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The purpose of this paper is to provide an outline of the major contributions in the literature on the determination of the least distance in data envelopment analysis (DEA). The focus herein is primarily on methodological developments. Specifically, attention is mainly paid to modeling aspects, computational features, the satisfaction of properties and duality. Finally, some promising avenues of future research on this topic are stated.

DEA is a methodology based on mathematical programming for the assessment of relative efficiency of a set of decision-making units (DMUs) that use several inputs to produce several outputs. DEA is classified in the literature as a non-parametric method because it does not assume a particular functional form for the underlying production function and presents, in this sense, some outstanding properties: the efficiency of firms may be evaluated independently on the market prices of the inputs used and outputs produced; it may be easily used with multiple inputs and outputs; a single score of efficiency for each assessed organization is obtained; this technique ranks organizations based on relative efficiency; and finally, it yields benchmarking information. DEA models provide both benchmarking information and efficiency scores for each of the evaluated units when it is applied to a dataset of observations and variables (inputs and outputs). Without a doubt, this benchmarking information gives DEA a distinct advantage over other efficiency methodologies, such as stochastic frontier analysis (SFA). Technical inefficiency is typically measured in DEA as the distance between the observed unit and a “benchmarking” target on the estimated piece-wise linear efficient frontier. The choice of this target is critical for assessing the potential performance of each DMU in the sample, as well as for providing information on how to increase its performance. However, traditional DEA models yield targets that are determined by the “furthest” efficient projection to the evaluated DMU. The projected point on the efficient frontier obtained as such may not be a representative projection for the judged unit, and consequently, some authors in the literature have suggested determining closest targets instead. The general argument behind this idea is that closer targets suggest directions of enhancement for the inputs and outputs of the inefficient units that may lead them to the efficiency with less effort. Indeed, authors like Aparicio et al. (2007) have shown, in an application on airlines, that it is possible to find substantial differences between the targets provided by applying the criterion used by the traditional DEA models, and those obtained when the criterion of closeness is utilized for determining projection points on the efficient frontier. The determination of closest targets is connected to the calculation of the least distance from the evaluated unit to the efficient frontier of the reference technology. In fact, the former is usually computed through solving mathematical programming models associated with minimizing some type of distance (e.g. Euclidean). In this particular respect, the main contribution in the literature is the paper by Briec (1998) on Hölder distance functions, where formally technical inefficiency to the “weakly” efficient frontier is defined through mathematical distances.

All the interesting features of the determination of closest targets from a benchmarking point of view have generated, in recent times, the increasing interest of researchers in the calculation of the least distance to evaluate technical inefficiency (Aparicio et al., 2014a). So, in this paper, we present a general classification of published contributions, mainly from a methodological perspective, and additionally, we indicate avenues for further research on this topic. The approaches that we cite in this paper differ in the way that the idea of similarity is made operative. Similarity is, in this sense, implemented as the closeness between the values of the inputs and/or outputs of the assessed units and those of the obtained projections on the frontier of the reference production possibility set. Similarity may be measured through multiple distances and efficiency measures. In turn, the aim is to globally minimize DEA model slacks to determine the closest efficient targets. However, as we will show later in the text, minimizing a mathematical distance in DEA is not an easy task, as it is equivalent to minimizing the distance to the complement of a polyhedral set, which is not a convex set. This complexity will justify the existence of different alternatives for solving these types of models.

As we are aware, this is the first survey in this topic.

The aim of this paper is to determine the main reasons that lead to information systems outsourcing, the reservations that are initially present in front of this kind of contract and the factors considered necessary for the success of outsourcing in the case of Spanish public universities. With this aim, a survey has been made among information systems managers in those universities. The results show the possibility of establishing a typology of universities depending on the position they have adopted with respect to outsourcing.

Motivated by a lack of evidence regarding the effect of migration on entrepreneurship in a highly informal country, such as Colombia, this paper has a twofold purpose. First, it explores how Venezuelan immigration affects entrepreneurial activity in Colombian regions. Second, it intends to shed light on this relationship, by distinguishing between formal and informal sectors.

With a sample of 1,776,063 individuals, from the Labor Survey Gran Encuesta Integrada de Hogares (GEIH) from the Departamento Administrativo Nacional de Estadística (DANE), the authors employ an instrumental variable approach to account for the selection of immigrants into locations with more or less desirable conditions.

The results suggest Venezuelan immigration positively influences self-employment and own-account workers, but negatively affects employers. However, once these immigrants proliferate in the informal sector, the effects increase.

This paper brings new insights into the intersection between immigration, unofficial economies, and entrepreneurship. First, while the prior literature focuses on migration from developing to developed countries, migratory flows between developing economies and its effects on local entrepreneurial activity remain unexplored. Second, although informality is mostly common in developing countries, little (albeit growing) evidence of its role in the relationship between migration and entrepreneurship research exists. Finally, the authors bring together these two phenomena to enhance our understanding of different types of entrepreneurial activities when immigration and informality take place. Policy implications are derived from these insights.

This study aims to explore how local authority child and family practitioners understood and implement the contextual safeguarding approach focusing, in particular, on what practitioners felt supported and hindered implementation.

This qualitative study drew upon semi-structured interviews and focus groups to explore the perspectives of 18 frontline workers, team managers and senior managers in a London authority. The transcribed accounts were analysed using thematic analysis.

Participants reported that the strain on services because of sustained budget cuts was overwhelming, even without the additional challenge of implementing this new approach. Further challenges in relation to implementation included parental-capacity focused legislation and conflicting perspectives between stakeholders. This study recommends that proper funding must be committed to safeguarding partnerships if contextual safeguarding is to be successfully implemented. Additionally, child protection practitioners should aim to develop a collaborative and child-welfare focused network of community agencies and organisations if young people are to be safeguarded in their communities.

As the sample required specialist knowledge to participate in this study, this study cannot claim that the findings are generalisable to all social workers.

To the best of the authors’ knowledge, this is the first external evaluation of the implementation of the contextual safeguarding approach in a local authority independent of the contextual safeguarding team at the University of Bedfordshire since the evaluation of Hackney.

Google Scholar Citations (GSC) provides an institutional affiliation link which groups together authors who belong to the same institution. The purpose of this paper is to ascertain whether this feature is able to identify and normalize all the institutions entered by the authors, and whether it is able to assign all researchers to their own institution correctly.

Systematic queries to GSC’s internal search box were performed under two different forms (institution name and institutional e-mail web domain) in September 2015. The whole Spanish academic system (82 institutions) was used as a test. Additionally, specific searches to companies (Google) and world-class universities were performed to identify and classify potential errors in the functioning of the feature.

Although the affiliation tool works well for most institutions, it is unable to detect all existing institutions in the database, and it is not always able to create a unique standardized entry for each institution. Additionally, it also fails to group all the authors who belong to the same institution. A wide variety of errors have been identified and classified.

Even though the analyzed sample is good enough to empirically answer the research questions initially proposed, a more comprehensive study should be performed to calibrate the real volume of the errors.

The discovered affiliation link errors prevent institutions from being able to access the profiles of all their respective authors using the institutions lists offered by GSC. Additionally, it introduces a shortcoming in the navigation features of Google Scholar which may impair web user experience.

Some institutions (mainly universities) are under-represented in the affiliation feature provided by GSC. This fact might jeopardize the visibility of institutions as well as the use of this feature in bibliometric or webometric analyses.

This work proves inconsistencies in the affiliation feature provided by GSC. A whole national university system is systematically analyzed and several queries have been used to reveal errors in its functioning. The completeness of the errors identified and the empirical data examined are the most exhaustive to date regarding this topic. Finally, some recommendations about how to correctly fill in the affiliation data (both for authors and institutions) and how to improve this feature are provided as well.

The purpose of this paper is to provide a better understanding of the links between labor market conditions and academic performance by disentangling the effects of unemployment. The contribution of this study is, therefore, threefold: first, it provides new evidence on the link between labor market conditions and educational decisions; second, it quantifies separately the two separate effects of unemployment on academic performance at age 15; and third, it analyses heterogeneous effects of the “family” and “local labor market” – proxied through the unemployment rate of the school community – effects.

The analysis of the impact of unemployment on academic performance is performed through hierarchical linear regressions.

The results show that academic performance at age 15 is affected by labor market conditions, and, at the same time, previous performance determines future educational decisions. Thus, these results highlight the sensitivity of students’ educational decisions and academic performance to shifts in the labor market.

This suggests that strategies aimed at reducing early school dropout rates should not be restricted solely to the education system. In other words, school failure is not only dependent on schools and, hence, on education policies.

This paper contributes to the existing literature by providing new evidence on the relationship between short-term labor market dynamics and academic performance. More specifically, this paper represents a significant step forward in comparison to the previous literature as it has provided responses to three key questions faced by countries with high unemployment and high early school dropout.

The granular structure of a grinding wheel determines its performance remarkably when grinding. Nowadays, grinding wheels are man-made porous conglomerates of hard abrasive grains bonded with a binder. As an engineered material, it would be interesting to foresee the behaviour of the wheel, but it is hindered under its complex heterogeneous nature. Recently, some models based on the discrete element method (DEM) have been presented to model the grinding wheel. This paper aims to identify and propose a framework that must comply with such models and to identify new applications for DEM models in grinding.

First, the characteristics of the grinding wheel are described. In this way, the framework of DEM models of a grinding wheel material is developed, reproducing both the granular morphology and stiffness.

The paper asserts a promising future that provides the DEM in the modelling of grinding.

The potential of DEM in grinding is analysed, proposing new applications. It can be used as topography model, which can also model the stiffness. In addition, DEM opens a new interesting research line: the modelling of the grit breakout. It draws up the development of essential dressing and wear models.