How Do Household Tasks Shape Employment Contracts? The Provision of Care in Portugal

This study illustrates the complexities involved in outsourcing domestic work to the market. It draws on an original dataset of paid domestic workers in Portugal to examine how specific tasks interact with and explain contractual arrangements. A fuzzy cluster analysis categorizes paid domestic workers into caregivers and cleaners; however, a great degree of overlap implies that caring also entails cleaning tasks necessary for the care receiver’s well-being. A subsequent Tobit regression analysis shows that caregivers have more formal and stable contracts but earn lower wages and have longer working hours relative to cleaners. The study finds a segmentation of national origin and that some migrants are at a disadvantage in care work. The study also examines how employers deal with the idiosyncrasies of domestic work such as navigating trust-related issues.     

节事价值共创的非对称性及影响因素——基于观众和演职人员主体

主体间的价值共创是节事活动创新与发展的重要推力,既有研究指出价值共创机制受参与主体和多种因素的共同影响,但是各因素聚类特征、充要条件及共创路径稳健性之间的影响机理尚存争议。文章基于观众和演职人员价值共创的主体间性,调研了720份有效样本,基于三因素理论和结构模型定量研究节事价值共创参与度、原真性和地方依恋因素的非对称性及影响机理,得到如下结论:(1)因素聚类的非对称性是导致主体内行为策略非对称性的主因;(2)因素聚类的非对称性又是导致价值共创充要条件非对称性的主因;(3)主体间价值共创的充要条件影响共创路径的稳健性;(4)应重视研究价值共创机制中因素聚类、充要条件及共创路径稳健性之间的理论关系。     

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.     

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.     

Improving candy industry competitiveness: Retailers’ perception regarding customer satisfaction

This study aims to classify service quality elements in candy industry in order to determine their instrumentality to customer satisfaction. To address this purpose, a Fuzzy Kano questionnaire was distributed to 512 major retailers of candy products of four predominant candy companies in Iran. Subsequently, we calculated satisfaction increment index (SII) and dissatisfaction decrement index (DDI) for each of the quality elements. Brand name and quality are considered as must-be elements, while availability of credit purchases is considered as indifferent element by the majority of retailers. Eight out of 24 studied elements are found to be considered as attractive elements by majority of customers. Regular visits element ranks first in terms of satisfaction increment index (SII). This paper provides helpful insight for marketers to prioritize improvement of different quality elements. Therefore, this paper helps organizations to perceive their customers needs more thoroughly and improve their customer satisfaction policy.     

基于因子与聚类分析的江苏省邮政业务协同运作实效研究

中国邮政业务出现了发展缓慢、停滞甚至倒退的现象,邮政业务创新成为不可回避的现实问题。通过2013年江苏邮政通信企业统计数据,对江苏13个邮政局的邮政各类业务协同发展水平状况以及资产配置水平进行因子分析和聚类分析。得出江苏省邮政业务地区发展的层次分布情况,分析了业务发展差距的原因,并总结了邮政在协同发展邮政业务的经验。     

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。     

Trade-size clustering and price efficiency

Using a sample of 26 markets, this paper investigates if trade-size clustering affects price efficiency. Our results suggest that more clustering trades are associated with greater resemblance of a random walk, less pricing errors, and shorter price delays. Moreover, we examine three underlying mechanisms to explain how clustering improves efficiency. First, we show that clustering trades are informative, consistent with the idea that stealth traders leverage such tactics to convey private information to prices. Second, we discover that clustering trades are positively related to investor attention (stock liquidity), implying that informed clustering trades happen at the presence of enormous uninformed investors. High attention and liquid markets help reduce the trading friction, thereby prompting quick price adjustments to private information released by the stealth trading.     

下一代互联网:OpenFlow-Kmeans流表聚类算法

互联网的发展,对传输质量要求越来愈高,本文针对OpenFlow流表转发,提出并实现OpenFlow-Kmeans流表聚类转发算法,该算法提升准确率27.64%,实验表明,该算法能够满足复杂环境下,对流表的分类转发需求。