Using clustering ensemble to identify banking business models

The business models of banks are often seen as the result of a variety of simultaneously determined managerial choices, such as those regarding the types of activities, funding sources, level of diversification, and size. Moreover, owing to the fuzziness of data and the possibility that some banks may combine features of different business models, the use of hard clustering methods has often led to poorly identified business models. In this paper we propose a framework to deal with these challenges based on an ensemble of three unsupervised clustering methods to identify banking business models: fuzzy c‐means (which allows us to handle fuzzy clustering), self‐organizing maps (which yield intuitive visual representations of the clusters), and partitioning around medoids (which circumvents the presence of data outliers). We set up our analysis in the context of the European banking sector, which has seen its regulators increasingly focused on examining the business models of supervised entities in the aftermath of the twin financial crises. In our empirical application, we find evidence of four distinct banking business models and further distinguish between banks with a clearly defined business model (core banks) and others (non‐core banks), as well as banks with a stable business model over time (persistent banks) and others (non‐persistent banks). Our proposed framework performs well under several robustness checks related with the sample, clustering methods, and variables used.     

Analysis of the Service Dominant Logic network,authors, and articles

The present study analyses research conducted in Service Dominant Logic (S-D logic), providing an overview of its intellectual structure. For that purpose, a structured approach was adopted through the implementation of bibliometric methods, using co-citation analysis combined with performance analysis and an integrative science mapping approach, which considered a timeline, a graph, and a distance-based perspective. This allowed the identification of the leading authors and of six clusters of articles based on bibliographic coupling, along with the most prominent research themes clustered in five subdomains of research based on co-occurrence of terms. The networks extracted show the associations between the main articles and concepts treated by the S-D logic community, unveiling the salient challenges and prospective expansion facing its future theoretical and practical context.     

基于主成分与聚类分析法的城市土地利用规划分区研究——以广州市为例

[目的]土地利用分区是土地利用总体规划的核心内容之一,是合理确定土地利用方向,优化土地利用结构与布局的重要途径。为了对广州市土地利用及未来发展方向提供理论指导,结合其土地利用现状和特点,选取土地利用结构、土地开发利用程度、社会经济状况和环境资源承载力4项一级指标及15项二级指标,建立土地利用综合分区指标体系。[方法]通过SPSS19.0软件,运用主成分分析法提取出前4个主成分,并将其作为新的样本数据,采用层次聚类分析法对广州市土地利用进行综合分区。[结果]根据聚类分区结果,将广州市分为4类土地利用区:中心发达区,包括荔湾区、海珠区、天河区和越秀区;综合发展区,包括白云区、番禺区、花都区、增城区和从化区;重点潜力区即南沙区;资源组合区是(新)黄埔区。根据各分区的差异性,提出各区域土地资源开发利用中存在的主要问题及未来发展方向。[结论]根据各区的自然经济条件及土地利用状况,将广州市分为4类土地利用区具有合理性,能为广州市今后土地利用规划的科学编制提供参考。     

Macroeconomic Announcements and the Distribution of Price-Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.     

基于灰色聚类的珠三角区域物流竞争能力分析

建立区域物流能力指标体系,收集相关数据,应用灰色定权聚类分析法,对珠三角各个城市物流能力各项指标定量分析。依据结果,判断各个城市属于哪个类别,分析各个城市的物流发展潜力并提出相关建议。     

北京市药品批发企业物流能力分级研究

结合北京市药品批发企业特点,建立了基于信息熵和模糊聚类的分类模型,并依据聚类结果,提出了药品批发企业物流能力分级方法。模型以实际调研数据为基础,首先应用信息熵理论简化评价指标体系,然后运用熵权法加权的模糊聚类方法对简化后的指标体系进行聚类分析。根据聚类情况,将北京市药品批发企业按物流能力划分为三级,同时指出影响分级结果的指标因素及相应权重,期望为政府监管和行业发展提供一定的指导。     

我国畜产品价格波动分析——基于ARCH类模型

运用ARCH类模型对我国主要畜产品的价格波动率进行了分析。结果表明:牛肉、羊肉和鸡肉的价格波动具有显著的波动积聚性,鸡蛋价格波动没有显著的异方差效应;除牛肉市场外,羊肉和鸡肉市场不具有高风险、高回报的特征;猪肉、牛肉、羊肉和鸡肉的价格波动没有非对称性。认为应在畜产品市场出现大的价格波动时及时采取平抑措施,且政府需规范畜产品市场秩序、完善畜产品市场制度。     

一种基于数据挖掘的面条品质综合评价方法

为了准确评价面条品质,文章以46种不同品牌的市售面条为材料,通过实验采集面条样本的力学性能数据和其他属性数据,对构建的数据集进行主成分分析,并借助其结果进行聚类分析,样本最终被划分成5个类,对面条样本进行感官评价。参考感官评价的指标再对每一个簇中的样本进行评价,描述出每个簇中面条样本的品质特性。该方法融合了多种数据分析和评价方法,既具备数据分析的客观性,又不失主观评价的优势。     

基于价值累加理论的大学生网上群聚行为规律及对策研究

本文通过将价值累加理论引入至大学生网上群聚行为研究,剖析出大学生网上群聚行为的内在特点和规律形式,深入分析了在价值累加理论的六个构成因素——结构性诱因、结构性紧张、一般性信念、触发因素、行动动员和社会控制的实现的作用下,大学生网上群聚行为的发生产生机制,并进一步探究出技术时代新形势下网上群聚行为切实可行的对策建议。     

International Market Segmentation and Cross-Export Strategies Development Case Study: Iranian Furniture Industry

ABSTRACT

By developing an international market and significant differences between countries in this regard, segmentation becomes an increasingly important concept in marketing. In this article, the international market of Iranian furniture industry is segmented and cross-exporting strategies are developed to increase the market share of Iranian furniture in each segment. To achieve this, two distance functions are introduced based on correlation between export groups to cluster countries with k-means algorithm. After market segmentation for increasing sales in each segment, cross-exporting strategies are predicted by extracting association rules in each segment based on Apriori algorithm to set export baskets.