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Recommendation-based Team Formation for On-demand Taxi-calling Platforms

Authors:

Jieping YeAuthors Info & Claims

CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management

Pages 59 - 68

https://doi.org/10.1145/3357384.3357869

Published: 03 November 2019 Publication History

Abstract

On-demand taxi-calling platforms often ignore the social engagement of individual drivers. The lack of social incentives impairs the work enthusiasms of drivers and will affect the quality of service. In this paper, we propose to form teams among drivers to promote participation. A team consists of a leader and multiple members, which acts as the basis for various group-based incentives such as competition. We define the Recommendation-based Team Formation (RTF) problem to form as many teams as possible while accounting for the choices of drivers. The RTF problem is challenging. It needs both accurate recommendation and coordination among recommendations, since each driver can be in at most one team. To solve the RTF problem, we devise a Recommendation-Matrix-Based Framework (RMBF). It first estimates the acceptance probability of recommendations and then derives a recommendation matrix to maximize the number of formed teams from a global view. We conduct trace-driven simulations using real data covering over 64,000 drivers and deploy our solution on a large on-demand taxi-calling platform for online evaluations. Experimental results show that RMBF outperforms the greedy-based strategy by forming up to 20% and 12.4% teams in trace-driven simulations and online evaluations, and the drivers who form teams and are involved in the competition have more service time, number of finished orders and income.

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Cited By

TÜRKKAHRAMAN ŞKARABULUT K(2023)Sosyal Ağ Varlığında Takım Oluşturma Problemine Hibrit Bir Genetik Algoritma ÖnerisiA Hybrid Genetic Algorithm Proposal for the Team Formation Problem Considering Social NetworkDeu Muhendislik Fakultesi Fen ve Muhendislik10.21205/deufmd.202325731525:73(181-192)Online publication date: 26-Jan-2023
https://doi.org/10.21205/deufmd.2023257315
Hao YZhang TZhao PLiu YSheng VXu JLiu GZhou X(2023)Feature-Level Deeper Self-Attention Network With Contrastive Learning for Sequential RecommendationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.325046335:10(10112-10124)Online publication date: 1-Oct-2023
https://doi.org/10.1109/TKDE.2023.3250463
Costa ARamos FPerkusich MNeto ASilva LCunha FRique TAlmeida HPerkusich A(2022)A Genetic Algorithm-Based Approach to Support Forming Multiple Scrum Project TeamsIEEE Access10.1109/ACCESS.2022.318634710(68981-68994)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3186347
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Index Terms

Recommendation-based Team Formation for On-demand Taxi-calling Platforms
1. Information systems

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Published In

cover image ACM Conferences

CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management

November 2019

3373 pages

ISBN:9781450369763

DOI:10.1145/3357384

General Chairs:
Wenwu Zhu
Tsinghua University, China
,
Dacheng Tao
University of Massachusetts, USA
,
Xueqi Cheng
Institute of Computing Technology, CAS, China
,
Program Chairs:
Peng Cui
Tsinghua University, China
,
Elke Rundensteiner
Worcester Polytechnic Institute, USA
,
David Carmel
Amazon Research, USA
,
Qi He
LinkedIn, USA
,
Jeffrey Xu Yu
Chinese University of Hong Kong, China

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 03 November 2019

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Funding Sources

Didi Gaia Collborative Research Funds for Young Scholars
Science and Technology Major Project of Beijing
National Science Foundation of China (NSFC)

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CIKM '19

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CIKM '19: The 28th ACM International Conference on Information and Knowledge Management

November 3 - 7, 2019

Beijing, China

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CIKM '19 Paper Acceptance Rate 202 of 1,031 submissions, 20%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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CIKM '25

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The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

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Cited By

TÜRKKAHRAMAN ŞKARABULUT K(2023)Sosyal Ağ Varlığında Takım Oluşturma Problemine Hibrit Bir Genetik Algoritma ÖnerisiA Hybrid Genetic Algorithm Proposal for the Team Formation Problem Considering Social NetworkDeu Muhendislik Fakultesi Fen ve Muhendislik10.21205/deufmd.202325731525:73(181-192)Online publication date: 26-Jan-2023
https://doi.org/10.21205/deufmd.2023257315
Hao YZhang TZhao PLiu YSheng VXu JLiu GZhou X(2023)Feature-Level Deeper Self-Attention Network With Contrastive Learning for Sequential RecommendationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.325046335:10(10112-10124)Online publication date: 1-Oct-2023
https://doi.org/10.1109/TKDE.2023.3250463
Costa ARamos FPerkusich MNeto ASilva LCunha FRique TAlmeida HPerkusich A(2022)A Genetic Algorithm-Based Approach to Support Forming Multiple Scrum Project TeamsIEEE Access10.1109/ACCESS.2022.318634710(68981-68994)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3186347
Chengi HWed SZhang LZhou ZTongi Y(2021)Engaging Drivers in Ride Hailing via Competition: A Case Study with Arena2021 22nd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM52706.2021.00016(19-28)Online publication date: Jun-2021
https://doi.org/10.1109/MDM52706.2021.00016
Naunthong P(2021)Understanding Organizational Characteristics for the Adoption of On-Demand Delivery: A Case Study of Thai Industries2021 6th International Conference on Business and Industrial Research (ICBIR)10.1109/ICBIR52339.2021.9465847(97-101)Online publication date: 20-May-2021
https://doi.org/10.1109/ICBIR52339.2021.9465847
Sun XYin Y(2021)Decentralized game-theoretical approaches for behaviorally-stable and efficient vehicle platooningTransportation Research Part B: Methodological10.1016/j.trb.2021.08.012153(45-69)Online publication date: Nov-2021
https://doi.org/10.1016/j.trb.2021.08.012
Gómez-Zará DDeChurch LContractor N(2020)A Taxonomy of Team-Assembly SystemsProceedings of the ACM on Human-Computer Interaction10.1145/34152524:CSCW2(1-36)Online publication date: 15-Oct-2020
https://dl.acm.org/doi/10.1145/3415252
Ye TAi WZhang LLuo NZhang LYe JMei QGupta RLiu YShah MRajan STang JPrakash B(2020)Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing EconomyProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3394486.3403286(2368-2377)Online publication date: 23-Aug-2020
https://dl.acm.org/doi/10.1145/3394486.3403286

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