Complex networks for benchmarking in global universities rankings
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Complex networks for benchmarking in global universities rankings Esteban Fernández Tuesta1 · Máxima Bolaños‑Pizarro2 · Daniel Pimentel Neves1 · Geziel Fernández3 · Justin Axel‑Berg4 Received: 29 January 2020 © Akadémiai Kiadó, Budapest, Hungary 2020
Abstract Finding a set of units that can serve as a reference for growth or improvement in positions within a ranking is not a simple task, since each ranking method can place the same unit in different positions and may even differ in relative position within the ranking. This study proposes a method that applies a combination of network analysis and efficiency methods to global university rankings. Complex networks allow the creation of a graph structure that selects a set of units that change positions in consecutive rankings and also the selection of the set of nodes that are linked with a selected node. For this new set, it is possible to calculate the efficiency level using Data Envelopment Analysis (DEA), from which the benchmarks of the indicators for each of the selected universities can be computed. The purpose of this paper is to develop a methodology to find a set of universities that compete with any university selected from those in the global university rankings, in particular ARWU, THE and QS. Moreover, this work also proposes to estimate the efficiency level of each university that competes with the selected university using the Data Envelopment Analysis methodology in order to establish benchmarks for each of the target Universities. This methodology is replicable for any university in any ranking or set of rankings. Given the high volatility of rankings, this process can serve university policy makers in selecting indicators to focus on for improved results in the short term. Keywords Global universities rankings · Research evaluation · Benchmarking · ARWU · THE · QS Mathematics Subject Classification 62-07 · 62-09 · 62F07 JEL Classification I21 · I23 · C67 · C50
* Máxima Bolaños‑Pizarro [email protected] Extended author information available on the last page of the article
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Vol.:(0123456789)
Scientometrics
Introduction Universities and Research Centers have long competed almost invisibly for prominent positions on the international stage. Student attraction, research funding, awards, and positive reputation within society are among the most intense fields of competition (Tuesta et al. 2019). With the appearance of the first global university ranking in 2003 by the Shanghai Jiao Tong University’s Institute of Higher Education (now Graduate School of Education) (Cheng and Liu 2007; Liu and Cheng 2005; Liu et al. 2005), followed by other rankings such as the Times Higher Education Supplement’s QS World University Ranking (Times QS ranking) (Buela-Casal et al. 2007) and the Leiden ranking in 2007 (Waltman et al. 2012). The grounds of competition shifted from local rivalries to an international arena. Many governments and institutions have been challenged to improve access to higher education for students from lower cultural capital gr
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