Tackling the heterogeneity of HEIs by combining different data sources and applying advanced conditional benchmarking techniques

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Tackling the heterogeneity of HEIs by combining different data sources and applying advanced conditional benchmarking techniques

Type: Article in monograph or in proceedings
Title: Tackling the heterogeneity of HEIs by combining different data sources and applying advanced conditional benchmarking techniques
Author: Daraio C.Gregori M.Catalano G.Moed H.F.
Journal Title: STI 2018 Conference Proceedings
Start Page: 535
End Page: 544
Publisher: Centre for Science and Technology Studies (CWTS)
Issue Date: 2018-09-11
Keywords: Scientometrics
Abstract: The assessment of the performance of Higher Education Institutions (HEIs) at the micro (institutional), meso (regional) and macro (country) level is an important and recurrent question in the higher education’s policy debate. However, the analysis of the performance of HE systems is far from being easy to deal with. One of the main critical issues to address properly the assessment of performance, in a multi-level (systemic) perspective, is the consideration of the heterogeneity of the HEIs involved. There are different sources of heterogeneity, including the mission, the national context, the presence or absence of medical schools, the legal status and the disciplinary orientation and degree of specialization. Among the heterogeneity factors of HEIs, disciplinary specialization or subject mix is considered one of the most relevant. This paper addresses the issue of heterogeneity in its multidimensional faces by adopting two approaches. The first is integrating heterogeneous sources of available data, and the second the application of advanced econometric techniques, which allow comparing or benchmarking HEIs by capturing observed and unobserved heterogeneity.
Handle: http://hdl.handle.net/1887/65361
 

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