Research Article
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Year 2022, Volume: 11 Issue: 4, 176 - 184, 31.12.2022

Abstract

References

  • Awunyo-Vitor, D., (2012). Comprehensive motor insurance demand in Ghana: Evidence from Kumasi metropolis. Management, 2(4), 80-86.
  • Awel, Y. M., & Azomahou, T. T., (2015). Risk preference or financial literacy? Behavioural experiment on index insurance demand. MERIT Working Papers 2015-005, United Nations University.
  • Beck, T., & Webb, I., (2003). Economic, demographic, and institutional determinants of life insurance consumption across countries. The World Bank Economic Review, 17(1), 51-88.
  • Bryan, G. (2019). Ambiguity aversion decreases the impact of partial insurance: Evidence from African farmers. Journal of the European Economic Association, 17(5), 1428-1469.
  • Browne, M. J., & Hoyt, R. E., (2000). The demand for flood insurance: empirical evidence. Journal of Risk and Uncertainty, 20(3), 291-306.
  • Browne, M. J., Knoller, C., & Richter, A., (2015). Behavioral bias and the demand for bicycle and flood insurance. Journal of Risk and Uncertainty, 50(2), 141-160.
  • Browne, M. J., & Kim, K., (1993). An international analysis of life insurance demand. Journal of Risk and Insurance, 60(4), 616-634.
  • Cole, S., Giné, X., Tobacman, J., Topalova, P., Townsend, R., & Vickery, J., (2013). Barriers to household risk management: Evidence from India. American Economic Journal: Applied Economics, 5(1), 104-35.
  • Corcos, A., Montmarquette, C., & Pannequin, F., (2020). How the demand for insurance became behavioral. Journal of Economic Behavior & Organization, 180, 590-595.
  • Cronbach, L.J., (1958). Proposals leading to analytic treatment of social perception scores, in Tagiuri R. and Petrullo L. eds. Person Perception and Interpersonal Behavior. Stanford University Press, Stanford, ISBN: 9780758134486.
  • Dragos, S. L., (2014). Life and non-life insurance demand: the different effects of influence factors in emerging countries from Europe and Asia. Economic research-Ekonomska istraživanja, 27(1), 169-180.
  • Halek, M., & Eisenhauer, J. G., (2001). Demography of risk aversion. Journal of Risk and Insurance, 68(1), 1-24.
  • Hertwig, R., Barron, G., Weber, E. U., & Erev, I., (2004). Decisions from experience and the effect of rare events in risky choice. Psychological Science, 15(8), 534-539.
  • Hsu, Y. C., Chou, P. L., & Shiu, Y. M. (2016). An examination of the relationship between vehicle insurance purchase and the frequency of accidents. Asia Pacific Management Review, 21(4), 231-238.
  • Jaspersen, J. G., (2016). Hypothetical surveys and experimental studies of insurance demand: A review. Journal of Risk and Insurance, 83(1), 217-255.
  • Josef, A. K., Richter, D., Samanez-Larkin, G. R., Wagner, G. G., Hertwig, R., & Mata, R., (2016). Stability and change in risk-taking propensity across the adult life span. Journal of Personality and Social Psychology, 111(3), 430.
  • Jurkovicova, M., (2016). Behavioral aspects affecting the purchase of insurance different behavior of men and women. Economic Review, 45(2), 181-96.
  • Kahneman, D., & Tverskey, A., (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.
  • King, J. E., (2008). Binary logistic regression, in Osborne J.W. eds., Best Practices in Quantitative Methods. Sage Publications, California, ISBN: 9781412940658.
  • Kline, P., (1994). An Easy Guide to Factor Analysis. Routledge, UK, ISBN: 9780415094900.
  • Kunreuther, H. C., Pauly, M. V., & McMorrow, S., (2013). Insurance and Behavioral Economics: Improving Decisions in The Most Misunderstood Industry. Cambridge University Press, UK, ISBN: 978-0521608268.
  • Lewis-Beck, M., Bryman, A. E. & Liao, T.F., (2003). The Sage Encyclopedia of Social Science Research Methods. Sage Publications, California, ISBN: 9781412950589.
  • Lusardi, A., & Mitchell, O. S., (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5-44.
  • Insurance Association of Türkiye (TSB). (2021). Number of Insurance Policies. https://www.tsb.org.tr/en/stats [Date Accessed: June 22, 2022].
  • OECD. (2021). OECD Insurance Statistics 2021, OECD Publishing. https://doi.org/10.1787/2307843x Date Accessed: June 22, 2022].
  • Outreville, J. F., (2014). Risk aversion, risk behavior, and demand for insurance: A survey. Journal of Insurance Issues, 37(2), 158-186.
  • Pitthan, F., & De Witte, K., (2021). Puzzles of insurance demand and its biases: A survey on the role of behavioural biases and financial literacy on insurance demand. Journal of Behavioral and Experimental Finance, 30, 100471.
  • Rabin, M., & Thaler R. H., (2001). Anomalies: Risk aversion. The Journal of Economic Perspectives, 15(1), 219–232.
  • Schlesinger, H., (2013). The Theory of insurance demand, in Dionne, G. eds., Handbook of Insurance, SpringerLink, ISBN: 9781461401551.
  • Sherden, W. A., (1984). An analysis of the determinants of the demand for automobile insurance. Journal of Risk and Insurance, 51(1), 49-62.
  • Shi, P., Zhang, W., & Valdez, E. A., (2012). Testing adverse selection with two‐dimensional information: evidence from the Singapore auto insurance market. Journal of Risk and Insurance, 79(4), 1077-1114.
  • Tennyson, S., (2011). Consumers’ insurance literacy: Evidence from survey data. Financial Services Review, 20(3), 165-179.
  • TURKSTAT. (2021). Road Motor Vehicles, December 2021. https://data.tuik.gov.tr/Bulten/Index?p=Road-Motor-Vehicles-December-2021-45703&dil=2 [Date Accessed: June 22, 2022].
  • Tversky, A. & Kahneman, D., (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
  • Tversky, A. & Kahneman, D., (1989). Rational choice and the framing of decisions. The Journal of Business, 59(4), 251–278.
  • Uddin, M. A., (2017). Microinsurance in India: Insurance literacy and demand. Business and Economic Horizons, 13(2), 182-191.
  • Weedige, S. S., Ouyang, H., Gao, Y., & Liu, Y., (2019). Decision making in personal insurance: Impact of insurance literacy. Sustainability, 11(23), 6795.
  • Zietz, E. N., (2003). An examination of the demand for life insurance. Risk Management and Insurance Review, 6(2), 159-191.
  • Zweifel, P. & Eisen, R., (2012). Insurance Economics. SpringerLink, ISBN: 9783642205484

THE INFLUENCE FACTORS OF CONSUMERS’ COMPREHENSIVE CAR INSURANCE DEMAND: EVIDENCE FROM TURKEY

Year 2022, Volume: 11 Issue: 4, 176 - 184, 31.12.2022

Abstract

Purpose- Car insurance stands out as the most important line in the individual insurance industry. Even though it is a legal obligation for drivers to have car liability insurance in many countries, there is a coverage gap in comprehensive insurance, especially in emerging countries such as Turkey. Although the comprehensive car insurance penetration rate has slightly increased in the last five years in Turkey, it still has limited coverage. The study investigates the effects of perceived insurance benefit and insurance literacy variables, in addition to socio-economic indicators, as the determinants of comprehensive car insurance demand in Turkey
Methodology- The survey method was used for data collection. The survey was prepared digitally and distributed to car owners in Turkey via a social media platform using a simple random method. The total number of usable responses obtained was 261. The binary logistic regression was applied to determine the effect of the socio-economic factors, perceived insurance benefit, and insurance literacy on the comprehensive car insurance demand.
Findings- The results showed a significant and strong relationship between comprehensive car insurance demand and having a traffic ticket, driving experience, driver’s age, and vehicle age indicators. The other important determinants of comprehensive car insurance demand with a relatively low weight are perceived insurance benefit and insurance literacy. There was no relationship between insurance demand and driving frequency or experiencing a traffic accident.
Conclusion- This study has several practical implications for the insurance industry in terms of marketing, product development and the underwriting process. Insurance companies should consider the factors affecting consumers’ insurance demand while designing products and services. Furthermore, they should act together with regulatory authorities to organize awareness campaigns and financial literacy courses to better explain the individual and social benefits of insurance products and services.

References

  • Awunyo-Vitor, D., (2012). Comprehensive motor insurance demand in Ghana: Evidence from Kumasi metropolis. Management, 2(4), 80-86.
  • Awel, Y. M., & Azomahou, T. T., (2015). Risk preference or financial literacy? Behavioural experiment on index insurance demand. MERIT Working Papers 2015-005, United Nations University.
  • Beck, T., & Webb, I., (2003). Economic, demographic, and institutional determinants of life insurance consumption across countries. The World Bank Economic Review, 17(1), 51-88.
  • Bryan, G. (2019). Ambiguity aversion decreases the impact of partial insurance: Evidence from African farmers. Journal of the European Economic Association, 17(5), 1428-1469.
  • Browne, M. J., & Hoyt, R. E., (2000). The demand for flood insurance: empirical evidence. Journal of Risk and Uncertainty, 20(3), 291-306.
  • Browne, M. J., Knoller, C., & Richter, A., (2015). Behavioral bias and the demand for bicycle and flood insurance. Journal of Risk and Uncertainty, 50(2), 141-160.
  • Browne, M. J., & Kim, K., (1993). An international analysis of life insurance demand. Journal of Risk and Insurance, 60(4), 616-634.
  • Cole, S., Giné, X., Tobacman, J., Topalova, P., Townsend, R., & Vickery, J., (2013). Barriers to household risk management: Evidence from India. American Economic Journal: Applied Economics, 5(1), 104-35.
  • Corcos, A., Montmarquette, C., & Pannequin, F., (2020). How the demand for insurance became behavioral. Journal of Economic Behavior & Organization, 180, 590-595.
  • Cronbach, L.J., (1958). Proposals leading to analytic treatment of social perception scores, in Tagiuri R. and Petrullo L. eds. Person Perception and Interpersonal Behavior. Stanford University Press, Stanford, ISBN: 9780758134486.
  • Dragos, S. L., (2014). Life and non-life insurance demand: the different effects of influence factors in emerging countries from Europe and Asia. Economic research-Ekonomska istraživanja, 27(1), 169-180.
  • Halek, M., & Eisenhauer, J. G., (2001). Demography of risk aversion. Journal of Risk and Insurance, 68(1), 1-24.
  • Hertwig, R., Barron, G., Weber, E. U., & Erev, I., (2004). Decisions from experience and the effect of rare events in risky choice. Psychological Science, 15(8), 534-539.
  • Hsu, Y. C., Chou, P. L., & Shiu, Y. M. (2016). An examination of the relationship between vehicle insurance purchase and the frequency of accidents. Asia Pacific Management Review, 21(4), 231-238.
  • Jaspersen, J. G., (2016). Hypothetical surveys and experimental studies of insurance demand: A review. Journal of Risk and Insurance, 83(1), 217-255.
  • Josef, A. K., Richter, D., Samanez-Larkin, G. R., Wagner, G. G., Hertwig, R., & Mata, R., (2016). Stability and change in risk-taking propensity across the adult life span. Journal of Personality and Social Psychology, 111(3), 430.
  • Jurkovicova, M., (2016). Behavioral aspects affecting the purchase of insurance different behavior of men and women. Economic Review, 45(2), 181-96.
  • Kahneman, D., & Tverskey, A., (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.
  • King, J. E., (2008). Binary logistic regression, in Osborne J.W. eds., Best Practices in Quantitative Methods. Sage Publications, California, ISBN: 9781412940658.
  • Kline, P., (1994). An Easy Guide to Factor Analysis. Routledge, UK, ISBN: 9780415094900.
  • Kunreuther, H. C., Pauly, M. V., & McMorrow, S., (2013). Insurance and Behavioral Economics: Improving Decisions in The Most Misunderstood Industry. Cambridge University Press, UK, ISBN: 978-0521608268.
  • Lewis-Beck, M., Bryman, A. E. & Liao, T.F., (2003). The Sage Encyclopedia of Social Science Research Methods. Sage Publications, California, ISBN: 9781412950589.
  • Lusardi, A., & Mitchell, O. S., (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5-44.
  • Insurance Association of Türkiye (TSB). (2021). Number of Insurance Policies. https://www.tsb.org.tr/en/stats [Date Accessed: June 22, 2022].
  • OECD. (2021). OECD Insurance Statistics 2021, OECD Publishing. https://doi.org/10.1787/2307843x Date Accessed: June 22, 2022].
  • Outreville, J. F., (2014). Risk aversion, risk behavior, and demand for insurance: A survey. Journal of Insurance Issues, 37(2), 158-186.
  • Pitthan, F., & De Witte, K., (2021). Puzzles of insurance demand and its biases: A survey on the role of behavioural biases and financial literacy on insurance demand. Journal of Behavioral and Experimental Finance, 30, 100471.
  • Rabin, M., & Thaler R. H., (2001). Anomalies: Risk aversion. The Journal of Economic Perspectives, 15(1), 219–232.
  • Schlesinger, H., (2013). The Theory of insurance demand, in Dionne, G. eds., Handbook of Insurance, SpringerLink, ISBN: 9781461401551.
  • Sherden, W. A., (1984). An analysis of the determinants of the demand for automobile insurance. Journal of Risk and Insurance, 51(1), 49-62.
  • Shi, P., Zhang, W., & Valdez, E. A., (2012). Testing adverse selection with two‐dimensional information: evidence from the Singapore auto insurance market. Journal of Risk and Insurance, 79(4), 1077-1114.
  • Tennyson, S., (2011). Consumers’ insurance literacy: Evidence from survey data. Financial Services Review, 20(3), 165-179.
  • TURKSTAT. (2021). Road Motor Vehicles, December 2021. https://data.tuik.gov.tr/Bulten/Index?p=Road-Motor-Vehicles-December-2021-45703&dil=2 [Date Accessed: June 22, 2022].
  • Tversky, A. & Kahneman, D., (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
  • Tversky, A. & Kahneman, D., (1989). Rational choice and the framing of decisions. The Journal of Business, 59(4), 251–278.
  • Uddin, M. A., (2017). Microinsurance in India: Insurance literacy and demand. Business and Economic Horizons, 13(2), 182-191.
  • Weedige, S. S., Ouyang, H., Gao, Y., & Liu, Y., (2019). Decision making in personal insurance: Impact of insurance literacy. Sustainability, 11(23), 6795.
  • Zietz, E. N., (2003). An examination of the demand for life insurance. Risk Management and Insurance Review, 6(2), 159-191.
  • Zweifel, P. & Eisen, R., (2012). Insurance Economics. SpringerLink, ISBN: 9783642205484

Details

Primary Language English
Subjects Economics, Finance, Business Administration
Journal Section Articles
Authors

Hasan MERAL 0000-0002-2079-0674

Yigit SENER This is me 0000-0002-5363-8492

Publication Date December 31, 2022
Published in Issue Year 2022 Volume: 11 Issue: 4

Cite

APA MERAL, H., & SENER, Y. (2022). THE INFLUENCE FACTORS OF CONSUMERS’ COMPREHENSIVE CAR INSURANCE DEMAND: EVIDENCE FROM TURKEY. Journal of Business Economics and Finance, 11(4), 176-184.

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