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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 recent global pandemic, but has been scarcely studied. This paper provides models, algorithms, and managerial insights to understand how to deploy and operate wheeled stalls in cities to scale up the stall economy. The spatial-queueing models characterize the stall operations of serving customers. The joint truck-stall routing model analytically captures the inventory replenishment operations. The personalized demand learning model effectively estimates customer demand while respecting the increasingly stringent privacy regulations. Combining these results leads to the optimal scheme of citywide stall deployment, which is then calibrated in a realistic setting with real data. The major finding is that the stall economy has potential for tapping large economic opportunities when the customer demand is low or moderate. The stall economy is able to provide high-quality service (in terms of the proximity to customers and the wait time) without incurring significant cost, thanks to the stall mobility, the operational flexibility, and the deployment adaptability. On the other hand, these advantages will diminish as the customer demand scales up. In addition, enhancing service quality by shortening the wait time, shrinking the customer walk distance and prolonging the shopping time poses different operational challenges, but can be accommodated by flexible stall deployment and operations. In a broader sense, this work demonstrates an expanded scope of retail operations reshaped by the pandemic and big data.


Wei Qi (祁炜) is an assistant professor in Operations Management at the Desautels Faculty of Management at McGill University. He is also a faculty advisor of the China’s Energy Group at the Lawrence Berkeley National Laboratory. His work has contributed to smart city operations concerning urban energy, mobility and retail logistics.  He is leading multiple internationally funded research projects, such as Fonds Québécois de la Recherche sur la Société et la Culture (FRQSC) - National Science Foundation of China (NSFC) Research Program on Smart Cities and Big Data. His research has been published in Operations Research, Manufacturing & Service Operations Management, and Production and Operations Management. His cross-disciplinary research has also appeared in the first-tier systems engineering journals such as IEEE Transactions on Power Systems and IEEE Transactions on Smart Gird. Wei earned a Ph.D. from UC Berkeley, an M.S. from UCLA and a B.E. from Zhejiang University, China.