Analyzing the Turkish insurance companies’ financial performance traded on BIST implementing the critic-based PIV method

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The insurance industry, which is an important component of the financial channel, is an essential part of the Turkish economy, and assessing the financial performance is critical for insurance companies to improve efficiency and productivity, increase competitiveness, and enhance fiscal health. The study presented a technique for assessing the financial performance of all insurance companies registered in Borsa Istanbul by implementing an integrated method that combines the Criteria Importance Through Intercriteria Correlation (CRITIC) and Proximity Indexed Value (PIV) methods. The rationale for implementing the PIV method is the lack of adequate financial studies available on the insurance companies that employed this specific model. Initially, 18 evaluation criteria were defined. The CRITIC method was applied for the criteria weights, and insurance companies were ranked using PIV. Subsequently, the COPRAS, VIKOR, ARAS, and SAW Multi-Criteria Decision-Making (MCDM) methodologies were applied. Performance rankings derived from PIV were compared with those obtained from other MCDM models employed. Finally, Spearman’s Rank Correlation and Kendall’s Rank Correlation Coefficient methods were applied to analyze the extent of correlations and interactions between ranking outcomes. The PIV assessment results pointed out that AGESA received the highest rank for financial performance, and AKGRT had the lowest rank. AGESA consistently received high rankings compared to all other methods examined. Nevertheless, RAYSG and AKGRT constantly ranked poorly. All deployed methods ranked AKGRT and RAYSG in the final two positions. The study’s findings underscore that ranking outcomes of PIV largely align with alternate MCDM methodologies utilized.

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    • Figure 1. Comparative rankings derived from MCDM methods
    • Table 1. Constructing the decision matrix
    • Table 2. Criteria and weights (Wj)
    • Table 3. Decision matrix adjusted with Z-value standardization
    • Table 4. Normalized decision matrix
    • Table 5. Weighted normalized decision matrix
    • Table 6. Weighted proximity index
    • Table 7. Overall proximity values
    • Table 8. Ranking results based on PIV
    • Table 9. Relative importance levels of decision alternatives and ranking
    • Table 10. Ranked Si, Ri, and Qi values
    • Table 11. Ranking results based on VIKOR
    • Table 12. Si, Ki, and ranking (R)
    • Table 13. Ranking the alternatives
    • Table 14. Ranking results of MCDM methodologies
    • Table 15. Spearman coefficient of rank correlation
    • Table 16. Correlation matrix (Kendall)
    • Table A1. Insurance companies traded on BIST and their codes
    • Table B1. Groups, evaluation criteria, codes and impact directions
    • Table C1. Example of correlation coefficient interpretation
    • Conceptualization
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    • Data curation
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    • Formal Analysis
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    • Funding acquisition
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    • Investigation
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    • Methodology
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    • Software
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    • Visualization
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