Surveys on Urban Freight Transport Workshop Summary

1. Surveys on Urban Freight TransportWorkshop Summary Workshop chair: Arnim Meyburg Rapporteur: Matthew Roorda Resource paper: Danièle Patier, Jean Louis Routhier, “How to Improve the Capture of Urban Goods Movement Data” Discussant: Michael Browne Contributed papers: Matthew Roorda, “ Comparing GPS and Non-GPS Methods…” Wulf-Holger Arndt, “Combination of Quantitative and Qualitative Methods…”

2. Participants • Pedro José Pérez Martinez, Spain • Alan Pisarski, USA • Christophe Rizet, France • Matthew Roorda, Canada • Jean Louis Routhier, France • Paulo Ueta, Brazil • Wulf-Holger Arndt, Germany • Imke Steinmeyer, Germany • Nina Karasmaa, Finland • Michael Browne, UK • Alban Igwe, Nigeria • Kara Kockelman, USA • Stephan Krygsman, S. Africa • Jacques Leonardi, UK • Richard McMahon, Ireland • Julius Menge, Germany • Arnim Meyburg, USA • Simo Pasi, Luxembourg • Danièle Patier, France

3. Key points raised • Urban goods and services movement are very complex; • Therefore it is important to very clearly define the purpose of the survey; • This will lead to a well-defined scope of the survey; • We must describe the scope clearly in relation to the “universe” of commercial travel; • For many purposes, we need to look at establishments’ economic activity (including goods movement) and the vehicle operations that result.

4. Definitions and Harmonisation • Develop a glossary of definitions that can be used as a resource • Researchers, practitioners can communicate • Studies can be compared • Data collection methods can be shared • Consistency with intercity freight flows and national economic accounts (I/O)

5. Technology (e.g. GPS) • Use of technology for goods movement data collection is likely to expand; • Technology should be seen as a complementary tool for data collection; • Can provide highly precise, rich and wide-ranging information; • This can improve respondent burden; • We need to find ways to overcome privacy issues.

6. Obtaining data from existing sources • Researchers need to be entrepreneurial about obtaining data from • Carriers, 3PL, large retailers , ports, technology providers, toll authorities, governments, etc. • Find win-win situations for data sharing

7. Data and Modelling • Descriptive statistics can be as valid a basis for data collection as modelling; • A mathematical model is not a prerequisite for data collection.

8. Some Research Challenges • Links between global supply chains and urban goods movement; • Substitution between consumer and business goods movement (e-business); • Complexity of sampling with diverse economic structures; • Understand implications of public policy decisions using techniques such as • Stated preference surveys • Before / after studies; • New/alternative techniques for data collection, e.g. • Qualitative methods • Web-based surveys.

9. Merci beaucoup!