Over the last decade, the growth in the availability of smartphone applications has profoundly reshaped transportation systems, with far-reaching active implications for travel demand. The adoption of financial instruments (e.g., quotas, monetary rewards, lotteries, incentives, etc.) in transportation smartphone applications has persuaded drivers to optimize their travel behaviour. For example, smartphone applications can provide information to travellers prior to their trips and en-route to help them avoid congested routes or events using a combination of public and private sector data and advanced analytics. Furthermore, incentives, an essential source of added value, often serve as the core attraction of the Mobility-as-a-Service (MaaS) value chain. Evidence has shown that some incentive instruments foster sustainable changes in travel behaviour and MaaS usage, while others introduce new barriers, such as induced demand.

There is no clear conclusion so far as to whether incentives are defeating jams or exacerbating them, as officials and academics are unable to measure app-reliant volume. There is a great need to develop methods to evaluate and validate the impact of incentives on both individual- and system-level performance. Besides, data-driven or model-driven Incentive-Based Active Demand Management (ADM) strategy optimization (considering financial and marketing restrictions) can also facilitate adaptation by improving applicability and robustness.

This Special Issue aims to solicit recent research on trends in traffic demand management and the MaaS value chain to find possibilities of using new forms of financial instruments, specifically incentives. Original research and review articles related to the theoretical development, modelling, simulation, and empirical experimentation of Incentive-Based ADM applications used for changes in individual-level travel behaviour or system-level congestion alleviation are welcome.

Potential topics include but are not limited to the following:

• Behavioral economics of financial instruments (e.g., tolling, incentives, quotas, etc.)
• Advanced modeling of active demand management
• Fine-, coarse-, or fixed-pricing in active demand management
• Pricing and investment of incentives
• Political economy of active demand management
• Mobility-as-a-Service with implementation of incentives
• Empirical validation of incentives in the Mobility-as-a-Service value chain
• Emerging methodologies in travel behavior data collection
• Advanced simulation models to emulate the adoption of active demand management or Mobility-as-a-Service