Risk Modeling of Interdependent Complex Systems of Systems: Theory and Practice

The emergence of the complexity characterizing our systems of systems (SoS) requires a reevaluation of the way we model, assess, manage, communicate, and analyze the risk thereto. Current models for risk analysis of emergent complex SoS are insufficient because too often they rely on the same risk functions and models used for single systems. These models commonly fail to incorporate the complexity derived from the networks of interdependencies and interconnectedness (I–I) characterizing SoS. There is a need to reevaluate currently practiced risk analysis to respond to this reality by examining, and thus comprehending, what makes emergent SoS complex. The key to evaluating the risk to SoS lies in understanding the genesis of characterizing I–I of systems manifested through shared states and other essential entities within and among the systems that constitute SoS. The term “essential entities” includes shared decisions, resources, functions, policies, decisionmakers, stakeholders, organizational setups, and others. This undertaking can be accomplished by building on state‐space theory, which is fundamental to systems engineering and process control. This article presents a theoretical and analytical framework for modeling the risk to SoS with two case studies performed with the MITRE Corporation and demonstrates the pivotal contributions made by shared states and other essential entities to modeling and analysis of the risk to complex SoS. A third case study highlights the multifarious representations of SoS, which require harmonizing the risk analysis process currently applied to single systems when applied to complex SoS.     

大众传播中的“国家教师”媒介形象分析

运用传播学内容分析法，以中央媒体对获得"全国教书育人楷模"和"最美教师"荣誉称号的"国家教师"相关报道为研究对象，从外在和内在两个方面对大众传播的"国家教师"媒介形象进行分析。外在形象包括教师性别、年龄、教龄、外表、场景以及任教的学校类别、区域、学科专业等方面，内在形象包括职业精神、职业知识和职业能力等方面。研究发现，大众媒体对"国家教师"形象的刻画和宣传符合社会公众认知教师职业的基本逻辑，起到了传递教师精神、端正教师形象、唤起社会尊重教师的功效，但也存在城乡教师形象传播刻板化以及教师普通人形象展现不充分等问题，可在后续的传播中对"国家教师"形象的价值倾向进行适当调整。     

Decision‐making under uncertainty in child protection: Creating a just and learning culture

The argument is made for having a positive error culture in child protection to improve decision‐making and risk management. This requires organizations to accept that mistakes are likely and to treat them as opportunities for learning and improving. In contrast, in many organizations, a punitive reaction to errors leads to workers hiding them and developing a defensive approach to their practice with children and families. The safety management literature has shown how human error is generally not simply due to a “bad apple” but made more or less likely by the work context that helps or hinders good performance. Improving safety requires learning about the weaknesses in the organization that contribute to poor performance. To create a learning culture, people need to feel that when they talk about mistakes or weak practice, there will be a constructive response from their organization. One aspect of reducing the blame culture is to develop a shared understanding of how practice will be judged and how those appraising practice will avoid the hindsight bias. To facilitate a positive error culture, a set of risk principles are presented that offer a set of criteria by which practice should be appraised.     

Estimating E-bayesian and hierarchical bayesian of scalar parameter of gompertz distribution under type II censoring schemes based on fuzzy data

In this study, the E-Bayesian and hierarchical Bayesian of the scalar parameter of a Gompertz distribution under Type II censoring schemes were estimated based on fuzzy data under the squared error (SE) loss function and the efficiency of the proposed methods was compared with each other and with the Bayesian estimator using Monte Carlo simulation.     

Conditional time-dependent nonparametric estimators with an application to healthcare production function

ABSTRACT

By using the probabilistic framework of production efficiency, the paper develops time-dependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.     

Heteroscedastic Global Tests that the Regression Parameters for Two or More Independent Groups are Identical

Simulation results are reported on methods that allow both within group and between group heteroscedasticity when testing the hypothesis that independent groups have identical regression parameters. The methods are based on a combination of extant techniques, but their finite-sample properties have not been studied. Included are results on the impact of removing all leverage points or just bad leverage points. The method used to identify leverage points can be important and can improve control over the Type I error probability. Results are illustrated using data from the Well Elderly II study.     

不同冷链服务模式下生鲜农产品供应链决策

基于单物流服务商、单供应商和单零售商构成的生鲜农产品供应链，构建3种冷链服务模式：承诺模式、提前要求模式与延后要求模式，探讨不同冷链服务模式对定价与冷链服务水平、企业绩效的影响。研究发现：某种冷链服务模式是否有利于消减数量与质量损耗依赖于产品易腐性、冷链服务成本及其分担比例。供应链成员无法在承诺模式与提前要求模式下形成统一的模式偏好。当物流服务商承担的冷链服务成本比例较低时，相比于提前要求模式，供应商偏好承诺模式，否则，偏好提前要求模式。承诺模式比提前要求模式更有利于物流服务商，然而对于零售商，结果正好相反。数值实验表明，虽然供应链成员无法对冷链服务模式形成整体的一致性偏好，但仍可实现局部的一致性偏好。     

Developing ethical approaches to data and civil society: from availability to accessibility

This research note reflects on the gaps and limitations confronting the development of ethical principles regarding the accessibility of large-scale data for civil society organizations (CSOs). Drawing upon a systematic scoping study on the use of data in the United Kingdom (UK) civil society, it finds that there are twin needs to conceptualize accessibility as more than mere availability of data, as well as examine the use of data among CSOs more generally. In order to deal with the apparent “digital divide” in UK civil society – where, despite extensive government rhetoric about data openness, organizations face not only the barriers of limited time, funds, and expertise to harness data but also the lack of representation within existing data – we present a working model in which ethical concerns accompanying data utilization by civil society may be better accounted. This suggests there is a need for further research into the nexus of civil society and data upon which interdisciplinary discussion about the ethical dimensions of engagement with data, particularly informed by insight from the social sciences, can be predicated.     

The 2015 welfare reform of the National Basic Livelihood Security System in South Korea: Effects on economic outcomes

In July 2015, South Korea’s National Basic Livelihood Security System (NBLSS) was reformed for the purposes of eliminating welfare blind spots and reducing poverty. The reform is expected to affect the recipients’ economic behaviours and choices. In this study, we used changes in benefits and eligibility for the NBLSS under the customised benefit system to identify the effects of the change in the NBLSS on a proposed set of economic outcomes – income, labour supply, consumption, savings, poverty reduction. To estimate the effects, we used data from the 10th–12th waves of the Korea Welfare Panel Study and employed a difference‐in‐differences framework integrated with the propensity scores. We found that the NBLSS helps the poor to reduce financial and material hardships through income and consumption increments, but that it does not provide disincentives to the recipients from participating in the labour market or from saving.     

大数据背景下基于社交网络的聚类随机游走抽样算法研究

数字经济时代,社交网络作为数字化平台经济的重要载体,受到了国内外学者的广泛关注。大数据背景下,社交网络的商业应用价值巨大,但由于其网络规模空前庞大,传统的网络分析方法 因计算成本过高而不再适用。而通过网络抽样算法获取样本网络,再推断整体网络,可节约计算资源, 因此抽样算法的好坏将直接影响社交网络分析结论的准确性。现有社交网络抽样算法存在忽略网络内部拓扑结构、容易陷入局部网络、抽样效率过低等缺陷。为了弥补现有社交网络抽样算法的缺陷,本文结合大数据社交网络的社区特征,提出了一种聚类随机游走抽样算法。该方法首先使用社区聚类算法将原始网络节点进行社区划分,得到多个社区网络,然后分别对每个社区进行随机游走抽样获取样本网 络。数值模拟和案例应用的结果均表明,聚类随机游走抽样算法克服了传统网络抽样算法的缺点,能够在降低网络规模的同时较好地保留原始网络的结构特征。此外,该抽样算法还可以并行运算,有效提升抽样效率,对于大数据背景下大规模社交网络的抽样实践具有重大现实意义。