TÜRKİYE’DE KAMU ÜNİVERSİTELERİNİN EĞİTİM-ARAŞTIRMA ETKİNLİKLERİ VE ETKİNLİK ARTIŞINDA STRATEJİK ÖNCELİKLERİN ROLÜ: ÇOK-AKTİVİTELİ VZA UYGULAMASI

Bu makalede, Çok Aktiviteli Veri Zarflama Analizi (ÇA-VZA) yöntemi ile Türkiye’deki 45 kamu üniversitesinin 2010 yılı için eğitim ve araştırma etkinlikleri ölçülmüştür. Üniversiteler, farklı işlevleri ile ilişkili olarak aynı anda birden fazla üretim fonksiyonu ile karşı karşıya olan kurumlardır. Bu nedenle, kaynaklarını temelde eğitim ve araştırma aktiviteleri arasında paylaştırmaya çalışan karar birimleri olarak değerlendirilebilirler. ÇA-VZA yönteminin matematiksel altyapısı paylaşılan bu değişkenleri farklı aktivitelere atamayı, bu yolla etkinlik hesaplamaları yapmayı mümkün kılmaktadır. Bu nedenle ÇA-VZA modeli, Türkiye’deki yükseköğretim sistemindeki üretim yapısına uyarlanmış ve uygulanmıştır. Sonuçlara göre; üniversitelerin, eğitim ve araştırma etkinlikleri bakımından farklı skorlara ulaştıkları görülmüş, böylece üniversiteler arasından “Araştırma Etkin” veya “Eğitim Etkin” üniversiteler tespit edilmiştir. Ayrıca, modelin aktivitelere farklı öncelikler atanmasına izin veren yapısı kullanılarak gerçekleştirilen senaryo analizleri ile her üniversitenin, daha etkin olduğu alana fazla öncelik atayarak toplam etkinlik skorunu artırabildiği gösterilmiş ve bu sonucun performans analizi ve stratejik planlamadaki önemi vurgulanmıştır.

Anahtar Kelimeler:

Çok Aktiviteli VZA, Üniversiteler, birleşik etkinlik, stratejik öncelikler, doğrusal-olmayan programlama

Türkiye’de kamu üniversitelerinin eğitim-araştırma etkinlikleri ve etkinlik artışında stratejik önceliklerin rolü: Çok-aktiviteli VZA uygulaması

In this study, the research and teaching efficiencies of 45 selected state universities in Turkey are measured by using the Multi-Activity Data Envelopment Analysis (MA-DEA) model for the year 2010. Universities are institutions which face multiple production functions simultaneously, therefore they can be considered as carrying out mainly research and teaching activities using common resources. The mathematical formulation of MA-DEA is capable of objectively assigning the shared variables to different activities. Hence, the model is adapted to the problem by assuming a suitable production process for the Turkish Higher Education System. Results first show that the MA-DEA model generates different efficiency scores for universities and hence “research efficient” and “teaching efficient” universities have been identified. In addition, since the structure of MA-DEA model allows each university can give different priorities to different activities, scenario analyses have been applied on this priorities and it is shown that by assigning higher priorities to the activities which they are more efficient, universities can reach higher total efficiencies. The importance of this result related with performance analysis and strategic planning is then emphasized.

Keywords:

Multi-Activity DEA, Turkish Universities, joint-efficiency, strategic priorities, nonlinear programming,

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