Sustainable revenue management: A smart card enabled agent-based modeling approach
Public transportation operators (PTOs) function in an increasingly competitive environment that demands new approaches to revenue management for complex transportation networks. Revenue management is important for maximizing revenue growth and has commonly been performed by optimizing product availability and price levels. However, PTOs operate in a sensitive societal context that requires innovative approaches to revenue management. In this paper, we propose a new, sustainable perspective on revenue management that considers individual customers' needs and requirements, environmental impacts, and PTO's financial viability. To demonstrate this perspective's efficacy, we developed a decision support tool using an agent-based modeling and simulation approach. The advantage of this microscopic method is its ability to capture the detailed operational and commercial aspects of transportation networks, as well as the heterogeneous consumer preferences relating to product price and service quality. We evaluated our modeling approach using real-world smart card transaction data collected from a major Dutch public transit authority. The results suggest that, by taking a customer-centric view and using an IT-enabled decision support system, PTOs can better explore the space of feasible solutions to find revenue management strategies that can lead to a sustainable situation.
sustainability revenue management smart cards agent-based modeling public transportation big data analytics multi-agent systems