ANALYZING FINANCIAL PERFORMANCES AND EFFICIENCY OF THE RETAIL FOOD IN SERBIA BY USING THE AHP – TOPSIS METHOD
DOI:
https://doi.org/10.5937/ekoPolj2001055LKeywords:
efficiency, retail food, Serbia, AHP, TOPSISAbstract
The aim and purpose of this paper is to point out to the quality of financial performance and efficiency of food retailers in Serbia, as well as measures for improvement in the future, based on theoretical knowledge and empirical analysis using AHP-TOPSIS methods. The problem of analyzing the financial performance of all companies, which includes trading companies, is very topical, significant and complex. Consequently, mathematical methods and models have lately been increasingly used. With this insight in mind, this paper investigates the financial performance and efficiency of food retailers in Serbia using AHP and TOPSIS methods. Of all the observed optimization criteria (cost of goods sold, operating costs, gross margin and net profit), the most significant was the cost of goods sold. The most efficient food retailer in Serbia is Aman. The Mercator-S Company is inefficient. In order to improve the efficiency of food retailers in Serbia, it is necessary to apply the Western business models (private brand, multichannel sales, organic food sales and others), the concepts of strategic management accounting and to strengthen the digitalization of business.
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References
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28. Martino, G. et al. (2017). Supply Chain Risk Assessment in the Fashion retail Industry: An Analytic Network Process Approach. International Journal of Applies research, 12(2), 140-154.
29. Pang, J. and Kogel, M (2013). Retail Bankruptcy Prediction. American Journal of Economics and Business Administration, 5(1), 29-46.
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32. Rogova, E. and Blinova, A. (2018). The Technical Efficiency of Russian Retail Companies: An Empirical Analysis. Zesz. Nauk. UEK, 5 (977), 171–185.
33. Saaty, T.L. (1970). Optimization in integers and Related Extremal Problems. New York: MCGraw-Hill.
34. Saaty, T.L. and Vargas, L.G. (2001). Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. International Series in Operations Research and Management Science, Springer.
35. Saaty T.L.(1980).The analytic hierarchy process. New York: McGraw-Hill.
36. Saaty, T.L. (2008). Decision Making With The Analytic Hierarchy Process. Int J Serv Sci, 1(1), 83-98.
37. Saaty, T.L. (1986). Axiomatic foundation of the Analytic Hierarchy Process. Management Science, 32(7), 841-855 .
38. Stojanovic, M. and Rogodic, D. (2016). Evaluating E-commerce Sites in Serbia Using AHP-TOPSIS Methods. Proceedings University of Synergy, 99-104. [in Serbia: Ocenjivanje sajtova za E-kupovinu u Srbiji upotrebom AHP-TOPSIS metoda. Zbornik radova univerziteta sinergija, 99-104].
39. Simbolon, R. and Elviani S. (2017). Bankruptcy Analysis Using Altman Z-score Model in Retail Trading Company Listed in Indonesia Stock Exchange. Proceedings of The 7th Annual International Conference (AIC) Syiah Kuala University and The 6th International Conference on Multidisciplinary Research (ICMR) in conjunction with the International Conference on Electrical Engineering and Informatics (ICELTICs) 2017, October 18-20, 2017, Banda Aceh, Indonesia, 273-279.
40. Trejo García , J. C., Martínez García, M. A. and Venegas Martínez, F. (2017). Credit risk management at retail in Mexico: An econometric improvement in the selection of variables and changes in their characteristics. Contaduría y Administracion, 62, 399-418.
41. Tsolas, I.E. (2015). Firm credit risk evaluation: a series two-stage DEA modeling framework. Ann Oper Res, 233, 483-500.
42. Üçüncü, T., Akyüz, K. C., Akyüz, İ., Bayram, B. Ç., Ve Ersen, N. (2018). Evaluation Of Financial Performance Of Paper Companies Traded At BIST With TOPSIS Method. Kastamonu Unıversıty Journal Of ForestryFaculty, 18(1), 92-98.
43. Urbonavičiūtė, K. and Maknickienė, N. (2019). Investigation of digital retail companies financial performance using multiple criteria decision analysis. Economics and Management/ Ekonomika ir vadyba, 11, 1-9.
44. Yousefi, A. ve Hadi-Vencheh, A. (2010). An integrated group decision making model and its evaluation by DEA for automobile industry. ExpertSystems with Applications, 37(8), 543-556.
45. Yonggan Zhao, Min Zhang, Sakamon Devahastin, Yaping Liu (2019. Progresses on processing methods of umami substances: A review . Trends in Food Science & Technology, 93, 125-135.
46. Wang, Y. J. and Lee, H. S. (2007). GeneralizingTOPSIS for fuzzy multiple-criteria group decision-making. Computers and Mathematics with Applications, 53, 1762–1772.
47. Zaernyuk, V.M. et al. (2016). Solving the Problem of Credit Defaults in Retail Sector. European Research Studies, XIX (2), 205-217.
2. Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264.
3. Bhargava, M., Dubelaar, C. and Scott, T. (1998). Predicting bankruptcy in the retail sector: an examination of the validity of key measures of performance. Journal of Retailing and Services, 5(6), 105-117.
4. Chang, D.Y.(1996). Aplikation of the extent analysis method on fuzy AHP. European journal of operational research, 95(3), 649-655.
5. Danielle Ufer, David L. Ortega, Christopher A. Wolf (2019). Economic foundations for the use of biotechnology to improve farm animal welfare. Trends in Food Science & Technology, 91, 129-139.
6. Harker P. T. and Vargas L.G.(1987). The Theory of Ratio Scale Estimation: Saatys Analytic Hierarchy Process. Management Science,. 33(11), 1383-1403.
7. Hanie, M., Boutkhoum,O., Tikniouine, A. and Agouti, T. (2016). Application of an integrated multi-criteria decision making AHP-TOPSIS methodology for ETL software selection. Springer Plus, 5(263), 1-17.
8. Hwang C.L., Yoon K.S. (1981). Multiple attribute decision making: methods and applications. Berlin: Springer.
9. Hwang, C. L., Yoon, K.P. (1995). Multiple Attribute Decision Making: An Introduction. Paperback / Sage Pubns.
10. Jacob Tizhe Liberty, Jalal Dehghannya, Michael O. Ngadi (2019). Effective strategies for reduction of oil content in deep-fat fried foods: A review. Trends in Food Science & Technology, 92, 172-183.
11. Jian Ju, Xueqi Chen, Yunfei Xie, Hang Yu, ... Weirong Yao (2019). Application of essential oil as a sustained release preparation in food packaging. Trends in Food Science & Technology, 92, 22-32.
12. S. Kalpana, S.R. Priyadarshini, M. Maria Leena, J.A. Moses, C. Anandharamakrishnan (2019). Intelligent packaging: Trends and applications in food systems. Trends in Food Science & Technology 93, 145-157.
13. Karan, M.B., Ulucan, A. and Kaya, M. (2008). Estimation of credit risk of retail stores by using their payment history: A combined logistic regression and multidea. 5th Internation Scientific Conference Business and Management 2008, 16-17 May 2008, Vilniua, Lithuania, 222- 227.
14. Keener, M.H. (August 2013). Predicting The Financial Failure Of Retail Companies In The United States. Journal of Business & Economics Research, 11(8), 373-380.
15. Kingyens, Angela Tsui-Yin Tran (2012). Bankruptcy prediction of companies in the retail – apparel industry using data envelopment analysis. Degree of Doctor of Philosophy Graduate Department of Chemical Engineering and Applied Chemistry University of Toronto.
16. Konuk, F. (2018). Financial and Performance Analysis of Food Companies: Application of Topsis and DEA. MANAS Journal of Social Studies, 7(3), 381-390.
17. Lau, K.H. (2013). Measuring distribution efficiency of a retail network through data envelopment analysis. Int.J.Production Economics, 146, 598-611.
18. Li, Z., Crook, J. and Andreeva, (2017). Dynamic prediction of financial distress using Malmquist DEA. Expert systems With Applications, 80, 94-106.
19. Li, Z., Crook, J. and Andreeva, G. (2014). Chinese Companies Distress Prediction: An Application of Data Envelopment Analysis. Journal of the Operational Research Society, 65, 466-479.
20. Lukić, R. (2011a). Evaluation of Retail Business Performance. Belgrade: Faculty of Economics [in Serbia: Evaluacija poslovnih performansi u maloprodaji].
21. Lukic, R. (2011b). Estimates of economic performance of organic food retail trade. Economic research, 24(3), 157-169.
22. Lukic, R. (2018). The Analysis of the Operative Profit Margin of Trade Companies in Serbia. Review of International Comparative Management, 19(9), 458-478.
23. Lukić, R., Lalić, S., Sućeska, A., Hanić, A. and Bugarčić, M. (2018). Carbon diohide emissions in retail food. Economics of Agriculture, 65(2), 859-874.
24. Lukic, R. (2018). Analysis of Return on Investment in Trade of Serbia: Current State and Prospects. Proceedings of the Matica Srpska for Social Sciences, 168 (4/2018), 777-803 [in Serbia: Анализа приноса на инвестиције трговине Србије: Актуелно стање и перспективе. Зборник Матице српске за друштвене науке].
25. Lukić, R., Lalić, S., Sućeska, A., Hanić, A. and Bugarčić, M. (2018). Carbon diohide emissions in retail food. Economics of Agriculture, 65(2), 859-874.
26. Lukic, R. (2019). Efficiency analysis of trading companies in Serbia. Proceedings of the Faculty of Economics Brčko, 13 (1), 15-27 [in Serbia: Analiza efikasnosti trgovinskih preduzeća u Srbiji. Zbornik radova Ekonomskog fakulteta Brčko].
27. Manini, R. and Amat, O. (2018). Credit scoring for the supermarket and retailing industry: Analysis and application proposal. Economics Working Paper Series, Working Paper No. 1614, Universitat Pompeu Fabra, Barcelona, Department of Economics and Business, 1-14.
28. Martino, G. et al. (2017). Supply Chain Risk Assessment in the Fashion retail Industry: An Analytic Network Process Approach. International Journal of Applies research, 12(2), 140-154.
29. Pang, J. and Kogel, M (2013). Retail Bankruptcy Prediction. American Journal of Economics and Business Administration, 5(1), 29-46.
30. Paradi, J.C., Wilson, D. and Yang, X.P. (2014). Data Envelopment Analysis of Corporate Failure for Non-Manufacturing Firms Using a Slacks-Based Measure. Journal of Service Science and Management, 7, 277-290.
31. Popović, S, Janković, I, & Stojanović, Ž., (2018). The importance of bank credits for agricultural financing in Serbia. Economics of Agriculture, 65 (1), 65-80.
32. Rogova, E. and Blinova, A. (2018). The Technical Efficiency of Russian Retail Companies: An Empirical Analysis. Zesz. Nauk. UEK, 5 (977), 171–185.
33. Saaty, T.L. (1970). Optimization in integers and Related Extremal Problems. New York: MCGraw-Hill.
34. Saaty, T.L. and Vargas, L.G. (2001). Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. International Series in Operations Research and Management Science, Springer.
35. Saaty T.L.(1980).The analytic hierarchy process. New York: McGraw-Hill.
36. Saaty, T.L. (2008). Decision Making With The Analytic Hierarchy Process. Int J Serv Sci, 1(1), 83-98.
37. Saaty, T.L. (1986). Axiomatic foundation of the Analytic Hierarchy Process. Management Science, 32(7), 841-855 .
38. Stojanovic, M. and Rogodic, D. (2016). Evaluating E-commerce Sites in Serbia Using AHP-TOPSIS Methods. Proceedings University of Synergy, 99-104. [in Serbia: Ocenjivanje sajtova za E-kupovinu u Srbiji upotrebom AHP-TOPSIS metoda. Zbornik radova univerziteta sinergija, 99-104].
39. Simbolon, R. and Elviani S. (2017). Bankruptcy Analysis Using Altman Z-score Model in Retail Trading Company Listed in Indonesia Stock Exchange. Proceedings of The 7th Annual International Conference (AIC) Syiah Kuala University and The 6th International Conference on Multidisciplinary Research (ICMR) in conjunction with the International Conference on Electrical Engineering and Informatics (ICELTICs) 2017, October 18-20, 2017, Banda Aceh, Indonesia, 273-279.
40. Trejo García , J. C., Martínez García, M. A. and Venegas Martínez, F. (2017). Credit risk management at retail in Mexico: An econometric improvement in the selection of variables and changes in their characteristics. Contaduría y Administracion, 62, 399-418.
41. Tsolas, I.E. (2015). Firm credit risk evaluation: a series two-stage DEA modeling framework. Ann Oper Res, 233, 483-500.
42. Üçüncü, T., Akyüz, K. C., Akyüz, İ., Bayram, B. Ç., Ve Ersen, N. (2018). Evaluation Of Financial Performance Of Paper Companies Traded At BIST With TOPSIS Method. Kastamonu Unıversıty Journal Of ForestryFaculty, 18(1), 92-98.
43. Urbonavičiūtė, K. and Maknickienė, N. (2019). Investigation of digital retail companies financial performance using multiple criteria decision analysis. Economics and Management/ Ekonomika ir vadyba, 11, 1-9.
44. Yousefi, A. ve Hadi-Vencheh, A. (2010). An integrated group decision making model and its evaluation by DEA for automobile industry. ExpertSystems with Applications, 37(8), 543-556.
45. Yonggan Zhao, Min Zhang, Sakamon Devahastin, Yaping Liu (2019. Progresses on processing methods of umami substances: A review . Trends in Food Science & Technology, 93, 125-135.
46. Wang, Y. J. and Lee, H. S. (2007). GeneralizingTOPSIS for fuzzy multiple-criteria group decision-making. Computers and Mathematics with Applications, 53, 1762–1772.
47. Zaernyuk, V.M. et al. (2016). Solving the Problem of Credit Defaults in Retail Sector. European Research Studies, XIX (2), 205-217.
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Published
2020-03-25
How to Cite
Lukić, R., Vojteski Kljenak, D., & Anđelić, S. (2020). ANALYZING FINANCIAL PERFORMANCES AND EFFICIENCY OF THE RETAIL FOOD IN SERBIA BY USING THE AHP – TOPSIS METHOD. Ekonomika Poljoprivrede, 67(1), 55–68. https://doi.org/10.5937/ekoPolj2001055L
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Original scientific papers
