Abstract
Online self-service applications are becoming increasingly available across different consumer-facing industries. While online channels offer potential benefits including cost savings, efficiency and convenience, their usage remains limited among older adults, as well as in service domains where complex decision making may be required to carry out transactions. In this study, a total of 120 adults 50 years of age and older participated in a set of research groups to explore attitudes toward, experiences with, and expectations regarding online self-service applications for automobile insurance. Study participants’ responses to a questionnaire, a use case walkthrough task, and group discussions indicated that phone/calling was the dominant channel for interacting with their automobile insurance company. People were mixed on their acceptance of online channels for insurance inquiries and transactions. Many believed that while online channels would offer convenience and speed, there were concerns about their use including tasks being complicated and the possibilities for making mistakes with great consequences. Results also suggested that prior experiences with or exposure to existing online channels, as well as general trust in technology, had a positive impact on future likelihood of using online channels for insurance. This further confirms the link between past experiences and future adoption intentions that was demonstrated by prior research in different technology domains, and suggests that providing and building experience may be key to increasing adoption and engagement. Implications regarding the interplay between technology-enabled online tools and human support are also discussed.
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The authors gratefully acknowledge the support of The Hartford Financial Services Group, Inc. For this research.
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Lee, C., D’Ambrosio, L., Coughlin, J.F. (2023). Older Adults’ Perceptions and Use of Digital Engagement Channels: In the Case of Automobile Insurance Services. In: Gao, Q., Zhou, J. (eds) Human Aspects of IT for the Aged Population. HCII 2023. Lecture Notes in Computer Science, vol 14042. Springer, Cham. https://doi.org/10.1007/978-3-031-34866-2_6
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