Ranking Iranian universities: an interpretative structural modeling approach

Mohammad Reza Zare Banadkouki, Mohammad Ali Vahdatzad (), Mohammad Saleh Owlia and Mohammad Mahdi Lotfi
Additional contact information
Mohammad Reza Zare Banadkouki: Meybod University
Mohammad Ali Vahdatzad: Yazd University
Mohammad Saleh Owlia: Yazd University
Mohammad Mahdi Lotfi: Yazd University

Scientometrics, 2018, vol. 117, issue 3, No 9, 1493-1512

Abstract: Abstract Ranking is widely considered to be an important tool for evaluating the performance, competitiveness, and success of academic institutions. An appropriate ranking system should evaluate the key missions of the higher education system in a way that helps to improve the leadership goals and activities carried out by the universities. Based on the concepts derived from the Iranian Higher Education Upstream Documents and Measures used internationally for university ranking, this study identifies 21 key measures that can be used in the ranking of Iranian universities. The measures are grouped into five categories: scientific infrastructure, scientific effectiveness, socio-cultural effectiveness, international interactions, and sustainability. Then, using the Interpretative Structural Modeling approach, the researchers develop a coherent rubric for establishing the ranking. The proposed conceptual model focuses primarily on the universities’ contribution to technological and scientific infrastructure, then secondarily on their contribution to scientific advancement and international interactions, and finally at a tertiary level on their socio-cultural effectiveness and sustainability.

Keywords: Higher education; Upstream documents; Measure; University rankings; Interpretive structural modeling (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-018-2946-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:117:y:2018:i:3:d:10.1007_s11192-018-2946-9

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-018-2946-9

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().