Evaluation of performance of European cities with the aim to promote quality of life improvements

This paper explores the possibilities presented by DEA to assess quality of life and evaluate the performance of city managers in what concerns the promotion of urban quality of life. Using the data provided by the Urban Audit program, from the European Union, we defined the city profile regarding quality of life for 206 cities. Two approaches are presented: the construction of a composite indicator of quality of life and the assessment of local management performance, contextualised by the GDP per capita to measure the ability of local authorities to promote quality of life given the economic condition of the country. The results identify the cities with urban best practices and present a model of intervention for the cities considered inefficient, based on benchmarking principles.     

Criteria for the selection of foster families and monitoring of placements.: Comparative study of the application of the Casey Foster Applicant Inventory-Applicant Version (CFAI-A)

Based on a literature review, this article frames different stages of the foster care process, identifying a set of standardized measures in the American and Portuguese contexts which, if implemented, could contribute towards higher levels of foster success. The article continues with the presentation of a comparative study, based on the application of the Casey Foster Applicant Inventory-Applicant Version (CFAI-A) questionnaire, in the aforementioned contexts. Taking a comparative analyses of CFAI-A's psychometric characteristics in four different samples as a starting point, one discovered that despite the fact that the questionnaire was adapted to Portuguese reality, it kept the quality values presented on the American samples. It specifically shows significant values regarding reliability and validity. This questionnaire, which aims to assess the potential of foster families, also supports the technical staff's decision making process regarding the monitoring and support of foster families, while it also promotes a better decision in the placement process towards the child's integration and development.     

The Cost of Not Knowing the Score: Self-Estimated Credit Scores and Financial Outcomes

This study analyzes consumers’ knowledge of their own credit situation and tests whether a lack of knowledge affects financial outcomes. The unique dataset from survey and credit report data includes self-estimates of credit scores and actual scores from a low-to-moderate income sample. We argue and show empirically that many respondents don’t know their credit score and generally underestimate their creditworthiness. Furthermore, our evidence suggests that this biased self-assessment may explain differences in perceived credit constraints and credit contracts, specifically credit card interest rates. Our research suggests that an important aspect of financial literacy is self-assessment, and that it is important to encourage consumers to regularly check their credit reports and scores so as to better understand their actual creditworthiness.     

Reverse logistics drivers: empirical evidence from a case study in an emerging economy

Academic and corporate interest in reverse logistics (RL) has risen considerably in recent years. In this context, the objective of this study was to identify the drivers that enable RL practice in an emerging economy. Firstly, international peer-reviewed publications on RL were used to develop a RL environment framework representing the main RL internal and external influences. Secondly, a case-based research was conducted in a large manufacturing company located in Southern Brazil. The results indicated that the most cited driver in the RL literature, the government and legislation, was not a main influence on the studied company. Environmental legislation is still limited in the country and struggles to provide incentives to increase materials recycling. An economic factor related to materials value recovery was also found to drive the backward flow. Finally, knowledge of the RL driving forces may support industries to better implement and manage reverse flows and to bridge the gap between existing and future solutions for reverse supply chains.     

Two-level network design with intermediate facilities: An application to electrical distribution systems

We consider the two-level network design problem with intermediate facilities. This problem consists of designing a minimum cost network respecting some requirements, usually described in terms of the network topology or in terms of a desired flow of commodities between source and destination vertices. Each selected link must receive one of two types of edge facilities and the connection of different edge facilities requires a costly and capacitated vertex facility. We propose a hybrid decomposition approach which heuristically obtains tentative solutions for the vertex facilities number and location and use these solutions to limit the computational burden of a branch-and-cut algorithm. We test our method on instances of the power system secondary distribution network design problem. The results show that the method is efficient both in terms of solution quality and computational times.     

Analysis of bivariate dichotomous data from a stratified two-stage cluster sample

In the health and social sciences, researchers often encounter categorical data for which complexities come from a nested hierarchy and/or cross-classification for the sampling structure. A common feature of these studies is a non-standard data structure with repeated measurements which may have some degree of clustering. In this paper, methodology is presented for the joint estimation of quantities of interest in the context of a stratified two-stage sample with bivariate dichotomous data. These quantities are the mean value π of an observed dichotomous response for a certain condition or time-point and a set of correlation coefficients for intra-cluster association for each condition or time period and for inter-condition correlation within and among clusters. The methodology uses the cluster means and pairwise joint probability parameters from each cluster. They together provide appropriate information across clusters for the estimation of the correlation coefficients.     

The healthcare supply network: current state of the literature and research opportunities

Abstract

This literature review maps recent studies addressing supply chain management (SCM) in the healthcare sector through a systematic approach that synthesises 74 empirical studies (2006–2016). Our approach adopts a network lens to map the literature and offers key contributions to the field. First, we show that there is a lack of network level studies. Second, there is an imbalance of research attention regarding the various types of supply, namely health services, medicines, medical supplies and blood supply. Third, we underline the advantages of the network lens, indicating network actors and flows between those actors that need further research. Fourth, we show an alarming lack of theoretical lens in healthcare SCM studies and draw attention to the fact that even when explicitly adopting a theory, some studies show inconsistencies between theoretical lens and level of analysis. Ultimately, we offer a map of future research for healthcare SCM through a network lens in order to improve the understanding the complexities of the healthcare sector.     

Catching a glimpse: Corona‐life and its micro‐politics in academia

The spread of COVID‐19 acutely challenges and affects not just economic markets, demographic statistics and healthcare systems, but indeed also the politics of organizing and becoming in a new everyday life of academia emerging in our homes. Through a collage of stories, snapshots, vignettes, photos and other reflections of everyday life, this collective contribution is catching a glimpse of corona‐life and its micro‐politics of multiple, often contradicting claims on practices as many of us live, work and care at home. It embodies concerns, dreams, anger, hope, numbness, passion and much more emerging amongst academics from across the world in response to the crisis. As such, this piece manifests a shared need to — together, apart — enact and explore constitutive relations of resistance, care and solidarity in these dis/organizing times of contested spaces, identities and agencies as we are living–working–caring at home during lockdowns.     

CO-tucker: a new method for the simultaneous analysis of a sequence of paired tables

Relationships between species and their environment are a key component to understand ecological communities. Usually, this kind of data are repeated over time or space for communities and their environment, which leads to a sequence of pairs of ecological tables, i.e. multi-way matrices. This work proposes a new method which is a combined approach of STATICO and Tucker3 techniques and deals to the problem of describing not only the stable part of the dynamics of structure–function relationships between communities and their environment (in different locations and/or at different times), but also the interactions and changes associated with the ecosystems’ dynamics. At the same time, emphasis is given to the comparison with the STATICO method on the same (real) data set, where advantages and drawbacks are explored and discussed. Thus, this study produces a general methodological framework and develops a new technique to facilitate the use of these practices by researchers. Furthermore, from this first approach with estuarine environmental data one of the major advantages of modeling ecological data sets with the CO-TUCKER model is the gain in interpretability.     

Histogram estimation of radon-nikodym derivatives for strong mixing data

Nonparametric inference for point processes is discussed by way of histograms, which provide a nice tool for the analysis of on-line data. The construction of histograms depends on a sequence of partitions, which we take tc be nonenibedded to allow partitions with sets of equal measure. This presents some theoretical problems, which are addressed with an assumption on the decomposition of second order moments. In another direction, we drop the usual independence assumption on the sample, replacing it by a strong mixing assumption. Under this setting, we study the convergence of the histogram in probability, which depends on approximation conditions between the distributions of random pairs and the product of their marginal distributions, and^almost completely, which is based on the decomposition of the second order moments. This last convergence is stated on two versions according to the assumption of Laplace transforms or the Cramer moment conditions. These are somewhat stronger, but enable us to recover the usual condition on the decrease rate of sets on each partition. In the final section we prove that the finite dimensional distributions converge in distribution to a Gaussian centered vector with a specified covariance.