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Applying Infomap-based Hierarchical Community Detection for Multi-Level City On-Demand Delivery Management

Zhang, Chengbo ; Zhang, Lina ; Liang, Wenbin and Yang, Xiao (2025) 28th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2025 p.2629-2634
Abstract

Efficient management of on-demand delivery systems is essential for modern urban logistics, especially in densely populated cities with complex spatial layouts. This study introduces a novel, computer-supported cooperative framework that utilizes Infomap-based hierarchical community detection to analyze spatial multilevel clustering patterns. The experiment was conducted to large scale on-demand delivery datasets from Shenzhen and Beijing, revealing integrated spatial clusters that align with cohesive urban layout. Through hierarchical detection, finer and fragmented clusters are identified, reflecting its diverse urban structure and delivery demands. The findings demonstrate the effectiveness of hierarchical community detection in... (More)

Efficient management of on-demand delivery systems is essential for modern urban logistics, especially in densely populated cities with complex spatial layouts. This study introduces a novel, computer-supported cooperative framework that utilizes Infomap-based hierarchical community detection to analyze spatial multilevel clustering patterns. The experiment was conducted to large scale on-demand delivery datasets from Shenzhen and Beijing, revealing integrated spatial clusters that align with cohesive urban layout. Through hierarchical detection, finer and fragmented clusters are identified, reflecting its diverse urban structure and delivery demands. The findings demonstrate the effectiveness of hierarchical community detection in uncovering spatial dependencies and optimizing resource allocation and delivery strategies. This framework provides practical insights for urban logistics, enabling tailored approaches for business hub placement, route allocation, and adaptive resource management.

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Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Hierarchical Structure, Infomap, Logistics Management, On-demand Delivery, Spatial Network
host publication
Proceedings of the 2025 28th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2025
editor
Shen, Weiming ; Shen, Weiming ; Abel, Marie-Helene ; Matta, Nada ; Barthes, Jean-Paul ; Luo, Junzhou ; Zhang, Jinghui ; Zhu, Haibin and Peng, Kunkun
edition
2025
pages
6 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
28th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2025
conference location
Compiegne, France
conference dates
2025-05-05 - 2025-05-07
external identifiers
  • scopus:105011506257
ISBN
9798331513054
DOI
10.1109/CSCWD64889.2025.11033440
language
English
LU publication?
no
id
03de90bf-f355-4488-9cd5-8b71a308e1a3
date added to LUP
2026-01-20 15:01:37
date last changed
2026-01-20 15:02:36
@inproceedings{03de90bf-f355-4488-9cd5-8b71a308e1a3,
  abstract     = {{<p>Efficient management of on-demand delivery systems is essential for modern urban logistics, especially in densely populated cities with complex spatial layouts. This study introduces a novel, computer-supported cooperative framework that utilizes Infomap-based hierarchical community detection to analyze spatial multilevel clustering patterns. The experiment was conducted to large scale on-demand delivery datasets from Shenzhen and Beijing, revealing integrated spatial clusters that align with cohesive urban layout. Through hierarchical detection, finer and fragmented clusters are identified, reflecting its diverse urban structure and delivery demands. The findings demonstrate the effectiveness of hierarchical community detection in uncovering spatial dependencies and optimizing resource allocation and delivery strategies. This framework provides practical insights for urban logistics, enabling tailored approaches for business hub placement, route allocation, and adaptive resource management.</p>}},
  author       = {{Zhang, Chengbo and Zhang, Lina and Liang, Wenbin and Yang, Xiao}},
  booktitle    = {{Proceedings of the 2025 28th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2025}},
  editor       = {{Shen, Weiming and Shen, Weiming and Abel, Marie-Helene and Matta, Nada and Barthes, Jean-Paul and Luo, Junzhou and Zhang, Jinghui and Zhu, Haibin and Peng, Kunkun}},
  isbn         = {{9798331513054}},
  keywords     = {{Hierarchical Structure; Infomap; Logistics Management; On-demand Delivery; Spatial Network}},
  language     = {{eng}},
  pages        = {{2629--2634}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Applying Infomap-based Hierarchical Community Detection for Multi-Level City On-Demand Delivery Management}},
  url          = {{http://dx.doi.org/10.1109/CSCWD64889.2025.11033440}},
  doi          = {{10.1109/CSCWD64889.2025.11033440}},
  year         = {{2025}},
}