Collecting mobility data is a notoriously costly and time-consuming activity. Making this process more efficient saves resources for the benefit of the most important element of a successful transport company: the quality of service. Furthermore, determining and providing load data for subsidies and bonuses requires working on the basis of empirical data.
The same is true for companies in other sectors that, having another core business, struggle to allocate the necessary resources to collect data and analyse the mobility of their employees, making it difficult for mobility managers to obtain the necessary information to prepare a really effective mobility plan that induces their employees towards more sustainable mobility.
Data analytics, together with data collection, both with innovative and traditional methods such as questionnaires and focus groups (related to personal traits, attitudes, habits, travel behaviour, daily activities, etc.), allow new strategies to be identified. This will make it possible to identify new variables influencing mobility behaviour, which will be useful for rethinking current services and developing new behavioural theories compared to the current ones (e.g., Theory of Planned Behaviour, TransTheoretical Model, the Stage model of Self-regulated Behavioural Change, ecc.).
The collected and analysed data can be visualised using a variety of tools such as GIS, web mapping, intuitive dynamic graphs that our experts will present to customers in detail.