City logistics through the canals? A simulation study on freight waterborne transport in the inner-city of Amsterdam

J.H.R. van Duin, R. Kortmann and S.L. van den Boogaard

International Journal of Urban Sciences, 2014, vol. 18, issue 2, 186-200

Abstract: This study investigates whether distributing goods across the water to the city of Amsterdam can be a potential future solution considering the busy traffic of the pleasure crafts and touring boats on the canals. A simulation model was developed to analyse the logistics performances and traffic influences for different fleet size configurations. The simulation tests have shown that four vessels are needed to guarantee the requested delivery times, a sufficient loading rate (82%) was generated for each ship, and no significant delays will happen due to interaction with other water traffic. Conclusion of this study is that a waterborne city logistics concept through the canals of Amsterdam has demonstrated the capability to reduce congestion in the inner-city and is able to satisfy the delivery requirements of the shopkeepers without significant interference with other waterborne traffic.

Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://hdl.handle.net/10.1080/12265934.2014.929021 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rjusxx:v:18:y:2014:i:2:p:186-200

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rjus20

DOI: 10.1080/12265934.2014.929021

Access Statistics for this article

International Journal of Urban Sciences is currently edited by Dongjoo Park and Mack Joong Choi

More articles in International Journal of Urban Sciences from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().