Partial Information in Fork-Join Operations: Evidence from Multi-Brand Cloud Kitchens

Abstract

Multi-brand cloud kitchens offer variety by co-locating multiple restaurant brands, allowing customers to order from multiple brands in a single order. To simplify ordering, platforms also offer pre-designed dish combinations, created either as platform bundles or by brands listing one brand's dish in another brand's menu. Our dataset of 6.24 million orders from a multi-brand operator in Asia (68 kitchens) suggests a significant operational penalty for multi-brand orders, as they are 48% more likely to be late than single-brand orders. Our field visits and interviews suggest that order fulfillment in a multi-brand cloud kitchen is a fork-join queuing process with information asymmetries. Estimates from a reduced-form regression indicate that orders requiring central synchronization across brands, but with information asymmetry for the chefs, have 63% higher odds of being late compared to single-brand orders. While congestion at cooking stations amplifies coordination costs for all orders, these orders are disproportionately affected. Furthermore, given that the platform hosts both its own and external brands in its kitchens, we find that external brands have roughly half the odds of being late due to multiple contributing factors: simpler menus, better process, and lower congestion. The latter is potentially due to the platform steering demand toward in-house brands by providing them with greater visibility. Our counterfactual analysis reveals that information sharing and prioritization are complements, as prioritizing multi-brand orders enhances performance only when chefs have complete information. Under partial information, FIFO may yield lower delays and better quality outcomes.