Paper Info
Title
The value of personalized dispatch in O2O on-demand delivery services
Abstract
•We discover that the delivery speed and delivery capacity of the crowd-sourced drivers vary considerably.•We build two personalized models to learn the behavior of crowd-sourced drivers.•We integrate the personalized models into the order assignment and routing model as a predict-while-optimize model.•We provide computational results on data from one mainstream O2O platform in China.•We show the values of personalization in O2O on-demand services.
Year
DOI
Venue
2023
10.1016/j.ejor.2022.05.019
European Journal of Operational Research
Keywords
DocType
Volume
Logistics,Personalization,Dispatch,Crowd-sourcing,Machine learning
Journal
304
Issue
ISSN
Citations 
3
0377-2217
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Jiawei Tao100.68
Hongyan Dai200.34
Weiwei Chen312512.21
Hai Jiang4275.25