Rankings and university performance: A conditional multidimensional approach

Abstract

University rankings are the subject of a paradox: the more they are criticized by social scientists and experts on methodological grounds, the more they receive attention in policy making and the media. In this paper we attempt to give a contribution to the birth of a new generation of rankings, one that might improve on the current state of the art, by integrating new kind of information and using new ranking techniques. Our approach tries to overcome four main criticisms of university rankings, namely: monodimensionality; statistical robustness; dependence on university size and subject mix; lack of consideration of the input-output structure. We provide an illustration on European universities and conclude by pointing on the importance of investing in data integration and open data at European level both for research and for policy making. University rankings are the subject of a paradox: the more they are criticized by social scientists and experts on methodological grounds, the more they receive attention in policy making and the media. In this paper we attempt to give a contribution to the birth of a new generation of rankings, one that might improve on the current state of the art, by integrating new kind of information and using new ranking techniques. Our approach tries to overcome four main criticisms of university rankings, namely: monodimensionality; statistical robustness; dependence on university size and subject mix; lack of consideration of the input-output structure. We provide an illustration on European universities and conclude by pointing on the importance of investing in data integration and open data at European level both for research and for policy making. I N S T I T U T D E S T A T I S T I Q U E B I O S T A T I S T I Q U E E T S C I E N C E S A C T U A R I E L L E S ( I S B A )UNIVERSITÉ

CEO compensation and bank efficiency: An application of conditional nonparametric frontiers

“…Therefore we have to reduce the dimension in the input-output space and thus to gain precision and reliability in our analysis. As proposed by Bădin et al (2012) and Daraio et al (2015), we apply a variable reduction procedure and we replace the inputs and outputs by their best (non-centered) linear combinations (see for details Daraio and Simar, 2007b, pp. 148-150).…”

Research project grouping and ranking by using adaptive Mahalanobis clustering

“…The quality of applicants The quality of applicants 0.20 f 3 Research feasibility study Dissemination and utilization of research results 0.15 f 4 Financial plan Financial plan 0.10 f 5 Institutional support Institutional support 0.10 f 6 Inclusion of students Inclusion of students 0.15 The set of all positively assessed project proposals with corresponding data of the form (1) will be denoted by P. The set P needed to be grouped according to their quality and a decision should be made on which projects shall be financed.…”

“…A fairly large body of literature is dedicated to the assessment and ranking of research projects (see, for example, [3,9,11]) and ranking of departments, institutes and universities closely associated therewith (see, for example, [4,8,14]). Most approaches use different multi-criteria decision making methods, most frequently the well-known Analytic Hierarchy Process (AHP) [15].…”

“…For example, grouping a set of interested buyers of sports shoes with respect to age, education and purchasing power can be used to define the promotion policy of a manufacturer of sports shoes or grouping university students depending on the type of their previous education and the achieved GPA can be used to define the admissions policy of that university [4,8,14].…”

University Enrolment Intentions From Students’ Viewpoint

“…However, this study only selected three brand equity dimensions (brand awareness, brand association and perceived quality) which found applicable for the current study. In addition, one of the elements of brand attribute called university ranking is also used to explain the enrolment intentions in higher educational institution (Millot, 2015;Daraio et al, 2015).…”