Assessing Food and Beverage Companies During a Time of Crisis: A Comparative MCDA Approach

Yıl 2024, Cilt: 8 Sayı: 3, 1568 - 1598, 27.09.2024

Orhan Emre Elma

https://doi.org/10.25295/fsecon.1394998

Öz

Financial performance analysis plays a pivotal role in assisting companies achieve their future goals more decisively and in identifying the shortcomings in their competition with their rivals. Multi-Criteria Decision Analysis (MCDA) methods are used in complex scenarios where decisions can be made in different variations based on more than one criterion. During the pandemic, uncertainty increased in all capital markets and the volatility of financial instruments was intensely felt. To that end, the performance of 23 companies listed in the Food and Beverage index of Borsa Istanbul, which is an emerging market, between the years 2020 and 2022, corresponding to the pandemic period, will be analyzed in this study. In the research, where 6 accounting and valuation-based ratios were used as criteria, CRITIC objective weighting technique was integrated and analyzes were made with VIKOR, GRA, TOPSIS, SAW, FUCA, ELECTRE III and COPRAS methods. The results of this research are noteworthy as it is the first study on the relevant index that includes 7 different methods comparatively. Interestingly, as a result of the study, the VIKOR method provided the most sustainable success in this period of historical uncertainty, while the FUCA method took the second place.

Anahtar Kelimeler

Capital Markets, Share Return, MCDA

Gıda ve İçecek Firmalarının Kriz Zamanında Değerlendirilmesi: Karşılaştırmalı Bir ÇKKA Yaklaşımı

Öz

Şirketlerin gelecek ile ilgili belirlemiş oldukları rotalara daha kararlı bir şekilde varmaları ve rakipleri ile rekabetlerinde aksayan yönlerini tespit etmeleri açısından finansal performans analizleri pivot bir rol üstlenmektedir. Kararların birden fazla kriter üzerinden farklı varyasyonlarda verilebildiği karmaşık durumlarda Çok Kriterli Karar Analizi (ÇKKA) yöntemleri kullanılmaktadır. Pandemi sürecinde tüm sermaye piyasalarında belirsizlik artmış ve finansal varlıklarda artan düzeyde volatilite hissedilmiştir. Bu amaçla, bu çalışmada gelişmekte olan bir piyasa olan Borsa İstanbul'un Gıda ve İçecek endeksinde yer alan 23 şirketin pandemi dönemine denk gelen 2020-2022 yılları arasındaki performansı analiz edilecektir. Kriter olarak 6 muhasebe ve değerlemeye dayalı oranın kullanıldığı araştırmada, CRITIC objektif ağırlıklandırma tekniği tercih edilmiş ve VIKOR, GRA, TOPSIS, SAW, FUCA, ELECTRE III ve COPRAS yöntemleriyle analizler yapılmıştır. Bu çalışmanın sonuçları, ilgili endekste 7 farklı yöntemin karşılaştırmalı olarak kullanıldığı ilk çalışma olması açısından dikkat çekicidir. İlginçtir ki, çalışma sonucunda VIKOR yöntemi bu tarihi belirsizlik döneminde en sürdürülebilir başarıyı sağlarken, FUCA yöntemi ikinci sırada yer almıştır.

Anahtar Kelimeler

Sermaye Piyasaları, Hisse Getirisi, ÇKKA

Kaynakça

• Akbulut, R. & Rencber, O. F. (2015). BİST’te İmalat Sektöründeki İşletmelerin Finansal Performansları Üzerine Bir Araştırma. Muhasebe ve Finansman Dergisi, (65), 117-136. https://doi.org/10.25095/mufad.396520
• Akbulut, O. Y. & Şenol, Z. (2021). Bütünleşik SD ve PROMETHEE ÇKKV Yöntemleri ile Portföy Optimizasyonu: BIST Gıda, İçecek ve Tütün Sektöründe Ampirik Bir Uygulama. Muhasebe ve Finansman Dergisi, (92), 161-182.
• Akkoç, S. & Vatansever, K. (2013). Fuzzy Performance Evaluation with AHP and TOPSIS Methods: Evidence from Turkish Banking Sector After the Global Financial Crisis. Eurasian Journal of Business and Economics, 6(11), 53-74.
• Aktan, B. & Bulut, C. (2008). Financial Performance Impacts of Corporate Entrepreneurship in Emerging Markets: A Case of Turkey. European Journal of Economics, Finance and Administrative Sciences, 12(8), 1530-2275.
• Ali, A. M., Abdelhafeez, A., Soliman, T. H. & ELMenshawy, K. (2024). A probabilistic hesitant fuzzy MCDM approach to selecting treatment policy for COVID-19. Decision Making: Applications in Management and Engineering, 7(1), 131-144.
• Almeida-Filho, A. T. D., de Lima Silva, D. F. & Ferreira, L. (2020). Financial Modelling with Multiple Criteria Decision Making: A Systematic Literature Review. Journal of the Operational Research Society, 72(10), 2161-2179.
• Amiri, M., Zandieh, M., Soltani, R. & Vahdani, B. (2009). A Hybrid Multi-Criteria Decision-Making Model for Firms’ Competence Evaluation. Expert Systems with Applications, 36(10), 12314-12322.
• Antil, P. & Singh, M. (2013). Performance Measurement of an Industry Using Simple Additive Weight. International Journal for Research in Applied Science and Engineering Technology, 1(3), 1-3.
• Aydoğan, E. K. (2011). Performance Measurement Model for Turkish Aviation Firms Using the Rough-AHP and TOPSIS Methods Under Fuzzy Environment. Expert Systems with Applications, 38(4), 3992-3998.
• Aytekin, S. & Sakarya, Ş. (2013). BIST’de İşlem Gören Gıda İşletmelerinin TOPSIS Çok Kriterli Karar Verme Yöntemi ile Finansal Performanslarının Değerlendirilmesi. Journal of Management and Economics Research, 11(21), 30-47.
• Bacidore, J. M., Boquist, J. A., Milbourn, T. T. & Thakor, A. V. (1997). The Search for the Best Financial Performance Measure. Financial Analysts Journal, 53(3), 11-20. https://doi.org/10.2469/faj.v53.n3.2081
• Bağcı, H. (2013). Ticari Bankalar ile Katılım Bankalarının Karlılık Performanslarının TOPSIS Yöntemi ile Karşılaştırılması. Unpublished Doctoral Dissertation, DEÜ Sosyal Bilimleri Enstitüsü.
• Bakırcı, F., Shiraz, S. E. & Sattary, A. (2014). BIST'de Demir, Çelik Metal Ana Sanayii Sektöründe Faaliyet Gösteren İşletmelerin Finansal Performans Analizi: VZA Süper Etkinlik ve TOPSIS Uygulaması. Ege Akademik Bakış, 14(1), 9-19.
• Balezentis, A., Balezentis, T. & Misiunas, A. (2012). An Integrated Assessment of Lithuanian Economic Sectors Based on Financial Ratios and Fuzzy MCDM Methods. Technological and Economic Development of Economy, 18(1), 34-53.
• Banaitiene, N., Banaitis, A., Kaklauskas, A. & Zavadskas, E. K. (2008). Evaluating the Life Cycle of a Building: A Multivariant and Multiple Criteria Approach. Omega, 36(3), 429-441.
• Baydaş, M. & Elma, O. E. (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, 4(2), 257-279. https://doi.org/10.31181/dmame210402257b
• 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. https://doi.org/10.1016/j.eswa.2022.116755
• Bayrakdaroğlu, A. & Ege, İ. (2008). Türkiye’deki Bankaların Performansının Analitik Hiyerarşi Süreci ile Değerlendirilmesi Üzerine Bir Model Önerisi. Türkiye İstatistik Kurumu 17. İstatistik Araştırma Sempozyumu, 32-49, Ankara.
• Burmaoğlu, S. & Kazancoğlu, Y. (2012). E-Government Website Evaluation with Hybrid MCDM Method in Fuzzy Environment. International Journal of Applied Decision Sciences, 5(2), 163-181.
• Chacko, G. & Evans, C. L. (2014). Valuation: Methods and Models in Applied Corporate Finance. FT Press.
• Chang, C. P. (2006). Managing Business Attributes and Performance for Commercial Banks. The Journal of American Academy of Business, 9(1), 104-109.
• Chang, T. H. (2014). Fuzzy VIKOR method: A Case Study of the Hospital Service Evaluation in Taiwan. Information Sciences, 271, 196-212.
• Chang, S. C. & Tsai, P. H. (2016). A Hybrid Financial Performance Evaluation Model for Wealth Management Banks Following the Global Financial Crisis. Technological and Economic Development of Economy, 22(1), 21-46.
• Chaurasiya, R. & Jain, D. (2022). Pythagorean fuzzy entropy measure-based complex proportional assessment technique for solving multi-criteria healthcare waste treatment problem. Granular Computing, 7(4), 917-930.
• Chelmis, E., Niklis, D., Baourakis, G. & Zopounidis, C. (2017). Multiciteria Evaluation of Football Clubs: The Greek Superleague. Operational Research, 19(2), 1-30. https://doi.org/10.1007/s12351-017-0300-2
• Chen, Z. S., Hu, Y. J., Ma, Z., Yang, H. H., Shang, L. L. & Skibniewski, M. J. (2024). Selecting optimal honeycomb structural materials for electronics clean rooms using a Bayesian best-worst method and ELECTRE III. Journal of Building Engineering, 108703.
• Cheng, J. M. S., Tsao, S. M., Tsai, W. H. & Tu, H. H. J. (2007). Will eChannel Additions Increase The Financial Performance of the Firm?-The Evidence from Taiwan. Industrial Marketing Management, 36(1), 50-57. https://doi.org/10.1016/j.indmarman.2006.06.011
• Çevikcan, E., Çebi, S. & Kaya, I. (2009). Fuzzy VIKOR and Fuzzy Axiomatic Design Versus to Fuzzy TOPSIS: An Application of Candidate Assessment. Journal of Multiple-Valued Logic and Soft Computing, 15(2-3), 181-208.
• Dahooie, J. H., Hajiagha, S. H. R., Farazmehr, S., Zavadskas, E. K. & Antucheviciene, J. (2021). A Novel Dynamic Credit Risk Evaluation Method Using Data Envelopment Analysis with Common Weights and Combination of Multi-Attribute Decision-Making Methods. Computers & Operations Research, 129. https://doi.org/10.1016/j.cor.2021.105223
• Diakoulaki, D., Mavrotas, G. & Papayannakis, L. (1995). Determining Objective Weights In Multiple Criteria Problems: the CRITIC Method. Computers & Operational Research, 22(7), 763-770. https://doi.org/10.1016/0305-0548(94)00059-H
• Do, D. T. (2022). Application of FUCA method for multi-criteria decision making in mechanical machining processes. Operational Research in Engineering Sciences: Theory and Applications, 5(3), 131-152.
• Doğan, M. (2013). Measuring Bank Performance with Gray Relational Analysis: The Case of Turkey. Ege Academic Review, 13(2), 215-226.
• Elma, O. E. (2023). Comparative Financial Performance Analysis of SMEs Traded on BIST with MCDA Techniques During the Pandemic Period. UYIK Proceedings Book 2023, 230-242, Sarajevo.
• Elma, O. E., Stević, Ž. & Baydaş, M. (2024). An Alternative Sensitivity Analysis for the Evaluation of MCDA Applications: The Significance of Brand Value in the Comparative Financial Performance Analysis of BIST High-End Companies. Mathematics, 12(4), 520.
• Erasmus, P. D. (2008). Evaluating Value Based Financial Performance Measures. Unpublished Doctoral Dissertation, Stellenbosch: University of Stellenbosch.
• Ervural, B. C., Zaim, S., Demirel, O. F., Aydın, Z. & Delen, D. (2018). An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews, 82, 1538-1550.
• Fernando, M. M. L., Escobedo, J. L. P., Azzaro-Pantel, C., Pibouleau, L., Domenech, S. & 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 MDCM, April, 159-166.
• Gauri, S. K. & Pal, S. (2010). Comparison of Performances of Five Prospective Approaches for The Multi-Response Optimization. The International Journal of Advanced Manufacturing Technology, 48(9), 1205-1220.
• Ghadikolaei, A. S., Khalili Esbouei, S. & Antucheviciene, J. (2014). Applying fuzzy MCDM for Financial Performance Evaluation of Iranian Companies. Technological and Economic Development of Economy, 20(2), 274-291.
• Giannoulis, C. & Ishizaka, A. (2010). A Web-Based Decision Support System with ELECTRE III for a Personalised Ranking of British Universities. Decision Support Systems, 48(3), 488-497.
• Guo, S. & Zhao, H. (2015). Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective. Applied Energy, 158, 390-402.
• Guo, Y. (2010). A Decision Method for M-Commerce Partner Selection Based on AHP/ELECTRE I. Journal of Computational Information Systems, 6(9), 3077-3086.
• Hemmati, M., Dalghandi, S. & Nazari, H. (2013). Measuring Relative Performance of Banking Industry Using a DEA and TOPSIS. Management Science Letters, 3(2), 499-504. https://doi.org/10.5267/j.msl.2012.12.025
• Ho, C. T. & Wu, Y. S. (2006). Benchmarking Performance Indicators for Banks. Benchmarking: An International Journal, 13(2), 147-159. https://doi.org/10.1108/14635770610644646
• Ho, W. R. J., Tsai, C. L., Tzeng, G. H. & Fang, S. K. (2011). Combined DEMATEL Technique with a Novel MCDM Model for Exploring Portfolio Selection Based on CAPM. Expert Systems with Applications, 38(1), 16-25.
• 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.
• Iniestra, J. G. & Gutiérrez, J. G. (2009). Multicriteria Decisions on Interdependent Infrastructure Transportation Projects Using an Evolutionary-Based Framework. Applied Soft Computing, 9(2), 512-526.
• Investment Office. (2022). Agriculture and Food Industry Report 2021. https://www.invest.gov.tr/tr/sectors/sayfalar/agrofood.aspx
• Iqbal, A. & Zhuquan, W. (2015). Working Capital Management and Profitability Evidence from Firms Listed on Karachi Stock Exchange. International Journal of Business and Management, 10(2), 231-235.
• Isabels, R., Vinodhini, A. F. & Viswanathan, A. (2024). Evaluating and Ranking Metaverse Platforms Using Intuitionistic Trapezoidal Fuzzy VIKOR MCDM: Incorporating Score and Accuracy Functions for Comprehensive Assessment. Decision Making: Applications in Management and Engineering, 7(1), 54-78.
• Julong, D. (1989). Introduction to Grey System Theory. The Journal of Grey System, 1(1), 1-24.
• Kanapeckiene, L., Kaklauskas, A., Zavadskas, E. K. & Seniut, M. (2010). Integrated Knowledge Management Model and System for Construction Projects. Engineering Applications of Artificial Intelligence, 23(7), 1200-1215.
• Kang, D. & Park, Y. (2014). Review-Based Measurement of Customer Satisfaction in Mobile Service: Sentiment Analysis and VIKOR Approach. Expert Systems with Applications, 41(4), 1041-1050. https://doi.org/10.1016/j.eswa.2013.07.101
• Kehribar, Ö., Karademir, F. & Evci, S. (2021). İşletmelerin COVID-19 Pandemisi Sürecindeki Finansal Performanslarının Entropi ve MAIRCA Yöntemleri ile Değerlendirilmesi: BIST Gıda, İçecek Endeksi Örneği. Business & Management Studies: An International Journal, 9(1), 200-214.
• Korkusuz, A., İnan, U., Özdemir, Y. & Başlıgil, H. (2020). Occupational health and safety performance measurement in healthcare sector using integrated multi criteria decision making methods. Journal of the Faculty of Engineering and Architecture of Gazi University, 35(1), 81-96.
• Kuo, M. S. & Liang, G. S. (2011). Combining VIKOR with GRA Techniques to Evaluate Service Quality of Airports Under Fuzzy Environment. Expert Systems with Applications, 38(3), 1304-1312.
• Leong, W. Y., Wong, K. Y. & Wong, W. P. (2022). A new integrated multi-criteria decision-making model for resilient supplier selection. Applied System Innovation, 5(1), 8.
• Levent, C. E. (2020). COVID-19 Salgınının Gıda ve İçecek Sektöründeki Şirketlerin Hisse Senedi Getiri ve Volatilitesine Etkisi. Electronic Turkish Studies, 15(6), 721-738.
• Lin, F., Chang, C. & Wu, S. (2009). A Study on the Relationship Between Related Party Transactions and Monthly Sales in Taiwan's Publicly Issued Companies. Journal of the Chinese Institute of Industrial Engineers, 26(5), 337-343.
• Lootsma, F. A. (Ed.). (1999). Multi-Criteria Decision Analysis Via Ratio and Difference Judgement. Boston, MA: Springer USA.
• Mabandla, N. Z. & Makoni, P. L. (2019). Working Capital Management and Financial Performance: Evidence from Listed Food and Beverage Companies in South Africa. Academy of Accounting and Financial Studies Journal, 23(2), 1-10.
• Mandic, K., Delibasic, B., Knezevic, S. & Benkovic, S. (2014). Analysis of the Financial Parameters of Serbian Banks Through the Application of the Fuzzy AHP and TOPSIS Methods. Economic Modelling, 43, 30-37. https://doi.org/10.1016/j.econmod.2014.07.036
• Mao, Q., Fan, J., Lv, J., Gao, Y., Chen, J. & Guo, M. (2024). A decision framework of offshore photovoltaic power station site selection based on Pythagorean fuzzy ELECTRE-III method. Journal of Renewable and Sustainable Energy, 16(2), 023502.
• Marbini, A. H. & Tavana, M. (2011). An Extension of the Electre I Method for Group Decision-Making Under a Fuzzy Environment. Omega, 39(4), 373-386.
• Martin, J. D. & Petty, J. W. (2000). Value-Based Management: The Corporate Response to the Shareholder Revolution. Boston, Massachusetts: Harvard Business School Press.
• Martin, C., Ruperd, Y. & Legret, M. (2007). Urban Stormwater Drainage Management: The Development of a Multicriteria Decision Aid Approach for Best Management Practices. European Journal of Operational Research, 181(1), 338-349.
• Mary, S. S. A. & Suganya, G. (2016). Multi-criteria decision making using ELECTRE. Circuits and Systems, 7(6), 1008-1020.
• Mohammed, K. I., Jaafar, J., Zaidan, A. A., Albahri, O. S., Zaidan, B. B., Abdulkareem, K. H., Jasim, A. N., Shareef, A. H., Baqer, M. J., Albahri, A. S., Alsalem, M. A. & Alamoodi, A. H. (2020). A uniform intelligent prioritization for solving diverse and big data generated from multiple chronic diseases patients based on hybrid decision-making and voting method. IEEE Access, 8, 91521-91530.
• Moosivand, A., Rangchian, M., Zarei, L., Peiravian, F., Mehralian, G. & Sharifnia, H. (2021). An application of multi-criteria decision-making approach to sustainable drug shortages management: evidence from a developing country. Journal of Pharmaceutical Health Care and Sciences, 7, 1-11.
• Mousavi-Nasab, S. H. & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 121, 237-253.
• Nguyen, P. H., Tsai, J. F., Nguyen, T. T., Nguyen, T. G. & Vu, D. D. (2020). A grey MCDM based on DEMATEL model for real estate evaluation and selection problems: A numerical example. The Journal of Asian Finance, Economics and Business, 7(11), 549-556.
• Ouattara, A., Pibouleau, L., Azzaro-Pantel, C., Domenech, S., Baudet, P. & Yao, B. (2012). Economic and Environmental Strategies for Process Design. Computers & Chemical Engineering, 36, 174-188.
• Ömürbek, N. & Eren, H. (2016). PROMETHEE, MOORA ve COPRAS Yöntemleri ile Oran Analizi Sonuçlarının Değerlendirilmesi: Bir Uygulama. Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 8(16), 174-187. https://doi.org/10.20875/sb.69615
• Özdemir, A. & Demireli, E. (2013). Mevduat Bankalarının Performansının ANP-TOPSIS ve ANP-VIKOR Bütünleşik Yaklaşımlarıyla Karşılaştırmalı Analizi: Borsa İstanbul (XU BANKA) Üzerine Bir Uygulama. Finans Politik ve Ekonomik Yorumlar Dergisi, 50(584), 59-80.
• Palepu, K. G., Bernard, V. L. & Healy, P. M. (2000). Business Analysis and Valuation: Using Financial Statements Cincinnati. Ohio, South Western College.
• Parashar, S., Bhattacharya, S., Titiyal, R. & Guha Roy, D. (2024). Assessing environmental performance of service supply chain using fuzzy TOPSIS method. Health Services and Outcomes Research Methodology, 24(1), 46-72.
• Pekkaya, M. (2015). Career Preference of University Students: An Application of MCDM Methods. Procedia Economics and Finance, 23, 249-255.
• Peng, Y., Wang, G., Kou, G. & Shi, Y. (2011). An Empirical Study of Classification Algorithm Evaluation for Financial Risk Prediction. Applied Soft Computing, 11(2), 2906-2915.
• Peng, Y. (2015). Regional Earthquake Vulnerability Assessment Using a Combination of MCDM Methods. Annals of Operations Research, 234(1), 95-110.
• Polatidis, H., Haralambidou, K. & Haralambopoulos, D. (2015). Multi-criteria decision analysis for geothermal energy: A comparison between the ELECTRE III and the PROMETHEE II methods. Energy Sources, Part B: Economics, Planning, and Policy, 10(3), 241-249.
• Qahtan, S., Sharif, K. Y., Zaidan, A. A., Alsattar, H. A., Albahri, O. S., Zaidan, B. B., Zulzalil, H., Osman, M. H., Alamoodi, A. H. & Mohammed, R. T. (2022). Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems. IEEE Transactions on Industrial Informatics, 18(9), 6415-6423.
• Radulescu, C. Z. & Radulescu, M. (2024). A Hybrid Group Multi-Criteria Approach Based on SAW, TOPSIS, VIKOR, and COPRAS Methods for Complex IoT Selection Problems. Electronics, 13(4), 789.
• Rostamzadeh, R., Govindan, K., Esmaeili, A. & Sabaghi, M. (2015). Application of Fuzzy VIKOR for Evaluation of Green Supply Chain Management Practices. Ecological Indicators, 49, 188-203.
• Roy, B. (1991). The Outranking Approach and the Foundations of ELECTRE Methods. Theory and Decision, 31, 49-73.
• Ruiz-Vélez, A., García, J., Alcalá, J. & Yepes, V. (2024). Sustainable Road Infrastructure Decision-Making: Custom NSGA-II with Repair Operators for Multi-Objective Optimization. Mathematics, 12(5), 730.
• Sampath, V. K. & Radhakrishnan, N. (2024). Prioritization of Sub-Watersheds Susceptible to Soil Erosion using Different Combinations of Objective Weighting and MCDM Techniques in an Ungauged River Basin. Water Resources Management, 1-23.
• Sandoval, E. (2001). Financial Performance Measures and Shareholder Value Creation: An Empirical Study for Chilean Companies. Journal of Applied Business Research, 17(3), 109-122. https://doi.org/10.19030/jabr.v17i3.2239
• Sennaroğlu, B. & Çelebi, G. V. (2018). A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transportation Research Part D: Transport and Environment, 59, 160-173.
• Shaverdi, M., Ramezani, I., Tahmasebi, R. & Rostamy, A. A. A. (2016). Combining Fuzzy AHP and Fuzzy TOPSIS with Financial Ratios to Design a Novel Performance Evaluation Model. International Journal of Fuzzy Systems, 18(2), 248-262.
• Solangi, Y. A., Longsheng, C. & Shah, S. A. A. (2021). Assessing and overcoming the renewable energy barriers for sustainable development in Pakistan: An integrated AHP and fuzzy TOPSIS approach. Renewable Energy, 173, 209-222.
• Song, H., Zhao, C. & Zeng, J. (2017). Can Environmental Management Improve Financial Performance: An Empirical Study of A-Shares Listed Companies in China. Journal of Cleaner Production, 141, 1051-1056.
• Stewart, G. B. (1990). The Quest for Value: The EVA Management Guide. New York: Harper Business.
• Sumrit, D. (2020). Supplier selection for vendor-managed inventory in healthcare using fuzzy multi-criteria decision-making approach. Decision Science Letters, 9(2), 233-256.
• Tanaji, B. A. & Roychowdhury, S. (2024). BWM Integrated VIKOR Method Using Neutrosophic Fuzzy Sets for Cybersecurity Risk Assessment of Connected and Autonomous Vehicles. Applied Soft Computing, 111628.
• Thakkar, J. J. (2021). Complex Proportion Assessment Method (COPRAS). Multi-Criteria Decision Making. Studies in Systems, Decision and Control, 336. Springer, Singapore.
• Trung, D. D., Bao, N. C., Van Duc, D., Ašonja, A. & Dudić, B. (2024). Selecting Mini Water Pump by Using Multi-Criteria Decision-Making Technique: Comparison of FUCA and PSI Methods. 2024 23rd International Symposium Infoteh-Jahorina IEEE, March, 1-7.
• Tsai, W. H., Lee, P. L., Shen, Y. S. & Hwang, E. T. (2014). A Combined Evaluation Model for Encouraging Entrepreneurship Policies. Annals of Operations Research, 221(1), 449-468.
• Türkmen, S. Y. & Çağıl, G. (2012). İMKB’ye Kote Bilişim Sektörü Şirketlerinin Finansal Performanslarının TOPSIS Yöntemi ile Değerlendirilmesi. Maliye ve Finans Yazıları, 1(95), 59-78.
• Tzeng, G. H. & Huang, C. Y. (2012). Combined DEMATEL Technique with Hybrid MCDM Methods for Creating the Aspired Intelligent Global Manufacturing & Logistics Systems. Annals of Operations Research, 197(1), 159-190.
• Uyguntürk, H. & Korkmaz, T. (2012). Finansal Performansın TOPSIS Çok Kriterli Karar Verme Yöntemi ile Belirlenmesi: Ana Metal Sanayi İşletmeleri Üzerine Bir Uygulama, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 7(2), 95-115.
• Venkateswarlu, P. & Sarma, B. D. (2016). Selection of equipment by using saw and Vikor methods. J. Engineering Res. Appl, 6(111), 2248-962261.
• Vezmelai, A., Lashgari, Z. & Keyghobadi, A. (2015). Portfolio Selection Using ELECTRE III: Evidence from Tehran Stock Exchange. Decision Science Letters, 4(2), 227-236.
• Wang, C. (2005). Ownership and Operating Performance of Chinese IPOs. Journal of Banking and Finance, 29(7), 1835-1856. https://doi.org/10.1016/j.jbankfin.2004.07.003
• Wang, Y. J. (2009). Combining Grey Relation Analysis with FMCGDM to Evaluate Financial Performance of Taiwan Container Lines. Expert Systems with Applications, 36(2), 2424-2432.
• Wang, L. E., Liu, H. C. & Quan, M. Y. (2016). Evaluating the risk of failure modes with a hybrid MCDM model under interval-valued intuitionistic fuzzy environments. Computers & Industrial Engineering, 102, 175-185.
• Wang, P., Zhu, Z. & Wang, Y. (2016). A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design. Information Sciences, 345, 27-45.
• Wanke, P., Kalam Azad, M. A., Barros, C. P. & Hadi-Vencheh, A. (2016). Predicting Performance in ASEAN Banks: An Integrated Fuzzy MCDM–Neural Network Approach. Expert Systems, 33(3), 213-229. https://doi.org/10.1111/exsy.12144
• Wu, H. Y., Tzeng, G. H. & Chen, Y. H. (2009). A Fuzzy MCDM Approach for Evaluating Banking Performance Based on Balanced Scorecard. Expert Systems with Applications, 36(6), 10135-10147.
• Wu, C. R., Lin, C. T. & Tsai, P. H. (2010). Evaluating Business Performance of Wealth Management Banks. European Journal of Operational Research, 207(2), 971-979.
• Wu, Y., Chen, K., Zeng, B., Xu, H. & Yang, Y. (2016). Supplier selection in nuclear power industry with extended VIKOR method under linguistic information. Applied Soft Computing, 48, 444-457.
• Yazdani, M., & Graeml, F. R. (2014). VIKOR and its applications: A state-of-the-art survey. International Journal of Strategic Decision Sciences (IJSDS), 5(2), 56-83.
• Yoon, K. P. & Hwang, C. L. (1995). Multiple Attribute Decision Making: An Introduction. Sage Publications.
• You, P., Guo, S., Zhao, H. & Zhao, H. (2017). Operation performance evaluation of power grid enterprise using a hybrid BWM-TOPSIS method. Sustainability, 9(12), 2329.
• Yüksel, S., Dincer, H. & Emir, Ş. (2017). Comparing the Performance of Turkish Deposit Banks by Using DEMATEL, Grey Relational Analysis (GRA) And MOORA Approaches. World Journal of Applied Economics, 3(2), 26-47. https://doi.org/10.22440/wjae.3.2.2
• Zavadskas, E. K., Kaklauskas, A., Banaitis, A. & Kvederyte, N. (2004). Housing Credit Access Model: The Case for Lithuania. European Journal of Operational Research, 155(2), 335-352.
• Zavadskas, E. K. & Vilutienė, T. (2006). A Multiple Criteria Evaluation of Multi-Family Apartment Block's Maintenance Contractors: I—Model for Maintenance Contractor Evaluation and the Determination of Its Selection Criteria. Building and Environment, 41(5), 621-632.
• Zavadskas, E. K., Turskis, Z., Dejus, T. & Viteikiene, M. (2007). Sensitivity Analysis of a Simple Additive Weight Method. International Journal of Management and Decision Making, 8(5), 555-574.
• Zhou, Z., Zhang, Y., Zhang, Y., Hou, B., Mei, Y., Wu, P., Chen, Y., Zhou, W., Wu, H. & Chen, F. (2024). Advanced CRITIC–GRA–GMM model with multiple restart simulation for assuaging decision uncertainty: An application to transport safety engineering for OECD members. Advanced Engineering Informatics, 60, 102373.