Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29897
Title: Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector
Authors: Alfiero, Simona 
Battisti, Enrico 
Hadjielias, Elias 
Major Field of Science: Social Sciences
Field Category: Economics and Business
Keywords: Black box technology;Disruptive technologies;Financial impacts;Insurance sector;Prediction of purchase behavior;Psychological drivers
Issue Date: 1-Oct-2022
Source: Technological Forecasting and Social Change, 2022, vol. 183
Volume: 183
Abstract: Disruptive technologies are changing the car insurance sector, with behavioral and adaptive impacts for individuals as well as organizations. An innovative factor in this industry is connected to telematics and concerns the installation of a small device called a ‘black box’, which is becoming more and more widespread, with consequent financial impacts on the insurance policy market. However, the psychological drivers that underpin consumers' intentions to purchase black box auto insurance are scarcely researched. To fill this gap, we used a mixed-methods sequential exploratory design to analyze a sample of 757 consumers. Our results, obtained through PLS-SEM, highlight that attitude, awareness, subjective norms, risk perception, and trust have a significant positive influence on consumers' intentions to purchase black box technology auto insurance, while the effect of perceived behavioral control is not supported. Furthermore, the blindfolding analysis underscores the predictive relevance of the model. Our results have important implications for auto insurance companies interested to better understand consumers' needs and motives in relation to the purchase of black box insurance.
URI: https://hdl.handle.net/20.500.14279/29897
ISSN: 00401625
DOI: 10.1016/j.techfore.2022.121896
Rights: © Elsevier Inc.
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation : University of Turin 
Cyprus University of Technology 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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