A New Integrated MCDM Framework for Academic Performance Analysis of Foundation Universities

Year 2023, Volume: 15 Issue: 1, 24 - 39, 31.01.2023

Sinan Çizmecioğlu Esra Boz Ahmet Çalık

https://doi.org/10.29137/umagd.1098902

Abstract

Most developed and developing countries encourage their universities to produce competent, high-quality, and widely distributed information in order to advance in a variety of fields. Academic publications and other related studies can be used to generate qualified information. The purpose of this study was to assess the academic performance of Turkey's foundation universities. MCDM approaches were used to analyze performance metrics such as publications, projects, and citations in foundation universities. The Entropy and Critic methods were used to calculate the weights of the criteria determined in the academic performance measurement. The results of these two approaches were combined using an adder operator, and the academic performance rating of foundation universities was established using the CoCoSo and Idocriw methods. On the other hand, the study's findings have a guiding quality for foundation institutions looking to improve their academic performance.

Keywords

Academical Performance, MCDM, Foundation Universities

Vakıf Üniversitelerinin Akademik Performans Analizi İçin Yeni Bir Bütünleşik ÇKKV Çerçevesi

Abstract

Gelişmiş ve gelişmekte olan ülkelerin çoğu birçok disiplin alanında ileri gidebilmek için üniversitelerine nitelikli, kaliteli ve yaygın etkiye sahip bilgi üretmeleri için teşvikler vermektedir. Nitelikli bilgilerin üretilmesi ise akademik yayınlar ve benzeri çalışmalar ile sağlanabilmektedir. Bu çalışmada Türkiye’deki vakıf üniversitelerinin akademik performansının ölçülmesine ilişkin bir araştırma yapılmıştır. Çalışmada vakıf üniversitelerindeki yayın, proje ve atıf gibi performans indeksleri ÇKKV yöntemleri ile değerlendirilmiştir. Entropi ve Critic yöntemleriyle akademik performans ölçümünde belirlenen kriterlerin ağırlıkları elde edilmiştir. Bu iki yöntemin sonuçlarını entegre etmek için ayrıca bir toplayıcı operatör kullanılmış ve ardından CoCoSo ve Idocriw yöntemleriyle vakıf üniversitelerinin akademik performans sıralaması oluşturulmuştur. Çalışmada elde edilen sonuçlar ise vakıf üniversitelerinin akademik performanslarını artırmasına yol gösterici bir nitelik taşımaktadır.

Keywords

Akademik Performans, Vakıf Üniversiteleri, ÇKKV

References

• Aguezzoul, Aicha, ve Silvio Pires. 2016. “3PL performance evaluation and selection: a MCDM method”. Ss. 87–94 içinde Supply Chain Forum: An International Journal. C. 17. Taylor & Francis.
• Akçakanat, Özen, EREN Hande, Esra Aksoy, ve Vesile Ömürbek. 2017. “Bankacilik sektöründe ENTROPI ve WASPAS yöntemleri ile performans değerlendirmesi”. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 22(2):285–300.
• Al-Juboori, Abbas Fadhil Mohammed Ali, Yunji Na, ve Franz Ko. 2011. “University ranking and evaluation: Trend and existing approaches”. Ss. 137–42 içinde The 2nd International Conference on Next Generation Information Technology. IEEE.
• Aladağ, Zerrin, Atakan Alkan, Ezgi Güler, ve Yasemin Özdin. 2018. “Akademik birimlerin veri zarflama analizi ve promethee yöntemleri ile performans değerlendirmesi: Kocaeli üniversitesi örneği”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 34(1):1–13.
• Alaşehir, Oğuzhan, Murat Perit Çakır, Cengiz Acartürk, Nazife Baykal, ve Ural Akbulut. 2014. “URAP-TR: a national ranking for Turkish universities based on academic performance”. Scientometrics 101(1):159–78.
• Baskurt, Oguz K. 2011. “Time series analysis of publication counts of a university: What are the implications?” Scientometrics 86(3):645–56.
• Diakoulaki, Danae, George Mavrotas, ve Lefteris Papayannakis. 1995. “Determining objective weights in multiple criteria problems: The critic method”. Computers & Operations Research 22(7):763–70.
• Kaptanoğlu, Dilek, ve Ahmet Fahri Özok. 2010. “Akademik performans değerlendirmesi için bir bulanık model”. İTÜDERGİSİ/d 5(1).
• Karami, Amin, ve Ronnie Johansson. 2014. “Choosing DBSCAN parameters automatically using differential evolution”. International Journal of Computer Applications 91(7):1–11.
• Karande, P., E. Zavadskas, ve S. Chakraborty. 2016. “A study on the ranking performance of some MCDM methods for industrial robot selection problems”. International Journal of Industrial Engineering Computations 7(3):399–422.
• Keshtkar, Mohammad Mehdi. 2017. “Performance analysis of a counter flow wet cooling tower and selection of optimum operative condition by MCDM-TOPSIS method”. Applied Thermal Engineering 114:776–84.
• Lavin, David E. 1965. “The prediction of academic performance.”
• Liu, Nian Cai, ve Ying Cheng. 2005. “The academic ranking of world universities”. Higher education in Europe 30(2):127–36.
• Mester, Gyula. 2011. “Academic Ranking of World Universities 2009/2010”. IPSI Journal, Transactions on Internet Research (TIR) 7(1):44–47.
• Nisel, Seyhan, ve Rauf Nisel. 2013. “Using VIKOR methodology for ranking universities by academic performance”. GSTF Journal of Mathematics, Statistics and Operations Research (JMSOR) 2(1):86.
• URAP (2021-2022). “Vakıf Üniversiteleri”. University Ranking by Academic Performance 2021-2022. Tarihinde (https://newtr.urapcenter.org/Rankings/2021-2022/VAKIF-ÜNİVERSİTELERİ).
• Wang, Tien-Chin, ve Hsien-Da Lee. 2009. “Developing a fuzzy TOPSIS approach based on subjective weights and objective weights”. Expert systems with applications 36(5):8980–85.
• Wu, Hung-Yi, Jui-Kuei Chen, I. Shuo Chen, ve Hsin-Hui Zhuo. 2012. “Ranking universities based on performance evaluation by a hybrid MCDM model”. Measurement 45(5):856–80.
• Yalcin, Nese, ve Ulaş Ünlü. 2018. “A multi-criteria performance analysis of Initial Public Offering (IPO) firms using CRITIC and VIKOR methods”. Technological and Economic development of Economy 24(2).
• Yazdani, Morteza, Pascale Zarate, Edmundas Kazimieras Zavadskas, ve Zenonas Turskis. 2019. “A Combined Compromise Solution (CoCoSo) method for multi-criteria decision-making problems”. Management Decision.
• Ying-Feng, Kuo, ve Chen Ling-Show. 2002. “Using the fuzzy synthetic decision approach to assess the performance of university teachers in Taiwan”. International journal of Management 19(4):593.
• Zavadskas, Edmundas Kazimieras, ve Valentinas Podvezko. 2016. “Integrated determination of objective criteria weights in MCDM”. International Journal of Information Technology & Decision Making 15(02):267–83.
• Zhou, Jianli, Yunna Wu, Chenghao Wu, Zhongqing Deng, Chuanbo Xu, ve Yong Hu. 2019. “A hybrid fuzzy multi-criteria decision-making approach for performance analysis and evaluation of park-level integrated energy system”. Energy Conversion and Management 201:112134.