Decoding the Drivers of Life Insurance Policy Preferences: A Multinomial Logistic Regression Analysis

Purpose: This study investigates the socio-demographic, economic, and behavioral determinants of life insurance policy preferences in Nepal. By employing a multinomial logistic regression (MLR) framework, it examines how these factors differentially influence choices among endowment, term, and whole life insurance. Design/methodology/approach: Using primary data from 368 policyholders in Kapilvastu district, Nepal, the study estimates an MLR model grounded in expected utility theory (EUT) and consumer choice behavior. Findings: Age, education, income, and policy duration emerge as pivotal drivers. Endowment policies are preferred by lower-income, less-educated respondents, while term insurance appeals to younger buyers with fewer dependents. High-income individuals favor whole life insurance, reflecting long-term financial planning. Conclusion: The research findings indicated that the elements that influence people’s decisions to purchase an endowment policy rather than whole life insurance. Implications: Insurers should segment markets by socioeconomic profiles and tailor policies to duration-sensitive buyers. Policymakers must enhance financial literacy to bridge demand gaps. Originality/value: This is the first study to empirically validate policy choice determinants in Nepal’s understudied market, offering novel insights into behavioral heterogeneity in emerging economies.