基于AHP与FCE方法的企业间竞争合作关系强度识别模型

企业间竞争与合作关系并非是对立的,而是统一的,竞争与合作具有"同素异相"的特性,是企业间的关系在不同外部约束及内部动力下所表现出的不同的强度。企业间竞争合作关系强度(SCCR)从最紧密的一体化关系到竞争最激励的敌对关系形成了一个谱系。文章从承诺效度、互动强度、资源依赖(竞争)强度、情感深度、收益强度五个维度构建了SCCR评判指标体系,并基于AHP(层次分析法)和FCE(模糊综合评判方法)建立了SCCR识别模型。同时,运用此模型对某汽车零部件企业和其供应商间的SCCR进行了识别。     

湖北省承接制造业转移现状、优劣势及对策分析

湖北省在承接产业转移方面具备明显的区位、科技与劳动力、市场和基础设施建设方面的优势,但是,行政服务的高成本与政策环境的低效率、产业配套能力不强、企业体制和中介服务落后和城市知名度不高等问题,都制约着湖北承接制造业转移的进程。因此,湖北省在制造业转移的步伐和质量方面应有相应的对策。     

An Empirical Study of Equivalence Judgments vs. Ratio Judgments in Decision Analysis*

Two commonly used elicitation modes on strength of preference, equivalence and ratio judgments, were compared in an experiment. The result from the experiment showed that ratio judgments were less effective than equivalence judgments. Based on an iterative design for eliciting multiattribute preference structures, equivalence judgments outperformed ratio judgments in estimating single‐attribute measurable value functions, while being nearly more effective than ratio judgments in assessing multiattribute preference structures. The implications of the results from the experiment are that multiattribute decision‐making techniques should take advantage of the decision maker's inclination of making effective equivalence trade‐off judgments, and that useful techniques should be devised to incorporate different commonly used techniques, such as multiattribute utility theory and the Analytic Hierarchy Process, to elicit and consolidate equivalence trade‐off judgments.     

社会工作两种视角的比较分析

从社会工作的发展历程来看，其实践先后经历了缺陷视角与优势视角两种模式，这两种模式关注的焦点与实践方式都有着很大的区别。伴随着对缺陷视角越来越多的质疑与批判，优势视角逐渐成为学术讨论的热点，更多的人提倡采用优势视角下的社会工作实践模式。为了更加全面、深人的认识和把握优势视角，对缺陷视角的全面深刻的认识不可或缺。本文将从视角假设、理论基础、社会工作者的角色及对社会工作的理解等方面对两种视角进行比较分析。     

Bayes factors based on test statistics

Summary.  Traditionally, the use of Bayes factors has required the specification of proper prior distributions on model parameters that are implicit to both null and alternative hypotheses. I describe an approach to defining Bayes factors based on modelling test statistics. Because the distributions of test statistics do not depend on unknown model parameters, this approach eliminates much of the subjectivity that is normally associated with the definition of Bayes factors. For standard test statistics, including the χ ²-, F -, t - and z -statistics, the values of Bayes factors that result from this approach have simple, closed form expressions.     

真情挚感 催人泪下——浅析鲍照的《拟行路难》

鲍照的《拟行路难》十八首从各个方面描写了人生的艰辛,它注意文章的谋篇布局,注意内容和形式的有机结合,从民歌中汲取丰富的营养,使诗歌面目为之一新,这种在继承的基础上勇于突破的创作实战,是值得今天诗歌创作者学习借鉴的。     

我国上市公司竞争力决定因素及其变动研究——基于2003-2006年的面板数据

采用2003-2006年面板数据对我国上市公司竞争力的实证研究发现:由于公司治理的竞争力相对较弱,使得我国上市公司总体竞争力水平不高.但上市公司竞争力的变动趋势表明,由于制度约束以及自身发展的需要,上市公司股权结构逐步合理、股东大会逐步规范、董事会以及监事会治理竞争力逐步提升,使得上市公司治理竞争力呈现上升趋势;而由于上市公司偿债能力以及增长能力的下降,使得其财务实力出现下降趋势.提升上市公司竞争力的根本是完善治理结构与治理机制,股权结构的优化必须伴随着投资者理性意识的培育方能奏效,否则可能导致更为严重的大股东行为.除此之外,上市公司还必须关注于财务状况的改善,以避免财务状况恶化和财务风险增加.     

关系强度、关系资源与新企业绩效——基于行为视角的实证研究

大多数研究认为,善于利用社会关系网络的创业者更可能收获更高的新企业绩效,但对关系资源在促进新企业绩效中的角色并没有引起足够重视.针对这一问题,本文考察了创业者所利用的关系强度、关系资源与新企业绩效之间的逻辑联系,以及资源获取行为对该作用过程的中介作用.研究发现:在创业过程中,越丰富利用关系资源的创业者更容易整合到更丰裕的创业资源,从而提升新企业绩效.尽管所利用关系强度更高的创业者往往能以更快的速度获取创业资源,但并不能确保创业者能够迅速应付创业初期的资源需求,并不会改善新企业绩效.本文的主要理论贡献在于嵌入到行为层面揭示了社会资本改善新企业绩效的作用机制及资源获取的中介作用,发现网络嵌入性资源是有助于解释新企业绩效差异的重要变量,这是对已有文献的重要补充.     

长直载流螺线管磁场的一种计算方法

本文从基本定义出发，正确得出了无限长直载流螺线管的其内、外部所激发磁场的分布情况，对现行教课书中的相关内容作了补充，澄清了模糊概念．     

Interpreting statistical evidence by using imperfect models: robust adjusted likelihood functions

Summary. The strength of statistical evidence is measured by the likelihood ratio. Two key performance properties of this measure are the probability of observing strong misleading evidence and the probability of observing weak evidence. For the likelihood function associated with a parametric statistical model, these probabilities have a simple large sample structure when the model is correct. Here we examine how that structure changes when the model fails. This leads to criteria for determining whether a given likelihood function is robust (continuing to perform satisfactorily when the model fails), and to a simple technique for adjusting both likelihoods and profile likelihoods to make them robust. We prove that the expected information in the robust adjusted likelihood cannot exceed the expected information in the likelihood function from a true model. We note that the robust adjusted likelihood is asymptotically fully efficient when the working model is correct, and we show that in some important examples this efficiency is retained even when the working model fails. In such cases the Bayes posterior probability distribution based on the adjusted likelihood is robust, remaining correct asymptotically even when the model for the observable random variable does not include the true distribution. Finally we note a link to standard frequentist methodology—in large samples the adjusted likelihood functions provide robust likelihood-based confidence intervals.