EX-POST IMPLICATIONS OF EX-ANTE DATA ACQUISITION STRATEGIES IN MULTIAGENT-TYPE URBAN FREIGHT POLICY EVALUATION

Data quality plays a relevant role in policy evaluation. Data quality is also strictly linked to questionnaire development and administration strategies. Willingness to pay estimates might be influenced by the data acquisition method adopted if an ex-post sophisticated modelling cannot compensate for the low quality data acquired. We test this hypothesis by comparing agent-generic vs. agent-specific data acquisition. This methodologically relevant question is investigated with respect to urban freight transport policy evaluation. In this field, in fact, heterogeneity among stakeholders' (i.e. retailers and transport providers) preferences is allegedly important since retailers, demanding freight transportation services, and transport providers, offering them, are characterised by, structurally and functionally motivated, differences in preferences. Results indicate that agent-specific data acquisition should be adopted. The analyst ought to take the longer data acquisition route when a strong and well rooted a priori knowledge suggests different agent-types' preferences are at work. This reflections are particularly valuable given ex-post agent-specific modelling cannot compensate for ex-ante agent-generic data acquisition procedure. Once perpetrated, the original sin cannot be redeemed.