applied with a physiologically‐based pharmacokinetic (PBPK) model of methylmercury (MeHg) to evaluate the variability of MeHg exposure in women of childbearing age in the U.S. population. The analysis made use of the newly available National Health and Nutrition Survey (NHANES) blood and hair mercury concentration data for women of age 16–49 years (sample size, 1,582). Bayesian analysis was performed to estimate the population variability in MeHg exposure (daily ingestion rate) implied by the variation in blood and hair concentrations of mercury in the NHANES database. The measured variability in the NHANES blood and hair data represents the result of a process that includes interindividual variation in exposure to MeHg and interindividual variation in the pharmacokinetics (distribution, clearance) of MeHg. The PBPK model includes a number of pharmacokinetic parameters (e.g., tissue volumes, partition coefficients, rate constants for metabolism and elimination) that can vary from individual to individual within the subpopulation of interest. Using MCMC analysis, it was possible to combine prior distributions of the PBPK model parameters with the NHANES blood and hair data, as well as with kinetic data from controlled human exposures to MeHg, to derive posterior distributions that refine the estimates of both the population exposure distribution and the pharmacokinetic parameters. In general, based on the populations surveyed by NHANES, the results of the MCMC analysis indicate that a small fraction, less than 1%, of the U.S. population of women of childbearing age may have mercury exposures greater than the EPA RfD for MeHg of 0.1 μg/kgg/day, and that there are few, if any, exposures greater than the ATSDR MRL of 0.3 μgg/kgg/day. The analysis also indicates that typical exposures may be greater than previously estimated from food consumption surveys, but that the variability in exposure within the population of U.S. women of childbearing age may be less than previously assumed.     

A Risk Analysis Framework for Cyber Security and Critical Infrastructure Protection of the U.S. Electric Power Grid

The purpose of this article is to introduce a risk analysis framework to enhance the cyber security of and to protect the critical infrastructure of the electric power grid of the United States. Building on the fundamental questions of risk assessment and management, this framework aims to advance the current risk analysis discussions pertaining to the electric power grid. Most of the previous risk-related studies on the electric power grid focus mainly on the recovery of the network from hurricanes and other natural disasters. In contrast, a disproportionately small number of studies explicitly investigate the vulnerability of the electric power grid to cyber-attack scenarios, and how they could be prevented or mitigated. Such a limited approach leaves the United States vulnerable to foreign and domestic threats (both state-sponsored and “lone wolf”) to infiltrate a network that lacks a comprehensive security environment or coordinated government response. By conducting a review of the literature and presenting a risk-based framework, this article underscores the need for a coordinated U.S. cyber security effort toward formulating strategies and responses conducive to protecting the nation against attacks on the electric power grid.     

Modeling Phytosanitary Risk of Unintended Commodity Use: The Example of U.S. Potato Exports to Mexico

Diversion of commodities from their intended use to an unintended use, e.g., when commodities intended for consumption are used as seed for planting, is an important issue in agricultural trade that has implications for the establishment of pests and pathogens in an importing country and for the appropriate strength of plant health measures. Consequently, understanding and accurately characterizing the risk of diversion from intended use is highly relevant to policymakers, trading partners, and in trade dispute arbitration. To our knowledge, no risk assessments have ever accounted for the likelihood of diversion from intended use. Here we present an approach to analyzing this risk using diversion of U.S. table stock potatoes to seed for planting by Mexican potato producers as a case study. We use probabilistic pathway models to characterize the movement of white, yellow, and russet potatoes from the United States into Mexico at current and double export volumes. We then model the likelihood of these potatoes being diverted for seed and the subsequent establishment of bacteria, nematode, and virus pests in Mexico. Our approach demonstrates how diversion from intended use can be quantified in one scenario and, in particular, how it can be analyzed to estimate the magnitude of diversion required to produce a high risk of pest establishment.     

Disease Spread Models to Estimate Highly Uncertain Emerging Diseases Losses for Animal Agriculture Insurance Policies: An Application to the U.S. Farm‐Raised Catfish Industry

Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm‐raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease‐impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm‐level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks.     

Treating and Drinking Well Water in the Presence of Health Risks from Arsenic Contamination: Results from a U.S. Hot Spot

The Safe Drinking Water Act of 1974 regulates water quality in public drinking water supply systems but does not pertain to private domestic wells, often found in rural areas throughout the country. The recent decision to tighten the drinking water standard for arsenic from 50 parts per billion (ppb) to 10 ppb may therefore affect some households in rural communities, but may not directly reduce health risks for those on private wells. The article reports results from a survey conducted in a U.S. arsenic hot spot, the rural area of Churchill County, Nevada. This area has elevated levels of arsenic in groundwater. We find that a significant proportion of households on private wells are consuming drinking water with arsenic levels that pose a health risk. The decision to treat tap water for those on private wells in this area is modeled, and the predicted probability of treatment is used to help explain drinking water consumption. This probability represents behaviors relating to the household's perception of risk.     

Bringing Japanese Continuous Improvement Approaches to U.S. Manufacturing: The Roles of Process Orientation and Communications*

Continuous improvement (CI) has played a key role in Japan's quality management. U.S. companies have begun to adopt CI in recent years. This paper studies the implementation of CI in seven U.S. manufacturing companies. We view values as the core concept of culture that impacts CI effectiveness. Using both qualitative and quantitative data with a sample of seven companies, we observe empirically a relationship between process-oriented values and CI effectiveness. We also find that communications involving workers is strongly associated with CI effectiveness. Finally, we find an association between process orientation and communication frequency, and argue that communications act as an intervening variable between process orientation and effectiveness.