Revenue Management and Operations Optimization for High Speed Rail

The increasing use of internet as a major ticket distribution channel has resulted in passengers becoming more strategic to fare policy. This potentially induces passengers to book the ticket well in advance in order to obtain a lower fare ticket, and later adjust their ticket when they are sure about trip scheduling. This is especially true in flexible refund markets where ticket cancellation and exchange behavior has been recognized as having major impacts on revenues. Therefore, when modeling this behavior, it is important to account for the characteristic of the passenger that optimally makes decision over time based on trip schedule and fare uncertainty. In this paper, the author proposes an inter-temporal choice model of ticket cancellation and exchange for railway passengers where customers are assumed to be forward looking agents. A dynamic discrete choice model (DDCM) is applied to predict the timing in which ticket exchange or cancellation occurs in response to fare and trip schedule uncertainty. Passengers’ decisions involve a two step process. First, the passenger decides whether to keep or adjust the ticket. Once the decision to adjust the ticket has been made, the passenger has the choice to cancel the ticket or to change departure time. The problem is formulated as an optimal stopping problem, and a two step look-ahead policy is adopted to approximate the dynamic programming problem. The approach is applied to simulated and real ticket reservation data for intercity railway trips. Estimations results indicate that the DDCM provides more intuitive results when compared to multinomial logit (MNL) models. In addition, validation results show that DDCM has better prediction capability than MNL. The approach developed here in the context of exchange and refund policies for railway revenue management can be extended and applied to other industries that operate under flexible refund policies.

• Record URL:
  • https://mti.umd.edu/sites/mti.umd.edu/files/NTC2014-SU-R-20%20Cinzia%20Cirillo.pdf
• 
• Summary URL:
  • http://ntc.umd.edu/node/37
• Summary URL:
  • https://mti.umd.edu/ntc/research/ntc2014-su-r-20-revenue-management-and-operations-optimization-high-speed-rail-pi
• Supplemental Notes:
  • This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  National Transportation Center at Maryland

  1124 Glenn Martin Hall
  University of Maryland
  College Park, MD  United States  20742

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Cirillo, Cinzia
• Publication Date: 2014-11

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; References; Tables;
• Pagination: 36p

Subject/Index Terms

• TRT Terms: High speed rail; Optimization; Yield management
• Uncontrolled Terms: Advance purchase tickets; Discrete choice models; Dynamic discrete choices; Railroad passengers; Refund policies; Ticket cancellation; Ticket exchange
• Subject Areas: Operations and Traffic Management; Passenger Transportation; Railroads;

Filing Info

• Accession Number: 01665613
• Record Type: Publication
• Report/Paper Numbers: Project ID: NTC2014-SU-R-20
• Files: UTC, TRIS, RITA, ATRI, USDOT
• Created Date: Apr 7 2018 12:19PM