Data envelopment analysis (DEA) is a nonparametric technique that includes models to evaluate the relative efficiency of Decision Making Units (DMUs). It has the ability to separate efficient units and inefficient units. One of the applications of this mathematical technique is evaluating performance of supply chain. According to such as the inefficiency factors of one DMU, is existence conges...

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...

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...

A resource allocation model (RAM) for not-for-profit organization in the framework of Data Envelopment Analysis (DEA) was introduced by Zhang and Cui ([1]). The model is an inverse formulation to the DEA model , as pointed in paper [2], and can be transformed into a parametric linear programming problem. Also a multi-objective programming problem was introduced in [2] to solve RAM when the effi...

Few inverse data envelopment analysis (DEA) models have incorporated non-discretionary measures based on radial efficiency values. However, the may be miscounted in approaches when some non-zero slacks appear. Furthermore, there is scant research DEA to estimate performance restaurant industry. Accordingly, this proposes non-radial analyze and output changes of Iranian restaurants while also pr...

As increasing disbursements (such as costs and fees) risk portfolio leverage risk) may affect managed fund performance, analysts go beyond risk-adjusted return measures for performance appraisal. A methodology that assesses in a multidimensional framework is data envelopment analysis (DEA). variant of DEA inverse DEA. In this paper, applied to determine output (investment income benefit payment...

In this paper, we show that inverse Data Envelopment Analysis (DEA) models can be used to estimate output with fuzzy data for a Decision Making Unit (DMU) when some or all inputs are increased and deficiency level of the unit remains unchanged.