Meituan: Algorithm Management in a Super App
Meituan, China’s lifestyle super app, uses powerful algorithms to optimize food delivery, bookings, and more. But as it scales convenience, it faces growing scrutiny over pressure on riders and fairness for merchants.
At a glance
Founded
2010
Headquarters
Beijing, China
Coverage
2,800+
(cities and counties across China)
Riders
500,000+
Abstract
Meituan, China’s largest lifestyle service platform, has transformed from a group-buying site into a super-app that integrates food delivery, travel, entertainment, and retail into a single digital ecosystem. Founded by Wang Xing in 2010, Meituan’s success lies in its ability to fuse multiple high- and low-frequency services around a common customer base, creating a seamless online-to-offline experience for over 600 million users across China.
Central to Meituan's massive achievement is its algorithmic infrastructure, which optimizes delivery routes, merchant visibility, and personalized recommendations to achieve real-time efficiency at a massive scale. However, this same system has sparked growing concern over labor exploitation, data-driven inequities, and algorithmic opacity.
This case study explores how Meituan’s algorithmic management drives both operational excellence and ethical challenges. As the company faced regulatory scrutiny over antitrust behavior and worker protection, it encountered a fundamental dilemma: whether to continue maximizing efficiency and profitability or to prioritize fairness, transparency, and social responsibility.
Applying frameworks such as Stakeholder Theory, Porter’s Five Forces, and Creating Shared Value (CSV), the study examines how Meituan can balance competing demands among customers, merchants, riders, and regulators. Designed as a problem-solving-oriented case, it invites learners to critically assess the governance of algorithmic systems and to propose strategic pathways for Meituan to align technological innovation with human welfare in China’s rapidly evolving digital economy.
Cover Photo: Nikkei Asia
All rights reserved. © 2025 Nikkei Business Lab Asia. No part of this publication may be copied, stored, or transmitted in any form. Copying or posting is an infringement of copyright.
Disclaimers:
(1) Regarding Case Study Content: This case study is based mainly on secondary data and analysis of publicly available information unless otherwise stated, and is intended solely for educational purposes. Any opinions expressed by the author(s) are designed to facilitate learning discussion and do not serve to illustrate the effectiveness of the company. Additionally, banner images and logos used in the case study are intended for visualization in an educational setting and it is not used to represent or brand the company. For any dispute regarding the content and usage of images and logos, please contact the team.
(2) Regarding University Affiliation and Titles of Authors: The university affiliation and titles of author(s) seen in the case study is based on their affiliation and title during the time of publication. It may or may not represent the current status of said author(s).
