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Evaluating Efficiency of Nina Distribution Company Using Window Data Envelopment Analysis and Malmquist Index

Authors: Hossein Taherian Far, Ali Bazaee

Abstract:

Achieving continuous sustained economic growth and following economic development can be the target for all countries which are looking for it. In this regard, distribution industry plays an important role in growth and development of any nation. So, estimating the efficiency and productivity of the so called industry and identifying factors influencing it, is very necessary. The objective of the present study is to measure the efficiency and productivity of seven branches of Nina Distribution Company using window data envelopment analysis and Malmquist productivity index from spring 2013 to summer 2015. In this study, using criteria of fixed assets, payroll personnel, operating costs and duration of collection of receivables were selected as inputs and people and net sales, gross profit and percentage of coverage to customers were selected as outputs. Then, the process of performance window data envelopment analysis was driven and process efficiency has been measured using Malmquist index. The results indicate that the average technical efficiency of window Data Envelopment Analysis (DEA) model and fluctuating trend is sustainable. But the average management efficiency in window DEA model is related with negative growth (decline) of about 13%. The mean scale efficiency in all windows, except in the second one which is faced with 8%, shows growth of 18% compared to the first window. On the other hand, the mean change in total factor productivity in all branches of the industry shows average negative growth (decrease) of 12% which are the result of a negative change in technology.

Keywords: Nina Distribution Company branches, window data envelopment analysis, Malmquist productivity index.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1128909

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References:


[1] N. Akbari, Din Mohammad A, measuring Dairy Farms' production with window data envelopment analysis. Sixth Conference of Agricultural Economics in Iran, 2007.
[2] T. A. Biyanaie, Providing an appropriate model for evaluating the performance of private banks. Third National Conference on DEA, 2010.
[3] T. Mehrjardi, A. F. Yazdi, and R. Mohebi, Modeling and predicting the efficiency of public and private banks in Iran Using artificial neural networks, fuzzy neural networks and genetic algorithms. Journal of asset management and financing, 2013, pp. 103-106.
[4] S. F. Jelodar, D. Motevali, Measuring productivity in academic units and ranking them based on the model of DEA and Malmquist Index. The Quarterly Journal of Commerce, vol. 48, 2009, pp. 101-69.
[5] N. F. Bany Amerian, The performance assessment of managers by using data envelopment analysis and Malmquist index. Third National Conference on DEA, 2011.
[6] G. Jahanshahloo, Alirezaie, The diagonal assessment of efficiency in data envelopment analysis, 1995.
[7] A. S. Mohaggar, M. Dehghan, and M. Hossein Zadeh, Productivity Analysis Using DEA and Malmquist Index hybrid model. Sixth International Conference on Management, 2008, pp. 1 - 15.
[8] H. Noorbakhsh, Performance analysis of telecommunications companies in provinces of Iran in the years 85-89 using window DEA and Malmquist Index. MAthesis, 2012.
[9] P. Drucker,The practice of Management. New York: Happer & row, 1998.
[10] D. N. Mania,and E. thanassoulis, A cost Malmquist productivity index. European journal of Operational Research, vol. 154 no.2, 2014, pp. 396-409.
[11] J. Odeck, Assessing the Relative and Efficiency and productivity growth of Inspection Services: An application of DEA and Malmquist indices. European journal of Operational Research, vol. 126, 2000, pp. 501-514.
[12] V. Sena, Total Factor productivity and Spillover hypothesis: Some new evidence. International journal of Production Economics, vol. 92, 2004, pp. 31-42.
[13] C.C. Sun, Evaluating and benchmarking productive performances of six industrials in taiwan Hsin Chu industrial Science park. Expert Systems with Applications, vol. 38, 2011, pp. 2195-2205.
[14] M. Dastgir, M. Momeni, S. Danashvar,, & A. M. Sarokolaei, Analyzing Financial Statements by Using Window data Envelopment Analysis Model (Output Oriented BCC) Evidence from Iran. Journal of Basic and Applied Scientific Research, vol. 12, 2012, pp. 12049-12055
[15] Y.Huang, H. I. Mesak, M. K. Hsu, and H. Qu, Dynamic efficiency assessment of the Chinese hotel industry. Journal of Business Research, vol. 65, 2012, pp. 59-67.
[16] F. yang, D. Wu, L. Liang, G. Bi, and D. Wu, supply chain DEA: Production Possibility set and performances Evaluation Model, Springer Science Business Madia, 2009, pp. 1-17.
[17] A. Charnes, and W.W. Cooper. “Preface To Topics in DEA”, Annals of operation Research, Z, 1985.
[18] A.Charnes, W. W. Cooper, and E. Rhodes, “Measuring The Efficiency of decision making units”, European Journal of Operational Research, vol. 2, no. 6, 1978, PP, 429-444.
[19] S.H. Chung, A.I. Lee, H.Y. Kang, and C.-W. Lai, A DEA window analysis on the product family mix selection for a semiconductor fabricator. Expert Systems with Applications, 35, 2008, pp, 379-388.
[20] N. Habibov‚ and L. Fan, Comparing and contrasting poverty reduction performance of social welfare programs across jurisdictions in Canada using Data Envelopment Analysis (DEA): An exploratory study of the era of devolution. Evaluation and Program Planning, vol. 33, 2010, pp. 457-467.
[21] M.J Farrel, "The Measurement of Productive Efficiency", Journal of Royal Statistical Society, vol. 120, 1957, pp. 253-281.
[22] M. Asmild, J. paradi, V. Aggarwal, and C. Schaffnit‚ Combining DEA window analysis, the Malmquist index approach in a study of the Canadian banking industry. Productivity Analysis, vol. 21, 2004, pp. 607-616.
[23] Y. Chen‚ and A. Aghaiqbal‚ DEA Malmquist productivity measure: New insight with an Application to computer Industry. European journal of Operational Reserch‚ vol. 159 no. 1 ‚ 2004. Pp. 239- 249
[24] F. Yang, D. Wu, L. Liang, G. Bi, D. DashWu, “Supply Chain DEA: Production Possibility Set and Performance Evaluation Model”, Springer Science+Business Media, LLC, 2009, pp. 1 –17.
[25] J. Cummins‚ S. Tenyon‚ and W. Marya‚ Consolidation and Efficiency in the US Life insurance industry. Journal of banking and finance‚ vol. 23‚ 1999, pp.325- 357.
[26] R. Fare, S. H. Groosskopf, M. Norris, Z. Zhang, Productivity growth, thechnical progress and efficiency chang in industrialized countries: Reply. The American Economic Review, vol. 84, no.1, 1994, pp. 66-83.
[27] D. W. Caves, L. R. Christensen, W. E. Diewert, Multilateral comparisons of output, input, and productivity using superlative index numbers. Economic Journal, vol. 2, 1982, pp. 73–86.
[28] G. Debreu, The coefficient of resource utilization. Econometrica, vol. 19, no. 3 1951, pp. 273–292.
[29] T. C. Koopmans, An analysis of production as an efficient combination of activities. In Koopmans, T. C., editor, Activity Analysis of Production and Allocation. Jhon Wiley and Sons, Inc 1951.