Vol. 10 No. 1 (2022): Business & Management Studies: An International Journal
Articles

The effect of pandemic conditions on financial success rankings of BIST SME industrial companies: a different evaluation with the help of comparison of special capabilities of MOORA, MABAC and FUCA methods

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  • Mahmut Baydaş
Mahmut Baydaş
Dr., Lecturer, Necmettin Erbakan University, Konya, Turkey

Published 2022-03-26

Keywords

  • Finansal Performans, MCDM, hisse getirisi, Spearman Korelasyon
  • Financial Performance, MCDM, stock return, Spearman’s Correlation Coefficient

How to Cite

The effect of pandemic conditions on financial success rankings of BIST SME industrial companies: a different evaluation with the help of comparison of special capabilities of MOORA, MABAC and FUCA methods. (2022). Business & Management Studies: An International Journal, 10(1), 245-260. https://doi.org/10.15295/bmij.v10i1.1997

Copyright (c) 2022 Mahmut Baydaş

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

The effect of pandemic conditions on financial success rankings of BIST SME industrial companies: a different evaluation with the help of comparison of special capabilities of MOORA, MABAC and FUCA methods. (2022). Business & Management Studies: An International Journal, 10(1), 245-260. https://doi.org/10.15295/bmij.v10i1.1997

Abstract

Considering COVID-19 pandemic conditions from an MCDM perspective, the change in the ranking positions of the companies before and during the pandemic conditions has become more critical for many researchers and especially financial decision-makers. In this study, different from other studies, a new methodological procedure was followed. For the first time, an MCDM method was chosen among the alternatives with an objective point of view, and the application was continued. In other words, the final performance evaluation is based on the results of this chosen method. In the first step, the financial performance of companies traded in the BIST SME Industry, which is the application area of the study, was calculated with three different MCDM methods (MOORA, MABAC and FUCA). In the second step, the ranking correlations between the calculated financial performance scores and the stock return in the current period were compared with the Spearman method. Finally, in the third step, based on this indirect objective reference verification result (as it is the most appropriate and successful), the necessary financial analyzes were made with the FUCA method. According to the findings, the FUCA method correlated higher with the stock return before and during the pandemic than the other MCDM methods. According to these results, when a performance comparison is made between before and during pandemic conditions, three changes become prominent: the most successful companies, the companies' overall ranking, and the favourite sectors have entirely changed for the base periods. This innovative procedure has been proposed for the first time in the literature and has been successfully applied.

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References

  1. Aifuwa, H. O., S. Musa ve S. A. Aifuwa (2020), “Coronavirus Pandemic Outbreak and Firms Performance in Nigeria”, Management and Human Resource Research Journal, Vol. (9)4, 15-25.
  2. Baležentis, A., T. Baležentis ve A. Misiunas (2012), “An integrated assessment of Lithuanian economic sectors based on financial ratios and fuzzy MCDM methods”, Technological and Economic Development of Economy, Vol. 18(1), 34-53.
  3. Ban, A.I., O. I. Ban, V. Bogdan, D. C. Sabau Popa ve D. Tuse (2020), “Performance Evaluation Model of Romanian Manufacturing Listed Companies by Fuzzy AHP and TOPSIS”, Technological and Economic Development of Economy, Vol. 26(4), 808-836.
  4. Baydaş, M. ve O. E. Elma (2021), “An objective criteria proposal for the comparison of MCDM and weighting methods in financial performance measurement: An application in Borsa Istanbul”, Decision Making: Applications in Management and Engineering, Vol. 4(2), 257-279.
  5. Baydaş, M. ve T. Eren (2021), “Finansal Performans Ölçümünde ÇKKV Yöntem Seçimi Problemine Objektif Bir Yaklaşım: Borsa İstanbul'da Bir Uygulama”, Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, Vol. 16(3), 664-687.
  6. Bayraktar, A. (2020), “COVID 19 pandemisinin finansal etkileri: BİST imalat sektörü uygulaması”, Turkish Studies, Vol. 15(8), 3415-3427. https://dx.doi.org/10.7827/TurkishStudies.46807
  7. Brauers, W. K. ve E. K. Zavadskas (2006), “The MOORA method and its application to privatization in a transition economy”, Control and cybernetics, 35, 445-469.
  8. Brigham, E. F. ve J. F. Houston (2019), Fundamentals of Financial Management, Cengage Learning.
  9. Carton, R. B. (2004), Measuring organizational performance: An exploratory study, Unpublished Doctoral Dissertation, Athens: The University of Georgia.
  10. Cinel, E. A. (2020), “COVID-19’un Küresel Makroekonomik Etkileri ve Beklentiler”, Politik Ekonomik Kuram, Vol. 4(1), 124-140.
  11. Danesh, D., M. J. Ryan ve A. Abbasi (2017), “A systematic comparison of multi criteria decision-making methods for the improvement of project portfolio management in complex organizations”, International Journal of Management and Decision Making, 16(3), 280–320.
  12. De Almeida-Filho, A. T., D. F. De Lima Silva ve L. Ferreira (2020), “Financial modelling with multiple criteria decision making: A systematic literature review”, Journal of the Operational Research Society, Vol. 72(10), 2161-2179.
  13. Demir, Z. (2020), “COVID-19’un BİST 100’deki Şirketlerin Mali Tabloları Üzerindeki Etkisinin Oran Yöntemi Ile Analizi”, Hitit Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, Vol. 13(2), 408-438.
  14. Devi, S., N. M. S. Warasniasih, P. R. Masdiantini ve L. S. Musmini (2020), “The Impact of COVID-19 Pandemic on the Financial Performance of Firms on the Indonesia Stock Exchange”, Journal of Economics, Business, and Accountancy Ventura, Vol. 23(2), 226-242.
  15. Dölen, T., S. S. Yanık ve Y. Ayanoğlu (2021), “Ara Dönem Finansal Raporlama Üzerindeki Etkileri: Havacılık Ve İlaç Sektörü Üzerine Bir Araştırma”, Muhasebe ve Finansman Dergisi, Special Issue, 149-168.
  16. Duran, M. S. ve M. Acar (2020), “Bir Virüsün Dünyaya Ettikleri: COVID-19 Pandemisinin Makroekonomik Etkileri”, International Journal of Social and Economic Sciences, Vol. 10(1), 54-67.
  17. Eldrandaly, K., A. H. Ahmed ve N. AbdelAziz (2009), “An expert system for choosing the suitable MCDM method for solving a spatial decision problem”, In 9th International conference on production engineering, design and control.
  18. Ertuğrul, İ. ve N. Karakaşoğlu (2009), “Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods”, Expert Systems with Applications, Vol. 36(1), 702-715.
  19. Feng, C. M. ve R. T. Wang (2000), “Performance evaluation for airlines including the consideration of financial ratios”, Journal of Air Transport Management, Vol. 6, 133–142.
  20. Göze Kaya, D. (2020), “Koronavirüs Pandemisinin Küresel Ekonomideki İzleri: Kamu Finansman Dengesi, Ticaret Hacmi, Enflasyon, İşsizlik ve Ekonomik Büyüme”, Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi (ASEAD), Vol. 7(5), 221-237.
  21. Karaoğlan S. ve S. Şahin (2018), “BİST XKMYA İşletmelerinin Finansal Performanslarının Çok Kriterli Karar Verme Yöntemleri İle Ölçümü ve Yöntemlerin Karşılaştırılması”, Ege Akademı̇k Bakış, Vol. 18(1), 63- 80.
  22. Kashid, U. S., U. D. Kashid ve S. N. Mehta (2019), “A Review of Mathematical Multi-Criteria Decision Models with A case study”, In International Conference on Efficacy of Software Tools for Mathematical Modeling (ICESTMM’19).
  23. Kung, J. Y., T. N. Chuang ve C. M. Ky (2011), “A fuzzy MCDM method to select the best company based on financial report analysis”, In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011) (pp. 2013-2017). IEEE.
  24. Olson, D. L., A. Mechitov ve H. Moshkovich (2001), “Learning aspects of decision aids”. In Multiple Criteria Decision Making in the New Millennium (pp. 41-48). Springer, Berlin, Heidelberg.
  25. Ozernoy, V. M. (1992), “Choosing the ‘Best’ multiple criterlv decision-making method”, INFOR: Information Systems and Operational Research, Vol. 30(2), 159-171.
  26. Öztürk, Ö., M. Y. Şişman, H. Uslu ve F. Çıtak (2020), “Effect of COVID-19 outbreak on Turkish Stock Market: a Sectoral-Level Analysis”, Hitit University Journal of Social Sciences Institute, Vol. 13(1), 56-68.
  27. Pamučar, D. ve G. Ćirović (2015), “The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC)”, Expert systems with applications, Vol. 42(6), 3016-3028.
  28. Rababah, A., L. Al-Haddad, M. S. Sial, Z. Chunmei ve J. Cherian (2020), “Analyzing the effects of COVID-19 pandemic on the financial performance of Chinese listed companies”, Journal of Public Affairs, Vol. 20(4), 1-6. https://doi.org/10.1002/pa.2440.
  29. Sałabun, W. ve K. Urbaniak (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.
  30. Soylu, Ö. B. (2020), “Türkiye Ekonomisinde Covıd-19’un Sektörel Etkileri”, Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi (ASEAD), Vol. 7(5), 169-185.
  31. Stewart, B. (2013), Best-Practice EVA: The definitive guide to measuring and maximizing shareholder value, New York: John Wiley & Sons, Inc.
  32. Tavana, M., M. Keramatpour, F. J. Santos-Arteaga ve E. Ghorbaniane (2015), “A fuzzy hybrid project portfolio selection method using data envelopment analysis, TOPSIS and integer programming”, Expert Systems with Applications, Vol. 42(22), 8432-8444.
  33. Tayar, T., E. Gümüştekin, K. Dayan ve E. Mandi (2020), “COVID-19 Krizinin Türkiye’de Sektörler Üzerinde Etkileri: Borsa İstanbul Sektör Endeksleri Araştırması”, Van Yüzüncü Yıl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, Salgın Hastalıkları Özel Sayısı, 293-320.
  34. Wang, Z. ve G. P. Rangaiah (2017), “Application and analysis of methods for selecting an optimal solution from the Pareto-optimal front obtained by multi-objective optimization”, Industrial & Engineering Chemistry Research, Vol. 56(2), 560-574.
  35. Wang, Z., S. S. Parhi, G. P. Rangaiah ve A. K. Jana (2020), “Analysis of Weighting and Selection Methods for Pareto-Optimal Solutions of Multi-objective Optimization in Chemical Engineering Applications”, Industrial & Engineering Chemistry Research, Vol. 59(33), 14850-14867.
  36. Wątróbski, J., J. Jankowski, P. Ziemba, A. Karczmarczyk ve M. Zioło (2019), “Generalized framework for multi-criteria method selection”, Omega, 86, 107–124.
  37. Yaakob, A. M. ve A. Gegov (2016), “Interactive TOPSIS based group decision making methodology using Z-numbers”, International Journal of Computational Intelligence Systems, Vol. 9(2), 311-324.
  38. Yükçü, S. ve G. Atağan (2010), “TOPSIS yöntemine göre performans değerleme”, Muhasebe ve Finansman Dergisi, 45, 28-35.

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