Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/228945
Authors: 
Frederhausen, Sebastian
Klumpp, Matthias
Year of Publication: 
2020
Citation: 
[Editor:] Jahn, Carlos [Editor:] Kersten, Wolfgang [Editor:] Ringle, Christian M. [Title:] Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 30 [ISBN:] 978-3-7531-2347-9 [Year:] 2020 [Pages:] 33-69
Abstract: 
Purpose: Global supply chains increasingly demand sustainable setups, from the first to the last mile in transportation. Particularly in urban settings, the use of commercial electric vehicles for transport tasks might be a suitable measure to increase overall sustainability. Methodology: For an initial structuring step of this growing research field, this paper conducts a systematic literature review based on Denyer and Tranfield (2010). The aim is to provide an overview regarding existing routing approaches for commercial electric vehicles, their characteristics and their suitability for typical application contexts in urban logistics (e.g. retail, parcel delivery, gastronomy). Findings: The results point out topical gaps regarding the specific characteristics considered in the routing models and the focus of their optimization objectives. Among others, research gaps where identified regarding specific urban logistics requirements like energy management considerations for cooling/heating, mixed fleet modelling and (partial) recharging. Originality: While the ecologic and economic impacts of electric vehicles have already been researched extensively, the OR-perspective on their commercial use still is an emerging topic. This review contributes to the structuring of this research field, which can play a key role in the practical application of electric vehicles in urban contexts.
Subjects: 
Logistics
Industry 4.0
Supply Chain Management
Sustainability
City Logistics
Maritime Logistics
Data Science
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-sa/4.0/
Document Type: 
Conference Paper

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