Who is this research for? Supply chain leaders, last-mile delivery executives, omnichannel retailers, and operations professionals responsible for gig-worker engagement, delivery costs, and service levels.
Top Answer
Delivery platforms may not always need to pay substantially more to get drivers to accept tasks faster. New research suggests drivers consider not only compensation but also how efficient, predictable, and convenient a delivery task appears. The implication is that driver engagement is partly an operations-design problem. How orders are batched, when deliveries are offered, what customer interaction is required, and how task characteristics are presented may help platforms improve acceptance without relying exclusively on higher pay.
Executive Summary
Getting independent drivers to quickly accept delivery tasks is a critical challenge for retailers using crowdshipping to support last-mile delivery. The usual solution is straightforward: offer drivers more money. But new research from Dr. Brian Fugate (Department of Supply Chain Management, Sam M. Walton College of Business), Nicolò Masorgo (Miami University, Walton PhD alumnus), David D. Dobrzykowski (Auburn University, formerly Walton College), and Christopher S. Tang (UCLA) suggests compensation is only part of the equation.
The researchers examined approximately two million completed crowdshipping tasks from a Fortune 100 U.S. grocery retailer. Instead of looking only at whether drivers accepted tasks, the researchers measured acceptance response time, or how long it took a driver to accept an available delivery task. They then examined how compensation interacted with three operational characteristics: delivery density, whether deliveries required customer interaction, and time of day.
The results indicate that more money generally encourages faster acceptance, but its impact diminishes as compensation increases. More importantly, the characteristics of the task change how effectively that money works. Drivers responded more favorably to denser delivery tasks, where more stops could be completed across fewer miles. Unattended deliveries, which reduce uncertainty associated with customer interaction, also made smaller compensation increases more effective at lower remuneration levels.
For delivery platforms, that suggests a shift in thinking. Rather than treating compensation as the default solution to driver shortages, managers can consider how route density, order batching, delivery type, scheduling, and task presentation affect the attractiveness of an offer.
Expert Insights: What should leaders know about designing delivery work?
When should platforms improve the delivery task instead of increasing driver pay?
Dr. Brian Fugate notes: "Pay is the costliest lever you have, so use it last. Ask three questions first. Can I batch this order with others nearby? Can the driver leave it at the door? Does it have to go out tonight? Evening tasks in our study sat longer and needed bigger raises to get picked up. For those orders, I'd test a next-morning slot or an evening delivery fee before a bigger driver bonus."
→ Takeaway: Spend extra pay on low-paying tasks, where each dollar buys the most speed. When a task already pays well or falls in the evening, fix the task first with denser routes or a next-morning slot.
How could AI help platforms match driver incentives to the characteristics of individual delivery tasks?
Dr. Brian Fugate explains: "I'd start with a 30-day pilot in one metro. Let an AI agent watch every open task and predict how long it will sit. When a task is about to miss its window, the agent picks the cheapest fix. It might add a nearby order, hold the task for morning, or raise the offer a few dollars. Then show drivers the stops, miles and drop type up front. Drivers weigh effort and certainty, so make both easy to see."
→ Takeaway: AI can price and shape each task. It can predict how fast an offer will be taken, then pick the cheapest fix, such as a denser batch, a later slot, or a small pay bump.
What lessons from crowdshipping could business leaders apply to other flexible or on-demand workforces?
Dr. Brian Fugate notes: "Every flexible worker runs the same math. How much work is this? How sure am I about what I'm walking into? When do I have to do it? Drivers in our study made that call on about 2 million tasks. Nurses picking up shifts and servers taking extra hours ask the same questions. Design the work to score well on all three, and the pay you already offer goes further."
→ Takeaway: Gig and shift workers judge a job by the effort, the risk and the timing, along with the pay. Design the work around those three and show them up front, and the pay you offer goes further.
Link to the Original Research
Published in Journal of Operations Management (2026)
Frequently Asked Questions
What is crowdshipping?
Crowdshipping is a last-mile delivery model in which independent drivers use a platform to select and complete delivery tasks. Unlike traditional employees working assigned routes or schedules, crowdshipping drivers can often choose among available opportunities. That flexibility creates an operational challenge for retailers: a delivery task must be attractive enough for a driver to accept it in time to meet customer expectations. This research examines engagement by measuring how long drivers take to accept tasks, providing a more detailed view than simply measuring whether a delivery is eventually accepted.
Does paying gig delivery drivers more make them accept orders faster?
The research indicates that higher compensation is associated with faster task acceptance, but the benefit of additional money diminishes as compensation rises. An extra dollar can therefore have a greater impact when a task offers relatively low compensation than when the task already pays substantially more. The authors estimate that a $4 increase around a $10 remuneration level reduces acceptance response time by about 10%, compared with about 5% around $50. That suggests platforms should consider where additional compensation will have the greatest impact rather than applying increases uniformly.
How does route density affect gig-driver engagement?
Denser delivery tasks appear more attractive to drivers because they allow more stops to be completed over fewer miles, improving the efficiency of the driver's effort. The study finds that delivery density strengthens the relationship between compensation and faster task acceptance. For managers, this suggests order batching can serve as an operational lever alongside compensation. Rather than automatically increasing pay for every difficult-to-fill task, platforms may be able to make some offers more appealing by creating efficient, higher-density delivery routes.
Do drivers prefer unattended deliveries?
The findings are more nuanced than a simple yes. At lower compensation levels, tasks containing more unattended deliveries make smaller increases in compensation more effective. Unattended deliveries can reduce uncertainty because drivers do not have to wait for or interact directly with customers. However, the researchers also find that higher-paying tasks with more attended deliveries can be attractive, potentially because customer interaction creates opportunities for additional tips or better ratings. Platforms should therefore consider delivery type and compensation together rather than assuming one format is always preferred.
