Understanding usability and user acceptance of usage-based insurance from users' view

Quintero J, Benenson Z (2019)


Publication Type: Conference contribution

Publication year: 2019

Publisher: Association for Computing Machinery

Pages Range: 52-57

Conference Proceedings Title: ACM International Conference Proceeding Series

Event location: Jakarta ID

ISBN: 9781450372480

DOI: 10.1145/3366750.3366759

Abstract

Intelligent Transportation Systems (ITS) cover a variety of services related to topics such as traffic control and safe driving, among others. In the context of car insurance, a recent application for ITS is known as Usage-Based Insurance (UBI). UBI refers to car insurance policies that enable insurance companies to collect individual driving data using a telematics device. Collected data is analysed and used to offer individual discounts based on driving behaviour and to provide feedback on driving performance. Although there are plenty of advertising materials about the benefits of UBI, the user acceptance and the usability of UBI systems have not received research attention so far. To this end, we conduct two user studies: semi-structured interviews with UBI users and a qualitative analysis of 186 customer inquiries from a web forum of a German insurance company. We find that under certain circumstances, UBI provokes dangerous driving behaviour. These situations could be mitigated by making UBI transparent and the feedback customisable by drivers. Moreover, the country driving conditions, the policy conditions, and the perceived driving style influence UBI acceptance.

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How to cite

APA:

Quintero, J., & Benenson, Z. (2019). Understanding usability and user acceptance of usage-based insurance from users' view. In ACM International Conference Proceeding Series (pp. 52-57). Jakarta, ID: Association for Computing Machinery.

MLA:

Quintero, Juan, and Zinaida Benenson. "Understanding usability and user acceptance of usage-based insurance from users' view." Proceedings of the 2nd International Conference on Machine Learning and Machine Intelligence, MLMI 2019, Jakarta Association for Computing Machinery, 2019. 52-57.

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