Cloud-Kitchens: Value Creation Through Co-Location

• Published in: Production and operations management Vol. 33; no. 2; pp. 512 - 529
• Main Authors: Rout, Arun, Dawande, Milind, Janakiraman, Ganesh
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.02.2024
• Subjects: Disruptive business models; food-delivery platforms; cloud kitchens
• ISSN: 1059-1478; 1937-5956
• DOI: 10.1177/10591478231224950

“Cloud Kitchens” are delivery-only facilities that house multiple restaurants. Food-delivery platforms operate such kitchens to exploit two advantages: (a) Location advantage, arising due to a cloud-kitchen’s central location—this enables lower delivery times to customers. (b) Consolidation advantage, which accrues when multiple restaurants choose to co-locate at the cloud kitchen—this enables the platform to use a common pool of delivery drivers, thereby reducing costs. However, a cloud-kitchen’s eventual impacts on both the restaurants and the platform are intricately connected through their respective decisions—namely, the restaurants’ location decisions and the platform’s delivery capacity and delivery time. We examine conditions under which a cloud kitchen simultaneously benefits the primary stakeholders: delivery platform, restaurants, and customers. Our game-theoretic analysis considers two restaurants and a delivery platform. The restaurants simultaneously decide whether to stay at their initial (extreme) locations or relocate to a centrally located cloud kitchen. The platform decides the driver headcount and the delivery times for customers. In line with industry trends, we show that as population density increases beyond a threshold, the restaurants co-locating at the cloud kitchen is first a Pareto-dominant equilibrium and then the unique equilibrium. The platform and customers also prefer this equilibrium, leading to a win-win-win for the stakeholders. A cloud-kitchen’s benefit to the platform further increases as the drivers’ operational environment becomes more constrained, i.e. drivers’ carry-limit and speed decrease, and driver cost increases.