目标导向层次分析方法

对含有抽象属性的多属性层次结构而言，层次分析法即AHP（包括DIS-AHP、ABS-AHP、IDE-AHP和SUP-AHP四种具体方法）会因比率比较基准缺失、权重内涵模糊不清或方案评价不保序而缺乏科学理性。为发展AHP，基于摆幅置权（SW）判断模式和多属性决策属性价值公度方法，首先给出了能为层次结构抽象属性上的SW判断提供支持的规约性多属性决策属性价值公度方法，然后由此并结合多属性价值理论给出了能够克服现有层次分析法内在缺陷的目标导向层次分析方法即ToAHP。相对于AHP，ToAHP在判断模式与权重内涵、方法建构的理论基础和相关假设检验、方案评价保序与其内在数理依据上具有明显的相对科学合理性。应用分析表明：在输入信息可比的条件下，ToAHP明显优于AHP的四种分析方法之中最具可信性的SUP-AHP方法。     

基于在线评论数据的产品需求趋势挖掘

随着经济水平的提高和物质生活的丰富，消费者的需求变化也越来越快。能否迎合市场需求的变化是企业产品成功的关键。随着社交媒体的发展，消费者为了分享购物体验发表了许多在线评论信息，其中蕴含着消费者的需求变化。本文在产品特征提取和属性情感分析的基础上，构建了垃圾评论识别模型。然后，利用时间序列分析模型预测下阶段的产品属性关注度和情感计算。最后结合历史数据的变化趋势，分析产品属性的重要性和市场满意情况。利用汽车论坛上的汽车评论数据对本文提出的研究模型进行了验证。研究结果可以为企业制定营销策略以及产品改进与创新提供决策支持。     

外贸企业汇率风险应急机制属性综合评价模型

企业管理者对于自身汇率风险应急机制情况的准确了解可以增强应对汇率风险的能力,如何客观地对汇率风险应急机制进行综合评价就显得至关重要。基于应急管理理论与汇率风险的特点,建立了汇率风险应急机制指标体系,然后利用层次分析法确定评价指标权重,运用属性测度理论构建了评价模型。最后通过算例分析,说明了该方法有可行性,能够为管理者提供科学、合理的决策依据。     

属性集容量确定的夹挤式测度模式及其推算模型

迄今，为解决多属性偏好关联决策属性集容量判断指数复杂性难题所提出的λ模糊测度模式与k-可加模糊测度模式，以及建构在它们之上的属性集容量确定的推算模型，尚存在着适用性差的技术不足。为此，以平衡容量判断的可操作性和容量推算的准确性为视角，提出了一种新容量测度模式，即关于容量判断与推算的夹挤式测度模式，并在此基础上通过引入决策者较易判断给出的容量序信息构建了相应的容量推算模型。基于数值模拟的对比分析表明：新模式不仅在应用可行性上高于k-可加模糊测度模式，而且从容量推算的准确性上看也明显优于λ模糊测度模式和k-可加模糊测度模式，因而对实际决策具有更强的适用性。     

A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution

This article suggests an efficient method of estimating a rare sensitive attribute which is assumed following Poisson distribution by using three-stage unrelated randomized response model instead of the Land et al. model (2011 Land, M., S. Singh, and S. A. Sedory. 2011. Estimation of a rare sensitive attribute using poisson distribution. Statistics 46 (3):351–60. doi:10.1080/02331888.2010.524300.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) when the population consists of some different sized clusters and clusters selected by probability proportional to size(:pps) sampling. A rare sensitive parameter is estimated by using pps sampling and equal probability two-stage sampling when the parameter of a rare unrelated attribute is assumed to be known and unknown.

We extend this method to the case of stratified population by applying stratified pps sampling and stratified equal probability two-stage sampling. An empirical study is carried out to show the efficiency of the two proposed methods when the parameter of a rare unrelated attribute is assumed to be known and unknown.     

Bayesian estimation of rare sensitive attribute

Randomized response models have been used to estimate a population proportion of a sensitive attribute. A randomized device is typically employed to protect respondent's privacy in a survey. In addition, an unrelated question is asked to improve the statistical efficiency. In this article, we propose Bayesian estimation of rare sensitive attribute using randomized response technique, which includes a rare unrelated attribute. Two cases are considered, the proportion of a rare unrelated attribute is known and unknown. A simulation study is conducted to assess the performance of the models using mean absolute error and coverage probability. The results show that the performance depends on the parameters and is robust to priors.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

Book Review

DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling, by Pierre Baldi and G. Wesley Hatfield, 2002, Cambridge University Press, Cambridge, United Kingdom, 213?+?xvi pp., [ISBN: 0-521-80022-6]     

从学理到实践:爱国主义定义的结构性解析

如何界定爱国主义这一定义一直是学术界讨论的问题。《〈中共中央宣传部教育部关于进一步加强和改进高等学校思想政治理论课的意见〉实施方案》实施后,《思想道德修养与法律基础》教材不再运用列宁关于爱国主义的定义,而用了一个新的定义。科学地理解爱国主义不仅是爱国主义本质的内在要求,而且是理性爱国主义教育的前提。从“非人民群众”的爱国情感、“祖国”与“国家”的关系、爱国主义“理性”与“非理性”的关系三个角度进行探讨,认为社会主义国家应倡导理性爱国主义。     

证券市场的信息生产制度——一个品质考核的理论进路

证券市场区别于其他市场的一个重要标志,是其建立了一个庞大、复杂、细密的信息披露体系。本文运用巴泽尔的品质考核理论,深入考察了证券商品的信息特性,并以此为理论线索,重新审视和解释了证券市场的信息生产制度。证券商品的品质考核问题在两个方面对证券法制度产生了根本性影响。一方面,它导致证券市场涌现出大量投资银行、会计师事务所、证券投资基金、证券评级公司等市场机构,从事大规模的证券信息生产,众多的机构管理法规因而成为证券法体系非常重要的组成部分。另一方面,它迫使证券市场建立起一套严格的信息生产体制,为证券市场持续、大规模的信息生产提供制度保障。