Stall Economy: The Value of Mobility in Retail on Wheels

Urban open space emerges as a new territory to embrace retail innovations. Selling products in public spaces with wheeled stalls can potentially become ubiquitous in our future cities. Transition into such a “stall economy” paradigm is being spurred by the rapidly advancing self-driving technologies. Motivated by this transformation, this paper provides models, theory, and insights of spatial queueing systems, in which one server moves around to meet mobile customers/machines and in which the “last 100 meters” are expensive. Specifically, we study two service modes: (i) on-demand, first come, first served and (ii) spatially and temporally pooling customer demands. In each mode, we derive the dependence of customer waiting and stall repositioning on two key decisions: the service zone size and the walking distance imposed on customers to meet a stall. In particular, for the on-demand mode, we propose and solve a “rendezvous problem” to analytically characterize the spatial distribution of the stall-customer meeting locations. We also propose a stylized joint truck-stall routing model to capture the inventory replenishment operations. Our main finding is that the stall economy potentially profits more than stationary retail, not only because of the mobility of stalls for providing proximity to customers, but also because of its operational flexibilities that allow for avoiding the “last 100 meters” and pooling demands. In a broader sense, this work looks toward an expanded scope of future retail empowered by self-driving technologies.

Funding: W. Qi acknowledges the support from the National Natural Science Foundation of China [Grants 72188101, 72272014] and the Institute for Data Valorization (IVADO) [Grant PRF-2019-1761010386].

Supplemental Material: The computer code and data that support the findings of this study and the online appendix are available within this article’s supplemental material at https://doi.org/10.1287/opre.2022.2404.