MERLIN: Model to Evaluate Revenue and Loadings for Intercity



MERLIN: Model to Evaluate Revenue and Loadings for Intercity

Authors

HOOD I S A, TCI Operational Research, UK

Description

In the years running up to privatisation, the various train operators of_British Railways looked into how they could design ticket structures by using yield management. They wanted to encourage price sensitive people to travel on the lighter loaded trains

Abstract

In the years running up to privatisation, the various train operators of_British Railways looked into how they could design ticket structures by using yield management. They wanted to encourage price sensitive people to travel on the lighter loaded trains without crowding out established and high-fare passengers at peak times. For example, one product that was introduced was the Apex ticket. This is much cheaper than other tickets, but has to be booked at least one week in advance and is quota controlled so that only a few, or none, are available on busier trains.

The breakup of the British Railways network into 25 individual Train Operating Companies (TOCs) has both intensified and fragmented this outlook. TOCs now have more freedom (albeit subject to regulation) to design their own timetables and fares structures that maximise their benefits. At the same time, they are coming under more scrutiny as to the standard of the products they offer, for example the crowding conditions on peak trains.

Also, there is now the possibility of competition between TOCs. On flows where 2 or more TOCs provide services, one is nominated as the 'lead operator.' They set the fares for the 'interavallable' tickets which can be used on any operator's service and which are subject to fares regulation. However, the other TOCs on this flow (the 'minor operators') are additionally allowed to introduce their own tickets which are valid on their services only. Their fares are not subject to regulation. This type of competition is mostly limited to flows where 2 or more operators were running services prior to privatisation. But the plan is to open it up more in the future, giving TOCs more freedom as to where they can run services.

In this changing environment, the Great Western Trains Company approached TCI Operational Research to build a model that could help them design their timetable and fares structure. Since then we have spent over 2 years developing a model called Merlin. In this paper we describe our methodology and how we approached calibrating the model so that it matches observed behaviour.

Publisher

Association for European Transport