This study suggests a novel application of Inverse Data Envelopment Analysis (InvDEA) in strategic decision making about mergers and acquisitions in banking. The conventional DEA assesses the efficiency of banks based on the information gathered about the quantities of inputs used to realize the observed level of outputs produced. The decision maker of a banking unit willing to merge/acquire an...

In this paper, we propose a novel method using multiple-objective programming problems to answer the following question: if among a group of decision making units (DMUs), a subset of DMUs are required to merge and form a new DMU with specific input/output levels and a predefined efficiency target, how much should be the outputs/inputs of the merged DMU? This question answered according to the c...

data envelopment analysis (dea) and balanced scorecard (bsc) are two well-known approaches for measuring performance of decision making units (dmus). bsc is especially applied with quality measures, whereas, when the quantity measures are used to evaluate, dea is more appropriate. in the real-world, dmus usually have complex structures such as network structures. one of the well-known network s...

many studies have been conducted to determine the efficiency of two-stage network structures in the recent years. the two-stage network with additional inputs to the second stage, in which the second stage is independent of the first stage are one of these structures. thus, there is a need for a model capable of calculating the efficiency of two-stage structures as well as efficiency of each st...

More than 200 papers have been published in the last 20 years on the topic of health supply chains (HSC). Looking at the research methodologies employed, less than 15 papers apply data envelopment analysis (DEA) models. This is in contrast to, for example, A Network Data Envelopment Analysis (NDEA) Model for Supply Chain Performance Evaluation where several reviews on respective NDEA models hav...

Many production systems have acquisition and merge operations to increase productivity. This paper proposes a novel method to anticipate whether a merger in a market is generating a major or a minor consolidation, using Inverse data envelopment analysis (InvDEA) model. A merger between two or more decision making units (DMUs) producing a single merged DMU that affects the efficiency frontier, d...

Users of data envelopment analysis (DEA) often presume efficiency estimates to be robust. While traditional DEA has been exposed to various sensitivity studies, network DEA (NDEA) has so far escaped similar scrutiny. Thus, there is a need to investigate the sensitivity of NDEA, further compounded by the recent attention it has been receiving in literature. NDEA captures the underlying performan...

Data Envelopment Analysis (DEA) is a linear programming methodology for measuring the efficiency of Decision Making Units (DMUs) to improve organizational performance in private and public sectors. However, if new DMU needs be known its score, DEA analysis would have re-conducted, especially nowadays, datasets from many fields been growing rapidly real world, which will need huge amount computa...

A mobile adhoc network is infrastructure-free and self configured network connected without wire. As it is infrastructure-free and no centralized control, such type of network are suitable only for conditional inter communication link. So initially maintaining Quality of Service and security aware routing is a difficult task. The main purpose of QoS aware routing is to find an optimal secure ro...