Abstract ID: 3.12940 | Accepted as Talk | Talk/Oral | TBA | TBA

Car dependency is a common feature of many mountain areas. The use of motorized private vehicles is associated with several problems: social exclusion, lack of accessibility to jobs and services affecting certain segments of population, congestion of roads and parking facilities at tourist spots and environmental externalities, and loss of attractiveness and competitivity. The present work drags data from the Daily Mobility Survey of the Camp de Tarragona, launched in 2020 prior to the COVID-19 pandemic and the lockout. Data collected provides detailed information about all journeys undertaken by respondents during the day before the interview. The number of valid questionnaires collected in those municipalities regarded as part of the mountain areas was 860, whereas the overall number was 9,228. Data collected comprised the main characteristics of the journeys: origin and destination, motivation, modal choice and time and duration, together with wide sociodemographic respondents’ information and their perceptions towards mobility. Results reveal, as expected, that modal split shares are highly dependent on the private vehicle in comparison to the rest of the surveyed region. A multinomial multilevel logistic regression is used to assess the determinants of modal choices while allowing us to capture the effect of unobserved heterogeneity at the municipality level. The empirical evidence confirms the strong correlation between residing in the mountain area and car dependency. At the same time, running separate models for the mountain municipalities and the rest of the surveyed areas unveils changes in the impacts of the sociodemographic variables on the probability of choosing the mode of transport. Results also signal time distance to central locations where jobs and services tend to concentrate as a critical aspect to take into account. These results pinpoint the need to design specific mobility policies addressed to mountain regions given the social and environmental consequences of car dependency.