Evaluation of Financial Performance of Textile Companies Traded in BIST Using Dynamic Intuitionistic Fuzzy WASPAS Method

Abstract

This study aims to evaluate the financial performances of companies traded in BIST Textile, Clothing, and Leather sectors in Borsa Istanbul with dynamic intuitionistic fuzzy WASPAS method which is one of the multi-criteria decision-making techniques. The textile sectors has been chosen due to its interaction with many sectors in terms of raw materials, production, R&D, logistics, and its direct impact on the country's economy. The criteria used in the study were determined by considering the dynamics of the sector. In the study, instead of financial ratios calculated on exact numbers, linguistic expressions that allow evaluation according to sectors dynamics, scores of other alternatives, and conflicting/supporting criteria scores were used. According to the analysis, the company with the highest financial performance among the textile companies traded in BIST between 2015 and 2019 was determined as Yataş.

Keywords

• Textile Sector
• Financial Performance
• Financial Ratio Analyze
• Multi-Criteria Decision Making
• WASPAS

BIST’te İşlem Gören Tekstil Firmalarının Finansal Performanslarının Dinamik Sezgisel Bulanık WASPAS Yöntemi ile Değerlendirilmesi

Abstract

Bu çalışmanın amacı, Borsa İstanbul’da BIST Tekstil, Giyim ve Deri sektöründe işlem gören işletmelerin finansal performanslarının çok kriterli karar verme tekniklerinden biri olan dinamik sezgisel bulanık WASPAS yöntemi ile değerlendirilmesidir. Tekstil sektörü hammadde, üretim, ar-ge, lojistik anlamında birçok sektörle etkileşim içerisinde olması ve ülke ekonomisine olan doğrudan etkisi nedeniyle seçilmiştir. Çalışmada kullanılan kriterler sektörün dinamikleri dikkate alınarak belirlenmiştir. Çalışmada kesin sayılar üzerinde hesaplanmış finansal oranlar yerine, sektör dinamiklerine, diğer alternatiflerin skorlarına ve çelişen/destekleyen kriter skorlarına göre değerlendirmeye olanak sağlayan dilsel ifadeler kullanılmıştır. Analiz sonuçlarına göre 2015-2019 dönemi için BIST’te işlem gören tekstil firmaları arasında finansal performansı en yüksek işletme Yataş işletmesi olarak belirlenmiştir.

Keywords

• Tekstil Sektörü
• Finansal Performans
• Finansal Oran Analizi
• Çok Kriterli Karar Verme
• WASPAS Yöntemi

References

1. Atanassov, K. (1986) Intuitionistic Fuzzy Sets, Fuzzy Sets and Systems, 20(1986) 87–96.
2. Altaş D., Giray S., (2005), Mali Başarısızlığın Çok Değişkenli İstatistiksel Yöntemlerle Belirlenmesi: Tekstil Sektörü Örneği, Sosyal Bilimler Dergisi, 2005 (2), 13-27.
3. Ayçin, E. (2019). Çok Kriterli Karar Verme: Bilgisayar Uygulamalı Çözümler, Nobel Akademik Yayıncılık.
4. Bridgman, P.W. (1922). Dimensional Analysis, Yale University Press, New Haven.
5. Miller, D.W. & Starr, M.K. (1969). Executive Decisions and Operations Research, PrenticeHall, Inc., Englewood Cliffs, NJ.
6. Boran, F. E., Genç, S., Kurt, M., & Akay, D. (2009). A Multi-Criteria Intuitionistic Fuzzy Group Decision Making For Supplier Selection with TOPSIS Method. Expert Systems with Applications, 36(8), 11363-11368.
7. Boltürk, E., & Kahraman, C. (2020). AS/RS Technology Selection Using İnterval-Valued Pythagorean Fuzzy WASPAS. Advances in Intelligent Systems and Computing. https://doi.org/10.1007/978-3-030-23756-1_104
8. Chakraborty, S., & Zavadskas, E. K. (2014). Applications of WASPAS Method in Manufacturing Decision Making. Informatica (Netherlands). https://doi.org/10.15388/Informatica.2014.01

9. Çetin A. C., (2006), Türk Tekstil Sektörü ve Türk Tekstil Firmalarının Etkinlik Düzeylerinin Belirlenmesi, Afyon Kocatepe Üniversitesi İ.İ.B.F. Dergisi, 8 (2), 255-278.
10. Faizi, S., Sałabun, W., Rashid, T., Zafar, S., & Wątróbski, J. (2020). Intuitionistic fuzzy sets in multi-criteria group decision making problems using the characteristic objects method. Symmetry, 12(9), 1382.
11. Gireesha, O., Somu, N., Krithivasan, K., & Shankar, S. S. (2020). IIVIFS-WASPAS: An Integrated Multi-Criteria Decision-Making Perspective for Cloud Service Provider Selection. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2019.09.053
12. Ilbahar, E., & Kahraman, C. (2018). Retail Store Performance Measurement Using A Novel Interval-Valued Pythagorean Fuzzy WASPAS Method. Journal of Intelligent and Fuzzy Systems. https://doi.org/10.3233/JIFS-18730
13. Ilbahar, E., Cebi, S., & Kahraman, C. (2020). Assessment of Renewable Energy Alternatives with Pythagorean Fuzzy WASPAS Method: A Case Study of Turkey. Advances In Intelligent Systems and Computing. https://doi.org/10.1007/978-3-030-23756-1_106
14. Kahraman, C., Cevik Onar, S., Oztaysi, B., & Ilbahar, E. (2019). Selection Among GSM Operators Using Pythagorean Fuzzy Waspas Method. Journal of Multiple-Valued Logic and Soft Computing.
15. Kahraman, C., Onar, S. C., Oztaysi, B., & Ilbahar, E. (2018). Type-2 Intuitionistic Fuzzy (IFS2) WASPAS. https://doi.org/10.1142/9789813273238_0037
16. Keshavarz Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Esmaeili, A. (2016). Multi-Criteria Evaluation Of Green Suppliers Using An Extended WASPAS Method with Interval Type-2 Fuzzy Sets. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2016.07.031
17. Konak T., Elbir G., Yılmaz S., Karataş B. M., Durman Y., Düzakın H., (2018), Borsa İstanbul’da İşlem Gören Tekstil Firmalarının TOPSIS ve MOORA Yöntemi ile Analizi, Çukurova Üniversitsi İİBF Dergisi, 22 (1), Haziran, 11-44.
18. Kutlu Gundogdu, F., & Kahraman, C. (2019). Extension of WASPAS with Spherical Fuzzy Sets. Informatica, 30(2), 269-292.
19. Mishra, A. R., Singh, R. K., & Motwani, D. (2019). Multi-Criteria Assessment of Cellular Mobile Telephone Service Providers Using Intuitionistic Fuzzy WASPAS Method with Similarity Measures. Granular Computing. https://doi.org/10.1007/s41066-018-0114-5
20. Nie, R. X., Wang, J. Q., & Zhang, H. Y. (2017). Solving Solar-Wind Power Station Location Problem Using An Extended Weighted Aggregated Sum Product Assessment (WASPAS) Technique With İnterval Neutrosophic Sets. Symmetry, 9(7), 106.
21. Park, J. H., Cho, H. J., & Kwun, Y. C. (2013). Extension of the VIKOR Method to Dynamic Intuitionistic Fuzzy Multiple Attribute Decision Making. Computers & Mathematics with Applications, 65(4), 731-744.
22. Peng, X., & Dai, J. (2017). Hesitant Fuzzy Soft Decision Making Methods Based on WASPAS, MABAC and COPRAS with Combined Weights. Journal of Intelligent & Fuzzy Systems, 33(2), 1313-1325.
23. Selimoğlu S., Orhan A. (2015), Finansal Başarısızlığın Oran Analizi ve Diskriminant Analizi Kullanılarak Ölçümlenmesi: BIST’de İşlem Gören Dokuma, Giyim Eşyası ve Deri İşletmeleri Üzerine Bir Araştırma, Muhasebe ve Finansman Dergisi, Nisan, 21-40.
24. Stanujkić, D., & Karabašević, D. (2019). An Extension of The WASPAS Method For Decision-Making Problems with Intuitionistic Fuzzy Numbers: A Case of Website Evaluation. Operational Research in Engineering Sciences: Theory and Applications. https://doi.org/10.31181/oresta19012010129s
25. Stojić, G., Stević, Ž., Antuchevičiene, J., Pamučar, D., & Vasiljević, M. (2018). A Novel Rough WASPAS Approach for Supplier Selection in A Company Manufacturing PVC Carpentry Products. Information (Switzerland). https://doi.org/10.3390/info9050121.
26. Szmidt, E., & Kacprzyk, J. (2008, June). Using intuitionistic fuzzy sets in text categorization. In International Conference on Artificial Intelligence and Soft Computing (pp. 351-362). Springer, Berlin, Heidelberg.
27. T.C. Sanayi ve Teknoloji Bakanlığı, 2019, Tekstil, Hazır Giyim ve Deri Sektörleri Raporu 2019, https://www.sanayi.gov.tr/plan-program-raporlar-ve-yayinlar/sektor-raporlari/mu0303011409.
28. Temizel, D , Bayçelebi, B., (2016), Finansal Oranların TOPSIS Sıralaması ile Yıllık Getiriler Arasındaki İlişki: Tekstil İmalatı Sektörü Üzerine Bir Uygulama. Anadolu Üniversitesi Sosyal Bilimler Dergisi , 16 (2) , 159-170 . doi: 10.18037/ausbd.389248
29. Triantaphyllou, E. & Mann, S.H. (1989). An Examination of the Effectiveness of Multi-Dimensional Decision-Making Methods: A Decision-Making Paradox. International Journal of Decision Support Systems. 5 (3): 303–312. doi:10.1016/0167-9236(89)90037-7.
30. Turskis, Z., Zavadskas, E. K., Antucheviciene, J., & Kosareva, N. (2015). A Hybrid Model Based on Fuzzy AHP and Fuzzy WASPAS for Construction Site Selection. International Journal of Computers, Communications and Control. https://doi.org/10.15837/ijccc.2015.6.2078
31. Xu, Z. (2007a). Some Similarity Measures Of Intuitionistic Fuzzy Sets And Their Applications To Multiple Attribute Decision Making. Fuzzy Optimization and Decision Making, 6(2), 109-121.
32. Xu, Z. (2007b). Intuitionistic fuzzy aggregation operators. IEEE Transactions on fuzzy systems, 15(6), 1179-1187.
33. Yazdani, M. (2015). New intuitionistic fuzzy approach with multi-objective optimisation on the basis of ratio analysis method. International Journal of Business and Systems Research, 9(4), 355-374.
34. Yıldırım, B. F. (2019). "Kredi Kartı Platformlarının Sezgisel Bulanık TOPSIS Yöntemi Kullanılarak Değerlendirilmesi". BDDK Bankacılık ve Finansal Piyasalar, 13 (1), 37-58.
35. Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of Weighted Aggregated Sum Product Assessment. Elektronika ir elektrotechnika, 122(6), 3-6.
36. Zadeh, L. A. (1965) Fuzzy Sets. Information and Control 8, pp. 338–353.
37. Zavadskas, E. K., Baušys, R., Stanujkic, D., & Magdalinovic-Kalinovic, M. (2016). Selection Of Lead-Zinc Flotation Circuit Design By Applying WASPAS Method with Single-Valued Neutrosophic Set. Acta Montanistica Slovaca. https://doi.org/10.5281/zenodo.3130624
38. Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2015). Selecting A Contractor By Using A Novel Method For Multiple Attribute Analysis: Weighted Aggregated Sum Product Assessment with Grey Values (WASPAS-G). Studies in Informatics and Control, 24(2), 141-150.
39. Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of Weighted Aggregated Sum Product Assessment. Elektronika Ir Elektrotechnika. https://doi.org/10.5755/j01.eee.122.6.1810
40. Zhang, W., Zhao, S., Dong, D., Zhu, Y., & Wang, D. (2020). A Multi-criterion Group Decision Making Method: CRITIC-WASPAS Based on Trapezoidal Intuitionistic Fuzzy Numbers. Advances in Intelligent Systems and Computing. https://doi.org/10.1007/978-3-030-32456-8_89