Reducing Traffic Incidents in Meal Delivery: Penalize the Platform or its Independent Drivers?
48 Pages Posted: 29 Sep 2022 Last revised: 15 Jun 2023
Date Written: September 28, 2022
Problem definition: On-demand meal-delivery platforms compete on delivery price and delivery time. Pressures associated with this type of competition have resulted in meal-delivery-related traffic violations and accidents. To curb reckless driving, some governments have imposed harsher traffic incident penalties on meal-delivery drivers. Despite these attempts, the number of meal-delivery-related traffic violations and accidents has not abated. At the same time, meal-delivery platforms often shirk their responsibilities for these incidents especially when their drivers are independent contractors. To improve public safety, there is an ongoing debate about whether the government should penalize platforms for delivery-related traffic incidents. This backdrop motivates us to examine the following research questions: How should an earnings-maximizing driver decide on their participation and delivery speed? How should a profit-maximizing platform determine the delivery fee to charge its customers and the commission to pay its independent drivers? How should a welfare-maximizing government determine its penalty policy to curb traffic incidents and improve public safety? Methodology/results: Our analysis of a three-stage Stackelberg game yields three interesting results regarding government penalties on drivers and the platform. First, imposing a higher incident penalty on drivers will backfire. It will push the platform to offer higher commissions to incentivize drivers to travel faster, resulting in more accidents and lower profit for the platform. Second, imposing a higher incident penalty on the platform will encourage it to lower commissions, which will induce drivers to travel at safer speeds. Third, penalizing only the platform (not the drivers) is a socially optimal policy. Managerial implications: We illustrate our findings by using data collected from a Chinese meal-delivery platform.
Keywords: Meal delivery platforms, Penalty system, Public safety, Traffic violations and accidents
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