2017•International Journal of Data Envelopment AnalysisRequires access

Provide a Model for Reallocating Resources in the Structure of Pasargadae Bank Branches With Emphasis on Efficiency and Productivity

Mostafa Bakhtiari, Mohsen Rostamy‐Malkhalifeh

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Abstract

Data envelopment analysis (DEA) creates many opportunities for collaboration between analyst and decision-maker. There are, however, situations in which all of the decision-making units (DMUs) fall under the umbrella of a centralized decision maker that oversees them. Many organizations such as bank branches, chain stores, … can do this. This centralized decision maker unit expect that resource allocation and revenue efficiency be in a way that DMUs not separately but in a group and simultaneously projected onto the efficiency frontier; as a result, it won’t be possible based on current DEA models. Therefore, centralized resource allocation or institutional allocation was formulated. There are situations in which centralized method presented in a central decision maker unit to allocate resources based on revenue efficiency. However, in reality value and rate are not often observed for all of the undesirable and desirable output units, which poses a problem in determining the revenue efficiency. Therefore, the best solution in these cases is to divide the outputs into two categories of known and unknown prices, which will be a more valid criterion for determining the revenue efficiency. In this paper, based on these methods, the revenue efficiency in branches of Pasargadae Bank will be analyzed and a comprehensive ranking will be made on these branches.

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What this paper is about

Data envelopment analysis (DEA) creates many opportunities for collaboration between analyst and decision-maker. There are, however, situations in which all of the decision-making units (DMUs) fall under the umbrella of a centralized decision maker that oversees them. Many organizations such as bank branches, chain stores, … can do this. This centralized decision maker unit expect that resource allocation and revenue efficiency be in a way that DMUs not separately but in a group and simultaneously projected onto the efficiency frontier; as a result, it won’t be possible based on current DEA models. Therefore, centralized resource allocation or institutional allocation was formulated. There are situations in which centralized method presented in a central decision maker unit to allocate resources based on revenue efficiency. However, in reality value and rate are not often observed for all of the undesirable and desirable output units, which poses a problem in determining the revenue efficiency. Therefore, the best solution in these cases is to divide the outputs into two categories of known and unknown prices, which will be a more valid criterion for determining the revenue efficiency. In this paper, based on these methods, the revenue efficiency in branches of Pasargadae Bank will be analyzed and a comprehensive ranking will be made on these branches.

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Available abstract

Data envelopment analysis (DEA) creates many opportunities for collaboration between analyst and decision-maker. There are, however, situations in which all of the decision-making units (DMUs) fall under the umbrella of a centralized decision maker that oversees them. Many organizations such as bank branches, chain stores, … can do this. This centralized decision maker unit expect that resource allocation and revenue efficiency be in a way that DMUs not separately but in a group and simultaneously projected onto the efficiency frontier; as a result, it won’t be possible based on current DEA models. Therefore, centralized resource allocation or institutional allocation was formulated. There are situations in which centralized method presented in a central decision maker unit to allocate resources based on revenue efficiency. However, in reality value and rate are not often observed for all of the undesirable and desirable output units, which poses a problem in determining the revenue efficiency. Therefore, the best solution in these cases is to divide the outputs into two categories of known and unknown prices, which will be a more valid criterion for determining the revenue efficiency. In this paper, based on these methods, the revenue efficiency in branches of Pasargadae Bank will be analyzed and a comprehensive ranking will be made on these branches.

Key concepts: Data envelopment analysis, Revenue, Ranking (information retrieval), Resource allocation, Productivity, Efficient frontier, Decision maker, Economics

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