Volume 25, Issue 2 (IIJEPR 2014)                   IJIEPR 2014, 25(2): 125-138 | Back to browse issues page

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Olfat L, Amiri M, Bamdad soofi J, Ebrahimpour Azbari M. A Network data envelopment analysis model for supply chain performance evaluation: real case of Iranian pharmaceutical industry. IJIEPR 2014; 25 (2) :125-138
URL: http://ijiepr.iust.ac.ir/article-1-460-en.html
A Network data envelopment analysis model for supply chain performance evaluation: real case of Iranian pharmaceutical industry
Laya Olfat 1, Maghsoud Amiri2 , Jjahanyar Bamdad soofi2 , Mostafa Ebrahimpour Azbari3
1- supervisor , layaolfat@gmail.com
2- advisor
3- student
Abstract:   (7226 Views)
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.
Keywords: supply chain Performance evaluation, Performance indicators, Factor Analysis, Network data envelopment analysis
Full-Text [PDF 727 kb]   (3818 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2012/08/11 | Accepted: 2013/09/24 | Published: 2014/05/26
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