Behavioral Modeling of Urban Freight Transport - Sustainable Urban Logistics: Concepts, Methods and Information Systems - page 236

level the policy is trying to influence. The results have been analyzed in terms of
WTP so to facilitate interpretation and, under this respect, the robust estimation
conducted on the coefficients' ratios allowed us to produce monetary confidence
intervals for each of the policy attribute considered. The comparison between M1
(linear effects) and M2 (non-linear effects) shows that potentially relevant biases
could characterize the results obtained if non-linearities in the effects are duly
accounted for. The limited amount of observations available do not suggest
extrapolating the results to a real-life context, however we trust the reader will
appreciate the methodology exposed as useful in providing local policy-makers
with relevant information. Future research will pursue two different but concurrent
objectives. On one side we will perform similar investigations on two other rel-
evant UGM agent-types, namely transport providers and own account, while, on
the other, from a methodological perspective, we will also investigate other
potentially relevant issues such as for instance: (1) various forms of heterogeneity
in preferences (e.g. investigating deterministic, stochastic, as well as both deter-
ministic and stochastic, see Marcucci and Gatta 2012 ); (2) develop interactive
choice models along the methodological lines proposed by Hensher and colleagues
at ITSL Sydney (Hensher and Puckett 2007 ; Puckett et al. 2007 ); (3) adopt
Bayesian estimation methods since they are particularly useful when researchers
are faced with a limited number of observations.
Acknowledgments Acknowledgments: we would like to thank Volvo Research Foundation for
funding the project SP-2007-50 ''Innovative solutions to freight distribution in the complex large
urban area of Rome'' and all those people who administrated the interviews, in particular Matteo
Russo, Silvia De Silvestris, Vivian Diaferia, Amedeo Nanni, Giacomo Lozzi, Matteo Genovese,
Francesco Di Antonio, Emanuele Barzagli, Amedeo Naponiello.
References
Ambrosini C, Routhier JL (2004) Objectives, methods and results of surveys carried out in the
field of urban freight transport: an international comparison. Trans Rev 24(1):57-77
Ambrosini C, Meimbresse B, Routhier JL, Sonntag H (2008) Urban freight policy-oriented
modelling in Europe. In: Taniguchi E, Thompson RG (eds) Innovations in city logistics, Nova
Science Publishing, New York, pp 197-212
Chow JYJ, Yang CHY, Regan AC (2010) State-of-the art of freight forecast modeling: lessons
learned and the road ahead. Transportation 37(6):1011-1030
Collins AT, Rose JM, Hess S (2012) Interactive stated choice surveys: a study of air travel
behavior. Transportation 39(1):55-79
Comi A, Delle Site P, Filippi F, Nuzzolo A (2012) Urban freight transport demand modelling: a
state of the art. In: European Transport/Trasporti Europei 2012 (51), ISTIEE, Trieste
Corò G, Marcucci E (2001) Le politiche per la logistica. In: Quaderni della Mobilità, Proceeding
della Conferenza Politiche economiche per il sistema dei trasporti e della logistica, Regione
Marche, Ancona, vol 1, pp 41-50
Daly S, Hess S, de Jong G (2010) Calculating errors for measures derived from choice modelling
estimates. ITS working paper, Institute for Transport Studies, University of Leeds