Article ID Journal Published Year Pages File Type
10321835 Expert Systems with Applications 2015 32 Pages PDF
Abstract
The purpose of this paper is to explore an innovative performance model for a two-stage sequential production process by combining data envelopment analysis (DEA) and back propagation neural network (BPNN). Recent literature shows a growing interest on performance modeling of two-stage production process using DEA. But, most previous studies on the scope of two-stage modeling are still limited to the efficiency measurement and also have neglected the progressive direction of predictive value and capacity. As an optimization technique, two-stage DEA model lacks predictive capacity. Despite an adaptive prediction model being a practical necessity, this area has rarely been addressed in the previous studies. This paper demonstrates an integrative approach to constructive performance modeling of a two-stage sequential production process by exploring predictive capacity of BPNN in conjunction with DEA. The effectiveness of our jointly integrated performance model through this study is empirically supported by its practical application to the financial banking operations across large U.S. banks.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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