arXiv subjects

Dariush Khezrimotlagh

Publications and source records attributed to Dariush Khezrimotlagh.

4 recordsLinked to original sources

arXiv2017

Decision Making and Productivity Measurement

In this article, the concepts of technical efficiency, efficiency, effectiveness and productivity are illustrated. It is discussed that when firms are not homogenous, the situation is the same as when each factor has a different unit of measurement from one firm to another, and there-fore, no meaningful discrimination can be expressed, unless a set of known weights are introduced to standardize data. A linear programming DEA model is used when a set of known weights are given to calculate the technical efficiency and efficiency of a set of homogenous DMUs with multiple input factors and output factors. A numerical example is also provided.

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arXiv2015

How to deal with numbers of decision making units and variables in data envelopment analysis

Sufficient numbers of Decision Making Units (DMUs) in comparison with the number of input and output variables has been a concern of using Data Envelopment Analysis (DEA) in the last three decades. There are several studies in the literature of DEA which have tried to handle this issue by providing additional procedures to increase the number of DMUs, decreasing the number of variables or finding a relationship between the number of DMUs and variables. However, there are no concerns about the number of DMUs in comparison with the number of variables while Kourosh and Arash Method (KAM) is applied. A geometric reason is provided to depict the validity of the method without any extra conditions or additional methodologies. The technique is quite simple with no computational complexities of current methodologies even if the number of DMUs is less than the number of variables. A real-life numerical example of 32 DMUs with 45 variables demonstrates the advantages of the proposed technique.

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arXiv2015

Differences between real and integer production possibility sets in data envelopment analysis

The real Production Possibility Set (PPS) is completely generated by observations in the real approach, but generating the integer PPS may not be possible by only using observations in the integer approach. In other words, this phenomenon says that all points in the real generated PPS are dominated by a point of the linear combination of observations, whereas there might be some points in the integer generated PPS which are not dominated with the points of the linear combination of observations. This paper shows how the integer production possibility set is made and the mixed-integer linear programming is defined. The paper also addresses some shortcomings in the recent mixed-integer linear programming while the integer axioms are considered.

math.OC↗

arXiv2015

How to detect outliers in data envelopment analysis by Kourosh and Arash method

One of the concerns about using non-parametric estimators such as Data Envelopment Analysis (DEA), is the presence of outliers. There are a good number of studies that mention this assessment in the literature of DEA, however, there is no clear definition to identify what outliers are in DEA. Moreover, most of the studies have used additional procedures which have high computational complexities. This paper proposes a suitable definition to identify outliers as well as a simple methodology to illustrate how DEA, by using Kourosh and Arash Method (KAM), is easily able to detect outliers without using additional technologies and their computational complexities. The methodology of detecting outliers by KAM is represented with an example which was used in previous research to depict DEA's weakness of detecting outliers. The results clearly reject this claim that DEA is not able to detect outliers.

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