Outliers in data envelopment analysis

Impact of Outliers in Data Envelopment ‎Analysis‎

This paper will examine the relationship between "Data Envelopment Analysis" and a statistical concept ``Outlier". Data envelopment analysis (DEA) is a method for estimating the relative efficiency of decision making units (DMUs) having similar tasks in a production system by multiple inputs to produce multiple ‎outputs.‎ An important issue in statistics is to identify the outliers. In this pap...

A new method for detecting outliers in Data Envelopment Analysis

We introduce a simple method for detecting outliers in Data Envelopment Analysis. The method is based on two scalar measures. The first is the relative frequency with which an observation appears in the construction of the frontier when testing the efficiency of other observations, and the second is the cumulative weight of an observation in the construction of the frontier. We provide a link t...

COMMON WEIGHTS DETERMINATION IN DATA ENVELOPMENT ANALYSIS

In models of data envelopment analysis (DEA), an optimal set of weights is generally assumed to represent the assessed decision making unit (DMU) in the best light in comparison to all the other DMUs, and so there is an optimal set of weights corresponding to each DMU. The present paper, proposes a three stage method to determine one common set of weights for decision making units. Then, we use...

Data envelopment analysis for imprecise data in Buyer-Seller Relationship

In the environment of business‐to‐business e‐commerce, Buyers and sellers in mature industrial markets can turn single transactions into long-term beneficial relationships by a deeper understanding of the complex connection between the two and buyers and sellers are uncertain about their roles. A “must-do” for the sellers, in particular, is to understand patterns of investment and reward,...

Finding Outlier DMUs in Data Envelopment Analysis