Direct Effects of City Logistics Measures and Urban Freight Demand Models - Sustainable Urban Logistics: Concepts, Methods and Information Systems - page 211

captured. Thus an advanced integrated modeling system is proposed below for
internal/external direct effect forecasting.
4 Urban Freight Demand Models
The need to find solutions to support the definition of new city logistics scenarios
which allow for both external costs and internal direct costs incurred by several
actors of freight restocking and shopping mobility has led to the investigation and
development of new demand models. Traditionally, these two demand segments
have been handled independently.
Shopping may be considered a major trip purpose as it forms part of the
lifestyle of the population. Nevertheless, most of the current transport literature
focuses on studying the characteristics of worker trips, with little emphasis being
placed on studying non-worker travel patterns, such as shopping trips (Mokhtarian
2004 ; Cao et al. 2010 ). Furthermore, shopping mobility has been studied as a
component of passenger demand through the relationships among travel behavior,
the built environment (e.g. land use allocated for different business activities) and
socio-economic characteristics (Nuzzolo and Coppola 2005 ; Ewing and Cervero
2010 ). In general, the focus of passenger transportation research is mainly on trip
generation, distribution and mode steps within the well-known four-step models.
Although researchers have increasingly argued the high incidence of multi-stop
trips in empirically observed behavior (e.g. Dellaert et al. 1998 ; Popkowski
Leszczyc et al. 2004 ), the commonly used modeling structure refers to round trips.
Various freight demand models have been proposed for simulating the freight
flows destined to commercial urban activities (i.e. restocking process), many of
which are multi-stage models (Taniguchi et al. 2001 ; Comi et al. 2012 ; de Jong
et al. 2012 ). The mechanism underlying the generation of freight transport demand
requires that quantity be used as the reference unit. Besides, the methods and
models used for direct effect forecasting require the use of vehicle units (Fig. 1 ).
Indeed, as stated above, vehicle O/D flows, interacting within the assignment
model, allow us to obtain link flows and then to estimate performances and
impacts of a given city logistics scenario. The translation of quantity into vehicle
flows has to investigate the process of restocking; therefore a reference unit closer
to those used by transport and logistics operators should be used, namely delivery
and tours. Delivery ( Nuzzolo et al. 2006 ; Muñuzuri et al. 2012 ) allows us to focus
on transport service type used for restocking (e.g. on own account or by third
party), and on shipment size, while tours should be used to investigate delivery
tours in relation to departure time, vehicle type, number and sequence of stops
(Nuzzolo et al. 2011 ; Nuzzolo and Comi 2013a ).
Few studies (Russo and Comi 2010 ; Gonzalez-Feliu et al. 2012 ) have analyzed
shopping mobility as a component of freight mobility and have considered that
actions impacting on purchasing behaviors of end consumers (e.g. location of retail
outlet, transport mode to use for shopping) can also affect restocking mobility.