Navigating Efficiency and Uncertainty: Risks of Relying on an At-Will Workforce in Urban Meal Delivery

Abstract

Increasing popularity in gig employment has enabled the use of an at-will workforce of self-contracted couriers to participate in many service industries serving urban areas. This gig workforce has come to play a particularly important role in the growing meal delivery service industry. Hiring at-will couriers for delivery job fulfillment can decrease the costs of satisfying nonstationary demand. However, at-will workers can show up for work at their will and without notice. Thus, this puts the service performance of the delivery company that relies on effective workforce management to ensure timely delivery of orders at risk. This work investigates the tradeoffs between using such an at-will workforce of couriers in place of a fixed fleet of drivers in servicing a meal delivery environment. A stochastic DES with tabu search heuristic and embedded ejection chain approach for optimal delivery job bundling, routing, and assignment was developed and run within a rolling horizon framework to replicate the dynamics of the meal delivery setting. Condition Value at Risk (CVaR) is adopted to measure the risk of late delivery due to uncertainty in workforce availability. Results from a numerical case study with 25 restaurants and 613 orders arriving over a 14-h period show tradeoffs from using at-will couriers in place of a comparable fixed fleet of drivers in terms of delivery resource utilization, efficiency risk of failing to satisfying orders and risk of significantly late delivery. Results indicate that using at-will couriers for meal delivery can enable more efficient use of delivery resources, but at the cost of a higher risk of late delivery, and sometimes intolerably late delivery, as compared to using a fixed fleet of drivers to fulfill orders.

Keywords

• order assignment
• gig workers
• crowdsourced delivery
• last-mile delivery
• ad hoc drivers
• flexible couriers