Abstract
This paper develops two-stage inverse data envelopment analysis models with undesirable outputs to formulate resource plans for 16 Chinese listed commercial banks whose outputs are increased and overall efficiency is kept unchanged in the short term. We use these models to meet three different output targets, namely, increasing both the desirable and undesirable outputs by the same percentage, increasing these outputs by different percentages, and increasing only the desirable outputs while keeping the undesirable outputs unchanged. We find that operation cost and interest expense are more flexible than labor in the adjustment process and that deposits have no obvious law of change. The findings of this work provide some suggestions for bank managers.
Highlights
Commercial banks play significant roles in an economy’s financial system, and their functions, service capabilities, and market status, are all rapidly evolving over time
As a reverse application of data envelopment analysis (DEA) that is suitable for complex systems, inverse DEA was introduced in [13] to formulate resource plans or set short-term output goals for a decision making unit (DMU)
Two-stage inverse DEA models are developed in this work to solve such problem
Summary
Commercial banks play significant roles in an economy’s financial system, and their functions, service capabilities, and market status, are all rapidly evolving over time. As a reverse application of DEA that is suitable for complex systems, inverse DEA was introduced in [13] to formulate resource plans or set short-term output goals for a decision making unit (DMU). We examine how to formulate resource plans that can help those banks that adopt a two-stage system achieve their output targets in the short term while maintaining their overall efficiency score. To solve this problem, we build two-stage inverse DEA models that consider both the changes in desirable and undesirable outputs.
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