Before revision:  Through the proposed methodology we have defined the core of a DSS for designing novel incentive mechanisms by operating on the policies in terms of QoI and user reputation scores .
After revision:  Through the proposed methodology we have defined the core of a DSS for designing novel incentive mechanisms by operating on the policies in terms of users' reputation scores, that also incorporate users' behaviours other than quality and quantity of contributions. Experimentally, we have considered the Waze dataset on vehicular traffic monitoring application and derived the disbursement of incentives comparing our method with baselines. Results demonstrate that our methodology, which also includes the local (microscopic) spatio-temporal distribution of behaviours, is able to better discriminate users' behaviours. This multi-scale characterisation of users represents a novel research direction and paves the way for novel policies on mobile crowdsensing systems .