Public transport crowdshipping: moving shipments among parcel lockers located at public transport stations

Author:

Wyrowski Alexander,Boysen NilsORCID,Briskorn Dirk,Schwerdfeger Stefan

Abstract

AbstractIn view of success stories of unicorn startups from the sharing and gig economy such as Airbnb, DiDi, or Uber, it is not surprising that postal service providers try to transfer the sharing idea toward their last-mile delivery services: owners of under-used assets (here private crowdshippers traveling anyway) are connected with users willing to pay for the use of these assets (here postal service providers having to deliver parcels). In this paper, we consider a special form of crowdshipping where public transport users, steered by a smartphone app, pick up parcels from parcel lockers, take these shipments with them on their subway rides, and deposit these parcels into other lockers. Finally, the actual recipients can pick up their shipments from their most convenient parcel lockers, e.g., on their own way back home from work. We formulate the optimization problem that matches crowdshipping demand and supply and determines the routes along lockers and crowdshippers each parcel takes. Specifically, we allow that each parcel is moved by multiple cooperating crowdshippers and solve this problem with different objective functions capturing the individual aims of the main stakeholders: shippers, crowdshippers, recipients, and the platform provider. We evaluate the relationship of these objectives and quantify the efficiency loss of a more restricted matching policy, where only a single crowdshipper can be assigned to each parcel’s complete path between origin and destination. Finally, we also explore the impact of delays and investigate whether specific objectives protect against unforeseen events.

Funder

Deutsche Forschungsgemeinschaft

Friedrich-Schiller-Universität Jena

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3