Recent advances in information technologies have increased our participation in “sharing economies,” where applications that allow networked, real-time data exchange facilitate the sharing of living spaces, equipment, or vehicles with others. However, the impact of large-scale sharing on sustainability is not clear, and a framework to assess its benefits quantitatively is missing. For this purpose, we propose the method of shareability networks, which translates spatio-temporal sharing problems into a graph-theoretic framework that provides efficient solutions. Applying this method to a dataset of 150 million taxi trips in New York City, our simulations reveal the vast potential of a new taxi system in which trips are routinely shareable while keeping passenger discomfort low in terms of prolonged travel time.