Chapter 1 Introduction

The complex reform process pertaining to the governance of the Italian University system (such as the progressive financial autonomy of Universities and the review of academic curricula) also increased competition between the universities.

Every year, before the first academic registration of students, the Censis Institute, other research institutions and organizations (including media) produce university rankings. Each of them takes into account several aspects referring to the university’s organization, reputation and student benefits, or the actual characteristics of students. Some of them also consider the employment rate of graduates. Generally speaking, these rankings are widely disputed because they do not issue a judgment as to which university is “better”. In fact, rankings are linked to the indicators chosen and the method used for summarizing them.

The aim of this paper is to propose some further rankings for a number of Italian universities, considering certain characteristics of graduates, from 2006 to 2011 (prior to and during the economic crisis).

We focus our attention on mismatching and overeducation because several studies have noted that as a result of the 2008 economic crisis, there has been a tendency towards higher over qualification rates across Europe [7,11]. Moreover, many schol­ars have found that job-educational mismatch (education mismatch) is a more promi­nent problem among graduates than skill shortage or skill gap [2,4,10]. In Italy, the percentage of overeducated medium-skilled employees in 2013 was 36%, while it was 19% in the EU28. In the same year, we observe a lower difference between the Italian rate and the EU28 if we consider the percentage of mismatched employees (36% for Italy and 27% for the EU28 [6, 9]).

In order to rank the performances of a number of Italian Universities, we adopted a method that allows us to consider different solutions according to three different scenarios (called Neutral, University and Job); three different roles ascribed to inclu­sion or exclusion of mismatching and overeducation rates (key criteria) in a pre-crisis period (2006) and during a crisis period (2011).

The scenarios refer to different weights linked to the covariates.

R. Allegro and O. Giambalvo, University Performance Before and During Economic Crises, UNIPA Springer Series, https://doi.org/10.1007/978-3-030-36142-6_1 weight to graduate characteristics with reference to job placement (objective and subjective covariates). Every scenario is compared with a neutral one (Scenario N), where the indicators are considered to have the same weight. The analysis is repro­duced in relation to the field of study. Data referring to Economics and Statistics (ES) and Political and Social Sciences graduates (PSS) are considered because they produce different employment rates [14, 15]. This choice is suggested by the lit­erature; many scholars [3, 8, 16] underline the different and significant effects on overeducation and mismatching in changing the fields of study.

The analysis was performed using a multi-criteria model approach [12, 13]. The Electre III model (ELimination Et Choix TRaduisant la REalite [12]), a class of multi-criteria models, which aims at constructing an outranking relationship, was adopted [1, 5]. These models were used for the first time in operational research. Recently, they are being adopted more and more frequently in many other fields.

The Electre model uses data from the STELLA (Statistiche in tema di laureati e lavoro) post-graduation placement sampling surveys conducted by the CILEA consortium in 2007 and 2012, interviewing graduates in 2008 and 2013.

The outline of this paper is as follows. Chapter 2 deals with mismatching and overeducation, showing their importance in analysing graduate placement results. Chapter 3 describes the methodology used for the analysis. Chapter 4 presents the data and Chap. 5 discusses the main results. A number of comments and conclusions are presented in Chap. 6.