Improving supply chain collaborations and performance of inefficient supply chain

Subject Areas : Data Envelopment Analysis

M. Sanei ^{1 *} , S. Mamizadeh-Chatghayeh ²

1 - Department of Mathematics, Islamic Azad University of Central Tehran Branch, Tehran, Iran
2 - Young researches club, Islamic azad university,Central Tehran branch, Tehran, Iran

Received: 2010-08-25 Accepted : 2010-08-25 Published : 2012-07-01

Keywords: Data Envelopment Analysis (DEA). Supply Chain Management (SCM). Intermediate products. Efficiency,

Abstract :

Modern manufacturing enterprises are required to collaborate by theirbusiness partners through their business process operations such as design,manufacture, distribution, and aftersales services. And furthermore performanceevaluation is of great importance for effective supply chain management. Therefore, DEA can help companies to remove some of the inefficiencies in operational processes in order to become more effective. Thecurrent paper develops one approach for determining the DEA projectionsfor inefficient supply chains. Meanwhile this approach aims at providingan easy, efficient and more practical approach based on the performanceevaluation for the multi-member supply chain. And ultimately, this modelis illustrated by an numerical example of Chinese commercial bank, andcase study application to provide of machine-making supply chain.

References:

[1] Chen Y., Cook  W.D., Li  N., & Zhu  J., Deriving the DEA frontier for two-stage processes . European Journal of Operational Research, 196(1) 1170-1176, 2009.

[2] Kao C., Hwang S. N., "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research 185, 418-429, 2008.

[3] Kim S., Smari W.W., On a collaborative commerce framework and architecture for next generation commerce. In:Proceedings of the 2005 International Symposium on Collaborative Technologies andSystems,pp.282–289, 2005. Availableat /http://ieeexplore.ieee.org/xpl/.

[4] Kumar  M., Vrat  P.,  Shankar  R., A fuzzy goal programming approach for vendor selection problem in a supply chain . Computers &Industrial  Engineering 46 (1), 69–85, 2004.

 [5] Mentzer J.T., et al. (2001): Defining Supply Chain Management, in:  Journal of Business Logistics, 22(2), 1 25, 2001.

 [6] Weber, Charles A., Desai, Anand, Non-cooperative negotiation strategies for vendor selection . European Journal of Operational Research 108, 208–223, 1998.

 [7] Yang F.Wu., D.Liang, L.Bi, G.,& Wu, D,D.(2009). Supply chain DEA :production  possibility set and  performance evaluation model. A‌n‌n‌a‌l‌s o‌f o‌p‌e‌r‌a‌t‌i‌o‌n r‌e‌s‌e‌a‌r‌c‌h,D‌O‌I 10.1007/s10479-008-0511-2