Navigating the Challenges of Mobile Big Data: The Case of Michigan's Super-Regional Shopping Centres

The increase of spatial big data has created unprecedented opportunities for business decisionmakers to leverage data analytics to gain a more intimate level of knowledge of their consumers and leverage that knowledge to advance their market position. Mobile big data is utilized to evaluate how super-regional shopping centres faired during the COVID-19 pandemic and the subsequent recovery period. Metrics such as dwell time, visitor count, and visitation count were derived from the data source and subsequently analyzed to forecast traffic in a post-pandemic scenario. The results indicate that shifts in consumer behaviour occurred, given that shopping centre visitations decreased during the recovery period after the mandated lockdowns. The study highlights both the technical and management limitations of location-enabled mobile data in estimating forecast models.