Hyper-Personalization in Motor Insurance: Understanding Telematics Insurance Adoption Using the Extended Technology Acceptance Model - Joshi, Rohit; Mishra, Sunil; Pardeshi, Anupama; Bhatia, Manpreet Kaur (Indian Journal of Marketing, 2024)
Purpose : The analysis of driving behavior and vehicle dynamics using telematics technology paved the way for current insurance underwriting and disruptions in automobile insurance. This study aimed to understand the behavioral intentions of users toward adopting telematics-based insurance products. Design/Methodology/Approach : Relevant constructs from extant literature were used to extend the technology acceptance model (TAM) to improve its explanatory power and identify meaningful linkages among the variables. A cross-sectional design with a quantitative survey examined how individuals perceived insurance telematics technology. Findings : Perceived enjoyment had the greatest impact, while perceived trust had the least impact on behavioral intentions. Perceived privacy risk lowered intentions to use telematics insurance. The extended TAM model proved valid, explaining 59% of the variance in behavioral intentions. Additionally, two-thirds of the respondents were open to adjusting their driving habits for safer driving if it meant lowering insurance premiums. Practical Implications : Telematics insurers and marketers were advised to prioritize ensuring a smooth transition for users to attain scalability and profitability. Marketers should emphasize the enjoyable aspects of telematics insurance while also addressing privacy concerns. Additionally, aligning users’ discount expectations with actual offerings was suggested to be crucial to bridge gaps. Originality/Value : This research provided valuable insights into a recent advancement in motor insurance in India, i.e., telematics-based insurance. As far as we know, it is among the pioneering studies conducted on this subject within the Indian subcontinent.