University evaluation is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university activities and performances are often measured by means of indicator variables. The available information are then summarized to respond to different aims. We argue that the evaluation process is a complex phenomenon that cannot be addressed by a simple descriptive approach. In this paper, we used a model-based approach to account for association between indicators and similarities among the observed universities. We examine faculty-level data collected from different sources, covering 55 Italian Economics faculties in the academic year 2009/2010. Making use of a clustering methodology, we introduce a biclustering model that accounts for both homogeneity/heterogeneity among faculties and correlations between indicators. Our results show that there are two substantial different performances between universities which can be strictly related to the nature of the institutions, namely the Private and Public profiles. Each of the two groups has its own peculiar features and its own group-specific list of priorities, strengths and weaknesses. Thus, we suggest that caution should be used in interpreting standard university rankings as they generally do not account for the complex structure of the data.

A biclustering approach to university performances: an Italian case study / Raponi, Valentina; Martella, Francesca; A., Maruotti. - In: JOURNAL OF APPLIED STATISTICS. - ISSN 0266-4763. - STAMPA. - 43:1(2016), pp. 31-45. [10.1080/02664763.2015.1009005]

A biclustering approach to university performances: an Italian case study

RAPONI, VALENTINA;MARTELLA, Francesca;
2016

Abstract

University evaluation is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university activities and performances are often measured by means of indicator variables. The available information are then summarized to respond to different aims. We argue that the evaluation process is a complex phenomenon that cannot be addressed by a simple descriptive approach. In this paper, we used a model-based approach to account for association between indicators and similarities among the observed universities. We examine faculty-level data collected from different sources, covering 55 Italian Economics faculties in the academic year 2009/2010. Making use of a clustering methodology, we introduce a biclustering model that accounts for both homogeneity/heterogeneity among faculties and correlations between indicators. Our results show that there are two substantial different performances between universities which can be strictly related to the nature of the institutions, namely the Private and Public profiles. Each of the two groups has its own peculiar features and its own group-specific list of priorities, strengths and weaknesses. Thus, we suggest that caution should be used in interpreting standard university rankings as they generally do not account for the complex structure of the data.
2016
biclustering; university performance; Gaussian mixture; factor model
01 Pubblicazione su rivista::01a Articolo in rivista
A biclustering approach to university performances: an Italian case study / Raponi, Valentina; Martella, Francesca; A., Maruotti. - In: JOURNAL OF APPLIED STATISTICS. - ISSN 0266-4763. - STAMPA. - 43:1(2016), pp. 31-45. [10.1080/02664763.2015.1009005]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/713060
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