An objectıve criteria proposal for the comparison of MCDM and weighting methods in financial performance measurement: An application in Borsa Istanbul
Financial performance research with multi-criteria decision making (MCDM) methods, is a common subject of study not only for researchers in the finance literature but also in the applied sciences. Financial performance manifests itself in an internal universe that a firm can directly control, while the share return of the same firm is shaped synchronically in an external universe that cannot be controlled directly. On the other hand, preferring the most suitable MCDM and weighting method to use in measuring financial performance is often regarded as a source of uncertainty. In this study, the share price is used as an external proxy and a tool for comparing MCDM methods, completely different from the previously proposed approaches based on the superiority of internal features. This study was conducted on 131 manufacturing companies in Borsa Istanbul, covering entire 20-quarter period between 2014 and 2018. The experimental findings of the study provide valid solutions for the MCDM and weighting selection problem, that can be proposed as a practical and indirect solution. The results show that preference ranking organization method for enrichment of evaluations (PROMETHEE) method used with hybrid weighting technique produced by far the best performance rankings in 19 out of 20 quarterly periods when compared to the technique for order preference by similarity to ideal solution (TOPSIS) and weighted sum approach (WSA).
Alp, İ., Öztel, A., & Köse, M. S. (2015). Entropi tabanlı Maut Yöntemi ile kurumsal sürdürülebilirlik performansı ölçümü: Bir vaka çalışması. Ekonomik ve Sosyal Araştırmalar Dergisi, 11(2), 65–81.
Alvandi, M., Fazli, S., Gholamreza Kordestani, G., & Rezaei, R. (2013). Evaluation and ranking the companies of auto and spare parts industry accepted in Tehran Stock Exchange using FAHP and VIKOR. International Research Journal of Applied and Basic Sciences, 5(7), 883–890.
Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200, 198–215. DOI: https://doi.org/10.1016/j.ejor.2009.01.021
Bodie, Z., Kane, A., & Marcus, J. A. (2003). Essentials of investments. (9th edition). New York: Mc Graw Hill, (Chapter 13).
Carton, R. B. (2004). Measuring organizational performance: an exploratory study. Georgia: Doctoral Dissertation, The University of Georgia.
Carton, R. B., & Hofer, C. W. (2006). Measuring organizational performance: Metrics for entrepreneurship and strategic management research. Cheltenham: Edward Elgar Publishing Limited, (Chapter 10). DOI: https://doi.org/10.4337/9781847202840
Çalış, N., & Sakarya, Ş. (2020). Finansal performans ve hisse senedi getirisi ilişkisi: BIST bankacılık endeksi üzerine bir inceleme. Manas Sosyal Araştırmalar Dergisi, 9(2), 1147–1059.
Damodaran, A. (2007). Return on capital (ROC), return on invested capital (ROIC) and return on equity (ROE): Measurement and implications. SSRN: 1105499, Stern School of Business, New York University, 1-69. DOI: https://doi.org/10.2139/ssrn.1105499
Danesh, D., Ryan, M. J., & Abbasi, A. (2017). A systematic comparison of multi-criteria decision making methods for the improvement of project portfolio management in complex organisations. International Journal of Management and Decision Making, 16(3), 280–320. DOI: https://doi.org/10.1504/IJMDM.2017.085638
Ertuğrul, İ., & Karakaşoğlu, N. (2009). Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods. Expert Systems with Applications, 36, 702–715. DOI: https://doi.org/10.1016/j.eswa.2007.10.014
Esbouei, S. K., Ghadikolaei, A. S., & Antucheviciene, J. (2014). Using FANP and fuzzy VIKOR for ranking manufacturing companies based on their financial performance. Economic Computation & Economic Cybernetics Studies & Research, 48(3), 141–162.
Gade, P. K., & Osuri, M. (2014). Evaluation of multi criteria decision making methods for potential use in application security. Karlskrona: Master’s Thesis, School of Computing at Blekinge Institute of Technology.
Ghadikolaei, S. A., Khalili Esbouei, S., & Antucheviciene, J. (2014). Applying fuzzy MCDM for financial performance evaluation of Iranian companies. Technological and Economic Development of Economy, 20(2), 274–291. DOI: https://doi.org/10.3846/20294913.2014.913274
Jablonsky, J. (2014). MS Excel based software support tools for decision problems with multiple criteria. Procedia Economics and Finance, 12, 251–258. DOI: https://doi.org/10.1016/S2212-5671(14)00342-6
Karaoğlan, S., & Şahin, S. (2018). BIST XKMYA işletmelerinin finansal performanslarının çok kriterli karar verme yöntemleri ile ölçümü ve yöntemlerin karşılaştırılması. Ege Academic Review, 18(1), 63–80. DOI: https://doi.org/10.21121/eab.2018135912
Kirkwood, C. W. (1997). Strategic decision making: Multiobjective decision analysis with spreadsheets. California: Duxbury Press, (Chapter 4).
Kou, G., Yang, P., Peng, Y., Xiao, F., Chen, Y., & Alsaadi, F. E. (2020). Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods. Applied Soft Computing, 86(105836), 1–14.
Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustainable housing affordability. Omega, 59, 146–156. DOI: https://doi.org/10.1016/j.omega.2015.05.013
Munier, N. (2006). Economic growth and sustainable development: Could multicriteria analysis be used to solve this dichotomy?. Environment, Development and Sustainability, 8, 425–443. DOI: https://doi.org/10.1007/s10668-005-8505-6
Odu, G. O. (2019). Weighting methods for multi-criteria decision making technique. Journal of Applied Sciences and Environmental Management, 23(8), 1449–1457.
Olson, D. L. (2004). Comparison of weights in TOPSIS models. Mathematical and Computer Modelling, 40, 721–727. DOI: https://doi.org/10.1016/j.mcm.2004.10.003
Özden, Ü. H., Başar, Ö. D., & Bağdatlı, S. K. (2012). İMKB’de işlem gören çimento sektöründeki şirketlerin finansal performanslarının VIKOR yöntemi ile sıralanması. Ekonometri ve İstatistik Dergisi, 17, 23–44.
Öztürk, E. (2017). Farklı finansal raporlardan elde edilen performans ölçütleri ile cari piyasa değerleri arasındaki ilişkinin belirlenmesi: BIST 50, Mali Çözüm Dergisi 142, 45–63.
Sałabun, W., & Urbaniak, K. (2020). A new coefficient of rankings similarity in decision-making problems. In: Krzhizhanovskaya V. et al. (Eds.) Computational science - ICCS 2020, (pp. 632-645). Switzerland: Springer.
Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, 379–423, 623–656. DOI: https://doi.org/10.1002/j.1538-7305.1948.tb00917.x
Stewart, B. (2013). Best-Practice EVA: The definitive guide to measuring and maximizing shareholder value, New York: John Wiley & Sons, Inc., (Chapter 5, Glossary). DOI: https://doi.org/10.1002/9781119204893
Şen, S. (2014). Farklı ağırlıklandırma tekniklerinin denendiği çok kriterli karar verme yöntemleri ile Türkiye’deki Mevduat bankalarının mali performans değerlendirmesi. İstanbul: Master’s Thesis, Mimar Sinan Fine Arts University Institute of Natural Sciences.
Taşabat, S. E., Cinemre, N., & Şen, S. (2015). Farklı Ağırlıklandırma tekniklerinin denendiği çok kriterli karar verme yöntemleri ile Türkiye’deki mevduat bankalarının mali performanslarının değerlendirilmesi. Social Sciences Research Journal, 4(2), 96–110.
Ünlü, U., Yalçın, N., & Yağlı, İ. (2017). Kurumsal yönetim ve firma performansı: TOPSIS yöntemi ile BIST 30 firmaları üzerine bir uygulama. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 19(1), 63–81. DOI: https://doi.org/10.16953/deusbed.09673
Velasquez, M., & Hester P. T. (2013). An analysis of Multi-Criteria decision making methods. International Journal of Operations Research, 10(2), 56–66.
Wang, Z., & Rangaiah, G. P. (2017). Application and analysis of methods for selecting an optimal solution from the Pareto-Optimal front obtained by multiobjective optimization. Industrial & Engineering Chemistry Research, 56, 560−574. DOI: https://doi.org/10.1021/acs.iecr.6b03453
Yaakob, A. M., & Gegov, A. (2016). Interactive TOPSIS based group decision making methodology using Z-Numbers. International Journal of Computational Intelligence Systems, 9(2), 311–324. DOI: https://doi.org/10.1080/18756891.2016.1150003
Yalçın, N., Bayrakdaroğlu, A., & Kahraman, C. (2012). Application of fuzzy multi-criteria decision making methods for financial performance evaluation of Turkish manufacturing industries. Expert Systems with Applications, 39, 350–364. DOI: https://doi.org/10.1016/j.eswa.2011.07.024