Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

6-2021

Abstract

Sustained work enthusiasms of drivers are crucial for the success of large-scale ride-hailing platforms. In this paper, we conduct the first-of-its-kind exploration to encourage active participation of drivers via competition. We design Arena, a competition where drivers compete for prizes via completing more trips. Through a pilot study covering over 2,600 participants, we uncover the easy-win problem, an overlooked and serious issue in competition design for real-world drivers. It refers to situations where one competitor does not show up during competition whereas the other easily wins. To solve the easy-win problem without impairing motivation of drivers, we devise a novel prediction-based matchmaking framework. On observing that no-shows are highly correlated to the online time of drivers during competition, we propose to identify potential no-shows by predicting drivers' online time and avoid matching potential noshow drivers with drivers that will show up so as to reduce easy-wins. We conduct large-scale experiments based on real competition data involving over 10,000 drivers. The results show that our prediction-based matchmaking scheme can effectively reduce the ratio of easy-wins.

Keywords

competition, spatial crowdsourcing

Discipline

Artificial Intelligence and Robotics | Graphics and Human Computer Interfaces

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of 2021 22nd IEEE International Conference on Mobile Data Management (MDM)

Identifier

10.1109/MDM52706.2021.00016

City or Country

Toronto, ON, Canada

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