In the real world, there are processes whose structures are like a parallel-series mixed network. Network data envelopment analysis (NDEA) is one of the appropriate methods for assessing the performance of processes with these structures. In the paper, mixed processes with two parallel and series components are considered, in which the first component or parallel section consists of the shared inputs, and the second component or series section consists of undesirable factors. By considering the weak disposability assumption for undesirable factors, a DEA approach as based on network slackbased measure (NSBM) is introduced to evaluate the performance of processes with mixed structures. The proposed model is illustrated with a real case study. Then, the model is developed to discriminate efficient units.
Network data envelopment analysis (NDEA) is a non-parametric technique to evaluate the relative efficiency of decision-making units (DMUs) with network structures. An interesting and important network structure is a two-stage feedback process in which the outputs of the second stage are used as the inputs for the first stage. The existing approach did not consider undesirable products and from experience though we know that in real applications, network structures may consist of desirable and undesirable products outputs in which undesirable products can be used in the systems. The present paper proposes a DEA-based method for evaluating the relative efficiency of such a two-stage-feedback network structure with undesirable factors. Directional distance function along with weak disposability assumption for undesirable outputs has been used to analyse the performance of the network. A real case on ecological system of 31 regions in China is used to illustrate the applicability of the proposed approach.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.