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Private health insurance companies operate within the realm of risk management, where effective risk handling is crucial to meet the expectations of beneficiaries. This research aims to evaluate the performance of private health insurance companies during the COVID-19 pandemic using neutrosophic sets. Linguistic assessments of alternatives (insurance companies) and criteria (performance factors) were converted into neutrosophic numbers with expert input. The MARCOS method based on neutrosophic sets, a multi-criteria decision-making (MCDM) technique, is applied to this uncertain decision-making problem, resulting in a ranked evaluation of the companies. The strength of this method lies in its ability to account for three membership degrees: truth, indeterminacy, and falsity. Additionally, a comprehensive sensitivity analysis using the entropy method was conducted to validate the stability and effectiveness of the proposed approach.

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Neutrosophic MARCOS Method for Evaluating the Performance of Insurance Companies During COVID-19 Pandemic

  • 会议论文

  • 发表日期：

    2025年

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  • M. Kavitha,
  • J. Aldring,
  • D. Ajay,
  • S. John Borg

摘要

Private health insurance companies operate within the realm of risk management, where effective risk handling is crucial to meet the expectations of beneficiaries. This research aims to evaluate the performance of private health insurance companies during the COVID-19 pandemic using neutrosophic sets. Linguistic assessments of alternatives (insurance companies) and criteria (performance factors) were converted into neutrosophic numbers with expert input. The MARCOS method based on neutrosophic sets, a multi-criteria decision-making (MCDM) technique, is applied to this uncertain decision-making problem, resulting in a ranked evaluation of the companies. The strength of this method lies in its ability to account for three membership degrees: truth, indeterminacy, and falsity. Additionally, a comprehensive sensitivity analysis using the entropy method was conducted to validate the stability and effectiveness of the proposed approach.