学习智障对我国企业竞争力弱化之影响

本文从系统的观点出发 ,运用反馈机制原理 ,对企业竞争优势弱化现象进行了较为系统、深入的分析 ,提出学习智障对企业竞争力的雪崩效应模型和组织学习力的滚雪球效应模型 ,以探索强化企业竞争优势的途径     

财务、会计目标和谐论——兼论企业财务管理目标的建立

财务、会计是社会生产发展到一定阶段的产物。实践中先有理财思想 ,后有会计行为。财务、会计是实现企业目标的重要环节 ,财务、会计目标的和谐统一 ,有利于财会工作的协调一致 ,有利于企业目标的实现 ,有利于财务、会计理论体系的构建     

建设工程管理决策中的系统分析方法

管理决策的科学性取决于管理方法、手段和技术的有效性。基于决策问题的系统分析方法是实施科学决策的基础,决策问题的提出是系统科学发展的动因。建设工程管理决策树立系统观点、应用系统方法进行量化和优化是提高其决策质量的有效方法。从系统分析与决策、建设工程管理决策的系统观以及建设选址问题中系统分析方法的应用三个方面理论与实际相结合,阐明了系统量化与优化对于建设工程管理决策的辅助支持作用,以期增强建设工程管理决策活动应用系统方法的自觉性,提高管理决策的质量和能力,促进建筑业的健康良性发展。     

Threshold decisions: how social workers prioritize referrals of child concern

This paper examines local authority social workers' decision‐making when considering referrals of children, where the concerns are on the margin of child protection procedures. In doing so, it describes the findings of a qualitative research study undertaken in the policy context of attempts to ‘refocus’ social work practice in the late 1990s and early twenty‐first century. Data collection involved interviews with social workers and parents in 23 cases. Conclusions are that referrals were evaluated on the basis of five key factors, specificity, severity, risk, parental accountability and corroboration, the use of which determined whether an initial assessment or an investigation of alleged abuse took place. The analysis builds on previous work in the child protection field, but demonstrates how the application of these factors differs between cases of child concern and cases of child protection. Policy implications concern the complexity of decision‐making in the uncertain context of limited referral information and it is proposed that the simplistic notion of a continuum of abuse is now outdated. Copyright © 2006 John Wiley & Sons, Ltd.     

一种基于神经网络和决策树的信用评估新方法

分析了数据挖掘在国内外金融领域的应用及研究现状,提出了一种基于神经网络和决策树相结合的信用评估新方法。该方法通过RBF神经网络,进行条件属性裁减,并利用决策树抽取出评估规则。此方法利用神经网络的“黑箱”工作特性,选择重要条件属性,并利用决策树自动生成评估规则,大大提高了信用评估的效率和客观性。     

基于数据挖掘的客户关系分析评价系统

分析功能的深化是客户关系管理(CRM)的一大发展趋势,应用数据挖掘技术建立的CRM分析评价系统,可以对客户的行为以及市场趋势进行有效的分析,为企业的各种决策提供定性和定量的依据。该系统主要模块包括:客户细分模块、客户行为分析模块和市场趋势分析模块。以上各个模块涉及了企业关心的各种客户行为及市场行为,通过各个模块的分析,企业可以辨认出高端客户,理解各种客户行为模式,并掌握市场发展趋势以保证企业在激烈的竞争中立于不败之地。     

西方国家高校组织的自主权及其启示

西方国家高校组织的自主权是通过大学内部立法、决策领导、组织协调、咨询等办学活动来实现的。大学自治组织系统主要由董事会 (校务会 )、校长、评议会等组成。校长由董事会 (校务会 )选举或产生 ,代表其行使学校决策及日常事务管理。大学自治组织一般拥有组织教学、筹集经费、开展学术研究、人事使用等权力 ,而这些权力的行使一方面要受到大学内部各种权力系统、管理层以及利益集团的制约 ,同时还要受到来自大学外部的各种专门组织和社会团体的监督     

决策理论中的理性主义与渐进主义及其适用性

理性主义和渐进主义都是决策理论中的主要的根源性模式。对这两种模式的可行性和应用性的批评、争议和讨论 ,引发了多种决策模式的出现 ,同时也使前者得到不断改进 ,促进了决策理论的发展。考察这两种模式的主要特点和它们的相互关系 ,探讨它们在实践中的适用性 ,考量其利弊 ,有助于我们进一步加深对这两种决策模式的认识 ,并使之能在适当的应用中发挥积极的作用 ,从而改善我们的决策方式和决策质量     

Bayesian validation assessment of multivariate computational models

Multivariate model validation is a complex decision-making problem involving comparison of multiple correlated quantities, based upon the available information and prior knowledge. This paper presents a Bayesian risk-based decision method for validation assessment of multivariate predictive models under uncertainty. A generalized likelihood ratio is derived as a quantitative validation metric based on Bayes’ theorem and Gaussian distribution assumption of errors between validation data and model prediction. The multivariate model is then assessed based on the comparison of the likelihood ratio with a Bayesian decision threshold, a function of the decision costs and prior of each hypothesis. The probability density function of the likelihood ratio is constructed using the statistics of multiple response quantities and Monte Carlo simulation. The proposed methodology is implemented in the validation of a transient heat conduction model, using a multivariate data set from experiments. The Bayesian methodology provides a quantitative approach to facilitate rational decisions in multivariate model assessment under uncertainty.     

Optimal sampling for repeated binary measurements

The authors consider the optimal design of sampling schedules for binary sequence data. They propose an approach which allows a variety of goals to be reflected in the utility function by including deterministic sampling cost, a term related to prediction, and if relevant, a term related to learning about a treatment effect To this end, they use a nonparametric probability model relying on a minimal number of assumptions. They show how their assumption of partial exchangeability for the binary sequence of data allows the sampling distribution to be written as a mixture of homogeneous Markov chains of order k. The implementation follows the approach of Quintana & Müller (2004), which uses a Dirichlet process prior for the mixture.