Abstract

To examine the relationship between privacy concerns and consumer choices, we develop a finite time-horizon dynamic structural model to study consumers’ adoption and use of Usage-Based Insurance (UBI). UBI enables auto insurers to collect individual-level driving data, provide feedback on driving performance, and offer individually targeted prices. Using detailed information on insurance premiums, adoption, retention decisions, and driving behavior (as measured by sensor data), we estimate the costs of using UBI including the privacy cost. During our study, the company (along with most competitors) announced an enhancement to privacy protection (limiting usage of location-based data); subsequently, there was a widely reported external data breach at a major, unrelated retailer. Our main empirical results indicate that (1) both initial and ongoing costs play crucial roles in customers’ adoption and dropout decisions; (2) the enhancement in privacy policy reduces the adoption cost and is associated with higher UBI adoption; and (3) despite being an external event, the major data breach is associated with a decrease in retention rates among customers currently being monitored. Sensitivity to these events varies by gender. These results are consistent with the view that consumers trade-off privacy costs for economic benefits.

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