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Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data

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  • Mahmut Baydaş

    (Faculty of Applied Sciences, Necmettin Erbakan University, Konya 42140, Turkey)

  • Dragan Pamučar

    (Department of Logistics, University of Defence in Belgrade, 11000 Belgrade, Serbia)

Abstract

A major difficulty in comparing and even choosing MCDM methods is the uncertainty of information about the consistent and unique characteristics of the results produced. The objective information content of the final scores produced by MCDM methods and their relevance to real life can give us an important idea about them. In this study, first of all, seven MCDM methods with different methodologies were applied to evaluate companies’ financial performance. Then, the obtained MCDM scores were compared using two different objective verification mechanisms. The first validation criterion is the relationship of a MCDM method to real-life rankings (share price). The second criterion is the standard deviation (SD) technique used to discover the objective information content of MCDM final scores. According to the results of this study, PROMETHEE and FUCA definitely outperform other methods in terms of both SD values and strength of correlation with reference real-life rankings. Also, FUCA is methodologically simpler than other methods. However, it produced nearly identical results as the sophisticated PROMETHEE method.

Suggested Citation

  • Mahmut Baydaş & Dragan Pamučar, 2022. "Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data," Mathematics, MDPI, vol. 10(7), pages 1-25, March.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1115-:d:783845
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    References listed on IDEAS

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    1. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    2. Gudiel Pineda, Pedro Jose & Liou, James J.H. & Hsu, Chao-Che & Chuang, Yen-Ching, 2018. "An integrated MCDM model for improving airline operational and financial performance," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 103-117.
    3. Feng, Cheng-Min & Wang, Rong-Tsu, 2000. "Performance evaluation for airlines including the consideration of financial ratios," Journal of Air Transport Management, Elsevier, vol. 6(3), pages 133-142.
    4. Darius Danesh & Michael J. Ryan & Alireza Abbasi, 2017. "A systematic comparison of multi-criteria decision making methods for the improvement of project portfolio management in complex organisations," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 16(3), pages 280-320.
    5. Behzadian, Majid & Kazemzadeh, R.B. & Albadvi, A. & Aghdasi, M., 2010. "PROMETHEE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 200(1), pages 198-215, January.
    6. Mehdi KESHAVARZ GHORABAEE & Edmundas Kazimieras ZAVADSKAS & Zenonas TURSKIS & Jurgita ANTUCHEVICIENE, 2016. "A New Combinative Distance-Based Assessment(Codas) Method For Multi-Criteria Decision-Making," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 25-44.
    7. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    8. Maria Rosaria Guarini & Fabrizio Battisti & Anthea Chiovitti, 2018. "A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes," Sustainability, MDPI, vol. 10(2), pages 1-28, February.
    9. Emrah Ayhan, 2019. "An Empirical Study For The Financial Situation Of Youth CSOs in TRB1 Region Of Turkey," Bingol University Journal of Economics and Administrative Sciences, Bingol University, Faculty of Economics and Administrative Sciences, vol. 3(2), pages 39-72, December.
    10. Nolberto Munier, 2006. "Economic Growth and Sustainable Development: Could Multicriteria Analysis be used to Solve this Dichotomy?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 8(3), pages 425-443, August.
    11. Lee, Hsing-Chen & Chang, Ching-Ter, 2018. "Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 883-896.
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    1. Ahmet Kaya & Dragan Pamucar & Hasan Emin Gürler & Mehmet Ozcalici, 2024. "Determining the financial performance of the firms in the Borsa Istanbul sustainability index: integrating multi criteria decision making methods with simulation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-44, December.

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