Determinants of user acceptance of digital insurance platform service on InsurTech: an empirical study in South Korea

ABSTRACT

In recent days, InsurTech services and users are growing rapidly worldwide. InsurTech, a combination of ‘insurance’ and ‘technology’, as an area of Fintech has become an essential innovation strategy of insurance companies. Even if InsurTech services and users are prevalent, there is a lack of empirical research on determinants of user acceptance of InsurTech. The objective of this study is to explore factors determining user acceptance of digital insurance platform services most popular within InsurTech in South Korea. The research model was derived from mainly three theories: the unified theory of acceptance and use of technology (UTAUT), information systems success model (ISSM) and innovation diffusion theory (IDT) with service characteristic factors (system quality, information quality, and service quality) and user characteristic factors (personal innovativeness, self-efficacy, and perceived risk). 249 survey responses from South Korea were analysed. According to the results, information quality exhibited an effect on performance expectancy and effort expectancy whereas service quality was shown to affect only effort expectancy. Furthermore, personal innovativeness affected performance expectancy, effort expectancy, and social influence, self-efficacy exhibited an effect on performance expectancy, and perceived risk affected performance expectancy and effort expectancy.

KEYWORDS:

• InsurTech
• Fintech
• digital insurance
• UTAUT
• user acceptance intention

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Fintech, a combination of ‘finance’ and ‘technology,’ refers to a new type of financial service based on the combination of finance and IT.

2 Regtech, a combination of ‘regulation’ and ‘technology,’ refers to services that help financial institutions effectively respond to a variety of regulations through technologies such as AI and big data analysis.

3 CFI: Comparative Fit Index.

4 TLI: Tucker Lewis Index

5 GFI: Goodness of Fit Index.

6 RMSEA: Root Square Error of Approximation.