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ASSESSING THE RELATIVE PERFORMANCE OF UNIVERSITY DEPARTMENTS: TEACHING VS. RESEARCH

Journal Name:

  • İstanbul Üniversitesi Ekonometri ve İstatistik Dergisi

Publication Year:

  • 2011

Key Words:

Keywords (Original Language):

Author NameUniversity of Author
Abstract (2. Language): 
Data Envelopment Analysis (DEA) is known as a non-parametric method to evaluate the relative efficiencies of a set of homogenous decision-making units (DMUs) (i.e., banking, health, education, etc.) that use multiple inputs to produce multiple outputs. DEA models also have applications for universities or specifically, departments of a university. In practice, determining input and output measures may be based on the available data. However, lack of defining an important measure or use of invalid data may mislead the decision maker. Therefore, this study aims to assess the affect of missing values such as by discarding of outputs on DMU’s efficiency values. The up-to-date data for the departments of an engineering faculty are considered and their performances are presented based on teaching and research oriented measures.
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Abstract (Original Language): 
Veri Zarflama Analizi (VZA) homojen karar verme birimler kümesinin (ör., bankacılık, sağlık, eğitim, vb.) göreli etkinliklerinin değerlendirilmesinde kullanılan parametrik olmayan bir yöntemdir. VZA modellerinin aynı zamanda üniversiteler ya da daha spesifik olarak üniversite bölümleri için de kullanılmıştır. Uygulamada, girdi ve çıktı ölçütlerinin belirlenmesi mevcut verilerden hareketle gerçekleştirilir. Fakat, önemli bir ölçütün ele alınmaması ya da güvenilir olmayan verilerin kullanılması karar vericiyi yanlış yönlendirebilir. Bu yüzden, çalışmada mevcut olmayan verilerin, örneğin çıktı ölçütlerinden çıkartılarak, karar verme birimlerinin etkinlik değerlerine etkisi değerlendirilmiştir. Bir Mühendislik Fakültesinde bulunan bölümlere ait güncel veriler incelenerek performans değerleri eğitim ve akademik araştırma yönünden değerlendirilmiştir.
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  • 13
125–138
  • English

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REFERENCES

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