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Faculty & Research


Does Real-time Feedback Make You Try Less Hard? A Study of Automotive Telematics (Revision 1 )

Working Paper
Problem definition: Mobile and internet-of-things (IoT) devices increasingly enable tracking of user behavior and they often provide real-time feedback to the consumers in an effort to improve their conduct. Growing adoption of such technologies leads to an important question, “Does real-time feedback provided to users improve their behavior?”The authors study real-time feedback in the context of automotive telematics that has been recognized as the most disruptive technology in the automotive insurance industry. Academic/Practical relevance: While telematics devices are already providing complex real-time feedback to drivers, the implications of such feedback on user behavior are still poorly understood. Given that effect of feedback is sometimes ambiguous and has thriving adoption in practice, it is important to study real-time feedback and identify the effect it has on human behavior, especially in such important applications as automotive. This understanding is important given that other attempts to make driving safer have led to unintended consequences in the past. Methodology: Using proprietary data on driving behavior, as measured by several parameters such as harsh braking, over speeding, and steep acceleration the authors investigate the impact of real-time feedback on driving behavior using econometric methods. To estimate the effect, they use matching methods and instrumental variable regression. Results: Contrary to much of the existing feedback literature, the authors find that, on average, the driving performance of users post-detailed feedback is 13.3% worse than the performance of users who do not review their detailed feedback. This impairment in performance translates into a one-year reduction in inter-accident time. The results suggest this deterioration is associated with increased sharp accelerations and over speeding. Drivers also demonstrate higher speed dispersion within a trip after feedback that results in 1.65% increased probability of an accident. Further, the authors demonstrate the critical role that insurance incentive thresholds play in the effect of real-time feedback. Managerial implications: The authors' results provide a key message to the firms employing real-time feedback that such technology can have unintended consequences. Further, they provide recommendations related to incentive thresholds and types of feedback that should be considered in designing real-time feedback applications to improve human behavior.