Journal
APPLIED SOFT COMPUTING
Volume 104, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2021.107199
Keywords
COVID-19; Private health insurance; Performance of insurance companies; MARCOS; Intuitionistic fuzzy sets
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This article identifies insurance companies' priority ranking in terms of healthcare services in Turkey during the COVID-19 outbreak through a multi-criteria performance evaluation methodology. A new Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) technique is proposed under an intuitionistic fuzzy environment. The outcomes reveal the most crucial factors as the payback period, premium price, and network in ranking insurance companies during the COVID-19 era.
Assessing and ranking private health insurance companies provides insurance agencies, insurance customers, and authorities with a reliable instrument for the insurance decision-making process. Moreover, because the world's insurance sector suffers from a gap of evaluation of private health insurance companies during the COVID-19 outbreak, the need for a reliable, useful, and comprehensive decision tool is obvious. Accordingly, this article aims to identify insurance companies' priority ranking in terms of healthcare services in Turkey during the COVID-19 outbreak through a multi-criteria performance evaluation methodology. Herein, alternatives are evaluated and then ranked as per 7 criteria and assessments of 5 experts. Experts' judgments and assessments are full of uncertainties. We propose a Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) technique under an intuitionistic fuzzy environment to rank insurance companies. The outcomes yielded ten insurance companies ranking in terms of healthcare services in the era of COVID-19. The payback period, premium price, and network are determined as the most crucial factors. Finally, a comprehensive sensitivity analysis is performed to verify the proposed methodology's stability and effectiveness. The introduced approach met the insurance assessment problem during the COVID-19 pandemic very satisfactory manner based on sensitivity analysis findings. (C) 2021 Elsevier B.V. All rights reserved.
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