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 |
CORE Recommender
SCOPUSTM
Citations
5
checked on Mar 14, 2024
WEB OF SCIENCETM
Citations
2
Last Week
0
0
Last month
checked on Oct 29, 2023
Page view(s)
179
Last Week
2
2
Last month
9
9
checked on Dec 21, 2024
Google ScholarTM
Check
Altmetric
This item is licensed under a Creative Commons License