Optimal delivery time and subsidy for IT-enabled food delivery platforms considering negative externality and social welfare

Purpose: Information technology-enabled gig platforms connect freelancers with consumers to provide short-term services or asset sharing. The growth of gig economy, however, has been accompanied by controversy, and, recently, food delivery platforms have been criticized for using data-driven techniques to set strict delivery time limits, resulting in negative externality. This study aims to provide managerial implications on the decisions of delivery time and subsidy for food delivery platforms.

Design/methodology/approach: The authors develop an analytical framework to investigate the optimal delivery time and subsidy provided to delivery drivers to maximize the gig platform's profit and compare the results with those of a socially optimal outcome. 

Findings: The study reveals that it is optimal for the platform to shorten the delivery time and raise the subsidy when the food price becomes higher; nevertheless, the platform should shorten the delivery time and lower the subsidy in response to a higher delivery fee. Increases in the food price or delivery fee have non-monotonic effects on the number of fulfilled orders and the platform's profit. In addition, the authors solve the socially optimal outcome and find that a socially optimal delivery time is longer than the platform's preferred length when the delivery fee is high and the negative externality is strong. 

Originality/value: The food delivery platform's optimal decision on delivery time is derived after taking negative externality into account, which is rarely considered in the prior literature but is a practically important problem.