Decision makers in urban goods movement (UGM) typically need to assess the impact new policy interventions might have on freight distribution. The effects of policy changes are inextricably related with the extant regulatory framework that also influences the relationships among the various actors inter-acting along the supply chain. The operators commonly considered important, given the crucial role they play in UGM, are: retailers, transport providers, and own-account. Notwithstanding the admittedly important role that a detailed knowledge of these three agent categories has for a correct policy implementation there is a limited knowledge concerning the specific preferences and behavior of each agent-type. It is de facto assumed that retailers, own-account and transport providers have homogenous preferences and can be seamlessly treated. The upsurge of behavioral models and the acquisition of data necessary to predict goods and vehicle flows both under the current and, more importantly, under altered policy/regulatory conditions explains the progressive importance that is attributed to an agent-based perspective. This research reports the result of a stated ranking exercise conducted in the Limited Traffic Zone in 2009 in the city center of Rome focusing on retailers which demand freight transport services and play an important role in extended supply chains. This paper proposes a comparison between two different Multinomial Logit model specifications where non-linear effects for the variations of the levels of the attributes considered are studied and detected. A meaningful comparison between willingness to pay measures derived by the two model specifications is proposed so to avoid known scale problems. The results obtained are very interesting and meaningful from a policy perspective since they show potentially differentiated effects of the policy implemented in deep contrast with the, often assumed, homogenous effect hypothesis.
