Unveiling Challenges to Management Control Systems in Higher Education: A Systematic Literature Review

Maya Lambovska () and Antoaneta Angelova-Stanimirova
Additional contact information
Maya Lambovska: Department of Management, University of National and World Economy, 1700 Sofia, Bulgaria
Antoaneta Angelova-Stanimirova: Department of Financial Control, University of National and World Economy, 1700 Sofia, Bulgaria

World, 2025, vol. 6, issue 3, 1-18

Abstract: In light of constrained resources and the rise of digitalisation in higher education, management control systems (MCSs) have emerged as essential tools for university management because of their integrity, flexibility, and effectiveness. This paper aims to elucidate the current challenges in the implementation and functioning of MCSs in higher education. To this end, a systematic literature review was undertaken in the Scopus and Web of Science databases, following the PRISMA guidelines. The review yielded 15 relevant sources published between 2020 and June 2025. Induction, deduction, content analysis, and K-means clustering were employed to analyse them. Forty-eight challenges to MCSs in higher education were identified and systematised into four groups (Growth Threats, Limitations, Malpractices, and Stakeholder Issues), covering twelve subgroups. These subgroups were ranked according to their frequency of mention. The top-ranked subgroups were HR problems (first), organisational constraints and management engagement (second), and technological integration and lack of technology training (third). All challenges were classified into clusters based on the countries analysed in the reviewed sources. This review primarily contributes to the existing knowledge by identifying and categorising the challenges to MCSs in higher education. Practically, it lays the groundwork for improving these MCSs, thus contributing to enhanced university management.

Keywords: control; management control systems; challenges; higher education; data-driven approach; systematic review; K-means clustering (search for similar items in EconPapers)
JEL-codes: G15 G17 G18 L21 L22 L25 L26 Q42 Q43 Q47 Q48 R51 R52 R58 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2673-4060/6/3/100/pdf (application/pdf)
https://www.mdpi.com/2673-4060/6/3/100/ (text/html)

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:gam:jworld:v:6:y:2025:i:3:p:100-:d:1701767

Access Statistics for this article

World is currently edited by Ms. Cassie Hu

More articles in World from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().