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

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

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
1- supervisor , layaolfat@gmail.com
2- advisor
3- student
Abstract:   (6696 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.
Full-Text [PDF 727 kb]   (3736 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2012/08/11 | Accepted: 2013/09/24 | Published: 2014/05/26

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.