Volume List  / Volume 5 (1)



DOI: 10.7708/ijtte.2015.5(1).09

5 / 1 / 74-81 Pages


Milan Andrejić - University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000, Belgrade, Serbia -

Milorad Kilibarda - University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000, Belgrade, Serbia -


Strategic decision making is very important in logistics. One of the most important strategic decisions in logistics is the selection of distribution channels. This paper proposes the efficiency of distribution channels as one of the main selection criteria. The efficiency of distribution channels simultaneously affects logistics costs and customer satisfaction. Based on the main characteristics of the distribution channels, such as delivery time, service level, volume of business, the level of errors and the different cost categories in this paper the PCA-DEA approach for measuring the efficiency and selection of certain types of distribution channels is proposed. Model is tested on the numerical example. Results show the great capability of the proposed model.

Download Article

Number of downloads: 3585


This paper was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia, through the project TR 36006, for the period 2011-2014.


Adler, N.; Golany, B. 2001. Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe, European Journal of Operational Research, 132: 260-273.


Adler, N.; Golany, B. 2002. Including principal component weights to improve discrimination in data envelopment analysis, Journal of Operations Research Society of Japan, 46: 66-73.


Adler, N.; Yazhemsky, E. 2010. Improving discrimination in Data Envelopment Analysis: PCA-DEA or Variable Reduction, European Journal of Operational Research. DOI: http://dx.doi.org/10.1016/j.ejor.2009.03.050, 202(1): 273-284.


Andrejić, M.; Bojović, N.; Kilibarda, M. 2013. Benchmarking distribution centers using Principal Component Analysis and Data Envelopment Analysis: a case study of Serbia, Expert Systems with applications. DOI: http://dx.doi.org/10.1016/j.eswa.2012.12.085, 40(10): 3926-3933.


Fernie, J.; Sparks, L. 2009. Logistics and Retail Management: Emerging Issues and New Challenges in the Retail Supply Chain. Kogan Page Limited, Philadelphia.


Hair, J.F.; Anderson, R.E.; Tatham, R.L.; Black, W.C. 1995. Multivariate data analysis. Englewood Cliffs, NJ: Prentice Hall.


Pedersen, S.G.; Zachariassen, F.; Arlbjorn, S.J. 2012. Centralization vs. de-centralization of warehousing: a small and medium-sized enterprise perspective, Journal of Small Business and Enterprise Development. DOI: http://dx.doi.org/10.1108/14626001211223946, 19(2): 352-369.


Rushton , A.; Croucher, P.; Baker, P. 2006. The handbook of logistics and distribution management. 3rd edition, Kogan page, London and Philadelphia.


Sharma, S. 1996. Applied Multivariate Techniques. John Wiley & Sons, Inc, New York.


Wanke, P.; Zinn, W. 2004. Strategic logistics decision making, International Journal of Physical Distribution & Logistics Management. DOI: http://dx.doi.org/10.1108/09600030410548532, 34(6): 466-478.