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An MCDM-based game-theoretic approach for strategy selection in higher education

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  • Ekinci, Yeliz
  • Orbay, Benan Zeki
  • Karadayi, Melis Almula

Abstract

This study proposes a framework for universities and governments to select strategies by considering the strategic interactions. The strategic choices of universities and governments can be determined by analyzing the related literature and discussing it with experts in higher education (HE). Because these experts form their evaluations depending on various criteria, the outputs of multi-criteria decision-making (MCDM) models are used to determine payoff values for players by considering all strategic combinations. After constructing the payoff matrix, the Nash equilibrium concept of game theory is used to determine optimal strategies for the universities and governments for simultaneously played games. Sequential versions of the games are also analyzed using backward induction. The results show that in all games constructed using criteria with different weights, either the government or the university, or both, preferred to motivate high-quality academic research. The proposed methodology can be used by the policymakers in the higher education area, both by the central planners (usually the government) and the universities.

Suggested Citation

  • Ekinci, Yeliz & Orbay, Benan Zeki & Karadayi, Melis Almula, 2022. "An MCDM-based game-theoretic approach for strategy selection in higher education," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:soceps:v:81:y:2022:i:c:s0038012121001786
    DOI: 10.1016/j.seps.2021.101186
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    References listed on IDEAS

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    1. Sarfaraz Hashemkhani Zolfani & Abdolhamid Safaei Ghadikolaei, 2012. "Application of MCDM methods in short-term planning for private universities based on balanced scorecard: a case study from Iran," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 10(2), pages 250-266.
    2. Wu, Yunna & Xu, Chuanbo & Zhang, Ting, 2018. "Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China," Energy, Elsevier, vol. 147(C), pages 1227-1239.
    3. Ann-Charlotte Fridh & Bo Carlsson, 2002. "special issue: Technology transfer in United States universities," Journal of Evolutionary Economics, Springer, vol. 12(1), pages 199-232.
    4. Joshua B. Powers, 2003. "Commercializing Academic Research," The Journal of Higher Education, Taylor & Francis Journals, vol. 74(1), pages 26-50, January.
    5. Mumtaz Karatas & Ilknur Karacan & Hakan Tozan, 2018. "An integrated multi-criteria decision making methodology for health technology assessment," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 12(4), pages 504-534.
    6. Wang, Derek D., 2019. "Performance-based resource allocation for higher education institutions in China," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 66-75.
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    1. Badiee, Aghdas & Moshtari, Mohammad & Berenguer, Gemma, 2024. "A systematic review of operations research and management science modeling techniques in the study of higher education institutions," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).

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