Institute for Transport StudiesFACULTY OF ENVIRONMENT

GROWING AND UNDERSTANDING PASSENGER RAIL DEMAND

What Can be Learnt fromRecent British Experience?

Professor Mark Wardman

OBJECTIVES OF PRESENTATION

• THEME OF TALK:

Are there lessons to be learnt from British railway experience?

• FOCUS OF TALK:

Commercial: evolution of passenger demand and revenue

• SCOPE OF TALK:

Suburban and inter-urban rail but not tram/metro

• STRUCTURE OF TALK:

Why is British Railway Experience Relevant?

What is happening in Britain and how do we understand it?

What might Argentine Railways learn from Britain?

BACKGROUND: THE CURRENT ORGANISATION OF UK RAIL

SINCE 1995 …….

•Separate infrastructure provider (Privatised Railtrack and then Public Sector Network Rail)

•19 franchised train operating companies, 5 open access train operators, 12 parent companies

•Franchises were 7 years, now minimum 10 up to 22 years

•Office of Rail Regulation - Economic and Safety Regulation

•Department for Transport – specifies, awards and monitors franchises

•3 rolling stock leasing companies

LEARNING FROM

INTERNATIONAL EXPERIENCE • France

Extensive and pioneering high speed network

RER excellent suburban network

BUT outside main lines and Paris: poor service, financially unviable, cost inefficient – SNCF 1937 model

• JapanVery dense and efficient network, and impressive high speed services

Privatised 1980s – vertical integration.

Highest rail mode share worldwide (31% of pass km)

• SpainImpressive high speed network

Starved of investment elsewhere and serious financial problems

LEARNING FROM INTERNATIONAL EXPERIENCE

• Germany Efficient

Strong patronage growth

Commercial objectives in long distance, competitive tendered local/regional

Gradual liberalisation

• Switzerland

Regular interval timetable with excellent connectivity

Very reliable services

Highest rail shares in Europe (18% against EU27 of 6%)

Strong and sustained demand growth

LEARNING FROM INTERNATIONAL EXPERIENCE

• Great Britain

High fares (Only 42 per cent of passengers are satisfied with the value for money for the price of their ticket)

Only 109 kilometres of high speed (300 kph) line

A 150 year old rail network near to capacity

Poor integration between modes (and sometimes between rail services)

Rail share 7% (much less outside London)

Only 1 metro system and only 5 cities with a light rail system (route!)

• So what can possibly be learnt from Britain?

BRITISH EXPERIENCE

Wide range of experience and practice that impacts on revenue

•Privatised but regulated Price controls on monopoly infrastructure provider and operators

Competition for the market (19 franchised operators)

On-track competition (5 open access operators and where franchises overlap)

•Commercial objectives since 1980sLong distance flows operating profit in 1980s

Incentives contribute to strong revenue growth

•Long history of structured economic/financial appraisal

Passenger Demand Forecasting Handbook (since 1986)

London Underground New Victoria Line Appraisal (1963)

Cambrian Coast (Rural Railway) Closure Appraisal (1969)

BRITISH EXPERIENCE

• Extensive Data on Rail DemandTicket sales 2000+ to 2000+ stations by four weekly period, numerous ticket types and covering many years

In 1980s, largest data set outside the Pentagon!

Management information not just accountancy system

• Supported Extensive Analysis of Travel Demand (see below)

• Appreciated other data sources (see below)

• Unprecedented demand growth (see below)

• Track record of innovation and initiatives (see below)

• Some impressive recent performance statistics (see below)

• LOT OF PRICING/MARKETING INNOVATION AND INITIATIVES

• RECENT UNPRECEDENTED DEMAND GROWTH

BRITISH EXPERIENCE

• Evidence of Supporting Extensive Research Evidence Base

• Major review studies/meta analyses have revealed:

UK prices elasticities (Wardman JTEP 2014)

167 UK studies and 1633 elasticitiesRail ticket sales data: 66 (40%) studies and 931 (57%) elasticities

UK journey time elasticities (Wardman Transportation 2012)

377 time elasticities from 69 UK studiesRail ticket sales data: 44 (64%) studies and 263 (70%) elasticities

UK valuations of time (Abrantes and Wardman, Trans Res A 2011)

1619 valuations from 203 UK studies303 (19%) from 56 (28%) studies commissioned by Railway Industry

UK valuations of reliability (Wardman and Batley, Transportation 2014)

11 studies and 40 late time values, 6 studies and 36 late time elasticities

COVERAGE OF RAIL FUNDED RESEARCH IN UK

In addition to key factors of fare, journey time and economic activity, many research studies covering a wide range of issues (E.G):

•Car parking provision•Security at stations•Crowding (seated in crowded trains and standing up)•On-train and off-train information provision•Revenue protection•Station improvements and staffing•Different types of seating layout •Recovery time•Cleanliness •Rolling stock type, design and comfort•On-board facilities (e.g. catering, wi-fi, toilets, information)•And many more ………..

COUNTRIES WITH LARGEST DEMAND GROWTH (%)

2010/1990 2010/2000

Sweden 72 38

Great Britain 70 47

Belgium 59 35

Switzerland 51 52

Spain 47 13

Netherlands 42 7

France 40 27

Germany 39 13

RATIO OF DEMAND 2011 TO 2007

Germany 0

France -1.5

Netherlands –.4

Spain -3.1

Swiss+3.3

Sweden+1

UK -4.3

Belgium 0.5

EU EUROPEAN RAIL COMPARISON STUDY 2013“We made clear in our 5 year plan published in January that we are under no illusion about the challenges that both we, and the passengers who use the railway, face on a daily basis, and the need to keep improving from the low base to which Britain's railway had sunk in the 1990s.

We continue to work with other railways so that we can all learn from best practice in our businesses and we welcome efforts by the Commission to provide improved consistency and transparency of data.”

David Higgins, chief executive, Network Rail

•Passenger satisfaction evidence for a mix of changes since 1990s and current relative performance

•14 attributes – for example: satisfaction, productivity, mode share, reliability, safety, demand growth …..

•UK top in 4, second in 2, third in two and fourth in 3

•UK top passenger satisfaction overall of 25 EU railways

(Germany 7th, France 10th, Italy 23rd)

BRITISH EXPERIENCE• Track record of price/marketing innovation and initiatives

1968 selective prices manual moved from distance to market based pricing

1970s – ‘two part pricing’ – Railcards purchased to allow discount fares

1980s – ‘Saver Fares’ for long distance market.

– Extensive promotional offers (2 for 1, add-ons, multi-buys, joint promotions with retailers)

1990s – Yield Management

2000s – fares regulation

– more fares innovation (discount tickets now 40% revenue)

– More promotional offers (Direct marketing, reward schemes, add-ons, trial offers)

• Higher (lower) prices in inelastic (elastic) markets.

• Use spare capacity in off-peak

• Minimise abstraction from higher revenue

AN EXAMPLE: MANCHESTER TO LONDON

Price differentiation in UK far exceeds anywhere else

•First Class Any Train Peak Single £230

•Standard Class Any Train Peak Single £160

•Standard Class Any Train Off-Peak Single £78

•First Class Advance (Specific Train) £30 (Off-Peak) - £210 (Peak)

•Standard Class Advance (Specific Train) £20 (Off-Peak) - £140 (Peak)

£1 ≈ 14 ARS

BRITISH EXPERIENCE

• Rail Passenger Demand Doubled since 1995 privatisation• Peak Rail Arrivals London Commuters 31% increase since 1996

(over ½ million passengers per day)• National rail fares increased on average by 89 per cent between

1997 and 2012, which corresponds to a 22 per cent increase in real terms.

• 6 per cent real terms reduction in motoring costs over period, while bus fares increased in real terms by 28 per cent.

• Government support £ per head (per pass km)Britain 85 (0.10) Sweden 244 (0.21)Switzerland 226 (0.09)Germany 141 (0.14)

PRIVATISATION EFFECT ON DEMAND• Privatisation/franchising has stimulated demand by:

Innovations and initiativesNewer rolling stockMore frequent servicesBetter performanceLow priced fares on some routes (demand at expense of revenue)

• But other factors at work

Structural change/regionalisationMobile technologyCar congestion Car use, company cars, student debt, inner city living

• Considerable uncertainty as to what has caused recent demand increases

• Empirical evidence on privatisation effect on demand is limited

WHAT WAS HAPPENING AT TIME OF PRIVATISATION?

Actual and Forecast Growth 1990-1998Flows GDP

Growth

ForecastGrowth

ActualGrowth

To London 100-200 miles 11.8% 6.3% 59.4%To London > 200 miles 10.5% 6.3% 53.6%Non London <20 miles 11.6% 5.6% 11.3%Non London 20-100 miles 12.0% 10.7% 18.2%Non London 101-200 miles 12.8% 10.7% 33.9%Non London > 200 miles 12.6% 10.7% 28.4%SE to London >20 miles 20.9% 5.0% 23.1%

WHAT EXPLAINS WHAT HAPPENING AT PRIVATISATION

Estimated Determinants of Demand (Multipliers)

  London Non London South East

GDP 1.301 (1) 1.196 (1) 1.149 (1)

Car Time 1.043 (4) 1.031 (5) 1.067 (3)

Fuel Cost 1.045 (3) 1.056 (2) 1.049 (5)

Population 1.038 (5) 1.022 (6) 1.055 (4)

Car Ownership 0.975 (6) 0.951 (3) 0.972 (6)

Post 1995 1.119 (2) 1.033 (4) 1.092 (2)

Total 1.606 1.307 1.440

PASSENGER DEMAND FORECASTING HANDBOOK

• Unique amongst railway administrations worldwide

• PDFH came about in 1986:

Provide consistent and solid basis for investment appraisal across BR

Supporting well founded investment proposals at Dept for Transport

• Intention to update regularly with evidence base

First Edition June 1986Second Edition 1989Third Edition 1997Fourth Edition 2002 Fifth Edition 2009

• Demise predicted post privatisation (or 25 sets of values)

• Was the worst kept secret in the nationalised rail industry

• Now widespread access through a ‘research club’

22

PDFH: ELASTICITY DRIVEN FORECASTING APPROACH

)(exp basenew

p

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POP

GDP

GDP

V

V

t

base

new

b

base

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c

base

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l

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BUSTIME

BUSTIME

BUSCOST

BUSCOST

CARTIME

CARTIME

FUELCOST

FUELCOST

r

base

new

a

base

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h

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AIRHEAD

AIRHEAD

AIRCOST

AIRCOST

BUSHEAD

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Employment instead for seasons/commuting trips GDP is per capita

g

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f

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GJT

GJT

FARE

FARE

23

FARES FORECASTING

Suppose we have a system of tickets (could be modes)

ARF fA

fR

fF

f FFFFaV 11111111

FAFRFFF fA

fR

fF

fFF FFFFaV 1

1 RARRRFR f

Af

Rf

Ff

RR FFFFaV 11

AfA

fR

fF

fRA QFFFFaV AAARAFA1

1 ………… plus other terms This is the Department for Transport’s STRATEGIC FARES MODEL used in regulating fares

CUSTOMISING THE CROSS ELASTICITIES

jii

jjjij V

Vff

fij is cross elasticity of demand for mode i (rail) with respect to some variable (say cost) on mode j (bus) Vj/Vi denotes the relative shares of j (bus) and i (rail) ji is the ‘diversion factor’ – proportion of change in mode j (bus) who divert to mode i (rail) when mode j (bus) changes Demonstrates variability of cross elasticities PDFH uses to customise mode and ticket type cross elasticities Also used conditional elasticities (for example, for reduce tickets is:)

fr_Cond = fr1 + frf + frr + fra

TIMETABLE RELATED SERVICE QUALITY (GJT)

V =kGJTg GJT = J + S + I J is the station-to-station journey time S is the service interval penalty I is the sum of the interchange penalties for any interchanges required.

Implicit elasticities to the three components are:

GJT

Ig

GJT

Sg

GJT

Jg ISJ

g is GJT elasticity, NOT time elasticity

26

RELIABILITY AND OTHER VARIABLES

g

base

basenewr

base

new

GJT

LLw

V

V

)(1

L is average lateness of trains in ‘base’ or ‘new’ situation wr is the weighting to convert one minute of lateness into equivalent journey time

Analogous approach for:

Crowding (Seated in crowded train or standing) Access/Egress Time New Rolling Stock On-board facilities So overall PDFH covers all the main variables of interest

HOW IS PDFH APPLIED IN PRACTICE?

The practical applications here covered are:•Business Planning – Trend Growth•Franchise Bidding – External Factors in Action•Reliability Incentives – Schedule 8•Government’s Medium Term Strategic Objectives – High Level Output Specification

But there are numerous other applications, e.g.•Fares regulation •Crowding appraisal•Revenue sharing among operators

LONGER TERM FORECASTING

FORECAST DEMAND INCREASES FROM GDP GROWTH (NON SEASONS)

  10 years 20 years

  1.5% 2.0% 2.5% 1.5% 2.0% 2.5%

Long Distance to London 33% 46% 60% 77% 113% 156%

Long from London 14% 20% 25% 31% 43% 56%

SE to London 19% 27% 34% 43% 61% 81%

Non London Core Long 19% 27% 34% 43% 61% 81%

Non London Non Core Long 13% 18% 23% 29% 40% 52%

Non London Short 13% 18% 23% 29% 40% 52%

LONGER TERM FORECASTING

• Value of a train company essentially driven by GDP and employment growth

• 1% per annum employment growth

13% season ticket growth after 10 years, 30% after 20 years

• 1% fuel price increases per annum

5% demand increase after 10 years, 10% after 20 years

• 1% congestion increases per annum

Up to 7% demand increase after 10 years, up to 15% after 20 years

• 1% bus fare increases per annum

Around 2% demand increase after 10 years, 4% after 20 years

FRANCHISE BIDDING

• The Department for Transport specifies the core franchise

Minimum service level, fares regulated (RPI + 1%), performance targets

• It then has built a ‘comparator model’ – PDFH compliant

• Uses this model to develop a ‘shadow bid’ to evaluate bids

• Franchise bidder can offer more or bid more

• Department evaluates bidders and selects preferred

HIGH LEVEL OUTPUT SPECIFICATION

• The High Level Output Specification (HLOS) sets out:

what the Government wants to be achieved by railway activities (during the period 2014 to 2019).

the funds that are available to secure delivery

• It is a statutory requirement of the Railways Act 2005.

• Does not specify the detail of how these strategic outputs met

• In period 2014/15 – 2018/19

train operators will pay £1.5 billion to operate franchises

Network Rail (Infrastructure provider) will get £18.3 billion grant (for new schemes and maintaining the existing infrastructure)

HIGH LEVEL OUTPUT SPECIFICATION

• For the period 2014-2019, the government declared four priorities

‘Electrified Spine’

Increase capacity and improve inter-urban journey times

Facilitate commuting into major urban areas

Improves links to airports (and ports for freight)

• It specified the major investment projects it wishes to see

• It specified new targets on reliability, capacity

• It expected continued improvements in safety, passenger satisfaction and value for money

HOW DOES THE GOVERNMENT WORK OUT WHAT IT CAN AFFORD?

• PDFH provides the basis for evaluation

• But it is a forecasting equation not a modelling tool

• And it doesn’t cover ‘supply side’

NETWORK MODELLING FRAMEWORK

• PDFH application tool with supply/cost side

• 566 x 566 origin-destination zone pairs for whole of GB

• Full fare tickets, reduced fare tickets, season tickets

• Used to test options for High Level Output Specifications

NETWORK MODELLING FRAMEWORK

• For each Origin-Destination movement, specify changes in exogenous factors, fares and train services (GJT)

• Calculate changes to base demand

• Assign the base demand to the network

• Determine changes in crowding and performance

• Iterate the demand element due to changes in crowding and performance until convergence

• Determine operator costs

• Appraise – are schemes worth it?

RELIABILITY INCENTIVES: SCHEDULE 8 (I)

• Aim

to incentivise Train Operators and Network Rail to maintain and improve their operational performance

• Designed to

compensate operators for the financial impact of poor performance attributable to Network Rail and other train operators

align financial incentives - so improve operations where cost is less than benefits to operators. Operators consider impacts on other operators

provide appropriate signals for investment decision-making by all concerned

•  Revised based on PDFH evidence in 2000, 2005 and 2013

• All based on detailed information on train performance

RELIABILITY INCENTIVES: SCHEDULE 8 (II)

THE FINANCIAL CONSEQUENCES OF SCHEDULE 8

• Calculations using MRE done on flow basis.

• 2012-13 financial year Network Rail had to pay £136m to train operators as a result of delays caused

• This is 20% of the annual profits

• Schemes is incentivising improvements in reliability performance (see earlier graph)

SO WHAT IS TRANSFERABLE TO ARGENTINE RAILWAYS?

These conclusions based on commercial issues

•PDFH is unique worldwide and is worth copying!

•Create evidence base for Argentina - do not reinvent the wheel!

Use Evidence from Elsewhere

Use Experience from Elsewhere

•Avoid mistakes from UK

Ensure adequate funding of research – particularly matching/collaborative

Avoid parochial viewpoint

Take a long-term strategic view and plan

•Critical is to identify a Champion – person or organisation

SO WHAT IS TRANSFERABLE TO ARGENTINE RAILWAYS?

• Needs data to support evidence base

Record or measure the amount of travel (use new technology)Monitor the behavioural effects of improvementsCollect survey based evidence on travel patternsUndertake market research on passenger preferences and attitudes Observe peoples’ choices

• Need to build skill base

CONCLUSIONS

• Sustainable railway needs to be more financially secure

• Need to grow the market (as well as more cost efficient)

• Identify marketing (price, product, promotion, place) that

Have been successful elsewhere in growing the rail market

Are relevant to the Argentine context

• Give train operators the freedom, encouragement and incentives to grow the rail market based on best relevant international practice

• Need to monitor and understand the rail market

• Need effective means of appraisal