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China’s Major Food Delivery Platforms Remove Late-Delivery Fines

Oct 16, 2025, 2:35 a.m. ET

China’s leading food delivery platforms are revamping how they manage delivery rider performance, moving away from cash penalties for late orders in favor of service-based incentive systems.

JD Daojia, the delivery arm of e-commerce giant JD.com, announced on Thursday that it has launched a pilot across 25 cities, including Shenzhen, Nanjing, Harbin, and Wuhan, replacing traditional late-delivery fines with a “service score” system. Under the new mechanism, riders who deliver orders past the expected time will no longer face direct cash deductions. Instead, points are deducted based on the severity of the delay, encouraging positive reinforcement rather than punitive measures.

In addition to the service score system, JD Daojia said it continues to roll out initiatives to enhance rider welfare. The company provides additional subsidies during extreme weather, runs programs such as rider child care funds, positive reinforcement incentives, and dedicated “rider care stations,” and is expanding its insurance offerings to improve the overall delivery experience.

Ele.me, another major player in China’s food delivery market, has also begun piloting a similar system. According to its official city rider account, the platform is testing a revised service score framework in cities including Nantong, Changzhou, Jieyang, and Jingdezhen. The initiative is designed to replace late-delivery deductions with a points-based system that rewards productivity and performance, and the platform plans to expand coverage to more cities by October.

Meituan, the largest food delivery operator in China, has similarly committed to eliminating late-delivery fines by the end of 2025. The company first piloted the “On-Time Card” in Quanzhou, allowing points deductions for late deliveries while rewarding timely performance. By August 2025, the system had expanded to 22 cities, reflecting a broader shift from a punitive “penalty-first” approach toward more scientific and positive incentives.

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