design of efficient skill training supply chain using network data envelopment analysis

Providing skills training is an essential need of different societies. considering the significance of the role of skill training in empowerment and employment of individuals through the training of skilled labor required by the labor market and industry, in this study the supply chain of skills training has been designed. in the proposed supply chain, according to the skill training aspects, a network structure is conceptualized to include appropriate factors in different layers of the supply chain. evaluating the performance of the supply chain is handled applying a network data envelopment analysis. network data envelopment analysis (ndea) is an efficient method analyzing all the factors included in the evaluation network. among the ndea models, the output-oriented bunker-chaarns cooper (bcc) model was selected due to the importance of the output of the supply chains of the skills training. in addition to efficiency, the concept of complementary loss is also introduced to validate the results. the research findings show the efficiency of various factors in the stages of the designed network. on the other hand, unlike the classic dea method, which shows the maximum efficiency of a factor, in the proposed network model, the efficiency priority is calculated and the efficiency is determined at each stage of the supply chain.