30 Sep 2025 (Tue) 11:00-12:15 | Seminar by Prof. Fang He

Strategic Coordination and Integration in Ride-Hailing Platforms

Speaker:

Prof. Fang He

Department of Industrial Engineering

Tsinghua University

Date:    Sep 30, 2025 (Tuesday)

Time:   11:00 am – 12:15 pm

Venue:  Room 8-28, 8/F Haking Wong Building, The University of Hong Kong

Abstract

This seminar synthesizes two complementary game-theoretic investigations that together illuminate how ride-hailing ecosystems can be steered toward greater efficiency and welfare. The first study frames idle drivers’ information-enabled relocation as a multi-stage leader–follower game on arbitrary service networks. The platform (leader) designs relocation subsidies; drivers (followers) relocate and compete for revenue. Existence and uniqueness results show that when volume imbalances are pronounced or commission rates are low, drivers’ self-interested moves already align with system objectives, making relocation-specific subsidies superfluous. In residual cases, spatial–temporal targeted incentives can double platform profit and markedly boost trip completions, with gains amplified on sparse networks and when driver behavior retains moderate stochasticity. The second study examines the rise of third-party integrated platforms (IPs) that match orders across heterogeneous service providers (SPs) under a revenue-sharing commission. A three-stage mixed-integer game reveals that integration outcomes hinge on four interactive forces: relative SP size, demand stimulation, profit redistribution, and commission design. Excessive consolidation dampens competition, discourages large SPs, and allows the IP to over-extract surplus—threatening industry welfare when worker supply is ample. A ceiling-commission policy emerges as an effective regulatory safeguard.

Bio

Dr. Fang He is Deputy Head for Research and Tenured Associate Professor in the Department of Industrial Engineering at Tsinghua University. He serves as the Executive Vice Dean of the Tsinghua University–COSCO Shipping Green & Intelligent Supply Chain Institute. His research focuses on network modeling and optimization, large-scale combinatorial optimization and deep reinforcement learning, producing more than 60 journal papers, including publications in TS (6), Transportation Research Part Series (40+), and POM (3). He serves as the Associate Editor of Transportation Science and the Editor of Transportation Research Part B. Dr. He is also a recipient of a national-level Young Talent Program in China, and his scholarly work has been implemented by China COSCO Shipping Group, AutoNavi Ride-Hailing, the Beijing 2022 Winter Olympics, and the Wuhan Power Grid, among other high-impact sectors. He has been recognized as an Elsevier Highly Cited Chinese Scholar for six consecutive years (2019–2024), with a single paper exceeding 600 citations. Dr. He received his B.S. degree in Civil Engineering from Tsinghua University in 2010 and his Ph.D. degree from the University of Florida in 2014.

Student Seminar by Dr. Yimo Yan on Sep 29, 2025, 3PM

Title: Event-driven policy optimization for dynamic ambulance dispatch: An attention-based reinforcement learning approach

Speaker: Dr. Yimo Yan (Department of Data and Systems Engineering)

Date: Sep 29, 2025 (Monday)

Time: 3:00 pm - 4:00 pm

Venue: Room 8-28, Haking Wong Building, The University of Hong Kong

Registration Link: https://forms.office.com/r/nvWGefbq5n

ITS Student Committee will provide light refreshments and drinks for registered participants.

Abstract: The global healthcare strain from events such as the COVID-19 pandemic has intensified ambulance shortages, leading to prolonged patient waiting times and increased mortality. In this respect, efficient ambulance dispatch presents a backbone for providing timely patient care. This paper tackles the problem of dynamic ambulance dispatch as a semi-Markov decision process, with the objective of minimizing severity-weighted waiting times through en-route re-dispatching and event-driven decisions. We propose a policy gradient algorithm with a self-attention approximator, which enables inter-task (patients) and inter-agent (ambulances) communications under uncertainty and variable inputs. To further enable interpretability, we distill the learned policy into a decision tree with theoretically grounded features. Experiments on synthetic and real-world cases demonstrate reduced average waiting time and its variance for patients, improved ambulance operational efficiency, and effective use of strategic withholding. Our approach contributes to the development of interpretable, rule-based ambulance dispatch systems in resource-constrained medical environments.

Bios: Dr. Yimo Yan graduated from the Department of Data and Systems Engineering at The University of Hong Kong in Aug 2025. Yimo’s work focuses on transportation and logistics optimisation, incorporating methods like mixed integer linear programming, reinforcement learning, deep learning and large language model. His research, published in various academic journals, addresses challenges in last-mile delivery and scheduling.

Student Seminar by Mr. Dongsheng He on Sep 22, 2025, 3PM

Title: From association to causality: Causal effects of urban transport infrastructure intervention in China using natural experiment approaches

Speaker: Mr. Dongsheng He (Department of Urban Planning and Design)

Date: Sep 22, 2025 (Monday)

Time: 3:00 pm - 4:00 pm

Venue: Room 1010, CLL, Department of Geography, 10/F, The Jockey Club Tower, The University of Hong Kong

Registration Link: https://forms.office.com/r/zrU3BubSh0

Food and drinks will be provided for successfully registered participants.

About the talk: China’s rapid urbanisation has driven extensive construction and expansion of transport infrastructure, notably high-speed rail and intra-city rail transit systems. Such infrastructure projects are characterised by substantial financial investment, long construction timelines, and high sunk costs. Policymakers often assume that these investments generate broad benefits, including economic growth, improved public health, and enhanced social equity. However, most of the current studies rely on cross-sectional observations, which have significant limitations in establishing causal relationships. This seminar introduces a series of large-scale impact assessments of transport infrastructure projects in China, such as urban greenways and metro systems, using natural experiment methods to evaluate their effects on travel behaviours, traffic safety, and housing property values. The findings indicate that the expected benefits of transport infrastructure do not always exist as commonly presumed. Consequently, more nuanced and rigorous evaluations are necessary to better understand the effectiveness and mechanisms of such interventions.

About the speaker: Dongsheng He is currently a PhD candidate in the Department of Urban Planning and Design at the University of Hong Kong. His primary research areas include causal inference of transportation infrastructure impacts, land use and transport integration, and volumetric urban design in high-density cities. He has published more than ten papers in international journals such as Transportation Research Part A/D, Urban Studies, and Landscape and Urban Planning.