Estimation of Deprivation Level Functions using a Numerical Rating Scale

Evaluating and quantifying human suffering in humanitarian operations offers an innovative and potentially powerful way to assess the performance of humanitarian logistics (HL) and help build optimization models. Previous studies have suggested deprivation cost as a metric and have estimated deprivation cost functions for water using willingness‐to‐pay. Our study proposes deprivation levels, defined as the degree of human suffering caused by lack of access to a good or service, and estimates deprivation level functions using a numerical rating scale. Analyzing data collected from respondents with and without disaster experience, we find that individuals in the latter category estimate deprivation differently from the beneficiaries of disaster relief. Our study demonstrates that deprivation levels can be expressed as logistic growth functions with a typical S‐shape, and that these can be integrated into HL optimization models to better account for human suffering.     

Critical Infrastructure Vulnerability to Spatially Localized Failures with Applications to Chinese Railway System

This article studies a general type of initiating events in critical infrastructures, called spatially localized failures (SLFs), which are defined as the failure of a set of infrastructure components distributed in a spatially localized area due to damage sustained, while other components outside the area do not directly fail. These failures can be regarded as a special type of intentional attack, such as bomb or explosive assault, or a generalized modeling of the impact of localized natural hazards on large‐scale systems. This article introduces three SLFs models: node centered SLFs, district‐based SLFs, and circle‐shaped SLFs, and proposes a SLFs‐induced vulnerability analysis method from three aspects: identification of critical locations, comparisons of infrastructure vulnerability to random failures, topologically localized failures and SLFs, and quantification of infrastructure information value. The proposed SLFs‐induced vulnerability analysis method is finally applied to the Chinese railway system and can be also easily adapted to analyze other critical infrastructures for valuable protection suggestions.     

系统症结辨识的模糊分析与应用

本文基于模糊因果网络分析,提出了系统症结辨识的一种新思路,实例研究了吉林省轻工业发展现状的主要症结所在．     

项目风险分析与管理

本文在分析比较传统风险分析方法的基础上,提出了一个更为有效的风险分析方法,即“交叉分析-蒙特卡罗模拟”综合模型。并利用此模型对H集团的某技改投资项目进行了案例分析。在此基础上,提出了建立项目风险防范预警系统的风险管理模式。     

Bootstrap Estimation of Benchmark Doses and Confidence Limits with Clustered Quantal Data

The benchmark dose (BMD) is an exposure level that would induce a small risk increase (BMR level) above the background. The BMD approach to deriving a reference dose for risk assessment of noncancer effects is advantageous in that the estimate of BMD is not restricted to experimental doses and utilizes most available dose-response information. To quantify statistical uncertainty of a BMD estimate, we often calculate and report its lower confidence limit (i.e., BMDL), and may even consider it as a more conservative alternative to BMD itself. Computation of BMDL may involve normal confidence limits to BMD in conjunction with the delta method. Therefore, factors, such as small sample size and nonlinearity in model parameters, can affect the performance of the delta method BMDL, and alternative methods are useful. In this article, we propose a bootstrap method to estimate BMDL utilizing a scheme that consists of a resampling of residuals after model fitting and a one-step formula for parameter estimation. We illustrate the method with clustered binary data from developmental toxicity experiments. Our analysis shows that with moderately elevated dose-response data, the distribution of BMD estimator tends to be left-skewed and bootstrap BMDL s are smaller than the delta method BMDL s on average, hence quantifying risk more conservatively. Statistically, the bootstrap BMDL quantifies the uncertainty of the true BMD more honestly than the delta method BMDL as its coverage probability is closer to the nominal level than that of delta method BMDL. We find that BMD and BMDL estimates are generally insensitive to model choices provided that the models fit the data comparably well near the region of BMD. Our analysis also suggests that, in the presence of a significant and moderately strong dose-response relationship, the developmental toxicity experiments under the standard protocol support dose-response assessment at 5% BMR for BMD and 95% confidence level for BMDL.     

Assessing the cumulative effects of stress: The association between job stress and allostatic load in a large sample of Chinese employees

Job stress can lead to various system dysfunctions, but until now no reliable biomarkers for its assessment have been identified. Allostatic load (AL) is an index that enables the cumulative effect on the body of chronic stress to be assessed, and is derived from a set of relevant biological measures. In this study, a 13-parameter index (building on the original 10-item index) was used to examine the relationship between job strain and AL. Participants were 1219 healthy Chinese employees. Job strain was measured using the Job Content Questionnaire, and AL was assessed by various possible stress responses, including blood pressure, cholesterol, indicators of glucose metabolism, and hormone and inflammation markers. AL in the high job strain group differed sharply from that in the low job strain group. The AL score was positively associated with age and educational level. Several individual parameters also differed between the two groups. Men scored significantly higher on AL and cardiovascular and metabolic health outcomes, whereas for women the associations appeared in the biological indicators. Analyses indicated that decision latitude (DL) and job demands were significantly related to AL. Job demands correlated significantly with the primary biological indicators and DL with the secondary health outcomes. In conclusion, this study provides evidence of the value of measuring allostatic load in assessing the chronic effects of job stress.     

消费者持续满意度研究——基于快乐适应视角

从动态视角研究消费者满意是营销学研究的前沿问题.本文从快乐适应角度考察消费者如何在消费决策过程中获得持续的满意.问卷调查研究发现,尽管不同产品的满意度会随时间的延续下降,但剔除价格变动因素后,由于互动性产品给消费者带来的快乐更不易适应,满意度并未随时间发生明显改变;情感性产品给消费者带来满意容易适应,满意度随时间的推移明显下降;实用性产品并未给消费者带来明显的情感刺激,因此,消费者对这类产品的满意度相对比较稳定.根据快乐适应理论,商品的互动性带来的消费的不易适应性是影响持续满意度的主要因素.本研究的结论为消费者、厂商、政府部门在购买商品、生产产品和制定政策等方面提供建议.     

临床医学学科带头人胜任特征模型建构——量化与质化结合的方法

胜任特征模型研究是人力资源管理理论和实践的前沿问题,然而目前研究多采用单一的方法。本研究首先使用O*NET问卷对494位医院工作人员进行工作分析,然后对20位学科带头人进行行为事件访谈,结合进行专家小组访谈,构建临床医学学科带头人的胜任特征模型。研究发现多方法构建模型具有较好的效果。该职位胜任特征模型包括18项特征,可以分为个性特征,认知技能,管理能力三个理论层次。此外,本研究发现了个性化关怀等三项较新的素质要求。     

探析江苏经济发展变化的源泉:基于SDA的分析

本文采用结构分解分析SDA模型对1990-2005年江苏省经济发展变化的源泉进行了实证研究。主要结论:第一,江苏经济增长长期主要靠消费拉动,中期则更多地依赖投资驱动;第二,技术变化长期对降低三次产业中间消耗需求发挥了显著作用,但中期对第一、第二产业的影响不大;第三,技术进步改善了对绝大多数行业的中间消耗,尤其是对采掘业和资本密集型制造业;第四,消费对现代服务业的促进作用较大,而资本形成对采掘业及部分资本密集型、技术知识密集型行业影响较大;第五,煤炭采选业、电力等行业总产出的变化受制于省际间净调出变化,而服装皮革及其他纤维制品制造业受净出口增加的影响,充分反映出江苏资源、市场两头在外的经济结构特征。     

面向我国国立研究机构的人力资源配置模型研究

当今世界,科学技术作为第一生产力的作用日益突出,科学技术作为人类文明进步的基石和原动力的作用日益凸显,而国立研究机构作为中国科研体系的国家队和中坚力量,它的地位和规模在整个科研体系中是举足轻重的,因此合理配置国立研究机构的人力资源具有重大的理论和现实意义。目前的人力资源配置研究多针对企业,而中国的国立研究机构有其自身的特点,不能套用企业的人力资源配置方法。中国科学院作为国家在科学技术方面的最高学术机构,作为科技事业的国家队和火车头,具有代表性,因此本文以中国科学院为例,利用问卷调查、专家访谈、文献调研等方法,对影响我国国立研究机构人力资源配置的因素进行研究,并将人力资源的配置看作一个决策问题,综合考虑了发展战略、人均经费当量、人员结构、学科建设等多个约束,采用自上而下和自下而上相结合的方法,建立了面向国立研究机构的人力资源配置模型。该模型克服了以往国立研究机构对子机构人员数量通过简单趋势外推等方法进行预测的做法,集成了历史数据和专家经验,既不脱离历史情况又能够反映机构的发展战略,是一种适合国立研究机构的人力资源配置方法。该方法在中国科学院的应用实践,验证了模型的有效性。