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Research Article

Determinants of Life Insurance Demand, Consumer Perspective - A Case Study of Ayeduase-Kumasi Community, Ghana

Eric Effah Sarkodie1* and Hadrat M Yusif2

1Department of Accounting Studies Education, College of Technology Education, University of Education, Kumasi, Winneba, Ghana

2Departments of Economics, College of Arts and Social Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

*Corresponding Author:
Eric Effah Sarkodie
University of Education, College of Technology Education
Department of Accounting Studies Education
Kumasi, Ghana
Tel: +233246810974
E-mail: [email protected]

Received date: July 14, 2015 Accepted date: July 24, 2015 Published date: July 31, 2015

Citation: Sarkodie EE, Yusif HM (2015) Determinants of Life Insurance Demand, Consumer Perspective - A Case Study of Ayeduase-Kumasi Community, Ghana. Bus Eco J 6:170. doi:10.4172/2151-6219.1000170

Copyright: © 2015 Sarkodie EE, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

This study finds out the determinants of life insurance demand in the Ayeduase-Kumasi community from the perspective of consumers. The study adopted Logistic regression modeling technique with 256 cross section observations. Income, higher education, number of dependents, employment by someone else and better perception about insurance firms improved the chances of taking life insurance. Age however, has negative relationship with the odds of taking life insurance. Number of dependents was statistically significant at 1%. Age and Type of employment were both significant at 5% while’s income and education level were significant at 10%. Overall the Chi-Square showed that the model was statistically significant at less than 0.001. This study had similar results to previous studies and deviates as well. Çelik and Kayali found a positive relationship between income and odds of taking insurance and that was not different from the results of this study. Contrary to Çelik and Kayali, higher education influences positively the odds of taking life insurance. Moreover, segmenting customers into different groups by using the type of employment as basis of segmentation could help insurance firms to prescribe policies that customers may patronize.

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