IOE-STAGE SITE

Xiuli Chao

Xiuli Chao receives funding to improve the efficiencies of sharing economy

U-M IOE professor, Xiuli Chao, receives funding from Didi for a project focused on improving the efficiencies of sharing economy through enhanced matching and contract design.

Xiuli Chao, U-M Industrial and Operations Engineering (IOE) professor, has received research funding from Didi Chuxing Technology Co (DiDi) for a project focused on improving the efficiencies of sharing economy through enhanced matching and contract design.

“We are pleased that DiDi funded this project,” Chao said. “It will allow us to develop efficient algorithms and contracts that are not only theoretically valuable, but will also lead to a practical impact.”

“We are pleased that DiDi funded this project. It will allow us to develop efficient algorithms and contracts that are not only theoretically valuable, but will also lead to a practical impact.”

Xiuli Chao
Professor, U-M Industrial & Operations Engineering

DiDi is an app-based platform that provides its users with mobile access to transportation options such as taxi-hailing, bus service, bike sharing, car rental service and food delivery. The company is based in Beijing and serves over 550 million users worldwide.

The project’s application is not limited to DiDi, and can be applied to other platforms involving a two-sided market that use the sharing economy model such as Uber and Lyft. The sharing economy model is defined by more peer-to-peer interaction than traditional producer-consumer economic models.

Chao will employ a range of operations research-based methodologies.

“Optimization models will be developed based on queueing networks and Markov decision processes, and fluid approximations and reinforcement learning techniques will be adopted to derive provably near optimal solutions,” he said.

Chao is the co-principal investigator of the project. Yafeng Yin, U-M Civil and Environmental Engineering professor, serves as a principal investigator on the project.

Chao joined U-M IOE in 2007. His research interests include queueing, scheduling, financial engineering, inventory control and supply chain management. Applications of his research include energy, manufacturing and service systems.