Factors Affecting Potential Consumers to Variable Life Insurance: Based on Theory of Planned Behavior
- DOI
- 10.2991/assehr.k.200515.076How to use a DOI?
- Keywords
- variable life insurance, based on theory of planned behavior
- Abstract
Houwan is one of the countries with the highest aging index in the world. Therefore, Taiwanese people begin to plan and invest for the future. And low cost, high guarantee and high interest rate become the high quality insurance in the eyes of customers, which has life insurance. Commodities that are guaranteed and funded are becoming popular with the public. Variable life insurance is a dual function policy with both “life insurance guarantee” and ”investment option”. The main focus of this study is the theory of planned behavior. Data is collected by questionnaires. Different demographic variables are explored for potential customers. Descriptive analysis is conducted using SPSS statistical software to explore the demographic variables on purchasing behavior. The factor analysis is then used to extract the data influencing the consumer purchasing behaviors. Multiple regression analysis is also used to explore the various factors that influence the findings. Finally, based on the empirical results, this study will put forward academic implications, purchasing behavior implications and follow-up suggestions.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Song Chen AU - Linda Lin-Chin Lin AU - Cheng Te Ma PY - 2020 DA - 2020/05/20 TI - Factors Affecting Potential Consumers to Variable Life Insurance: Based on Theory of Planned Behavior BT - Proceedings of the Tarumanagara International Conference on the Applications of Social Sciences and Humanities (TICASH 2019) PB - Atlantis Press SP - 439 EP - 446 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.200515.076 DO - 10.2991/assehr.k.200515.076 ID - Chen2020 ER -