Integrating Decision Field Theory Within System Dynamics Framework for Modeling the Adoption Process of Ride Sourcing Services

The rise of ride-sourcing services has changed the transportation industry, reshaping urban mobility services. This paper presents an integrated framework of the adoption of ride-sourcing services and its impact on transportation markets using a combined approach of System Dynamics (SD) and Extended-Decision Field Theory (E-DFT). Drawing on data from ride-sourcing platforms such as Uber and Lyft, the study investigates the temporal dynamics and trends of ride-sourcing demand. SD modeling is employed to capture the complex interactions and feedback loops within the ride-sourcing ecosystem at system-level. The integration of System Dynamics and extended DFT allows for a more comprehensive and holistic modeling of the ridesourcing market. It enables exploration of various scenarios and policy interventions, providing insights into the long-term behavior of the market and facilitating evidence-based decision-making by policymakers and industry stakeholders while accommodating individual users' decisions based on changing preferences and environments.