Advances in data envelopment analysis

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

Capacity utilization in data envelopment analysis with integer data

In the process of production, some of the inputs are fixed and cannot easily be changed, such as work hours of workers and hours of administrative or work, these types of inputs are fixed and others are variables. In this paper, by considering some inputs or outputs which are limited, their amounts must be integrated; this concept for integer data is extended. We show the importance of subject ...

Complex-Valued Data Envelopment Analysis

Data Envelopment Analysis (DEA) is a nonparametric approach for measuring the relative efficiency of a decision making units consists of multiple inputs and outputs. In all standard DEA models semi positive real valued measures are assumed, while in some real cases inputs and outputs may take complex valued. The question is related to measuring efficiency in such cases. As far as we are aware, ...