Using the Crowd of Taxis to Last Mile Delivery in E-Commerce: a methodological research

Chao Chen () and Shenle Pan ()
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Shenle Pan: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique

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Abstract: Crowdsourcing is gathering increased attention in freight transport areas, mainly applied in internet-based services to city logistics. However, scientific research, especially methodology for application is still rare in the literature. This paper aims to fill this gap and proposes a methodological approach of applying crowdsourcing solution to Last Mile Delivery in E-commerce environment. The proposed solution is based on taxi fleet in city and a transport network composed by road network and customer self-pickup facilities that are 24/7 shops in city, named as TaxiCrowdShipping system. The system relies on a two-phase decision model, first offline taxi trajectory mining and second online package routing and taxi scheduling. Being the first stage of our study, this paper introduces the framework of the system and the decision model development. Some expected results and research perspectives are also discussed.

Keywords: Last mile delivery; Crowdsourcing; Taxi trajectory data mining; Freight transport; City logistics (search for similar items in EconPapers)
Date: 2016-03-24
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Citations: View citations in EconPapers (12)

Published in Service Orientation in Holonic and Multi-Agent Manufacturing, 2016, ⟨10.1007/978-3-319-30337-6_6⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01480533

DOI: 10.1007/978-3-319-30337-6_6

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