Engaging drivers via competition: A case study with arena

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 compl...

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Main Authors: CHENG, Hao, WEI, Shuyu, ZHANG, Lingyu, ZHOU, Zimu, TONG, Yongxin.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/6788
https://ink.library.smu.edu.sg/context/sis_research/article/7791/viewcontent/mdm21_cheng.pdf
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spelling sg-smu-ink.sis_research-77912022-01-27T09:59:50Z Engaging drivers via competition: A case study with arena CHENG, Hao WEI, Shuyu ZHANG, Lingyu ZHOU, Zimu TONG, Yongxin. 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. 2021-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6788 info:doi/10.1109/MDM52706.2021.00016 https://ink.library.smu.edu.sg/context/sis_research/article/7791/viewcontent/mdm21_cheng.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University competition spatial crowdsourcing Artificial Intelligence and Robotics Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic competition
spatial crowdsourcing
Artificial Intelligence and Robotics
Graphics and Human Computer Interfaces
spellingShingle competition
spatial crowdsourcing
Artificial Intelligence and Robotics
Graphics and Human Computer Interfaces
CHENG, Hao
WEI, Shuyu
ZHANG, Lingyu
ZHOU, Zimu
TONG, Yongxin.
Engaging drivers via competition: A case study with arena
description 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.
format text
author CHENG, Hao
WEI, Shuyu
ZHANG, Lingyu
ZHOU, Zimu
TONG, Yongxin.
author_facet CHENG, Hao
WEI, Shuyu
ZHANG, Lingyu
ZHOU, Zimu
TONG, Yongxin.
author_sort CHENG, Hao
title Engaging drivers via competition: A case study with arena
title_short Engaging drivers via competition: A case study with arena
title_full Engaging drivers via competition: A case study with arena
title_fullStr Engaging drivers via competition: A case study with arena
title_full_unstemmed Engaging drivers via competition: A case study with arena
title_sort engaging drivers via competition: a case study with arena
publisher Institutional Knowledge at Singapore Management University
publishDate 2021
url https://ink.library.smu.edu.sg/sis_research/6788
https://ink.library.smu.edu.sg/context/sis_research/article/7791/viewcontent/mdm21_cheng.pdf
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