Diverse aspects of our everyday lives increasingly feature sensor-based technologies. Despite the importance of understanding how business and consumers exploit and adopt these technologies, the information systems (IS) community has thus far devoted relatively little attention to the topic. Accordingly, in this paper, we foster an exploration of the issue among IS scholars by focusing on the emergent use of sensor-based technologies in the automotive insurance industry. Insurance providers have increasingly begun to turn to such technologies to gain competitive advantage around risk assessment and behavior-based pricing. To investigate this phenomenon, we consider the experiences of two organizations operating distinct national contexts: Progressive Insurance (US) and Generali (Italy). These two insurance providers have been first movers in adopting sensor-based technologies for risk assessment and policy pricing. First, we highlight the key similarities and differences between the cases with regard to the technologies adopted, business models pursued, and anticipated benefits and pitfalls for the companies and their consumers. Second, in a more holistic way, we discuss the implications and unintended consequences of sensor-based technologies in the automotive insurance industry. We formulate several research questions that provide opportunities and encourage more research in this emerging area of study.
Marabelli, Marco; Hansen, Sean; Newell, Sue; and Frigerio, Chiara
"The Light and Dark Side of the Black Box: Sensor-based Technology in the Automotive Industry,"
Communications of the Association for Information Systems: Vol. 40
, Article 16.
Available at: https://aisel.aisnet.org/cais/vol40/iss1/16