Problem statement:This study focuses on problems of congestion and how they might be treated in Universities, also investigates a methodology to measure undesirable outputs congestion in addition to inputs congestion, from both theoretical and empirical perspectives. Congestion indicates an economic state where inputs are overly invested. Evidence of congestion occurs whenever reducing some inputs can increase outputs. Approach: The main thrust of this study is to measure congestion in undesirable outputs and inputs by using Data Envelopment Analysis (DEA), by a proposed linear model. Results: We Using a data set of university and jointly evaluate desirable University output (e.g., graduate) and the simultaneous undesirable output (e.g., dropout) that occurs. Conclusion: The results show that inefficiency is associated with congestion in the study departments of University; particular congestion in undesirable output has most correlation with the efficiency.
Supply chain is one important problem in industry and economy. Measuring supply chain performance becomes difficult because of the need to deal with the multiple performance measures related to the supply chain members, and to integrate and coordinate the performance of those members. The tradition approaches for measuring efficiencies cannot be applied directly to the problem of evaluating the efficiency of supply chains. This is because some measures linked to supply chain members cannot be simply classified as "outputs" or "inputs" of the supply chain. We present several models that directly evaluate the performance of the supply chain as well as its members, while considering the relationship between the members. The modeling processes are based upon the concept of noncooperative and cooperative games. In this paper, we have applied network data envelopment analysis (DEA) approach for measuring performance of supply chain, which consider the system as composed by distinct processes or stages, each one with its own inputs and outputs and with intermediate flows among the stages. The proposed method reduced computations and also determination of efficiency of overall supply chain and efficiency of each supply chain members.
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