Financial Performance of BIST Sustainability Index Enterprises: Unearthing the Most Optimum MCDA Methods for Decision-Makers

Yıl 2024, , 461 - 478, 31.10.2024

Orhan Emre Elma

https://doi.org/10.51551/verimlilik.1410272

Öz

Purpose: The aim of this study is to examine the financial performance of companies traded in BIST Sustainability index using 7 MCDA applications. Although there have been previous studies on aforementioned index, this study will be the first comparative and most comprehensive study conducted across 7 methods.
Methodology: Analyzes were performed using VIKOR, FUCA, MOORA, GRA, COPRAS, SAW and CODAS methods and the CRITIC technique for the financial performance of 34 companies that achieved to remain in the relevant index continuously for 11 periods, within the timeframe spanning from Q1 2019 to Q3 2021.
Findings: According to the comparative MCDA analysis, the highest capacity was found in the VIKOR method with 65.8% (p<0.01). The FUCA method followed the relevant method with 61.14% (p<0.01) and the MOORA method with 55.08% (p<0.02) capacities. COPRAS, SAW and CODAS were established as the methods with the lowest capacity.
Originality: This study is the first sustainability index study that measures the MCDA applications capacity with regard to association between the outputs they produce for corporations and the stock returns of the relevant firms and conclusively makes a comparison among analyzed methods. In this sense, it makes significant contributions to the literature.

Anahtar Kelimeler

Capital Markets, Share Return, Sustainability, MCDA

BIST Sürdürülebilirlik Endeksi İşletmelerinin Finansal Performansı: Karar Vericiler için en Optimum ÇKKA Yöntemlerinin Ortaya Çıkarılması

Öz

Amaç: Bu çalışmanın amacı, BIST Sürdürülebilirlik endeksinde işlem gören şirketlerin finansal performansını ÇKKA uygulamaları ile incelemektir. Daha önce bu endeksle ilgili çalışmalar olmakla birlikte, bu çalışma 7 metot üzerinden gerçekleştirilen ilk karşılaştırmalı ve en kapsamlı çalışma olacaktır.
Yöntem: Ç1 2019 ile Ç3 2021 arasındaki 11 dönem boyunca sürekli ilgili endekste kalmayı başarabilmiş 34 şirketin finansal performansı için VIKOR, FUCA, MOORA, GRA, COPRAS, SAW ve CODAS yöntemleri ile CRITIC tekniği kullanılarak analizler gerçekleştirilmiştir.
Bulgular: Yapılan karşılaştırmalı ÇKKA analizine göre en yüksek kapasite %65.80 ile VIKOR yönteminde bulunmuştur (p<0,01). FUCA yöntemi %61,14 (p<0,01) ve MOORA yöntemi ise %55,08 (p<0,02) kapasiteleri ile ilgili yöntemi takip etmişlerdir. COPRAS, SAW ve CODAS ise en düşük kapasiteye sahip metotlar olarak tespit edilmişlerdir.
Özgünlük: Bu çalışma, ÇKKA yöntemlerinin kapasitesini, şirketler için ürettikleri skorlar ile ilgili şirketlerin hisse getirileri arasındaki ilişkiye göre ölçen ve bu şekilde yöntemler arası karşılaştırma yapan ilk sürdürülebilirlik endeksi çalışmasıdır. Bu anlamda literatüre önemli katkılar sağlamaktadır.

Anahtar Kelimeler

Sermaye Piyasaları, Hisse Getirisi, Sürdürülebilirlik, ÇKKA

Kaynakça

• Aduba, J.J. (2022). “Framework for Firm-Level Performance Evaluations Using Multivariate Linear Correlation with MCDM Methods: Application to Japanese Firms”, Asia-Pacific Journal of Regional Science, 6(1), 1-44.
• Akdemir, D.M. and Şimşek, O. (2023). “A Financial Performance Evaluation via Hybrid MCDM Methods: A Case of Amazon.com Inc”, Istanbul Business Research, 52(1), 199-232.
• Arsu, Ş.U. and Arsu, T. (2023). “Evaluation of the Corporate Sustainability Performance of Manufacturing Companies in the BIST Sustainability Index with Multi-Criteria Decision-Making Methods”, Business & Economics Research Journal, 14(4), 479-501.
• Batrancea, L.M., Nichita, A. and Cocis, A.D. (2022). “Financial Performance and Sustainable Corporate Reputation: Empirical Evidence from the Airline Business”, Sustainability, 14(20), 13567.
• Baydaş, M., Elma, O.E., & Pamučar, D. (2022). “Exploring the Specific Capacity of Different Multi Criteria Decision Making Approaches under Uncertainty using Data from Financial Markets”, Expert Systems with Applications, 197, 116755.
• Brauers, W.K.M., Ginevičius, R. and Podvezko, V. (2010). “Regional Development in Lithuania Considering Multiple Objectives by the MOORA Method”, Technological and Economic Development of Economy, 16(4), 613-640.
• Büyüközkan, G., Karabulut, Y. and Mukul, E. (2018). “A Novel Renewable Energy Selection Model for United Nations' Sustainable Development Goals”, Energy, 165, 290-302.
• Ceyhan, İ.F. and Kara, M. (2023). “Analyzing the Financial Performance of Automotive Companies Before and After Industry 4.0: An Application in the BIST Sustainability Index”, Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 10(1), 183-205.
• Dağıstanlı, H.A. (2023). “An Integrated Fuzzy MCDM and Trend Analysis Approach for Financial Performance Evaluation of Energy Companies in Borsa Istanbul Sustainability Index”, Journal of Soft Computing and Decision Analytics, 1(1), 39-49.
• Deng, J. (1989). “Introduction to Grey Theory System”, The Journal of Grey System, 1(1), 1-24.
• Diakoulaki, D., Mavrotas, G. and Papayannakis, L. (1995). “Determining Objective Weights in Multiple Criteria Problems: The CRITIC Method”, Computers & Operations Research, 22(7), 763-770.
• Dong, J.Y., Chen, Y. and Wan, S.P. (2018). “A Cosine Similarity based QUALIFLEX Approach with Hesitant Fuzzy Linguistic Term Sets for Financial Performance Evaluation”, Applied Soft Computing, 69, 316-329. DOI: 10.1016/j.asoc.2018.04.053
• Elma, O.E. (2023a). “A Comparative MCDA Application on The Long-Term Performance of IPOs During the Pandemic on Borsa Istanbul”, Journal of Economics Business and Political Researches, 8(20), 269-293.
• Elma, O.E. (2023b). “Comparative Financial Performance Analysis of SMEs Traded on BIST with MCDA Techniques During the Pandemic Period”, IV. International Applied Statistics Congress (UYIK 2023), September 26-29 2023, Sarajevo, Bosnia and Herzegovina, 230-242.
• Erdoğan, N.K., Altınırmak, S., Şahin, C. and Karamaşa, Ç. (2020). “Analyzing the Financial Performance of Football Clubs listed in BIST using Entropy Based COPRAS Methodology”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 63, 39-53.
• Fernando, M.M.L., Escobedo, J.L.P., Azzaro-Pantel, C., Pibouleau, L., Domenech, S. and Aguilar-Lasserre, A. (2011). “Selecting the Best Portfolio Alternative from a Hybrid Multiobjective GA-MCDM Approach for New Product Development in the Pharmaceutical Industry”, 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making, April 11-15 2011, 159-166, Paris, France.
• Ghadikolaei, A.S., Khalili Esbouei, S. and Antucheviciene, J. (2014). “Applying Fuzzy MCDM for Financial Performance Evaluation of Iranian Companies”, Technological and Economic Development of Economy, 20(2), 274-291.
• Hsieh, L.F., Wang, L.H., Huang, Y.C. and Chen, A. (2010). “An Efficiency and Effectiveness Model for International Tourist Hotels in Taiwan”, The Service Industries Journal, 30(13), 2183-2199.
• Hsu, L.C. (2014). “A Hybrid Multiple Criteria Decision-Making Model for Investment Decision Making”, Journal of Business Economics and Management, 15(3), 509-529.
• Iç, Y.T., Yurdakul, M. and Pehlivan, E. (2022). “Development of a Hybrid Financial Performance Measurement Model using AHP and DOE Methods for Turkish Commercial Banks”, Soft Computing, 26, 2959-2979.
• Kalogeras, N., Pennings, J.M., Benos, T. and Doumpos, M. (2013). “Which Cooperative Ownership Model Performs Better? A Financial‐Decision Aid Approach”, Agribusiness, 29(1), 80-95.
• Karaşan, A., Boltürk, E. and Kahraman, C. (2019). “A Novel Neutrosophic CODAS Method: Selection among Wind Energy Plant Locations”, Journal of Intelligent & Fuzzy Systems, 36(2), 1491-1504.
• Karimi, A. and Barati, M. (2018). “Financial Performance Evaluation of Companies Listed on Tehran Stock Exchange”, International Journal of Law and Management, 60(3), 885-900. DOI: 10.1108/IJLMA-12-2016-0145
• Keshavarz G.M., Zavadskas, E.K., Turskis, Z. and Antucheviciene, J. (2016). “A New Combinative Distance-Based Assessment (CODAS) Method for Multi-Criteria Decision-Making”, Economic Computation & Economic Cybernetics Studies & Research, 50(3), 25-44.
• Khan, K.I., Kabir, M.A., Mata, M.N., Correia, A.B., Rita, J.X. and Martins, J.N. (2021). “Portfolio Optimization”, Academy of Accounting and Financial Studies Journal, 25(Special Issue 2), 1-28.
• Khatib, S.F. and Nour, A. (2021). “The Impact of Corporate Governance on Firm Performance During the COVID-19 Pandemic: Evidence from Malaysia”, Journal of Asian Finance, Economics and Business, 8(2), 0943-0952.
• Kim, Y. and Chung, E.S. (2015). “Robust Prioritization of Climate Change Adaptation Strategies Using the VIKOR Method with Objective Weights”, JAWRA Journal of the American Water Resources Association, 51(5), 1167-1182.
• Kumar, P. and Sharma, D. (2023). “Benchmarking the Financial Performance of Indian Commercial Banks by a Hybrid MCDM Approach”, International Journal of Process Management and Benchmarking, 15(3), 285-309.
• Makki, A.A. and Alqahtani, A.Y. (2023). “Capturing the Effect of the COVID-19 Pandemic Outbreak on the Financial Performance Disparities in the Energy Sector: A Hybrid MCDM-Based Evaluation Approach”, Economies, 11(2), 61.
• Manrique, S. and Martí-Ballester, C.P. (2017). “Analyzing the Effect of Corporate Environmental Performance on Corporate Financial Performance in Developed and Developing Countries”, Sustainability, 9(11), 1957.
• Maqbool, S. and Zamir, N. (2021). “Corporate Social Responsibility and Institutional Investors: The Intervening Effect of Financial Performance”, Journal of Economic and Administrative Sciences, 37(2), 238-252.
• Moghimi, R. and Anvari, A. (2014). “An Integrated Fuzzy MCDM Approach and Analysis to Evaluate the Financial Performance of Iranian Cement Companies”, The International Journal of Advanced Manufacturing Technology, 71(1-4), 685-698.
• Ocon, J.D., Cruz, S.M.M., Castro, M.T., Aviso, K.B., Tan, R.G.R. and Promentilla, M.A.B. (2018). “Optimal Multi-Criteria Selection of Hybrid Energy Systems for Off-Grid Electrification”, Chemical Engineering Transactions, 70, 367.
• Opricovic, S. and 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.
• Ozcalici, M. and Bumin, M. (2020). “An Integrated Multi-Criteria Decision-Making Model with Self-Organizing Maps for the Assessment of the Performance of Publicly Traded Banks in Borsa Istanbul”, Applied Soft Computing, 90, 106166.
• Özdağoğlu, A., Gümüş, Y., Özdağoğlu, G. and Gümüş, G.K. (2017). “Evaluating Financial Performance with Grey Relational Analysis: An Application of Manufacturing Companies Listed on Borsa Istanbul”, Muhasebe ve Finansman Dergisi, 73, 289-312.
• Paul, K. and Lydenberg, S.D. (1996). “Do Ethical Screens Make a Difference?: A Comparison of the Domini Social Index 400 and Standard and Poor's 500”, Proceedings of the International Association for Business and Society, July 7 1996, 201-212.
• Pérez-Dominguez, L., Durán, S.N.A., López, R.R., Pérez-Olguin, I.J.C., Luviano-Cruz, D. and Gómez, J.A.H. (2021). “Assessment Urban Transport Service and Pythagorean Fuzzy Sets CODAS Method: A Case of Study of Ciudad Juárez”, Sustainability, 13(3), 1281.
• Phan, T.T.H., Tran, H.X., Le, T.T., Nguyen, N., Pervan, S. and Tran, M.D. (2020). “The Relationship between Sustainable Development Practices and Financial Performance: A Case Study of Textile Firms in Vietnam”, Sustainability, 12(15), 5930.
• Sarraf, F. and Nejad, S.H. (2020). “Improving Performance Evaluation Based on Balanced Scorecard with Grey Relational Analysis and Data Envelopment Analysis Approaches: Case Study in Water and Wastewater Companies”, Evaluation and Program Planning, 79, 101762.
• Stević, Ž., Durmić, E., Gajić, M., Pamučar, D. and Puška, A. (2019). “A Novel Multi-Criteria Decision-Making Model: Interval Rough SAW Method for Sustainable Supplier Selection”, Information, 10(10), 292.
• Tey, D.J.Y., Gan, Y.F., Selvachandran, G., Quek, S.G., Smarandache, F., Abdel-Basset, M. and Long, H.V. (2019). “A Novel Neutrosophic Data Analytic Hierarchy Process for Multi-Criteria Decision-Making Method: A Case Study in Kuala Lumpur Stock Exchange”, IEEE Access, 7, 53687-53697. https://doi.org/10.1109/ ACCESS.2019.2912913.
• Türegün, N. (2022). “Financial Performance Evaluation by Multi-Criteria Decision-Making Techniques”, Heliyon, 8(5), e09361.
• United Nations. (1987). “Our Common Future”, United Nations, World Commission on Environment and Development (Brundtland Report), Oxford University Press, Oxford.
• Venanzi, D. (2010). “Financial Performance Measures and Value Creation: A Review”, SSRN, 1716209, 1-36. DOI: 10.2139/ssrn.1716209.
• Wang, Y.J. (2008). “Applying FMCDM to Evaluate Financial Performance of Domestic Airlines in Taiwan”, Expert Systems with Applications, 34(3), 1837-1845.
• Yasmin, M., Tatoglu, E., Kilic, H.S., Zaim, S. and Delen, D. (2020). “Big Data Analytics Capabilities and Firm Performance: An Integrated MCDM Approach”, Journal of Business Research, 114, 1-15.
• Zavadskas, E.K., Kaklauskas, A. and Sarka, V. (1994). “The New Method of Multicriteria Complex Proportional Assessment of Projects”, Technological and Economical Development of Economy, 1, 131–139.
• Zionts, S. and Wallenius, J. (1983). “An Interactive Multiple Objective Linear Programming Method for A Class of Underlying Nonlinear Utility Functions”, Management science, 29(5), 519-529.
• Zopounidis, C. and Doumpos, M. (2013). “Multicriteria Decision Systems for Financial Problems”, Top, 21, 241-261.