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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Fernandes, H. & Ferreira, F. (2023). Health insurance risk assessment using cognitive mapping and multiple‐criteria decision analysis. International Transactions of Operations Research. 30 (5), 2158-2188
Exportar Referência (IEEE)
H. E. Fernandes and F. A. Ferreira,  "Health insurance risk assessment using cognitive mapping and multiple‐criteria decision analysis", in Int. Transactions of Operations Research, vol. 30, no. 5, pp. 2158-2188, 2023
Exportar BibTeX
@article{fernandes2023_1711700222127,
	author = "Fernandes, H. and Ferreira, F.",
	title = "Health insurance risk assessment using cognitive mapping and multiple‐criteria decision analysis",
	journal = "International Transactions of Operations Research",
	year = "2023",
	volume = "30",
	number = "5",
	doi = "10.1111/itor.12895",
	pages = "2158-2188",
	url = "https://onlinelibrary.wiley.com/doi/abs/10.1111/itor.12895"
}
Exportar RIS
TY  - JOUR
TI  - Health insurance risk assessment using cognitive mapping and multiple‐criteria decision analysis
T2  - International Transactions of Operations Research
VL  - 30
IS  - 5
AU  - Fernandes, H.
AU  - Ferreira, F.
PY  - 2023
SP  - 2158-2188
SN  - 0969-6016
DO  - 10.1111/itor.12895
UR  - https://onlinelibrary.wiley.com/doi/abs/10.1111/itor.12895
AB  - Health insurance risk analysis is crucial to the development of the insurance industry, allowing insurance companies to anticipate potential losses in health insurance’s inverted product life cycle. The health insurance risk evaluation process is, however, carried out in various ways, which limits the application of transparency, fairness, and justice principles in the calculation of risk rewards. By combining cognitive mapping and measuring attractiveness by a categorical-based evaluation technique (i.e., MACBETH, a multiple-criteria decision analysis technique), this study sought to create a nonparametric and distinctive decision support system for individual private health insurance risk analysis. The proposed system facilitates greater transparency in the calculation of health insurance risk rewards. The results of a real-world application of this system were analyzed and discussed in face-to-face group meetings with independent experts who work for two of the largest insurance companies in Portugal, thereby incorporating realism into the proposed evaluation mechanism. The advantages and limitations of this assessment framework are also discussed.
ER  -