A latent class choice based model system for railway optimal pricing and seat allocation

Homogeneous service with heterogeneous products: Relationships among airline ticket fares and purchase fences

“…Thirdly, the proposed concept can also be extended to other transportation fields such as cruise (Sun et al, 2011) and parking (Guadix et al, 2009) to explore the influence of different types of fences. Last but not least, the developed model can be incorporated into a revenue optimization problem for seeking the optimal resource allocation (Hetrakul and Cirillo, 2014 …”

Can You Get a Ticket? Adaptive Railway Booking Strategies by Customer Value

“…Similar research has been conducted in the railway system, but as far as the authors are aware, there are only the works of Cirillo et al (2011), Hetrakul and Cirillo (2013), Piening et al (2013), Hetrakul and Cirillo (2014), and Chen and Wang (2013). However, these two fields are still focused on applying their results to decide the amount of seat overbookings and the allocations of seats among different fare classes, rather than identifying an individual's value to decide how to respond to the individual's request.…”

“…Cirillo et al (2011) established an MNL model for the railway industry to explain passengers' choice of booking time, and combined it with a linear-regression demand function to find optimal fares. Hetrakul and Cirillo (2014) further used their logit and demand models to jointly decide optimal ticket prices and seat allocations.…”

Joint Decision Model of Group Ticket Booking Limits and Individual Passenger Dynamic Pricing for the High-Speed Railway

“…Zheng et al [25] and Zheng et al [26] applied dynamic pricing to China's high-speed railway and proposed appropriate fare grades and optimal prices. Hetrakul and Cirillo [27,28] first formulated latent class and mixed logit models by internet booking data to analyze railway passenger choice behavior, then proposed a joint optimization model for pricing and seat allocation with the assumption of deterministic demand. All studies of railway revenue management are based on prepared line planning [29], train diagrams [30], and timetables [31].…”