How good are retailers in predicting transport providers’ preferences for urban freight policies?… and vice versa?

The success or failure of urban freight transport measures crucially depends on local policy makers’ knowledge and awareness of stakeholders’ preferences. The behavioral approach calls for stakeholder-specific data acquisition and model estimation. Considering the cost and time to perform an appropriate data acquisition process and the ever present aim of compressing research costs, it is important to investigate innovative data acquisition procedures that can satisfy the above mentioned constraints while not sacrificing data quality. The paper tests the capability of an alternative, less expensive and faster to administer procedure of acquiring stakeholder-specific data capable of reproducing policy evaluation results (i.e. willingness to pay measures) derivable from a standard data acquisition process. In more detail, the paper investigates the respective capabilities retailers and transport providers have in predicting each other responses to a stated ranking exercise aimed at measuring agents’ preferences for alternative urban freight policies for the limited traffic zone in the city center of Rome. Results show that retailers are capable of predicting with a good level of accuracy transport providers’ preferences for a given policy while the opposite is not true. This represents an important step forward in willingness to pay estimation for policy changes when the substitution rates between the various attributes considered are the main research objective of a strategic level analysis. Were this possible one could, in fact, interview retailers alone to understand also which would be transport providers’ preferences for the policies evaluated.