S Rajesh, Dr. Kavitha Shanmugam, Dr. Ilankadhir M


Purpose: Technology-driven insurance companies use disruptive technologies to innovate, improve, and automate their products and services. With the help of connected devices, especially wearable, health insurance companies can access the customers’ risk profile, customize suitable products, and charge premiums based on the physical activities of the customer tracked with the help of smartwatches. Customers consider several factors before using a Smartwatch. The current research is undertaken to determine the factors that determine the usage of the Smartwatch. Theoretical framework: This study has employed the Unified Theory of Acceptance and Use of Technology (UTAUT) with Trust as an extended variable to determine the influence of variables on behavioral intention while also discussing the explanatory power (R square) and effect size (f square) of the model. UTAUT also tests the moderating effect of Gender on behavioral intention. Design/methodology/approach: A Survey was conducted among the general population over eighteen years of age and using the smartwatch. The sample size was 131 and the responses were collected through a structured questionnaire. All the items of the constructs were measured on a five-point Likert scale and responses were quantified. Variance-based Structural Equation Modelling (SEM) using Smart PLS (version 4.0) is used to test and validate the model. Findings: From the results, it is inferred that performance expectancy and Trust significantly affect behavioral intention, while effort expectancy, facilitating conditions, and social influence don't. Research, Practical & Social implications: The study will create awareness in society about the importance of staying healthy to prevent or minimize the impact of non-communicable diseases by tracking physical activities using a Smartwatch. Insurance companies can customize fitness-based products, provide a discount on premiums, and pass on other benefits to customers. Insurance companies can leverage this technology to create health awareness among the general public improve profit and reduce claims. Originality/value: The data was analyzed using Smart PLS (version 4.0) software by measuring the measurement and structural models. From the path coefficients, it is inferred that performance expectancy and Trust significantly affect behavioral intention. R square value indicates the proposed model has a medium explanatory power in explaining the behavioral intention. f square value indicates that performance expectancy and trust have a moderate effect on the behavioral intention of using the smartwatch.

Keyword : Unified Theory of Acceptance and Use of Technology (UTAUT); Smartwatch; Behavioral Intention; Trust; Non Communicable diseases (NCDs);

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