Multi-Criteria Analysis of Electric Vans for City Logistics

Jarosław Wątróbski, Krzysztof Małecki, Kinga Kijewska, Stanisław Iwan, Artur Karczmarczyk and Russell G. Thompson
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Jarosław Wątróbski: Faculty of Computer Science, West Pomeranian University of Technology, Żołnierska 52 Str., 71-210 Szczecin, Poland
Krzysztof Małecki: Faculty of Computer Science, West Pomeranian University of Technology, Żołnierska 52 Str., 71-210 Szczecin, Poland
Kinga Kijewska: Faculty of Economics and Engineering of Transport, Maritime University of Szczecin, Pobożnego 11 Str., 70-507 Szczecin, Poland
Artur Karczmarczyk: Faculty of Computer Science, West Pomeranian University of Technology, Żołnierska 52 Str., 71-210 Szczecin, Poland
Russell G. Thompson: Department of Infrastructure Engineering, The University of Melbourne, Parkville 3010, Australia

Sustainability, 2017, vol. 9, issue 8, 1-34

Abstract: Atmospheric emissions of anthropogenic origin are one of the most important problems in cities. A particularly discrete ecological footprint in urban environment is made by urban freight transport. This problem has become the key challenge for all stakeholder groups involved in freight transport in urban areas. Over the recent years, there has been a growing interest in using alternative fuel vehicles in urban logistics, including those equipped with electric drive systems. This paper presents a multi-criteria analysis (MCA) of selected electric vehicles (EVs) in the context of their application for the purposes of deliveries in cities. In methodological terms, we present a unique MCA-based approach for evaluation of Electric Freight Vehicles (EFVs). A successful attempt is made to build a multistep MCA procedure based on two carefully selected MCDA methods (PROMETHEE II and fuzzy TOPSIS) to handle both certain and uncertain data sets in a single decision process. In practical terms, we successfully demonstrate the usefulness of the proposed approach by creating a set of decision maker’s preference models (based on certain and uncertain data) of carefully selected EFVs and provide sensitivity and robustness analyses of the obtained solutions.

Keywords: city logistics; urban freight transport; electric freight vehicles (EFVs); sustainable transport; environmental friendly transport; multi-criteria decision making; multi-criteria model; PROMETHEE II method; fuzzy TOPSIS method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

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