Flowers and bees: spatial network effects in the adoption of a sharing-economy platform

This article empirically analyzes the spatiotemporal diffusion of a car-sharing platform that connects consumers with individual car owners. The authors develop a model of adoption by both consumers and providers that accommodates network effects across locations, as consumers travel to pick up cars, and information asymmetry, as only the providers' locations are shown on a map. They apply it to data at the earliest stage of the platform and find that proximity and consumer mobility play a significant role in the spatial network effects of existing providers on consumers across locations. Consequently, the impact of additional supply at a destination on consumer adoptions at an origin varies by origin–destination pair and is asymmetric, as certain destinations draw more visitors than others and given differences in local characteristics. In contrast, existing consumers have a limited impact on provider adoptions. Through seeding experiments, the authors investigate how the geographic distribution of initial participants impacts the platform diffusion and find that targeting the supply side in big cities leads to the highest platform growth. They also use their parameter estimates to measure the long-term impact of a local promotional campaign and show that it is mostly local despite spatial network effects.