A Hybrid MEREC-CoCoSo-MARCOS Framework for Assessing Financial Performance: Evidence from Istanbul Stock Exchange
DOI:
https://doi.org/10.5281/zenodo.20573610Parole chiave:
Financial performance, MEREC, CoCoSo, MARCOS, BIST, Multi-criteria decision makingAbstract
This study evaluates the financial performance of firms operating in the BIST Non-Metallic Mineral Products Sector for the period 2013–2022 by employing a hybrid multi-criteria decision-making (MCDM) framework. The analysis integrates the MEREC method for objective criterion weighting with the CoCoSo method for performance ranking, while the MARCOS approach and Spearman rank correlation analysis are used to test the robustness and consistency of the results. Four financial indicators representing liquidity, operational efficiency, profitability, and financial risk dimensions are included in the evaluation: Current Ratio (CUR), Asset Turnover Ratio (ATR), EBITDA Margin (EBM), and Leverage Ratio (LEV). The findings reveal that EBITDA Margin consistently emerges as the most influential criterion throughout the analysis period, indicating that operational profitability constitutes the primary determinant of firm performance in the sector. In contrast, leverage and liquidity indicators exhibit relatively lower explanatory power. The ranking results further demonstrate that certain firms maintain consistently superior performance across the years, while others display persistent underperformance and greater sensitivity to changing macroeconomic conditions. Robustness tests conducted through the MARCOS method produce highly similar ranking structures, and the Spearman correlation coefficients indicate strong statistical agreement between the applied methodologies. Overall, the results suggest that financial performance in the BIST non-metallic mineral products sector is predominantly driven by operational profitability and efficiency rather than short-term liquidity or debt structure. The study contributes to the literature by applying recent objective weighting and compromise-based MCDM methods within a sector-specific and long-term financial performance evaluation framework.
Riferimenti bibliografici
Abdel-Basset, M., Ding, W., Mohamed, R., & Metawa, N. (2020). An integrated plithogenic MCDM approach for financial performance evaluation of manufacturing industries. Risk Management, 22(3), 192–218.
https://doi.org/10.1057/s41283-020-00061-4
Acar, E., & Sarıyer, G. (2021). Financial performance evaluation of Turkish basic metal industry: Combining AHP and TOPSIS. Journal of Academic Research in Economics, 13(2).
https://doi.org/10.18092/ulikidince.734976
Akgün, A., & Şamiloğlu, F. (2016). Financial performance evaluation of BIST manufacturing companies by TOPSIS method. Muhasebe ve Finansman Dergisi, 72, 95–112.
https://doi.org/10.25095/mufad.1087406
Ayaydın, H., Durmuş, S., & Pala, F. (2017). Gri ilişkisel analiz yöntemiyle Türk lojistik firmalarında performans ölçümü. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 8(21), 76–94.
https://doi.org/10.17823/gusb.2590
Brigham, E. F., Houston, J. F., & Clark, D. A. (2004). Fundamentals of financial management.
Damodaran, A. (2012). Investment Valuation: Tools and Techniques for Determining the Value of Any Asset (3rd ed.). Wiley.
Çilek, A., Şeyranlıoğlu, O., & Konuş, C. (2025). Profitability Based Financial Performance Analysis in BIST Basic Metal Industry Sector: LOPCOW-RSMVC Hybrid Multi-Criteria Decision Making Model. İşletme Araştırmaları Dergisi, 17(1), 1–29.
https://doi.org/10.57116/isletme.1613012
Dincer, H., & Yuksel, S. (2019). Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: A comparative analysis based on the hybrid fuzzy decision-making approach. Energy, 175, 1259–1270.
https://doi.org/10.1016/j.energy.2019.03.143
Ersoy, N. (2023). Applying an integrated data-driven weighting system – CoCoSo approach for financial performance evaluation of Fortune 500 companies. E&M Economics and Management, 26(3), 92–108.
https://doi.org/10.15240/tul/001/2023-3-006
Ertuğrul, İ., & Karakaşoğlu, N. (2009). Performance evaluation of Turkish cement firms with fuzzy AHP and TOPSIS methods. Expert Systems with Applications, 36(1), 702–715.
https://doi.org/10.1016/j.eswa.2007.10.014
Feng, C. M., & Wang, R. T. (2000). Performance evaluation for airlines including the consideration of financial ratios. Journal of Air Transport Management, 6(3), 133–142.
https://doi.org/10.1016/S0969-6997(00)00003-X
Göktolga, Z. G., & Karakış, E. (2018). Bireysel emeklilik şirketlerinin finansal performanslarının bulanık AHP ve VIKOR yöntemi ile analizi. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 19(1), 92–108.
Hwang, C. L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer.
Keshavarz‐Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antuchevičienė, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13(4), 525.
https://doi.org/10.3390/sym13040525
Mastilo, Z., Štilić, A., Gligović, D., & Puška, A. (2024). Assessing the banking sector of Bosnia and Herzegovina: An analysis of financial indicators through the MEREC and MARCOS methods. Journal of Central Banking Theory and Practice, 13(1), 167–197.
https://doi.org/10.2478/jcbtp-2024-0008
Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455.
https://doi.org/10.1016/S0377-2217(03)00020-1
Ömürbek, N., Karaatlı, M., & Yetim, T. (2014). Analitik hiyerarşi süreci temelli TOPSIS ve VIKOR yöntemleri ile performans değerlendirmesi. Süleyman Demirel Üniversitesi İİBF Dergisi, 19(2), 47–71.
Özekenci, S. Y. (2024). Financial performance measurement of companies in the BIST sustainability 25 index with LBWA and MEREC-based CRADIS methods. Mehmet Akif Ersoy Üniversitesi İİBF Dergisi, 11(3), 1184–1211.
https://doi.org/10.30798/makuiibf.1465069
Stević, Ž., & Brković, N. (2020). A novel integrated FUCOM-MARCOS model for evaluation of human resources in a transport company. Logistics, 4(1), 4. https://doi.org/10.3390/logistics4010004
Tzeng, G. H., & Huang, J. J. (2011). Multiple attribute decision making: methods and applications. CRC press.
Wang, T. C., & Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980–8985. https://doi.org/10.1016/j.eswa.2008.11.035
Yazdani, M., Zarate, P., Zavadskas, E. K., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501–2519. https://doi.org/10.1108/MD-05-2017-0458
Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Electronics and Electrical Engineering, 122(6), 3–6. https://doi.org/10.5755/j01.eee.122.6.1810
Zopounidis, C., & Doumpos, M. (2002). Multi-criteria decision aid in financial decision making: Methodologies and literature review. Journal of Multi-Criteria Decision Analysis, 11(4–5), 167–186. https://doi.org/10.1002/mcda.333
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