ANOTHER WAY TO DETERMINE WEIGHTS OF BALANCED PERFORMANCE EVALUATIONS

Year 2016, ICEBSS Special Issue, 151 - 161, 06.11.2016

İhsan Alp

Abstract

In case of multiple inputs and outputs,
performance of Decision
Making Units (DMU) is defined
as the ratio of weighted sum of outputs to weighted sum of inputs.
There are two group ways to determine the weights of performance : objective
and subjective approaches mainly. In the subjective approaches, weights which
will be given to the inputs and outputs are determined based on the opinion of
DMUs or experts. In the objective approaches, weights are found via models  and calculations which are not based on
personal judgments. One of them is the most important and widely used Data
Envelopment Analysis (DEA) method. Data Envelopment analysis is a nonparametric
and operations research-based technique. DEA, in the performance calculations,
assigns weights to multiple inputs and outputs in an objective manner by means
of a linear programming model to maximize the performance of each DMU.

There may be two disadvantages
for the weights which calculated by this method:

I.  To give
very small or zero weights to important inputs and outputs.

II. 
In aggregate
evaluation, computed weights generally to be different for each input and
output for different decision- makers; in the performance evaluation,
importances or weights of the inputs and outputs not to happen same for every
DMU.

One way for eliminate the disadvantages
mentioned above is to use common weights when calculating the performance of
DMUs. Another method is to use the correlation coefficients between inputs and
outputs. Mentioned methods in this work will be interpreted by applying to the
data of a real-world problem.

Keywords

Data envelopment analysis, common weigths, performans calculations, correlation

DENGELİ PERFORMANS AĞIRLIKLARININ HESAPLANMASINDA DİĞER BİR YOL

Abstract

Çok girdi ve çıktı olması durumunda, karar verme
birimlerinin (KVB) performans hesabı, ağırlıklı çıktılar toplamı bölü ağırlıklı girdiler
toplamı olarak tanımlanır. Performans ağılıklarını belirlemede başlıca iki yol vardır: Sübjektif ve objektif
yaklaşımlar. Sübjektif yaklaşımlarda girdi ve çıktılara verilen ağırlıklar
KVB’nin ya da uzmanların görüşlerine dayalı belirlenir. Objektif yaklaşımlarda
ise ağırlıklar kişisel görüşlere dayanmayarak model ve hesaplamalar yardımıyla
tespit edilir. Bunlardan en yaygınca kullanılanı Veri Zarflama Analizi (VZA) yöntemidir. VZA yöntemi parametrik
olmayan yöneylem araştırması tabanlı bir tekniktir. VZA performans
hesaplamalarında çok girdi ve çok çıktıyı her KVB’nin performansını en büyük
yapacak ağırlıkları doğrusal programlamayla objektif biçimde hesaplar.

Bu
yöntemle hesaplanan ağırlıklar için iki dezavantaj vardır: I.Önemli

girdi ve
çıktılara sıfıra yakın veya sıfır ağırlık vermek.

II.  Performans
hesaplamalarında her bir girdi ve çıktıya farklı karar vericiler için farklı
ağırlıklar ataması

KVB’lerinin
performansı hesaplanırken yöntemin yukarıda bahsedilen dezavantajlarını elimine
etmenin bir yolu ortak ağırlıklar kullanmaktır. Başka bir yöntem girdilerle
çıktılar arasında korelasyonları kullanmaktır.

 

Keywords

Veri zarflama analizi, ortak ağırlıklar, performans hesaplamaları, korelasyon

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