Extracting cover sets from free fuzzy sorting data

Assignment of items to multiple categories requires suitable statistical methods. The present paper provides a new approach to solve this task. The concept of fuzzy sets is extended to cover sets (sets of overlapping clusters) in a simple manner introducing a vector of item membership sums. The application of the new concept is exemplified by modifying the fuzzy cluster analysis algorithm of Kaufman and Rousseeuw (Finding groups in data: an introduction to cluster analysis, 1990) to cover set cluster analysis appropriately. Wide equivalence of the numerical problems is demonstrated from Lagrange multipliers and Karush-Kuhn-Tucker conditions. Additionally, some extensions are introduced to the algorithm to improve its behavior for suboptimal large or small numbers of clusters. The adapted algorithm in most cases reproduces single sortings for correct numbers of clusters. Two applications to empirical free fuzzy sorting data sets are provided. Limitations of the algorithm are discussed.     

The integration of fuzzy sets and statistics: toward strict falsification in the social sciences

Whilst statistics take up a prominent place in the social science research toolkit, some old problems that have been associated there with have not been fully resolved. These problems include bias through the inclusion of irrelevant variation and the exclusion of relevant variation, which may lead to hidden and spurious correlations in more extreme—however not at all unthinkable—cases. These issues have been addressed by Ragin by building a case for the usage of fuzzy set theory in social science. In this paper, we take a complementary view, insofar as we incorporate fuzzy set theory in current statistical analyses. Apart from shedding new light on the main issues associated with (population based) statistics, this approach also offers interesting prospects for the falsification of theories—rather than single relations between variables—in the social sciences.     

The analysis of risk perception with fuzzy means-end approach

Visitors’ risk perceptions have been found to influence the on-site behavior of tourists and their intention to return to a destination or to recommend it to others. This study discusses how the uses of a means-end approach with fuzzy conceptualization in eliciting the perception of tourism risks in a better understanding of the visitors’ perceptual orientation toward the tourism values. We provide a hierarchy value map that fuses the attribute–consequence–value (A–C–V) and fuzzy linguistics to effectively and efficiently understand vacation risks and risk characteristics. Fuzzy logic is also adopted to deal with the ill-defined nature of the tourist linguistic judgments required in the proposed means-end chain. This research findings suggest that additionally to managing the most likely risks, tourist resorts should be prepared to cope with worst case scenarios such as “Thunderstorm”, “Bus accident”, “Food poisoning” and “Cable car accident”. From an overall risk perceptive, tourists are most concerned with dominant perceptual orientation of risk delivers being “Bus accident” → “Decrease of trust in the safety management as a result of the event of damage” → “Anger”.     

Thresholds in pareto sets

We use catastrophe theory to discuss the generic ways in which a system determined by the optimization of several real-valued functions, such as a pure exchange economy, can break its stability and make a transition from ‘slow’ to ‘fast’ movement.     

基于突变理论的高校稳定状况动态模糊评价研究

从稳定状态到不稳定的过程是一个复杂并且包含有着大量的突发性非连续性变化过程,为了研究和发现导致学校稳定状况产生突变的因素,科学地评判并预警,本文结合突变理论,运用模糊隶属函数和突变级数,将突变理论与模糊分析结合起来,对与学生有关的学校稳定系统进行多层目标分解,再根据归一公式进行量化递归运算,最后得到学校稳定总突变隶属函数值,进而通过分析不同时期学校稳定总突变隶属函数值及其变化趋势,动态地对学校稳定状况进行模糊综合评判并通过实例进行了检验。     

Modeling large data sets in marketing

In the last two decades, marketing databases have grown significantly in terms of size and richness of available information. The analysis of these databases raises several information-related and statistical issues. We aim at providing an overview of a selection of issues related to the analysis of large data sets. We focus on the two important areas: single source databases and customer transaction databases. We discuss models that have been used to describe customer behavior in these fields. Among the issues discussed are the development of parsimonious models, estimation methods, aggregation of data, data-fusion and the optimization of customer-level profit functions. We conclude that problems related to the analysis of large databases are far from resolved, and will stimulate new research avenues in the near future.     

基于区间直觉模糊集TOPSIS法的供应商选择

供应商的选择一直是供应链管理的核心和关键,直接影响着整条供应链的运营。文章首先介绍了供应商选择的研究现状,在此基础上构建了供应商选择的评价指标体系,并引入直觉模糊集TOPSIS法进行供应商的选择。最后用一个实例阐述该指标体系和方法的应用,为供应商的选择提供了一种新的方法。     

A modular fuzzy inference system approach in integrating qualitative and quantitative analysis of store image

The image situation in a store includes various stimuli, such as color, sound, scent, taste, layout and space, which are important clues for buyers. This paper describes store image response and a fuzzy logic model developed by comprehensive literature studies on image measurements (including atmospheric factors) and perceptual measures. Here, a fuzzy inference system is proposed as an alternative approach to handle effectively the impreciseness and uncertainty that are normally found in store image selection processes. This paper also shows that the proposed decision-making model is application to modified stimulus?Corganism?Cresponse (S?CO?CR) framework for integrating qualitative and quantitative analysis. The result of the simulation indicates a numerical and linguistic change in the store image perception after analyzing three input parameters. This finding is able to provide a solid foundation on which retailers and decision makers can base suitable strategies for ensuring the efficiency and stability of store image management system.     

Scaling criterion of questionnaire items

Criterion scaling is a technique for scaling questionnaire item responses so as to maximize their correlation with an external criterion. The correlation between the criterion and the scaled item is equal to the correlation ratio or η coefficient. The results of rescaling the ninth grade questionnaire of the “Equal Educational Opportunity Survey” is presented and compared to the subjective scaling used in the Report. Criterion scaling increased all correlations but the change is not substantial enough to change the interpretation of the Report.     

In search of content validity: facet analysis as a qualitative method to improve questionnaire design

In this paper, two scales are examined for the measurement of self-regulation. The item content is evaluated for its specific usefulness for measuring self-regulation of obesity patients. Qualitative facet analysis (QFA), an application of Guttmann’s Facet Theory, is used to investigate whether item content sufficiently covers the intended content area. This form of content analysis constitutes a systematic, effective and critical tool for improving the content validity of questionnaires. It discovers topics that are underrepresented or overrepresented. The method offers a way to clarify the relationship between concrete item phrases and the desired content as defined by construct and theory. It allows the researcher to improve his or her understanding of the items as a stimulus and of the similarities of items, and allows the formulation of a possible structure for confirmative factor analysis. Various ways to improve the content of both scales are identified.     

基于模糊C-均值聚类的ETC系统客户的逃费分析研究

随着我国ETC系统的普及,ETC系统客户的管理也成了急需解决的问题。文章主要通过利用模糊C-均值聚类的方法对采集到的收费数据进行分析,找出异常点对应的ETC系统客户,进行重点分析和重点监控,确定是否存在逃费行为,以减少通行费的流失,实现科学、合理、高效的管理。     

Online banking performance evaluation using data envelopment analysis and axiomatic fuzzy set clustering

This paper presents a hybrid model to conducting performance measurements for Internet banking by using data envelopment analysis (DEA) and axiomatic fuzzy set (AFS) clustering. For each bank, DEA is applied to select a best combination by computing an aggregated efficiency score based on outputs, such as web metrics and revenue; and inputs, such as equipment, operation cost and employees. Then AFS clustering method is used to classify the best combination into different groups and provide the definitely semantic interpretations for the evaluation results. Identification of operational fitness and business orientation of each firm, in this way, will yield insights into understanding the weaknesses and strengths of banks, which are considering moving into Internet banking.     

基于直觉模糊集TOPSIS法的运输路径选择

运输路径选择是一个多属性决策问题,路径选择的合理化势必对企业的经济效益产生影响。文章根据TOPSIS的价值函数模型,通过对物流运输系统的分析,提取5个影响路径选择的因素,使用直觉模糊集确定属性的指标值和权重,建立一种基于直觉模糊集TOPSIS法的运输路径选择模型。数据实例说明该方法不仅解决了决策过程中出现的模糊性信息,而且还克服了传统评价指标的单一性缺陷,是一种有效、实用的方法,可为解决直觉模糊多属性决策提供新途径。     

Principal components at work: the empirical analysis of monetary policy with large data sets

The empirical analysis of monetary policy requires the construction of instruments for future expected inflation. Dynamic factor models have been applied rather successfully to inflation forecasting. In fact, two competing methods have recently been developed to estimate large‐scale dynamic factor models based, respectively, on static and dynamic principal components. This paper combines the econometric literature on dynamic principal components and the empirical analysis of monetary policy. We assess the two competing methods for extracting factors on the basis of their success in instrumenting future expected inflation in the empirical analysis of monetary policy. We use two large data sets of macroeconomic variables for the USA and for the Euro area. Our results show that estimated factors do provide a useful parsimonious summary of the information used in designing monetary policy. Copyright © 2005 John Wiley & Sons, Ltd.     

基于模糊组合权的模糊TOPSIS方法在供应商选择中的应用研究

供应商的选择在供应链管理中是很重要环节,供应商选择的成功与否将直接影响到整个供应链的竞争优势,故有必要对供应商选择进行深入研究。本文将已有的模糊组合权方法和模糊TOPSIS方法相结合,提出一种基于模糊组合权的模糊TOPSIS方法,并将其应用于供应商的选择研究中。文章首先总结已有的相关研究结果,给出供应商评价的准则,接着介绍三角模糊数的相关理论,推出模糊组合权及模糊TOPSIS的算法步骤,最后通过一个算例验证方法的可行性。     

基于直觉模糊集的供应链战略合作伙伴选择

企业建立良好的战略合作伙伴关系可以使供应链产生更强的竞争优势。文章通过对供应链战略合作伙伴的基本原则和影响因素进行分析,建立了合作伙伴的评价指标,运用直觉模糊集广义混合加权集结算子,对合作伙伴选择问题进行了综合评价,并通过实例说明该方法能够很好的解决供应链战略合作伙伴选择的实际问题,具有科学性和可操作性。     

上药“回家”

这是一场横跨沪港两地4家上市公司的重组。重组后,两家医药上市公司将被注销,一家上市公司医药资产将被清空——吸纳了三家上市公司医药资产,拥有研发、制造、分销、零售完备产业链的“新上药”横空出世。     

A note on mixture sets in decision theory

Decisions in Economics and Finance -