In this paper we propose a synthetic indicator for evaluating Italian universities’ scientific research using Scimago Institutions Ranking (SIR) 2014 data. It is an annual report published by Scimago Lab., a Spanish company which produces some bibliometric indicators using Scopus databank, an Elsevier product, for several kinds of research Institutions. Differently from other world university research ranking, such as University Ranking by Academic Performance (URAP) or Performance Ranking of Scientific Papers for World Universities (NTUR), SIR doesn’t supply a league table of Institutions, preferring not to carry on an indicators aggregation to obtain a global ranking. Starting from some indicators computed by SIR, after having analysed the distribution shape, fitted parameters of some statistical models, calculated an appropriate standardization, we aggregate the indicators to get a Synthetic Indicator (from now, SI) of research evaluation. The obtained synthetic indicator has been used to rank Italian Higher Education Institutions (from now, HEIs). This ranking has been compared first with the ranking of the National Agency for the Evaluation of Universities and Research Institutes (ANVUR), based on the Evaluation of Research Quality (VRQ 2004-2010) results, and then with the ranking based on the assignments of the competitive allocation model (research share of FFO) yearly attributed to the Italian HEIs by the Ministry of University and Research (MIUR). The results of the analysis show a moderate positive correlation between SI and the VQR 2004-2010 indicators, the standardized mark (r=0,543) and FFO per capita (r=0,487). The original contributions of the paper are i) the creation of a Synthetic Indicator, with a Gaussian distribution, summarizing the SIR variables; ii) the highlighting of a convergence between ANVUR evaluation, based on peer to peer and bibliometric analysis but using only few publications, and the analysis proposed in this paper, which uses bibliometric data from Scopus, but related to all the publications in the same period.

In the last decade, the world of academia has faced a period of strong/severe resource constraints/reduction. At the same time, there has been an increasing interest of the Ministry of Research (MIUR) in designing methods to evaluate University performance in order to rank efficient Universities and to reduce potential inefficiencies, so providing the administration authorities with measures that may be used for an optimal resources allocation. With this increasing interest in University performance, a wide academic debate has emerged about the models and measures adopted, based on several quantitative measures of inputs that, sometimes, have been borrowed from the Italian Health organizational model, much more consolidated in its experience. We cite, for all, the students evaluation in terms of standard cost within the resources allocation model introduced last year, and the “customers” satisfaction measurement, whose main goal is to provide an independent system of regular evaluation of student satisfaction and of the University teaching quality. The aim of this paper is to deal with the students opinion about the quality of teaching, as perceived as “users” while attending their academic courses in the health area. We agree with the statement that the high quality of healthcare services provided to the community depends also on the main factor, the human capital involved in supplying them. In Italy, the academic courses belonging to the health area provide the access to a limited number of students who passed a hard selection. This rule was introduced by the law n.264/1999 to harmonize the Italian University system to the European one in order to guarantee the high quality of students higher education in this field. And that quality of the education, according to the law, depended on the places in the classrooms, on the equipment and scientific laboratories for teaching; on the teaching staff and technical personnel; on the assistance and tutoring service, on the apprenticeships and places available in laboratories and classrooms equipped for practical, on the presence of technical-practical and laboratory activities. For the Government, that is the main donor for Italian Universities, the level of student satisfaction is of great importance to evaluate the quality of their courses. It is actually measured by different points of view as quality of teachers, teaching materials and logistical support. The law n.370/1999 states that Italian Universities have to systematically carry out a survey on the satisfaction of “teaching” of their students; this survey is named Opinione degli studenti . Recently, the National Agency of Evaluation (ANVUR) has been entrusted to oversee the related processes. Since 2013, the University of Bari, like the other Universities, has adopted the ANVUR guidelines.

Kakwani suggested a decomposition of Gini concentration ratio by components in which the concentration ratio of the whole variable is a linear combination of the concentration ratios of the components, the weights being the products of the shares of the same components and some correlation coefficients. In this note we show that in the case of some null observations of the component, which is very common in applications, each of the three factors of the decomposition can be split in two parts, one due to positive observations and another due to null observations. This paper gives a more complete interpretation of the results of the applications of Kakwani decomposition.

The paper aims at analyzing, in a retrospective way, the performance of a cohort of 13,452 students, who, in the academic year 2008-09, were enrolled for a one year more than the scheduled years to take their degree, to examine their university behavior depending on the events happened from the beginning of their university career (the main career events may be: transfer to another university, abandon, change of course, to take a degree). Through the use of segmentation trees, we would like to verify the influence of some explanatory variables (sex, type of faculty and course of study, type of previous diploma) on students’ behavior, in order to track some student profiles, based on different events. Some indicators will be calculated (eg. drop-out rate, graduation rate, etc.) and they will be put in relation with some quantitative explanatory variables (maturity grade, average exams grade) in order to verify whether the performances during the university period and, before, at the college, influence the student behavior, so they can be taken as a predictor.

We carry out an end-to-end bibliometric performance analysis of Italian higher education institutions (HEIs) using data from the latest (2014) release of the Scimago Institutions Rankings (SIR). We track six variables through the following chain: inputoutput-excellence-outcome-productivity. Factor analysis (FA) then allows us to ascertain that the primary indicators are orthogonal and represent a quantity and a quality/productivity dimension respectively. Productivity of research is computed either in term of output or outcome. The quantity dimension is size-dependent while the quality and productivity dimension is size independent. We also carry out an analysis of performance according to the geographical area where Italian HEIs are located.

La presente nota si propone di illustrare il procedimento mediante il quale ottenere l’espressione compatta dell’indice di dissomiglianza di Gini come misura globale della distanza tra distribuzioni normali, di medie diverse e di varianze diverse. L’applicazione dimostra come tale formula dell’indice semplice di dissomiglianza per distribuzioni normali sia di agevolissimo calcolo

Nel lavoro è stato analizzato il fenomeno dell'abbandono degli studi universitari, partendo da una particolare definizione del collettivo degli studenti rinunciatari e prendendo in considerazione le motivazioni alla base della loro scelta, per individuare le principali cause dell'abbandono ed intervenire sulle eventuali inefficienze imputabili all'ateneo.

Nel presente contributo si intende esaminare le modalità di valutazione dell’attività di ricerca degli Atenei proposte da VIA-Academy e da Scival Spotlight di Elsevier mettendone in evidenza aspetti positivi e criticità, anche in relazione ai risultati della valutazione della ricerca VTR 2001-2003 condotta dal Comitato di Indirizzo per la Valutazione della Ricerca (CIVR). Dalla fine del 2010 la Virtual Italian Academy (VIA-Academy) ha fornito il proprio contributo al dibattito sulla valutazione della ricerca scientifica in Italia stilando una graduatoria, costantemente aggiornata, delle istituzioni di ricerca italiane (Università ed altri enti di ricerca) utilizzando vari indicatori bibliometrici, ed in particolare l’indice di Hirsch; Scival Spotlight di Elsevier punta allo stesso obiettivo analizzando i paper accademici presenti nella banca dati Scopus. Entrambi gli approcci si inseriscono nell’alveo di altre proposte di valutazione degli atenei a livello internazionale come Arwu Shanghai, Times Higher Education World University Rankings, Scimago e QS World University Rankings.