Shared mobility is considered a more sustainable alternative to private modes. Nonetheless, its sudden and sometimes “out of control” emergence poses issues that need to be addressed. Lack of regulations and public space mismanagement cause sidewalks and city roads to be overcrowded with shared vehicles (especially in the case of micromobility). This causes nuisance and safety concerns and hinders the societal benefits shared mobility may provide. Shared mobility hubs have the potential to address these issues. The research was carried out within the context of the SmartHubs project, an EIT Urban Mobility project initiated in 2021 by a diverse consortium of 7 cities, companies, and universities to develop and validate effective and economically viable mobility hub solutions. This degree project aims to improve the Decision-Support-Tool (DST) developed by SmartHubs to identify locations of shared-mobility hubs having high potential in driving sustainable travel usage. To achieve that, the thesis proposes a methodology for determining smart hub locations and their corresponding utilities based on the combination of GIS cluster analysis of free-floating shared mobility parking patterns and a stated-preference study. The potential hub locations were determined from the cluster analysis of free-floating trip characteristics. Using the stated preference survey data, the thesis develops a model to estimate the probability of parking at the hub as a function of explanatory variables, including walking distance, reward policies and the parking situation. The model testing results showed that the proposed methodology can well predict the hub (usage) demand and improve the current DST originally developed in the SmartHubs project.