萨缪尔森的《经济分析基础》与现代西方经济学的数学化

本文对美国著名经济学家、美国第一个诺贝尔经济学奖获得者保罗·A·萨缪尔森的代表作《经济分析基础》的主要内容作了系统的概括性分析,并在此基础上,对萨缪尔森的理论和分析方法及其对现代西方经济学的影响作了客观的的评价。     

An approximation algorithm for the <Emphasis Type="Italic">k</Emphasis>-level capacitated facility location problem

We consider the k-level capacitated facility location problem (k-CFLP), which is a natural variant of the classical facility location problem and has applications in supply chain management. We obtain the first (combinatorial) approximation algorithm with a performance factor of \(k+2+\sqrt{k^{2}+2k+5}+\varepsilon\) (ε>0) for this problem.     

Maximizing Business Returns to Corporate Social Responsibility (CSR): The Role of CSR Communication

By engaging in corporate social responsibility (CSR) activities, companies can not only generate favorable stakeholder attitudes and better support behaviors (e.g. purchase, seeking employment, investing in the company), but also, over the long run, build corporate image, strengthen stakeholder–company relationships, and enhance stakeholders' advocacy behaviors. However, stakeholders' low awareness of and unfavorable attributions towards companies' CSR activities remain critical impediments in companies' attempts to maximize business benefits from their CSR activities, highlighting a need for companies to communicate CSR more effectively to stakeholders. In light of these challenges, a conceptual framework of CSR communication is presented and its different aspects are analyzed, from message content and communication channels to company- and stakeholder-specific factors that influence the effectiveness of CSR communication.     

中国英语学习者使用非词语化名词thing特点分析--基于语料库的调查研究

非词语化是普遍存在的语言现象,而thing是常用的非词语化词之一。基于一个中国学习者语料库和一个本族语者语料库的对比,研究了中国学习者使用thing的特点。结果表明,中国学习者倾向于过度使用该词,而且存在许多语义模糊、冗余、替代和搭配不当的用法;但随着语言水平的提高,该词的使用频率显著下降,这说明中国学习者对该词的使用符合中介语的发展规律。结合研究结果尝试分析了这些特点的成因,发现学习者的词汇能力、学习策略、语言负迁移和中介语心理认知机制等因素造成了中国学习者过度及不当使用thing的现象。     

我国民间借贷的风险防范研究

我国民间借贷所存在的融资优势是：市场定位适当;效率高、期限短;信息渠道畅通,准入条件较低;对中小企业发展有推动作用。近年来民间借贷发展很快,出现了一系列问题,其中一些问题的出现直接扰乱了金融秩序,尤其以企业为主导进行的民间借贷活动最为明显。存在的风险是：资金大规模流向房地产行业,潜在威胁大;大规模融资易导致非法集资;高利率可能导致中小企业偿债困难。防范民间借贷风险的对策建议是：将民间借贷纳入统一的监管体系;探讨分类法律监管模式,规范中小企业民间融资;加强公众教育,抵制非法集资;建立健全民间借贷风险监督预警机制;引导民间资本选择正确的投资方向,规避投资风险。保护好民间资金市场,积极合理的引导,可以使大规模的民间借贷资金能够为我国实体经济的发展做出贡献。     

以党的群众路线教育活动推进大学生思想政治教育工作精细化

高校群众路线教育实践活动为高校思想政治教育精细化提供了契机。面对高校在校生数量的连年增加,教育对象的差异性给思想政治教育工作提出了严峻挑战。从思想政治教育体现出的许多新特点来看,学生教育精细化管理的创新是必然趋势。要通过建立健全运行机制、建立信息管理系统,增强精细化思想政治教育的执行力,才能确保高校思想政治教育精细化工作的有效开展。     

试论高校“思想政治理论课”教师教育教学能力提升

高校＂思想政治理论课＂教学具有鲜明的时代性特征,新形势下多元化的价值取向对教师的教育教学能力提出了新要求,而当前高校＂思想政治理论课＂教师教育教学能力呈现出知识结构亟待更新、教学模式单一、忽视现代网络技术、教学效果不佳等问题。可以通过政府加大经费支持力度、高校组织教学观摩展评、教师积极参加培训和交流加强集体备课的措施,提升＂思想政治理论课＂教师教育教学能力,促进教师的身心健康及专业发展,改善教学效果。     

An Application of EM Algorithm to a Change-Point Problem

We consider the problem of change-point in a classical framework while assuming a probability distribution for the change-point. An EM algorithm is proposed to estimate the distribution of the change-point. A change-point model for multiple profiles is also proposed, and EM algorithm is presented to estimate the model. Two examples of Illinois traffic data and Dow Jones Industrial Averages are used to demonstrate the proposed methods.     

Vector random fields with compactly supported covariance matrix functions

The objective of this paper is to construct covariance matrix functions whose entries are compactly supported, and to use them as building blocks to formulate other covariance matrix functions for second-order vector stochastic processes or random fields. In terms of the scale mixture of compactly supported covariance matrix functions, we derive a class of second-order vector stochastic processes on the real line whose direct and cross covariance functions are of Pólya type. Then some second-order vector random fields in R^d${\mathbb{R}}^d$ whose direct and cross covariance functions are compactly supported are constructed by using a convolution approach and a mixture approach.     

Model averaging for M-estimation

M-estimation is a widely used technique for robust statistical inference. In this paper, we study model selection and model averaging for M-estimation to simultaneously improve the coverage probability of confidence intervals of the parameters of interest and reduce the impact of heavy-tailed errors or outliers in the response. Under general conditions, we develop robust versions of the focused information criterion and a frequentist model average estimator for M-estimation, and we examine their theoretical properties. In addition, we carry out extensive simulation studies as well as two real examples to assess the performance of our new procedure, and find that the proposed method produces satisfactory results.