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The introduction of innovative mobility services such as car sharing leads to changes in users’ travel habits, inducing a shift of travel demand from existing travel modes. An analysis of such changes should be performed to promote car sharing, managing travel demand effectively. Policies should be developed to induce the switch only from private modes, avoiding the shift from public transport and active modes. In order to reach this aim, data from a mobility survey carried out in Turin (Italy) were used to study modal choices. Decision Trees were adopted to complement the analyses following an econometric approach. One decision tree was estimated for each mode used by respondents in a specific trip, to identify trip attributes affecting the intention to switch to car sharing. Thus, threshold values of each variable that entice a modal shift are mode-specific, thus better informing policies aimed at maximizing the benefits of car sharing.

A multimodal perspective in the study of car sharing switching intentions