Measuring the Relative Efficiency in Multi-Component Decision Making Units and its Application to Bank Branches
Abstract
In many cases of data envelopment analysis (DEA), decision
making units (DMUs) can be separated into different components.
These DMUs are called multi-component DMUs, and studying them is
known as multi-component DEA. In multi-component DEA some inputs
are shared among the components of a DMU, and some components involve
into producing some outputs of the DMU. In this paper, we survey
measuring the relative efficiency in multi-component DEA. It is shown
that using common idea for measuring the efficiency of multi-component
DMUs, the relative efficiency of an evaluating DMU may be not obtained.
Therefore, present paper proposes a new DEA model which can
obtain the relative efficiencies of multi-component DMUs. Some facts
about the proposed approach are also provided by theorems. Moreover,
the proposed DEA model is compared to another approach in literature
utilizing a set of data about 19 bank branches.
making units (DMUs) can be separated into different components.
These DMUs are called multi-component DMUs, and studying them is
known as multi-component DEA. In multi-component DEA some inputs
are shared among the components of a DMU, and some components involve
into producing some outputs of the DMU. In this paper, we survey
measuring the relative efficiency in multi-component DEA. It is shown
that using common idea for measuring the efficiency of multi-component
DMUs, the relative efficiency of an evaluating DMU may be not obtained.
Therefore, present paper proposes a new DEA model which can
obtain the relative efficiencies of multi-component DMUs. Some facts
about the proposed approach are also provided by theorems. Moreover,
the proposed DEA model is compared to another approach in literature
utilizing a set of data about 19 bank branches.
Keywords
Data envelopment analysis (DEA), multicomponent
decision making units, relative efficiency, absolute efficiency.
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