A new data envelopment analysis model for evaluating the performance of expert systems in supply chain management

In supply chain management (SCM), the company that evaluates expert systems (ES) has competitive advantage over competitors. Performance evaluation of the ES in SCM is a significant yet complex task which requires careful consideration of various performance criteria. Therefore, evaluation of the performance of ES in SCM is an important issue and it has a strategic significance for every company. One of the techniques that can be used for evaluation of the performance of ES is data envelopment analysis (DEA). In the current study, we introduce a novel model for evaluating the performance of ES in SCM using new range adjusted measure (RAM) model in the existence of dual-role factor and stochastic data. We present a case study in SCM of a drink industry in Iran.

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