Determinants for citizens' location data sharing with public institutions during a pandemic: the Italian case

Data on real-time individuals’ location may provide significant opportunities for managing emergency situations. For example, in the case of outbreaks, besides informing on proximity of people, hence supporting contact tracing activities, location data can be used to understand spatial heterogeneity in virus transmission. However, individuals’ low consent to share their data, proved by the low penetration rate of contact tracing apps in several countries during the COVID-19 pandemic, re-opened the scientific and practitioners’ discussion on factors and conditions triggering citizens to share their positioning data.

Following the APCO model (Smith et al. 2011), and based on Privacy Calculus and Reasoned Action Theories, the study investigates factors that bring citizens to share their location data with public institutions during outbreaks.

To this end, an explanatory survey was conducted in Italy during the second wave of COVID-19, collecting 245 questionnaire responses. Structural equations modeling was used to contemporary investigate the role of trust, perceived benefit, and perceived risk as determinants of the intention to share location data during outbreaks.

Results shows that citizen’s trust in public institutions, the perceived benefits, and the perceived risk are significant predictor of the intention to disclose personal tracking data with public institutions. Results indicate that the latter two factors impact individuals' willingness to share data more than trust, prompting public institutions to rethink how they launch and manage the adoption process for these technological applications.