Dea ranking of municipalities of the Republic of Serbia based on efficiency of SMEs in agribusiness
Abstract
The most important aspect of any business is efficiency. The goal is to achieve a greater output results using less inputs, i.e. to maximize the use of available inputs. Numerous mathematical and statistical procedures, such as DEA technique (Data Envelopment Analysis), take an important place in the process of the effective management of the company and its business activities. This paper illustrated the application of DEA technique in assessing the business efficiency of SMEs in agribusiness in Vojvodina Measuring the efficiency of business operations of SMEs is based on the values of the following indicators: fixed assets, working capital, number of companies, number of employees, total income, profit and loss. The data used to calculate the values of indicators of business efficiency were obtained from the Statistical Office of the Republic of Serbia, based on the annual accounts of SMEs in agribusiness for four-year average (2008-2011). The aim of this paper is statistical assessment of business efficiency of SMEs in agribusiness using DEA technique, and then, based on the results obtained, to perform the ranking of Vojvodina municipalities in which observed SMEs were located, and finally, based on 4 models, to show sensitivity of DEA technique compared to different combination of input / output indicators, so therefore, caution is needed when this method is used. If the combination of parameters in the model is better, the results are more realistic, since if a key parameter is omitted, wrong decisions could be made.
References
Andersen P. & Petersen N. A. (1993): A Procedure for Ranking Efficient Units in Data Envelopment Analysis, Management Science, 39(10), 1261-1264.
Bulajić M., Savić G., Savic S., Mihailović N., Martić M. (2011a): Efficiency assessment of banks in Serbia. TTEM- Technics Technologies Education Management, Bosnia and Herzegovina, Sarajevo, 6 (3), 657-662.
Bulajić M., Savić G. & Savić S. (2011b): DEA approach in ranking the banks in Serbia. Paper presented at the XXXVIII Symposium on Operational Research. Faculty of Economics, University of Belgrade. The Proceedings SYMOPIS-2011, (pp.134-137).
Ceranic S. & Maletic R. (2010): Small and medium enterprises as development factor of agribusiness in Republic of Serbia. Apstract magazin, Hungary, 4 (3-4), 45-50.
Gverovski, M., Risteska A. & Dimeski S. (2011): Small and medium enterprises: economic development drivers. Management, 16 (59), 87-94.
Jirong, E., & Gail (1996): ). A Shadow-Price Frontier Measurement of Profit Efficiency in Chinese Agriculture. American Journal of Agricultural Economics, 78(1), 146-156.
Lilienfeld A. & Asmild M. (2007): Estimation of excess water use in irrigated agriculture: A Data Envelopment Analysis approach. Agricultural water management, 94, 73–82.
Maletic R., Ceranic S. & Popovic B. (2011): Small and medium enterprises as factors in reducing poverty in rural communities Serbian, Economics of Agriculture, Belgrade, 57 (1), 121-132.
Maletic R., Kreca M. & Bucalo D. (2012): DEA technique in a function of measuring banks efficiency. Paper presented at the "Life Cycle Engineering and Management", The Proceedings DQM-2012, pp.429-435, Belgrade
Maletic R., Maletic P., Kreca M. & Popovic B. (2013): Comparative analysis of ranking municipalities in Vojvodina using DEA and I-distance methods. Int. J. Agricult. Stat. Sci., 9 (2): 471-480.
Milind S. (2003): Efficiency of banks in a developing economy: The case of India. European Journal of Operational Research, 148 (3), 662-671.
Mihailovic, N., Bulajic, M., & Savic, G. (2009). Ranking of banks in Serbia. YUJOR, 19 (2), 323-334.
Mohamed M. (2006): Modeling the efficiency of GCC banks: a data envelopment analysis approach. International Journal of Productivity and Performance Management 56 (7), 623-643. Doi: 10.1108/17410400710823651
Monchuk C.D., Chen Z. & Bonaparte Y. (2010): Explaining production inefficiency in China's agriculture using data envelopment analysis and semi-parametric bootstrapping. China Economic Review, 21 (2), 346–354.
Popovic B., Maletic R., Ceranic S., Paunovic T. & Jankovic-Soja S. (2011): Defining homogenous areas of Serbia based on development of SME in agribusiness using the cluster analysis. TTEM - Technics Technologies Education Management, Bosnia and Herzegovina, Sarajevo, 6, (3), 811-818.
Shenngen F. & Xiaobo Z. (2002): Production and productivity growth in Chinese Agriculture: New National and Regional Measures. Economic Development and Cultural Change, The University of Chicago.
Scheel H. (2000): EMS - Efficiency Measurement System User’s Manual. Version 1.3. http://www.wiwi.uni-jena.de/Mikro/pdf/ems.pdf, April 10, 2014
Vennesland B (2005): Measuring rural economic development in Norway using data envelopment analysis.