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Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India

Imperfections in the private market increase the scope of social insurance worldwide. Social insurance is designed to provide protection against heterogeneous risks. In a welfare state, consumer's demand for social insurance arises from the need for optimum policy coverage. Likewise, government...

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Autores principales: Ansari, Zahin, Tabash, Mosab I., Akhtar, Asif, Khan, Samar H., Al-Matari, Ebrahim Mohammed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806392/
https://www.ncbi.nlm.nih.gov/pubmed/31692691
http://dx.doi.org/10.1016/j.heliyon.2019.e02683
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author Ansari, Zahin
Tabash, Mosab I.
Akhtar, Asif
Khan, Samar H.
Al-Matari, Ebrahim Mohammed
author_facet Ansari, Zahin
Tabash, Mosab I.
Akhtar, Asif
Khan, Samar H.
Al-Matari, Ebrahim Mohammed
author_sort Ansari, Zahin
collection PubMed
description Imperfections in the private market increase the scope of social insurance worldwide. Social insurance is designed to provide protection against heterogeneous risks. In a welfare state, consumer's demand for social insurance arises from the need for optimum policy coverage. Likewise, government intervention facilitates the insurance market by minimizing the effect of imperfect information and moral hazard. Designing cost and benefits of a policy, assessing the required level of risk to be taken and selecting integrated services (for example, medical care) are among the salient roles of the supplier. The present paper tries to find out the main drivers for social insurance in India. For this purpose, we have applied the Analytic Hierarchy Process (AHP) to determine the most important alternative among the different alternatives. The model consists of nine criteria and three alternatives. The results show that the consumer's demand is on the top of the hierarchy which signifies that the optimum policy coverage must be given due to consideration for mass administration of social insurance programs. The findings are important for policymakers in order to address consumer's needs so that enrollments in the insurance policies can be enhanced. The contribution of the study significantly includes the determination of a new set of study variables along with the application of the AHP methodology.
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spelling pubmed-68063922019-11-05 Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India Ansari, Zahin Tabash, Mosab I. Akhtar, Asif Khan, Samar H. Al-Matari, Ebrahim Mohammed Heliyon Article Imperfections in the private market increase the scope of social insurance worldwide. Social insurance is designed to provide protection against heterogeneous risks. In a welfare state, consumer's demand for social insurance arises from the need for optimum policy coverage. Likewise, government intervention facilitates the insurance market by minimizing the effect of imperfect information and moral hazard. Designing cost and benefits of a policy, assessing the required level of risk to be taken and selecting integrated services (for example, medical care) are among the salient roles of the supplier. The present paper tries to find out the main drivers for social insurance in India. For this purpose, we have applied the Analytic Hierarchy Process (AHP) to determine the most important alternative among the different alternatives. The model consists of nine criteria and three alternatives. The results show that the consumer's demand is on the top of the hierarchy which signifies that the optimum policy coverage must be given due to consideration for mass administration of social insurance programs. The findings are important for policymakers in order to address consumer's needs so that enrollments in the insurance policies can be enhanced. The contribution of the study significantly includes the determination of a new set of study variables along with the application of the AHP methodology. Elsevier 2019-10-19 /pmc/articles/PMC6806392/ /pubmed/31692691 http://dx.doi.org/10.1016/j.heliyon.2019.e02683 Text en © 2019 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Ansari, Zahin
Tabash, Mosab I.
Akhtar, Asif
Khan, Samar H.
Al-Matari, Ebrahim Mohammed
Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India
title Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India
title_full Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India
title_fullStr Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India
title_full_unstemmed Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India
title_short Identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from India
title_sort identifying and ranking the driving forces of social insurance by analytical hierarchy process: evidence from india
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806392/
https://www.ncbi.nlm.nih.gov/pubmed/31692691
http://dx.doi.org/10.1016/j.heliyon.2019.e02683
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