Showing 2 results for Network Data Envelopment Analysis
Laya Olfat, Maghsoud Amiri, Jjahanyar Bamdad Soofi, Mostafa Ebrahimpour Azbari,
Volume 25, Issue 2 (5-2014)
Abstract
Having a comprehensive evaluation model with reliable data is useful to improve performance of supply chain. In this paper, according to the nature of supply chain, a model is presented that able to evaluate the performance of the supply chain by a network data envelopment analysis model and by using the financial, intellectual capital (knowledge base), collaboration and responsiveness factors of the supply chain. At the first step, indicators were determined and explained by explanatory Factor Analysis. Then, Network Data Envelopment Analysis (NDEA) model was used. This paper is the result of research related to supply chain of pharmaceutical companies in Tehran Stock Exchange and 115 experts and senior executives have been questioned as sample. The results showed that responsiveness latent variable had the highest correlation with supply chain performance and collaborative, financial and intellectual capital (knowledge base) latent variables were respectively after that. Four of the twenty eight supply chains which were studied obtained 1 as the highest performance rate and the lowest observed performance was 0.43.
Hamed Fazlollahtabar, Sepide Ebadi,
Volume 34, Issue 1 (3-2023)
Abstract
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 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.
