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An assessment framework to support collective decision making on urban freight transport

    Ruggero Golini Affiliation
    ; Cindy Guerlain Affiliation
    ; Alexandra Lagorio Affiliation
    ; Roberto Pinto Affiliation

Abstract

This paper proposes a framework that supports the collection and classification of information about the features of a city relevant to Urban Freight Transport (UFT). The information is organized in a framework of 28 different layers that are then stored in a Geographic Information System (GIS) tool to enable efficient data retrieval and effective information graphical display. The resulting GIS tool thus represents a decision support system for UFT problems, providing decision makers and stakeholders with a wide range of easy to understand information aimed to support the identification and preliminary evaluation of UFT solutions. Moreover, by providing a standardized set of features and sources of information, the framework enables the comparison of different cities. To illustrate the benefits, prototypical real-scale tests based on the framework have been realized in two mid-sized European cities: Bergamo (North of Italy) and Luxembourg. For both cities, data were mainly collected from publicly available sources and organized according to the framework. The data and information collected have been used in collaboration with the stakeholders in order to identify the priorities of intervention and evaluate alternative UFT solutions. The real-scale applications confirmed the usability and effectiveness of the framework in engaging stakeholders and support the process of envisioning shared UFT solutions.

Keyword : urban freight transport, city logistics, stakeholder engagement, last-mile distribution, GIS, collaboration platform

How to Cite
Golini, R., Guerlain, C., Lagorio, A., & Pinto, R. (2018). An assessment framework to support collective decision making on urban freight transport. Transport, 33(4), 890-901. https://doi.org/10.3846/transport.2018.6591
Published in Issue
Dec 5, 2018
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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