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Abstract
The two-stage Data Envelopment Analysis (DEA) is widely applied to assess the efficiency of commercial banks in recent years. Even though this approach well simulates the sequence of banks production process, the independent operations within sub-stages are generally ignored, and the cooperative or non-cooperative relations between sub-stages are usually investigated separately.Please check whether short title on odd pages have been set correctly. Commercial banking production system, however, has complex internal structure within which parallel and series structure can co-exist, and cooperative relations may concurrently occur with non-cooperative ones. In this paper, we develop a hybrid two-stage DEA to consider simultaneously the series-parallel internal structure and the cooperative-Stackelberg relations between sub-stages. The data of 19 Chinese listed commercial banks are used to show the abilities of the proposed models. This approach represents a powerful and flexible efficiency measurement implement that can be applied when the system in question has a complex internal structure in terms of both sub-systems features and sub-systems relations.
Highlights
Introduced by Charnes et al [8], Data Envelopment Analysis (DEA) is a non-parametric mathematical method for assessing the relative efficiency of a set of homogenous Decision Making Units (DMUs)
If the operations within a sub-stage are ordered in series, the problem can be mathematically formulated to a three-stage DEA modelling such as a network DEA framework proposed by Matthews [28] or to a more general multi-stage systems case studied by Kao [17]; but, if the internal operations of a sub-stage are organized in parallel and effectuated independently, how to evaluate and decompose the efficiency of the system with respecting the different efficiency formation mechanisms?
The means of overall efficiency in the cooperative-Stackelberg case with different leaders are both lower than those of overall efficiency in the cooperative approach. These results suggest that in our application, the performance of profits making stage (PMS) is relatively dominant in the overall efficiency formation for most of the commercial banks, and non-cooperation relations between deposits collecting stage (DCS) and PMS will probably decrease the overall efficiency of the banking systems
Summary
Introduced by Charnes et al [8], Data Envelopment Analysis (DEA) is a non-parametric mathematical method for assessing the relative efficiency of a set of homogenous Decision Making Units (DMUs). Lozano [26] summarized more than twenty network DEA applications in the efficiency measurement of banks or bank branches, and the author indicated that most studies consider two-stage systems in series. This structural feature presents certain insufficiencies in the banks performance evaluation. If the operations within a sub-stage are ordered in series, the problem can be mathematically formulated to a three-stage DEA modelling such as a network DEA framework proposed by Matthews [28] or to a more general multi-stage systems case studied by Kao [17]; but, if the internal operations of a sub-stage are organized in parallel and effectuated independently, how to evaluate and decompose the efficiency of the system with respecting the different efficiency formation mechanisms?.
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