There Is More to Crowdshipping Than Money: Understanding How Operational Characteristics Influence Driver Behaviors

Abstract

The increasing cost of last-mile delivery has motivated omnichannel grocery retailers to implement crowdshipping. Crowdshipping is a platform-based last-mile delivery model that relies on engaging drivers who are independent contractors to quickly accept delivery tasks. While studies often focus on the impact of monetary incentives, we draw on perspectives from the service operations literature to explore the moderating effect of three theoretical mechanisms (effort efficiency, uncertainty, and utility), on the curvilinear relationship between monetary incentives and driver engagement. Specifically, we test how delivery density, delivery type (attended vs. unattended), and time of the day interact with monetary incentives to influence driver's task acceptance response time. Econometric analyses of a dataset comprising about two million observations from a US Fortune 100 grocery retailer's crowdshipping platform confirm the “diminishing negative” effect of remuneration on task acceptance time. More importantly, we reveal that task operational characteristics affect how monetary incentives influence task acceptance time. While task density and unattended deliveries amplify the curvilinear relationship, evening tasks flatten it and are accepted slower than those scheduled in the daytime. Our findings suggest that drivers evaluate tasks based on perceived effort, uncertainty, and utility, offering valuable insights for platforms and future research.