The Impact of Rail Fares Complexity on Demand Paul Metcalfe (PJM Economics) Chris Heywood and Rob Sheldon (Accent) Tony Magee (ATOC) Paul Metcalfe Tel +44 (0)1202 831 316 paul@pjmeconomics.co.uk

Rail fares complexity: pros and cons A complex fare structure benefits customers as it offers the opportunity to find the preferred combination of cost, speed, flexibility, and comfort. But complexity may also become a barrier to ticket purchase for customers who are not willing or able to apply the necessary time and effort to evaluate all the options. The current fare structure in the UK is perceived as complex. Which? (2011): Only 1% of rail passengers interviewed correctly identified all the various restrictions of Advance, Off-Peak, and Anytime tickets SPAFT (2011): 15% stated they had previously purchased a ticket that was not valid on the train they were taking and therefore had to purchase another ticket MW - Change to 1st bullet

Relevant previous work Accent 2013 sought to determine the optimal number of fares and conditions for a flow in terms of maximising demand. Found that consumers can ‘buy into’ increased complexity if they can see that this provides cheap deals and this is the price area that they focus on. Relevant but excluded Advance fares. SPAFT 2011 did incorporate Advance fares and found a broad lack of understanding or awareness of Advance tickets and restrictions. But did not quantify the elasticities of demand or revenue with respect to simplification or appraise the desirability of alternative fares regimes. MW - Changed to clarify the position in relation to guidance

Purpose of this study Overall objective Specific objectives To understand the impacts on passenger demand of simplification of the fares structure, with a particular focus on Advance fares Specific objectives To estimate whether the typical Advance fares structure coexisting within the overall fares regime has any adverse impact on demand To determine if a more optimal Advance fares structure may exist that differs from the typical Advance fares structures offered currently The overall objective of the study was to look at the potential traffic impacts of the proposed Sizewell C construction on the wellbeing of local communities in an innovative and comprehensive manner which complements traditional modes of transport assessment. The study results are intended to inform Suffolk County Council in their discussions with EDF Energy on means of addressing the impacts.   More specifically, the research aimed to achieve the following objectives: To review approaches to assessing the social and community impacts of changes in traffic flows (especially HGVs) on people within directly affected communities, identifying best practice and also any correlations between pre-construction perceptions and actual experiences during construction. To research, through appropriate engagement activities with individuals in communities living (relatively) nearby the route, the perceived effects of an increase in traffic flows on the B1122 and the A12 through Yoxford, having regard to any previous comparable experiences. To analyse the type, scale and range of impacts that are envisaged to arise, to examine the consistency and consensus in such views and to identify any correlations between those views and respondent characteristics such as their location and socio-economic profile.

Survey sample Pilot study 1 119 observations Pilot study 2 Main stage 1041 observations Web survey Route: London-Leeds 93% bought a train ticket in the last month 22% of these considered making the trip by car

Survey design: matching real world complexity Ticket type choice Do not travel by train Train service choice

Alternatives OR Advance Anytime 58 different ticket types Offpeak Super-offpeak 25 possible train services Preferred departure/arrival time + 12 earlier and later services (increments equal to the base frequency for the route in question) Respondents who chose an off-peak or super-offpeak tickets, or a ticket that is specific to a company do not see all the options Single/return, first class/standard, valid on any company/valid on specific train-operating companies OR “Not train” alternative

Complexity levels The alternatives shown depend on a ‘complexity’ attribute, with four levels 1 As now: The price of advance tickets varies from service to service. 2 The price of advance tickets is the same whichever train service is booked. 3 Advance tickets will no longer be offered for sale and so passengers would have to choose one of the other ticket types, or not to travel by train at all. 4 A more expensive Advance is added to the offer that is valid in a time band rather than just on a specific service. Current-style Advance tickets would also be available in this scenario.

Other attributes Relative to the base fare Fare 9 levels, from -20% to +20%, in 5% increments Duration Relative to the base duration

Analysis: Nested mixed logit model Lower level train service choice One separate choice for each leg (outward and return) Variables: fare, duration, deviation from ideal departure/arrival time Log sum term The expected utility from the choice of train service if a ticket type is chosen, depending on the restrictions regarding the train operating company they can be used on and on travel on off-peak or super off-peak times Upper level ticket type choice One choice for each trip Variables: fare, ticket can be used on any service (for each leg), log sum term (each leg), “not train” alternative, “not train” alternative interacted with complexity levels 2, 3, and 4

Results: train service choice Variable Coef. Std. error P>|z| 95% Conf. Interval Fare -0.114 0.003 0.000 -0.120 -0.108 Duration (hours) -0.428 0.063 -0.551 -0.304 number of hours after ideal departure/arrival time -0.898 0.050 -0.996 -0.801 number of hours in excess of 2 hours after ideal departure/arrival time -2.349 0.100 -2.545 -2.153 number of hours before ideal departure/arrival time -1.926 0.069 -2.063 -1.790 number of hours in excess of 2 hours before ideal departure/arrival time -1.496 0.128 -1.746 -1.245

Results: ticket type choice Variable Coef. Std. error P>|z| 95% Conf. Interval fare -0.035 0.001 0.000 -0.036 -0.034 ticket can be used on any service in the outward leg -1.653 0.072 -1.794 -1.512 ticket can be used on any service in the return leg -2.181 0.098 -2.374 -1.988 logsum (outward leg) 0.275 0.019 0.239 0.312 logsum (return leg) 0.146 0.017 0.113 0.180 Not train -9.605 0.468 -10.523 -8.688 Not train * Complexity level 2 (all advance tickets same price) 1.056 0.216 0.632 1.480 Not train * Complexity level 3 (no advance tickets) 4.799 0.401 4.013 5.585 Not train * Complexity level 4 (flexible-advance tickets available) -0.086 0.222 0.698 -0.522 0.349

Results: share of preference Origin: Leeds, Destination: London Ticket type Complexity levels 1 (As now) 2 (All advance tickets same price) 3 (No advance tickets) 4 (flexible-advance tickets available) Advance Single 43.27% 45.60% 0% 18.92% 1st class 30.23% 22.93% 12.63% Advance Flexible 42.63% 16.00% Anytime 4.15% 4.53% 8.46% 1.48% 1.19% 1.29% 2.38% 0.42% Return 4.61% 7.48% 1.47% 1.78% 1.79% 3.18% 0.62% Off-Peak 7.11% 7.88% 13.38% 2.50% 1.86% 1.61% 0.53% Super Off-Peak 1.41% 2.16% 0.47% 5.33% 6.77% 7.49% 2.18% Not train 0.43% 1.35% 53.86% 0.16%

Preliminary conclusions If all advance tickets had the same price, the impact on overall rail demand would be negative, but likely to be small. The impact on the share of the different ticket types would also be small If advance tickets were not available, the demand for rail travel from Leeds to London would fall more than 50% New “flexible advance” tickets could take more than 50% of the market

Next steps Segment results (users vs. non-users, frequent vs. non-frequent users, journey purpose) Calibration of results to reflect real-world market shares of train vs. other modes and of the different train ticket types Design tool to simulate the impacts on rail demand and revenue for hypothetical changes in the availability of ticket types and fares