Meituan has announced that it will treat algorithm governance as a crucial component of its corporate social responsibility, focusing on the pressing concerns raised by its delivery riders. The company aims to shift its algorithmic focus from "efficiency first" to "people-oriented," thereby safeguarding the legitimate rights and interests of riders and striving to enhance their sense of fulfillment, happiness, and security.

The company stated that "late delivery penalties" were once a major concern for riders, especially new ones. To address this issue, Meituan has introduced a penalty exemption measure for late deliveries, replacing negative deductions with a scoring system. By 2025, this penalty exemption will be implemented nationwide, encouraging riders to earn positive points based on three dimensions: "safety," "punctuality," and "service," effectively reducing the pressure on delivery personnel. Concurrently, the order dispatch system for new riders has been improved to ensure that those in their "probationary period" do not receive overly complex orders.

Meituan also mentioned that it encourages riders to "slow down and earn more." The company provides positive incentives for riders to comply with traffic rules by incorporating their traffic safety performance into the evaluation system. The higher the "safety score," the greater the rewards. Additionally, riders who maintain a record of zero red-light violations receive a "Wait for the Light Award." By 2025, this award is expected to cover nearly 200 cities, with an investment of 70 million yuan, benefiting nearly 1.28 million rider instances. In related cities, red-light violations by riders have significantly decreased, while delivery punctuality rates have remained stable.

Meituan stated that it will continue to optimize algorithms related to pricing, time estimation, and route standardization. The company will implement measures such as abolishing late delivery penalties, improving service score rules, and holding algorithm consultation forums. It will also explore automatic recognition and time compensation for complex delivery scenarios, as well as dynamic compensation for "hard-to-deliver" orders. These efforts aim to continuously enhance the delivery experience for riders and the quality of service for users, driving new progress and effectiveness in algorithm governance.