"Uber" Your Cooking: The Sharing-Economy Operations of a Ghost-Kitchen Platform

Abstract

"Ghost kitchens" are emerging as an innovative alternative to traditional food-delivery restaurants. A ghost kitchen has no storefront or dining area. It only accepts online orders from food delivery platforms via mobile apps. Due to its limited capacity, each ghost kitchen offers only a very limited number of dishes. We study a ghost kitchen platform that works as an intermediary between home chefs and customers. It allows customers to select dishes from multiple kitchens in a single order; we call it Multi-Dash. Despite a captivating sharing-economy future, in which ghost kitchens unlock the great potential of delicious homemade food for customers and earnings for home chefs, the operational challenges are immense: The multi-dash setting leads to a longer wait (which affects the customer adoption rate), and a higher delivery cost. We address these challenges by building an analytical model that integrates these factors. To characterize the on-demand customer waiting time, we propose and solve a generalized fork-join queuing problem. Moreover, we analyze the delivery cost of an order-pooling strategy designed to enhance operational efficiency. Our findings demonstrate that ghost kitchen platforms can be more profitable than traditional food delivery platforms because of their multi-dash capability, reduced fixed costs, increased productivity, and chef specialization. On the other hand, the optimal service radius of ghost kitchens has to be smaller than that of traditional restaurants because of the additional delivery costs of multi-dash. Our findings may shed light on how to scale up ghost kitchen platforms toward "uberizing" urban cooking services.

Keywords: ghost kitchens, sharing-economy, fork-join queue, on-demand service, vehicle routing