Identifying Systemically Important Banks: A temporal approach for macroprudential policies

Contrary to the general belief, systemic risk does not only regard the risk posed by balance sheet relationships and interdependencies among institutions. It also features a temporal dimension related to the inappropriate responses of financial market participants to changes in risk over time. This paper proposes a method to simultaneously address the cross-sectional and the time dimension in which systemic risk materializes. The method is based on the TOPHITS algorithm. It provides three scores, namely borrowing, lending and time scores: the first two represent the systemic importance of the borrowing and the lending activity associated with each financial institution,while the third represents an empirical Early Warning Signal of the financial crisis. Our findings reveal that the identification of the time score as an indicator for an incoming market distress could be relevant to design macro prudential policies.     

Delay causes analysis in complex construction projects: a Semantic Network Analysis approach

Delays are among the most crucial adversaries to the success and performance of construction projects, making delay analysis and management a critical task for project managers. This task will be highly complicated in large-scale projects such as construction, which usually consist of a complex network of heterogeneous entities in continuous interaction. Traditional approaches and methods for the analysis of delays and their causes have been criticised for their ability to handle complex projects, and for considering the interrelationships between delay causes. Addressing this gap, this research introduces an alternative approach for delay causes analysis by adopting Semantic Network Analysis (SNA) method. The paper reports the results from an investigation of delays in construction projects in the Oil-Gas-Petrochemical sector using SNA. The method’s capacity to identify and rank delay causes, which can assist managers in selecting appropriate measures for eliminating them, are empirically examined and discussed. The paper argues that SNA leads to a more comprehensive understanding of the main causes of delay in large and complex projects, allowing a better identification and mapping of the interrelationships between these discrete factors.     

The embeddedness of organizational performance: Multiple Membership Multiple Classification Models for the analysis of multilevel networks

We present a Multiple Membership Multiple Classification (MMMC) model for analysing variation in the performance of organizational sub-units embedded in a multilevel network. The model postulates that the performance of organizational sub-units varies across network levels defined in terms of: (i) direct relations between organizational sub-units; (ii) relations between organizations containing the sub-units, and (iii) cross-level relations between sub-units and organizations. We demonstrate the empirical merits of the model in an analysis of inter-hospital patient mobility within a regional community of health care organizations. In the empirical case study we develop, organizational sub-units are departments of emergency medicine (EDs) located within hospitals (organizations). Networks within and across levels are delineated in terms of patient transfer relations between EDs (lower-level, emergency transfers), hospitals (higher-level, elective transfers), and between EDs and hospitals (cross-level, non-emergency transfers). Our main analytical objective is to examine the association of these interdependent and partially nested levels of action with variation in waiting time among EDs – one of the most commonly adopted and accepted measures of ED performance. We find evidence that variation in ED waiting time is associated with various components of the multilevel network in which the EDs are embedded. Before allowing for various characteristics of EDs and the hospitals in which they are located, we find, for the null models, that most of the network variation is at the hospital level. After adding these characteristics to the model, we find that hospital capacity and ED uncertainty are significantly associated with ED waiting time. We also find that the overall variation in ED waiting time is reduced to less than a half of its estimated value from the null models, and that a greater share of the residual network variation for these models is at the ED level and cross level, rather than the hospital level. This suggests that the covariates explain some of the network variation, and shift the relative share of residual variation away from hospital networks. We discuss further extensions to the model for more general analyses of multilevel network dependencies in variables of interest for the lower level nodes of these social structures.     

Learning from service users’ involvement: a research about changing stigmatizing attitudes in social work students

Abstract

Stigmatizing attitudes can create barriers to forming partnership with service users and to developing people’s empowerment. So, social work education must help students overcome their stigmatizing attitudes. A useful strategy for bringing about changes is service users’ and carers’ involvement in social work education, providing students with direct exposure to stigmatized people in roles that emphasize their humanity and strengths, rather than their deficits. The present study assessed the impact of a one-day meeting with service users and carers members of self-help and mutual-aid groups on freshman social work students. Students completed an adapted version of Attitudes to Mental Illness Questionnaire before and after the meeting, and answered several qualitative questions. Data comparisons suggest that after face-to-face contact with service users and carers, social work students showed reduced stigmatizing attitudes. Implications for further research and social work education are discussed.     

Whom Do Centenarians Rely on for Support? Findings From the Second Heidelberg Centenarian Study

ABSTRACT

This paper provides a detailed picture of the sources and types of informal support available to centenarians, depending on their housing and care arrangements. Participants were 112 centenarians and 96 primary contacts of centenarians enrolled in the population-based Second Heidelberg Centenarian Study. Findings indicate that children of centenarians were their primary source of support in daily life. Those without living children had overall less help. Most frequently reported was help with administrative tasks, regardless of centenarians’ residence or living arrangement. All other types of help (e.g., with activities of daily living and housework) were reported by about one-third and were mostly provided by children; centenarians without children were more likely to have friends/neighbors involved in some of these tasks. The one category reported by a third of the centenarians regardless of residence, living arrangements, or presence of a child was help with socializing/companionship. Findings constitute an important step toward identifying and meeting the support needs of centenarians and their families. Policy implications are discussed.     

基于行动者网络理论的三网融合发展战略研究

行动者网络理论为三网融合的发展提供了一种新视角和新的分析工具。研究表明:三网融合既是技术创新和市场竞争推动的结果,也是政府管制的结果;作为核心行动者,政府应采取合理的手段调整行动主体的行为,引导其积极加入到网络中;在多异质行动者参与的三网融合博弈进程,由于诸多利益因素的存在,网络有可能重构,甚至瓦解。我国应从制定合理的发展路径和科学的实施步骤、完善政策资源供给和重视各方利益整合等方面加强三网融合发展战略指导。     

k-means-based algorithm for blockmodeling linked networks

The paper presents a k-means-based algorithm for blockmodeling linked networks where linked networks are defined as a collection of one-mode and two-mode networks in which units from different one-mode networks are connected through two-mode networks. The reason for this is that a faster algorithm is needed for blockmodeling linked networks that can better scale to larger networks. Examples of linked networks include multilevel networks, dynamic networks, dynamic multilevel networks, and meta-networks. Generalized blockmodeling has been developed for linked/multilevel networks, yet the generalized blockmodeling approach is too slow for analyzing larger networks. Therefore, the flexibility of generalized blockmodeling is sacrificed for the speed of k-means-based approaches, thus allowing the analysis of larger networks. The presented algorithm is based on the two-mode k-means (or KL-means) algorithm for two-mode networks or matrices. As a side product, an algorithm for one-mode blockmodeling of one-mode networks is presented. The algorithm’s use on a dynamic multilevel network with more than 400 units is presented. A situation study is also conducted which shows that k-means based algorithms are superior to relocation algorithm-based methods for larger networks (e.g. larger than 800 units) and never much worse.     

The potential of online social networking data for augmenting the study of high-risk personal networks among young men who have sex with men at-risk for HIV

Capturing dynamics in high-risk personal networks is essential for preventing HIV transmission. Online social networking data offer incentive to augment traditional selfreported approaches for network enumeration. To explore what online networks reveal about dynamics among high-risk associates, we examine the relationship between egocentric confidant and sex networks and personal Facebook friendship networks of a cohort of young Black men who have sex with men. Although overlap exists between self-reported and Facebook associates, the stabilities of each were unrelated. Confidants who were also Facebook friends with a respondent were, however, more likely to be retained. Thus, Facebook networks contain stable confidants.     

Impact of support networks for breastfeeding: A multicentre study

Background

The rates of breastfeeding worldwide are slowly improving since 1996. Europe is still trailing behind the global breastfeeding incidence and prevalence rates. Thus, breastfeeding promotion, protection, prolongation and support have become an important challenge as breastfeeding sharply decreases in the first six months of life.

Mediation Role of Dyadic Coping on Parenting Stress and Relational Resilience in Couples

This study aims to explore the mediating role of dyadic coping between relational resilience and parenting stress on married couples. The study participants comprised 229 married couples with at least one child and who have had a major life event. The relational resilience scale, parenting stress inventory, dyadic coping scale and personal information, and life events forms were used to collect data for this study. Data were analyzed with the actor–partner interdependence mediation model. The results revealed that dyadic coping actor–partner effects did not mediate between relational resilience and parenting stress. The results were discussed in relation to the social-ecological model and relevant literature. Based on the current findings, recommendations and implications for further research and practice were also proposed.