Sustainable revenue management: A smart card enabled agent-based modeling approach

Authored by Milan Lovric, Ting Li, Peter Vervest

Date Published: 2013-03

DOI: 10.1016/j.dss.2012.05.061

Sponsors: Netherlands Organization for Scientific Research (NWO)

Platforms: MATSim

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

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. (c) 2012 Elsevier B.V. All rights reserved.

Tags

Agent-based modeling Multi-agent systems Sustainability Big data analytics Public transportation Revenue management Smart cards