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Multidimensional Performance Evaluation Using the Hybrid MCDM Method: A Case Study in the Turkish Non-Life Insurance Sector

Year 2024, Volume: 11 Issue: 2, 854 - 883, 30.06.2024
https://doi.org/10.30798/makuiibf.1439172

Abstract

The aim of this study is to assess and rank the financial and service network performance of seven Turkish non-life insurance companies from 2018 to 2022 using the ENTROPY- MEREC - MACONT decision model. The study evaluates multidimensional firm performance based on selected performance indicators. The weights of these indicators were determined using ENTROPY and MEREC (method based on the removal effects of criteria) procedures. The MACONT (mixed aggregation by comprehensive normalization technique) procedure is used to obtain the multidimensional performance ranking of non-life insurance companies over time. The results of the MEREC and ENTROPY procedures indicate that the number of agencies, asset size, technical profit, and return on assets are generally effective criteria for the multidimensional performance of non-life insurance companies. The MACONT ranking results show that company IC2 had the best multidimensional performance during the analysis period. The validity and consistency of the results of the proposed decision model were tested using various sensitivity analyses.

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Year 2024, Volume: 11 Issue: 2, 854 - 883, 30.06.2024
https://doi.org/10.30798/makuiibf.1439172

Abstract

References

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Details

Primary Language English
Subjects Banking and Insurance (Other)
Journal Section Research Articles
Authors

Mehmet Zafer Taşcı 0000-0001-5848-259X

Publication Date June 30, 2024
Submission Date February 18, 2024
Acceptance Date May 15, 2024
Published in Issue Year 2024 Volume: 11 Issue: 2

Cite

APA Taşcı, M. Z. (2024). Multidimensional Performance Evaluation Using the Hybrid MCDM Method: A Case Study in the Turkish Non-Life Insurance Sector. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, 11(2), 854-883. https://doi.org/10.30798/makuiibf.1439172

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