Sector Financial Performance Analysis with Integrated SOWIA-ELECTRE III Methods: The Case of Turkish Real Sector
https://doi.org/10.26794/2587-5671-2026-30-3-1664-01
Abstract
The aim of this study is to determine the financial performance of the corporate sector employing the integrated SOWIA-ELECTRE III method. In this framework, the data of 10 real sectors operating in Borsa Istanbul over the period 2016–2022 are utilized. It was observed that the financial performance indicators affecting the sector performance varied over the years and that current liability rate, price to earning ratio, firm value/EBITA and return on equity ratios were important determinants of financial performance. According to the results of the performance rankings of the sectors obtained by the ELECTRE III method, it is understood that the highest performance was realized by retail trade in 2017, 2018, 2019, 2021 and 2022, construction and public works in 2016 and food, beverage and tobacco in 2020. In addition, the study compared sector performance rankings with sector index return rankings and the degree of the relationship was determined by the Spearman’s rank correlation coefficient. Accordingly, the correlation coefficients are positive, high and significant in 2017 and 2018. Accordingly, it can be said that there is a partial relationship between sector performances and sector returns. The study results show that portfolio managers and investors should give importance to financial performance analysis when making sector analysis, and economic managers that general economic conditions are important determinants in the development of sectors.
About the Authors
Z. Şenol
Sivas Cumhuriyet University
Turkey
Competing Interests:
Turkey
Zekai Şenol — PhD, Assoc. Prof., Finance and Banking Departmant, Faculty of Economics and Administrative Sciences
Sivas
Competing Interests:
The authors have no conflicts of interest to declare.
S. Şener
Sivas Cumhuriyet University
Turkey
Competing Interests:
Turkey
Sibel Şener — PhD, Assoc. Prof., Departmant of Management and Information Systems, Faculty of Economics and Administrative Sciences
Sivas
Competing Interests:
The authors have no conflicts of interest to declare.
T. Gülcemal
Sivas Cumhuriyet University
Turkey
Competing Interests:
Turkey
Tuba Gülcemal — PhD, Assoc. Prof., Departmant of Finance and Banking, Faculty of Economics and Administrative Sciences
Sivas
Competing Interests:
The authors have no conflicts of interest to declare.
References
1. Lebas M. J. Performance measurement and performance management. International Journal of Production Economics. 1995;41(1–3):23–35. DOI: 10.1016/0925–5273(95)00081-X
2. Shaverdi M., Ramezani I., Tahmasebi R., Rostamy A. A.A. Combining fuzzy AHP and fuzzy TOPSIS with financial ratios to design a novel performance evaluation model. International Journal of Fuzzy Systems. 2016;18(2):248–262. DOI: 10.1007/s40815–016–0142–8
3. Kennerley M., Neely A. Performance measurement frameworks: A review. In: Neely A., ed. Business performance measurement: Theory and practice. Cambridge: Cambridge University Press; 2004:145–155.
4. Clark B. Measuring performance: The marketing perspective. In: Neely A., ed. Business performance measurement: Theory and practice. Cambridge: Cambridge University Press; 2004:22–40.
5. Vujičić M. D., Papić M. Z., Blagojević M. D. Comparative analysis of objective techniques for criteria weighing in two MCDM methods on example of an air conditioner selection. Tehnika. 2017;72(3):422–429. DOI: 10.5937/tehnika1703422V
6. Liao H., Wu X., Mi X., Herrera F. An integrated method for cognitive complex multiple experts multiple criteria decision making based on ELECTRE III with weighted Borda rule. Omega. 2020;93:102052. DOI: 10.1016/j.omega.2019.03.010
7. Krishnan A. R., Kasim M. M., Hamid R., Ghazali M. F. A modified CRITIC method to estimate the objective weights of decision criteria. Symmetry. 2021;13(6):973. DOI: 10.3390/sym13060973
8. Tu Y., Shi H., Chen K., Liang Y., Zhou X., Lev B. Three-reference-point based group ELECTRE III method for urban flood resilience evaluation. Expert Systems with Applications. 2022;210:118488. DOI: 10.1016/j.eswa.2022.118488
9. Diakoulaki D., Mavrotas G., Papayannakis L. Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research. 1995;22(7):763–770. DOI: 10.1016/0305–0548(94)00059-H
10. Das M. C., Sarkar B., Ray S. On the performance of Indian technical institutions: A combined SOWIA-MOORA approach. Opsearch. 2013;50(3):319–333. DOI:10.1007/s12597–012–0116-z
11. Roy B., Bouyssou D. Comparison of two decision-aid models applied to a nuclear power plant siting example. European Journal of Operational Research. 1986;25(2):200–215. DOI: 10.1016/0377–2217(86)90086-X
12. Chavira D. A.G., Lopez J. C.L., Noriega J. J.S., Valenzuela O. A., Carrillo P. A.A. A credit ranking model for a parafinancial company based on the ELECTRE-III method and a multiobjective evolutionary algorithm. Applied Soft Computing. 2017;60:190–201. DOI: 10.1016/j.asoc.2017.06.021
13. Kou G., Lu Y., Peng Y., Shi Y. Evaluation of classification algorithms using MCDM and rank correlation. International Journal of Information Technology & Decision Making. 2012;11(1):197–225. DOI: 10.1142/S0219622012500095
14. Orakçı E., Özdemir A. Telafi edici çok kriterli karar verme yöntemleri ile Türkiye ve AB ülkelerinin insani gelişmişlik düzeylerinin belirlenmesi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2017;19(1):61–74. DOI: 10.5578/jeas.49652
15. Madhu P., Dhanalakshmi C. S., Mathew M. Multi-criteria decision-making in the selection of a suitable biomass material for maximum bio-oil yield during pyrolysis. Fuel. 2020;277:118109. DOI: 10.1016/j.fuel.2020.118109
16. Güler E., Avcı S., Aladağ Z. Türkiye’de illerin deprem hasar görebilirlik sıralamasında çok kriterli karar verme tekniklerinin başarısının copeland yöntemi ile değerlendirilmesi. Endüstri Mühendisliği. 2021;32(3):414–437.
17. Top M., Bulut T. Yeni birçok kriterli karar verme yöntemi: Bulut Endeks-Beta (Be-B). Verimlilik Dergisi. 2022;3:393–414. DOI: 10.51551/verimlilik.1031366
18. Akbulut O. Y. Finansal performans ile pay senedi getirisi arasındaki ilişkinin bütünleşik CRITIC ve MABAC ÇKKV teknikleriyle ölçülmesi: Borsa İstanbul çimento sektörü firmaları üzerine ampirik bir uygulama. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2020;(40):471–488. DOI: 10.30794/pausbed.683330
19. Orçun Ç. Enerji sektöründe WASPAS yöntemiyle performans analizi. Bolu Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2019;19(2):439–453. DOI: 10.11616/basbed.v19i47045.537839
20. Yalçın N., Bayrakdaroğlu A., Kahraman C. Application of fuzzy multi-criteria decision making methods for financial performance evaluation of Turkish manufacturing industries. Expert Systems with Applications. 2012;39(1):350–364. DOI: 10.1016/j.eswa.2011.07.024
21. Yavuz H., Öztel A., Yaşar Ö. Z. Bulanık VIKOR yöntemi ile finansal performans analizi: Türk kimya sektöründe bir uygulama. Yönetim ve Ekonomi Dergisi. 2020;27(3):535–555. DOI: 10.18657/yonveek.602919
22. Uygurtürk H., Korkmaz T. Finansal performansın TOPSIS çok kriterli karar verme yöntemi ile belirlenmesi: Ana metal sanayi işletmeleri üzerine bir uygulama. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2012;7(2):59–115.
23. Soy Temur A. Borsa Istanbul Turizm endeksi (XTRZM) firmalarının Entropi temelli ARAS, COPRAS ve TOPSIS yöntemleri ile finansal performans analizi. Verimlilik Dergisi. 2022;2:183–212. DOI: 10.51551/verimlilik.907897
24. Lima A., Soares V. Financial ratios applied to portfolio selection: Electre III methodology in buy-and-hold strategy. Revista Organizações em Contexto. 2013;9(17):281–319. DOI: 10.15603/1982–8756/roc.v9n17p281–319
25. Boonjing V., Boongasame L. Combinatorial portfolio selection with the ELECTRE III method: Case study of the stock exchange of Thailand. Afro-Asian Journal of Finance and Accounting. 2017;7(4):351–362. DOI: 10.15439/2016F228
26. Safaei Ghadikolaei A., Khalili Esbouei S., Antucheviciene J. Applying fuzzy MCDM for financial performance evaluation of Iranian companies. Technological and Economic Development of Economy. 2014;20(2):274–291. DOI: 10.3846/20294913.2014.913274
27. İç Y. T., Çelik B., Kavak S., Baki B. An integrated AHP-modified VIKOR model for financial performance modeling in retail and wholesale trade companies. Decision Analytics Journal. 2022;3:100077. DOI: 10.1016/j.dajour.2022.100077
28. Aduba J. J. Framework for firm-level performance evaluations using multivariate linear correlation with MCDM methods: Application to Japanese firms. Asia-Pacific Journal of Regional Science. 2022;6(1):1–44. DOI: 10.1007/s41685–021–00213–8
29. Karaoğlan S., Şahin S. BIST XKMYA İşletmelerinin finansal perfomanslarının çok kriterli karar verme yöntemleri ile ölçümü ve yöntemlerin karşılaştırılması. Ege Akademik Bakış. 2018;18(1):63–80. DOI: 10.21121/eab.2018135912
30. Kayahan Karakul A., Özaydın G. TOPSIS ve VIKOR yöntemleri ile finansal performans değerlendirmesi: XELKT üzerinde bir uygulama. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2019;(60):68–86.
31. Ekizler H. Dokuma, giyim eşyası ve deri sanayi sektöründeki işletmelerin performanslarının değerlendirilmesi: VIKOR ve TOPSIS yöntemleri. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2020;13(1):24–39. DOI: 10.25287/ohuiibf.556233
32. Söylemez Y. Finansal performans değerlendirmesinde TOPSIS ve gri ilişkisel analiz yöntemlerinin karşılaştırılması. Yönetim ve Ekonomi Araştırmaları Dergisi. 2020;18(3):61–79. DOI: 10.11611/yead.771575
33. Bozdoğan T., Odabaş A., Shegiwal A. H. Analysis of financial performance of foreign banks having branches in Turkey by TOPSIS and ELECTRE methods. Alanya Akademik Bakış Dergisi. 2021;5(2):1049–1067. DOI: 10.29023/alanyaakademik.871031
34. Akgün A. BIST enerji şirketlerinin CRITIC ve CODAS bütünleşik yaklaşımı ile finansal açıdan değerlendirilmesi. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2022;(48):338–356. DOI: 10.52642/susbed.1111547
35. Öndeş T., Özkan T. Bütünleşik CRITIC-EDAS yaklaşımıyla Covid-19 pandemisinin bilişim sektörü üzerindeki finansal performans etkisi. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi. 2021;12(2):506–522.
36. Türegün N. Financial performance evaluation by multi-criteria decision-making techniques. Heliyon. 2022;8(5): e09361. DOI: 10.1016/j.heliyon.2022.e09361
37. Chen Z., Wang X., Peng J., Zhang H., Wang J. An integrated probabilistic linguistic projection method for MCGDM based on ELECTRE III and the weighted convex median voting rule. Expert Systems. 2020;37(6):e12593. DOI: 10.1111/exsy.12593
38. Ömürbek N., Eren H. Promethee, Moora ve Copras yöntemleri ile oran analizi sonuçlarinin değerlendirilmesi: Bir uygulama. Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2016;8(16):174–187. DOI: 10.20875/sb.69615
39. Narayanamoorthy S., Brainy J. V., Shalwala R. A., Alsenani T. R., Ahmadian A., Kang D. An enhanced fuzzy decision making approach for the assessment of sustainable energy storage systems. Sustainable Energy, Grids and Networks. 2023;33:100962. DOI: 10.1016/j.segan.2022.100962
40. Zhong S., Chen Y., Miao Y. Using improved CRITIC method to evaluate thermal coal suppliers. Scientific Reports. 2023;13(1):195. DOI: 10.1038/s41598–023–27495–6
41. Roy B. The outranking approach and the foundations of Electre methods. Theory and Decision. 1991;31(1):49–73. DOI: 10.1007/BF00134132
42. Fancello G., Carta M., Fadda P. A decision support system based on Electre III for safety analysis in a suburban road network. Transportation Research Procedia. 2014;3:175–184. DOI: 10.1016/j.trpro.2014.10.103
43. Şener S. Legatum refah endeksi göstergeleri ve verileri kullanılarak refahın çok kriterli karar verme yöntemleri ile değerlendirilmesi. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2022;17(1):46–70. DOİ: 10.17153/oguiibf.981581
44. Micale R., Giallanza A., Russo G., La Scalia G. Selection of a sustainable functional pasta enriched with Opuntia using ELECTRE III methodology. Sustainability. 2017;9(6):885. DOI: 10.3390/su9060885
45. Leyva-López J.C., Solano-Noriega J.J., Gastélum-Chavira D.A., Gaxiola-Valenzuela T. A personnel selection model for a software development company based on the ELECTRE III method and a Variant of NSGA-II. Innovar: Revista de Ciencias Administrativas y Sociales. 2022;32(85):117–132. DOI: 10.15446/innovar.v32n85.100657
46. Vasegaard A. E., Picard M., Hennart F., Nielsen P., Saha S. Multi criteria decision making for the multi-satellite ımage acquisition scheduling problem. Sensors. 2020;20(5):1242. DOI: 10.3390/s20051242
Review
For citations:
Şenol Z., Şener S., Gülcemal T. Sector Financial Performance Analysis with Integrated SOWIA-ELECTRE III Methods: The Case of Turkish Real Sector. Finance: Theory and Practice. https://doi.org/10.26794/2587-5671-2026-30-3-1664-01
Views:
287
Email this article 