The impact of the traffic measure package (TMP) configuration on performance outputs of a behavioral policy measure (BPM) is in practice predominately estimated, but not yet substantiated. This was also the case for TMPs implemented in ‘Beter Benutten Vervolg’ (BBV), which was a program that executed hundreds of policy measures to get car users to avoid peak. That is why the research objective of this study is to gain insight into the impact of TMP configuration on the performance outputs of BPMs. The research methods for this study included a literature study, a practical knowledge study, a travel behavior questionnaire analysis and a data analysis of BPM data from BBV. The insights gained from the literature study and the practical knowledge study led to the formation hypotheses on a TMP configuration that could positively impact the performance outputs from a BMP within that package. These hypotheses were then tested using both the travel behavior questionnaire data and BPM data from BBV. Performing the two data analyses on the hypotheses, it is likely that when a BPM interacts with an IPM that incentivizes a switch to the same alternative mode, that BPM would have a higher degree of participation than an independently implemented BPM. It is also possible that a BPM in such a TMP configuration has a higher activity than an average BPM. Due to both performance outputs being positively impacted by the TMP configuration, it is assumed that the effectiveness from such a BPM would also be positively impacted by such a configuration. For the second hypothesis it is likely that when a BPM interacts with another BPM that incentivizes the switch to a different alternative mode, that BPM would have a lower degree of participation than an independently implemented BPM. It is however probable that a BPM in such a TMP configuration has a higher activity than an average BPM. Due to the degree of participation being negatively impacted and the activity being positively impacted by the TMP configuration it is not yet clear if the effectiveness of a BPM would be positively or negatively impacted by such a configuration. The results of this study led to two main policy implications. First, accompany a BPM with an infrastructural improvement that incentivizes the switch to the same mode.
Car users would be more likely to participate in such a BPM and when they participate there is an indication that the activity in avoiding peak is also higher. Both of these performance outputs being positively impacted would also lead to a higher effectiveness of this BPM. Second, offering multiple options for the car users to avoid peak. Less car users would probably participate in such a BPM. The car users that do participate probably have a higher activity in avoiding peak. It is still unclear if how the effectiveness of such a BPM is impacted.