管理者在校园风险管理中的职责和应掌握的策略

本文以风险管理中最为集中的教育行业为研究对象,对校园风险管理中的管理者应该具备和应掌握的策略进行剖析。     

风险社会与媒介表征

风险社会的形成与大众媒介表征密不可分:大众媒介通过拟态环境的构建,形成了公众的风险感知,促成了风险传播的蝴蝶效应.在此基础上,探讨媒介形成社会风险的三方面成因:价值层面上,媒介的社会整合功能不足,价值培养欠缺;制度层面上,公益节目欠缺,政府信息制度贯彻不力;内容层面上:网络媒介的风险长尾效应日渐突出.     

论中国转型期社会风险与政府治理

当前,中国社会正处于巨大的社会转型之中,体制转轨与结构转型加剧了社会风险的程度,严重影响了社会的正常运行和健康发展。同时,转型期的社会风险呈现出一系列新的特征,政府应从转变职能、扩大公众参与、建立信息机制、增强全民风险意识、健全风险管理制度、加强国际合作等方面提高风险治理能力,从而全面增强抵御风险的能力,促进和谐社会的构建。     

基于经济资本管理的贷款定价方法

阐述中国商业银行经济资本管理现状,基于经济资本管理,提出贷款定价模型假设,设计贷款定价模型框架,并提出该产品应用的意义和远景展望。     

“风险社会”理论视角下城市基本公共服务供给机制研究——以厦门市为例

在风险社会的时代背景下,加强城市基本公共服务供给,保障基本公共服务供给效果,不仅能够预防各种风险的发生,也能在风险发生后将危害降至最低程度。同时,通过风险社会的视阀来研究城市基本公共服务供给机制问题,也有助于深化基本公共服务供给的研究,推进服务型政府建设。在总结、借鉴前人研究成果的基础上,结合风险社会理论,重新构建城市基本公共服务供给机制,进行相关制度设计,具有方法论的创新意义。     

公办高校债务危机的治理研究

化解公办高校债务风险问题迫在眉睫,为此论证了公办高校破产清算的可能性,在识别高校债务偿还主体的基础上,厘清了高校偿债资金的来源,总结了缓解公办高校债务危机的短期方法,并提出治理高校债务危机的长效机制.     

中国企业海外资源并购中歧视性干预风险及其规避

无论是从国家利益还是企业发展的层面看,中国企业海外资源并购都是具有长远意义的战略选择.由于资源行业属于事关国计民生的战略性行业,无论是政府还是民众对于境外投资者始终带有一定的警惕性,因此,政治风险中的歧视性干预风险是中国企业海外资源并购过程中面临的最大、最不可预期的风险.中国企业应采取谋略巧妙地规避海外资源并购中歧视性干预风险,以使中国企业的海外资源并购之路走得更加稳健和踏实.     

Attenuating Initial Beliefs: Increasing the Acceptance of Anthropogenic Climate Change Information by Reflecting on Values

Anthropogenic climate change information tends to be interpreted against the backdrop of initial environmental beliefs, which can lead to some people being resistant toward the information. In this article (N = 88), we examined whether self‐affirmation via reflection on personally important values could attenuate the impact of initial beliefs on the acceptance of anthropogenic climate change evidence. Our findings showed that initial beliefs about the human impact on ecological stability influenced the acceptance of information only among nonaffirmed participants. Self‐affirmed participants who were initially resistant toward the information showed stronger beliefs in the existence of climate change risks and greater acknowledgment that individual efficacy has a role to play in reducing climate change risks than did their nonaffirmed counterparts.     

Analysis of Regional Scale Risk of Whirling Disease in Populations of Colorado and Rio Grande Cutthroat Trout Using a Bayesian Belief Network Model

Introduction and spread of the parasite Myxobolus cerebralis, the causative agent of whirling disease, has contributed to the collapse of wild trout populations throughout the intermountain west. Of concern is the risk the disease may have on conservation and recovery of native cutthroat trout. We employed a Bayesian belief network to assess probability of whirling disease in Colorado River and Rio Grande cutthroat trout (Oncorhynchus clarkii pleuriticus and Oncorhynchus clarkii virginalis, respectively) within their current ranges in the southwest United States. Available habitat (as defined by gradient and elevation) for intermediate oligochaete worm host, Tubifex tubifex, exerted the greatest influence on the likelihood of infection, yet prevalence of stream barriers also affected the risk outcome. Management areas that had the highest likelihood of infected Colorado River cutthroat trout were in the eastern portion of their range, although the probability of infection was highest for populations in the southern, San Juan subbasin. Rio Grande cutthroat trout had a relatively low likelihood of infection, with populations in the southernmost Pecos management area predicted to be at greatest risk. The Bayesian risk assessment model predicted the likelihood of whirling disease infection from its principal transmission vector, fish movement, and suggested that barriers may be effective in reducing risk of exposure to native trout populations. Data gaps, especially with regard to location of spawning, highlighted the importance in developing monitoring plans that support future risk assessments and adaptive management for subspecies of cutthroat trout.     

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.