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National Statistics Quality Review Series
Report No.22
Review of Bus, Coach and Light Rail
Statistics
Published by:
Department for Transport
Theme: Transport, Travel and Tourism
Department for Transport
Great Minster House
76 Marsham Street
London
SW1P 4DR
Tel: 020 7944 3000
Website: www.dft.gov.uk
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©Crown Copyright 2003
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Contact points:
For enquiries about this review publication:
Hilary Hillier
Transport Statistics Personal Travel,
Department for Transport
Tel: 020 7944 4440
e-mail: Hilary.Hillier@dft.gsi.gov.uk
For enquiries on the review programme:
The Review Programme Management Team, ONS
Tel: 020 7533 6298 / 01633 812864
Email: ns.quality.review.teams.ldn@ons.gov.uk
National Statistics are produced to high professional standards set out in the National
Statistics Code of Practice. They undergo regular quality assurance reviews to
ensure that they meet customer needs. They are produced free from any political
interference.
Review of Bus, Coach and Light Rail Statistics
This is the second review to be published under the National Statistics Transport,
Travel and Tourism theme.
National Statistics Quality Reviews
In 1999 the Government issued the “ Building Trust in Statistics ” White Paper,
which set out the framework for quality assuring National Statistics outputs. This was
confirmed in 2000 with the launch of National Statistics and publication of the
Framework for National Statistics. A key component of the Framework is:
“ a programme of thorough reviews of key outputs, at least every five years, with the
involvement of methodologists and outside expertise, as appropriate. ”
This programme of quality reviews is an important way of ensuring that National
Statistics and other official statistical outputs are fit for purpose and that we are
continuing to improve the quality and value of these outputs.
NATIONAL STATISTICS QUALITY REVIEW SERIES:
REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
National Statistics Quality Reviews
1. The White Paper Building Trust in Statistics set out the framework for quality assuring
National Statistics. A key component of the framework is:
“A programme of thorough reviews of key outputs, at least every five years, with the
involvement of methodologists and outside expertise, as appropriate.”
This programme of Quality Reviews is an important way of ensuring that
National
Statistics and other official statistical outputs are fit for purpose and that we are continuing
to improve the quality and value of these outputs.
Further information can be found on the National Statistics website:
http://www.statistics.gov.uk/methods_quality/quality_review/quality_review.asp
Introduction
2. This review covers the collection, analysis and dissemination of all aspects of
statistics on bus, coach and light rail – including operators, vehicles, passengers,
fares, quality of service, satisfaction with service and security issues. There are
currently five separate DfT surveys collecting information on aspects of bus or bus
and coach operations. The statistics collected are used widely within and outside
government, brief details are provided below. As some of the surveys cover the
Devolved Administrations, colleagues in Scotland, Wales and Northern Ireland
were invited to contribute to the review.
3. The five primary sources are as follows:
a) Annual survey of Public Service Vehicle (PSV) operators; operators are
sampled according to their size (number of operator discs) with a 100 per cent
sample of the largest operators. Main outputs are estimates of bus and light
rail patronage (passenger journeys), vehicle mileage, vehicle stock and
passenger receipts. Coverage; GB.
b) Quarterly survey of bus fares; a panel of around 100 large operators provides
information on fare changes which is used in compiling a bus fares index.
Coverage; GB.
c) Bus passenger satisfaction; survey of bus passengers undertaken by National
Opinion Polls (NOP) on a three year contract. Survey started in May 2000 in
response to an initiative by the Deputy PM at the Bus Summit in November
1999. Passengers are asked to rate a number of aspects of the bus journey
they have just made. Coverage is England outside London (Transport for
London (TfL) conducts a related survey in London, which we use to generate
figures for England as a whole).
d) Bus reliability; a panel of around 100 large operators in England outside
London provide quarterly information on lost scheduled bus mileage. TfL
provide information for London to enable us to generate an England figure.
The information is used to monitor a target for lost mileage set at the Bus
Summit.
e) Assaults on bus crew and passengers, vandalism on buses; three separate
surveys involving a panel of GB bus operators, the police and TfL. DFT
administers the bus crew and vandalism surveys (quarterly and annual
respectively). Collation of data and analysis, the police survey and TfL aspects
have been contracted out for a number of years, most recently to Oscar Faber
(contract ended in July 2001, no follow-up to date).
4. The results of these surveys are published in two DfT publications, the
annual ‘Bulletin of Public Transport Statistics GB’ and the quarterly ‘Bus
Quality Indicators’, both are available on the DfT transport statistics web site,
www.transtat.dft.gov.uk Statistics are also published in the annual ‘Transport
Statistics GB’, ‘RegionalTransport Statistics’ and ‘Transport Trends’.
Other sources of information are:
a) Bus and coach journey information for GB collected in the National Travel
Survey (the NTS has already been reviewed, the report is available at:
http://www.statistics.gov.uk/methods_quality/quality_review/downloads/1_NTS_re
port.pdf).
b) DVLA data on age of the GB bus fleet; administrative data derived from DVLA
vehicle registration database. A target for the age of the bus fleet was set at
the Bus Summit, this was the most convenient source of information at the
time.
c) ONS Corporate Services UK Price Index covering private coach hire.
d) The range of GB data held by Traffic Commissioners on local bus service
registration, operator licensing and monitoring.
e) GB Health and Safety Executive statistics on assaults on bus crew.
Scope of the Review
5. The review addressed the following questions in the consultation phase:
1.1
General Questions

Who are the data users?
(i)
What are the users’ needs from the outputs and do the outputs meet
those needs?
(ii)
Are we efficient and effective in meeting user needs?
(iii)
If not, what improvements should be introduced?
(iv)
Are there aspects of timeliness or cost effectiveness that can be
improved? (e.g. electronic data supply).
(v)
Are the inputs and methodologies used appropriate, and are they of
sufficient quality to meet purposes?
(vi)
Is the burden on data suppliers justified and held at the minimum
required level?
(vii)
Can any of the information on quality which is made available to users
be improved?
(viii)
Are there alternative data sources? (including non National Statistics
sources of sufficient quality/reliability).
6. The topic areas covered by the Review were:
i)
Local bus use (GB)
This includes patronage, vehicle kilometres and passenger receipts from the
annual PSV survey. Characteristics of local bus users and journey purpose from
the NTS.
Some specific areas investigated:





ii)
Usefulness of financial questions in PSV survey.
PSV survey; is it possible to collect reliable sub regional patronage statistics/ is
there a demand for such statistics?
Are NTS data consistent with PSV survey data? Is the operator measurement
of passenger journeys accurate/consistent?
Is there a demand for data on service volume (vehicle km) by peak/off peak,
weekday/weekend?
How reliable is the NTS rural accessibility indicator?
GB Coach travel and other non-local bus use (including contracts, charters
and tours).
Coach data are collected in the PSV survey and NTS.

Is there a case for producing patronage data, could NTS be used to provide
accurate estimates?


iii)
Or is PSV survey the best source? How could data collection/response be
improved?
What further information is needed on these services?
GB Local bus fares/pricing
Information collected in the DfT quarterly survey and used in the RPI. Pricing
information used by ONS in price indices.
Areas investigated:




iv)
Index methodology
Clarity of the bus fares survey form
Alternative methodologies
Quality of price indices used by ONS.
Local bus passenger satisfaction
Quarterly surveys of bus users in London and rest of England.
Areas investigated:








v)
The rating scale: are there better alternatives?
Usefulness of an extra question on service availability? (e.g. number and
frequency of services off-peak and at weekends).
Should importance of aspects of service be ranked? How would this information
be used?
Survey frequency, should it be less frequent?
Should published data be more disaggregated?
Should London and non London results be compared? Are there better
geographical comparisons?
Should there be a simple satisfied/not satisfied question? What form would it
take?
Is there a need for satisfaction data on ticketing (cash/smartcards/prepaid
tickets)?
Local bus reliability
Quarterly surveys of operated bus mileage in England and GB data collected by
Traffic Commissioners on number of services and punctuality.
Areas investigated:




Comparison of reporting in London and elsewhere – treatment of losses due to
traffic congestion.
Alternative methods of measurement.
Traffic Commissioners’ data supporting new reliability standards.
Local Authority data.

Extent of existing collection of data on bus punctuality (including by bus
operators).
Scope for collection of data on bus lane enforcement.

vi)
GB Bus related safety and security issues
Surveys of assaults on bus passengers and crew and vandalism, HSE statistics.
Areas investigated:


Establish whether there is still a need for these statistics.
If so, how can the information be collected most effectively? Specifically statistics
covering assaults on bus passengers.
Alternative data sources, e.g. HSE, bus company insurance records, Home
Office statistics.
Should more be collected on fear of crime?
Reliability of vandalism cost estimates.
London and outside London, are there data collection differences?




vii)
GB Vehicle statistics
Number and age of buses and coaches, low floor buses.
Areas investigated:








Age of Fleet; scope for regional or London/non London data.
Alternative sources, e.g. SMMT, TAS consultancy.
Scope for data to be collected from operators?
Quality of DVLA data base?
Stock of vehicles; which is best source (PSV survey, DVLA, other?).
Low floor fleet; best data source?
Possibility of separate data for bus and coach; age and fleet size.
Data on Euro emission standard.
viii) Light rail use in England
Detailed statistics on all light rail systems are collected annually as part of the PSV
survey. The Review Board considers that these should be part of the review, as light
rail is seen as providing a service similar to local buses.
Areas investigated:

Methods used by operators to produce patronage estimates.
Methodology
7. Following a competitive tendering process, WS Atkins were selected to carry
out the Review. The work was carried out under the supervision of a Review
Board (which met three times during the review programme).
The Review Board consisted of data providers, Departmental policy
customers, the Confederation of Passenger Transport (CPT), bus industry
representatives, an independent academic expert - Peter White of the
University of Westminster and data users (Annex A lists Review Board
membership). The majority of the work was in the form of 60 interviews with
data users and providers supplemented by larger workshop sessions, which
included a special meeting of the Transport Statistics Users Group. In addition,
comments could be sent electronically to the DfT and ONS web sites. The
methodology is set out in more detail in Chapter 1 of the Atkins report (Annex
B)
Recommendations
8. The Review produced over 30 recommendations. Some can be implemented
straightforwardly, others require more in depth consideration, and in some
cases a programme of work before they can be implemented.
9. The recommendations from the Review have been discussed with and
accepted by the Review Board. A full list of the recommendations (with report
paragraph references) and the actions proposed or already in hand are
presented in Annex C. A priority has been assigned to each recommendation.
10. The recommendations leading to the most substantive pieces of work are:
Local Bus Use
a) Improve the quality of patronage data and reconcile estimates from different
sources, especially at sub regional level. This is necessary in the light of the
demand for more detailed sub national data to support the local transport PSA
Delivery plan, LTPs, local PSAs and Best Value. DfT statisticians are already
visiting PTEs to investigate the differences between patronage figures produced
by PTEs and those published by DfT. They are also, investigating wide
differences between the patronage figures reported under Best Value Indicator
102 (number of annual bus passenger journeys at LA level) and LA level
estimates produced by DfT from the PSV survey. [Recommendations 4, 7 and
21].
DfT is planning to make available the most reliable sub regional data (subject to
any confidentiality constraints).
b) The need to develop indicators of service accessibility, in particular in response
to the recommendations of the Social Exclusion Unit study on transport. A new
branch has been established in DfT to progress this work, working closely with a
group of local authorities with expertise in this area. [Recommendation 5].
Non Local bus use
There is a demand for information on non-local patronage, especially for long
distance scheduled coach services. Collection of information on schools contracts
and Community Transport are also seen as gaps in the current statistics. DfT and
CPT will be meeting to discuss what it is feasible to collect in these areas.
[Recommendations 11-14].
Bus Fares
The current bus fares index methodology has remained unchanged for a number of
years. In that time, there have been a number of changes in bus travel: there is now
much more use of multi modal travel tickets, season tickets of varying duration, flat
fares and a wide variety of concessionary fares. DfT will be commissioning research
in 2003/04 to investigate this whole area (including the effect of multi modal tickets
on patronage estimates), with a view to introducing an improved local bus fares
index in 2004. [Recommendations 2, 15-18].
Punctuality
The Bus Partnership Forum of operators and local authorities will be starting work in
2003/04 to investigate the scope for the production of a national measure of local
bus service punctuality. This will also form part of the local transport PSA Delivery
Plan monitoring process. [Recommendations 25-27].
Safety and Security
The newly convened Safer Travel on buses and coaches Panel (STOP) and the
STOP data sub group will be progressing the Review’s recommendations on bus
crime and vandalism. [Recommendations 28-31].
11. Annex A sets out the membership of the Review Board, Annex B contains the
full WS Atkins report of the Review and Annex C the DfT’s proposed action on each
of the recommendations.
ANNEX A
REVIEW BOARD
Name
Hilary Hillier
Peter Openshaw
David Harley
Martin Higginson
Catherine Mason
Peter White
Andrew Thompson
Organisation
DfT –Transport Statistics
DfT – Bus Policy
Confederation
of
Passenger
Transport
Corus
Arriva plc
University of Westminster
Transport for London
Attending meetings:
David Champion DfT, TSPT1 – Review Manager
Mark Dickson DfT, TSPT1
Paul O’Hara DfT, TSPT1
ANNEX B
Report of Quality Review of Bus, Coach and Light Rail Statistics by WS Atkins Ltd.
ANNEX C
Full list of recommendations, with proposed DfT follow- up action.
ANNEX B
Quality Review of
Bus, Coach and Light Rail
Statistics
Final Report
QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
Contents
Section
1.
2.
3.
4.
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Page
Introduction
1
Background
1
The Review Process
1
Approach Stages
3
Structure of This Report
5
Local Bus Use
6
Key Datasets
6
Users’ Needs
6
Current Methodology
Quality Issues
11
14
Additional Needs
20
Recommendations
24
Non Local Travel
25
Datasets
25
Users’ Needs
25
Current Methodology
27
Quality Issues
Additional Needs
28
29
Recommendations
34
Fares
35
Dataset
35
Users’ Needs
35
Current Methodology
37
NTS
41
Quality Issues
Additional Needs
41
41
Recommendations
42
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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5.
6.
7.
8.
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Passenger Satisfaction
43
Dataset
43
Users’ Needs
43
Current Methodology
46
Current Methodology
46
Quality Issues
47
Additional Needs
47
Recommendations
51
Reliability
52
Datasets
Users’ Needs
52
52
Current Methodology/Quality Issues
55
Additional Needs
56
Recommendations
58
Other Themes
59
Safety & Security
59
Vehicle Stock
63
Light rail Statistics
67
Recommendations
69
Summary of Recommendations
1
General
1
Theme-Specific Recommendations
2
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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2.
Introduction
BACKGROUND
2.1
Atkins was commissioned by the Department for Transport (DfT) in April 2002 to
undertake a Quality Review of Bus, Coach and Light Rail Statistics for Great Britain,
as part of the Programme of National Statistics Quality Reviews.
2.2
The six month study aimed to assess:
 Users’ needs;
 How existing datasets meet these needs; and
 The quality of published statistics (particularly in terms of relevance,
accuracy, timeliness, accessibility and coherence).
2.3
The work was guided and appraised by a review board which was set up in
accordance with the Guidance on the National Statistics Quality Review
Programme1. The board comprised public transport planning experts, bus industry
representatives and relevant DfT personnel. A membership list is shown in the
Annex.
2.4
This report presents the findings of the review and our recommendations for
changes.
THE REVIEW PROCESS
2.5
Six different statistical themes were addressed in the review. These consisted of:
 Local Bus Use;
 Non-Local Bus Use;
 Bus Fares;
 Bus Passenger Satisfaction;
 Bus Reliability;
 Bus Safety and Security;
 Bus Vehicles; and
 Light Rail.
2.6
For the purposes of this report, a local bus service is one available to the general
public, where passengers pay separate fares and may board and alight within 24
kilometres (15 miles).
2.7
Non-local covers a range of different bus and coach services including express
buses, certain school buses, airport feeders, flexible/demand responsive services,
community transport, contract services, private hire and excursions. We recognise
1
A copy of Quality Review Guidance is available from the Review Programme Management Team at
ONS (Tel: 020 7533 6298 - GTN 3042 6298).
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that some of these can be registered as local buses for Fuel Duty Rebate (FDR)
purposes, but they have been included under ‘non-local’ for simplicity in this report.
2.8
The primary sources of data were:
 Annual survey of public service vehicle operators – which provides bus
patronage, vehicle mileage, vehicle stock and passenger receipts information.
 National Travel Survey – a household survey covering residents in Great
Britain, undertaken by the Office for National Statistics.
 Quarterly survey of bus fares – derived from a panel of around 100 large
operators.
 Quarterly survey of bus passenger satisfaction – passenger ratings’ of
aspects of their bus journey (England only).
 Quarterly survey of bus reliability – lost scheduled mileage data collected
from a panel of around 100 large operators in England outside London, and
equivalent data from Transport for London.
 Surveys of assaults on bus crew, passengers ad vandalism on buses – three
separate surveys involving a panel of bus operators in Great Britain.
2.9
Several other sources have also been included in the review and these are detailed
in the relevant chapter.
2.10
In addressing how the existing datasets meet users’ needs and how their value could
be increased, we considered various attributes of quality, including relevance,
accuracy, timeliness, accessibility, completeness, comparability, coherence,
awareness and cost. These are the core ‘review criteria’ that are mentioned
elsewhere in this report, however, their relative importance varied according to the
datasets being discussed.
2.11
Our review methodology rested on a number of key questions. These included:
 What are the purposes for which the data is being is being used? Do they
fulfil an end in themselves or are they inputs for other exercises?
 Are users’ requirements (gleaned through active consultation) being met by
the current sets of outputs?
 Are the inputs and methodologies used appropriate, and are they of sufficient
quality to meet the required purpose?
 Is the burden on operators justified and held at the minimum required level?
 Can the information which is available to users be improved? What are the
implications of those improvements in terms of DfT resources, the burden on
operators and the use that could be made with those improvements?
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APPROACH STAGES
2.12
There were several distinct phases in the approach adopted to address the main
aims of the study (as shown in Figure 1.1 below).
Figure 2.1 – Review Methodology
Methodology
Preparatory Audit
Policy Context
Appraisal
Preliminary Consultation
Consultation
Analysis

Relevance

Accuracy

Timeliness

Accessibility

Coherence

Others
Results
2.13
The initial phase consisted of an audit of datasets and published tables and a brief
review of the policy context which also included highlighting 10 Year Plan targets
relevant to the performance of bus, coach and light rail services. This phase set out
the context in which the review could take place.
2.14
In order to obtain an initial perspective on the overall appropriateness and quality of
the statistics and to obtain an indication of study priorities, we convened a workshop
including of a range of stakeholders (20th May). These stakeholders comprised bus
and coach operators (and association representatives), relevant DfT policy officers,
DfT statisticians, Passenger Transport Executive, local authority officers and
academic researchers. The workshop process consisted of examining national
statistics datasets and publication in terms of the review criteria.
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2.15
Following the preliminary consultation, a technical note was drawn up identifying how
the datasets were perceived to perform in meeting user needs, what were areas of
concern and what issues required further clarification. In discussion with the
Department, a second note was then prepared which was to be used in conducting
the main phase of the consultation.
2.16
This note essentially set out the priority questions to be put to operators, policy staff
and others in the course of subsequent interviews and workshops. These questions
sought, for example, to establish what information operators were looking for from
external sources, what uses academic researchers were making of official statistics,
what methods operators were using to calculate fare prices, how could coach
operators estimate non-local bus patronage and what solutions could be brought to
bear by the introduction and dissemination of new technologies in respect of
reliability and patronage estimation.
2.17
The main consultation phase of the study consisted of over 50 in-depth interviews
with operators, DfT staff, specialist consultants including both academics and private
sector experts and relevant market research companies. There were also two
workshops held with PTE and local authority staff directly involved in the collation,
production and policy use of bus, coach and light rail statistics.
2.18
The information yielded by the consultation phase was classified in terms of the
issues set out in the investigative note (which had grouped the issues by dataset
theme) and the review criteria were then applied to establish what are the users’
needs to be addressed as a priority, what are the perceived weaknesses of national
statistics and what improvements are being sought. Interim findings and
recommendations were obtained from the initial analysis and these were circulated to
the Review Board for discussion at a seminar (29th July 2002). The membership of
the Review Board comprised senior DfT statisticians and policy officers as well bus
company representatives, academics and representatives from relevant transport
agencies.
2.19
A considerable range of improvements were sought by consultees. As intended, the
Review Board offered their views on the appropriateness and relative importance of
the improvements sought. The recommendations made in this report have attempted
to reflect the priorities set out by the Review Board.
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STRUCTURE OF THIS REPORT
2.20
The main body of the report is structured according the dataset themes. Following
this introductory chapter:
 Chapter 2 addresses local bus use;
 Chapter 3 - non-local travel;
 Chapter 4 - fares;
 Chapter 5 – satisfaction; and
 Chapter 6 – reliability.
2.21
The remaining themes (safety and security, vehicles and light rail) are covered in
Chapter 7.
2.22
Each of the chapters has been structured in a systematic way to identify how the
data is currently used, issues associated with the current methodology, and aspects
of quality (analysed under headings of accuracy, robustness, relevance, burden,
accessibility, etc.), and unmet needs or additional data requirements.
2.23
The key recommendations are summarised in Chapter 8. Possible methodologies
and budgetary implications of the recommended feasibility studies are included in the
Annex, along with the members of the Review Board, a list of consultees involved in
the face to face interviews and a summary of metropolitan area survey
methodologies.
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3.
Local Bus Use
KEY DATASETS
 Data on passenger journeys (measured in terms of boardings), passenger
receipts and vehicle-kilometres (veh-kms) is collected annually through a
stratified sample survey of operators holding Public Service Vehicle (PSV)
operator’s licenses.
 Data on passenger journeys, travel distance and time, trip rates and time
taken to walk to bus stop is collected by the National Travel Survey (NTS) in a
weekly travel diary.
 Data on support and grants for local buses and concessionary fare
reimbursement is supplied by the relevant local authorities.
USERS’ NEEDS
3.1
The following section sets out the key user groups and their general needs.
Consideration of how the national statistics meet these needs, issues of quality and
proposals for improvements are given in subsequent sections.
Government
The key data needed are:
 patronage - to monitor
progress towards 10 Year
Plan target to increase
bus passenger journeys
by 10% (see panel);
 bus mode share - to
monitor the aspiration to
reduce car dependency
and increase use of more
sustainable modes;
Passenger Journeys on Local Buses
6,000
5,000
Passenger Boardings (mil)
3.2
4,000
3,000
2,000
1,000
 an indicator of general
service provision – to
monitor network coverage
and
bus
service
frequency;
0
89-90
90-91
91-92
92-93
England
93-94
94-95
Scotland
95-96
Wales
96-97
97-98
98-99
99-00
00-01
All Great Britain
Source: A Bulletin of Public Transport
Statistics, DTLR 2001
 rural bus service availability – to monitor progress towards the 10 Year Plan
target to achieve a one-third increase in the proportion of households within a
13 minute walk of an hourly or better bus service;
 indicators of people’s ability to access bus services in all areas and whether
services actually go to key local destinations to highlight areas of social
exclusion; and
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 financial information – the Government has limited powers to intervene in
setting fares, though there is a need to monitor fares increases to inform
decisions on concessions ,subsidies and other general policies.
3.3
In addition to monitoring and policy formulation, the local bus data are used to assist
Ministerial responses to Parliamentary questions (PQs), to inform Ministerial
speeches and to reply to letters/complaints from the public.
3.4
The consultation exercise showed that there is general satisfaction with the national
statistics that are currently published, though there was some need for passenger
kilometres to better describe the demand for bus travel. There was also a need for a
more comprehensive measure of ‘supply’ than vehicle kilometres to better reflect
changes in service provision and hence the attainment of the 10 Year Plan targets.
“Vehicle km is the best indicator we have of changes in bus services,
but it is not ideal. We want to know the passenger mileage.” (DfT
policy officer).
3.5
Service availability is particularly important from the point of view of social exclusion.
A Social Exclusion Unit study is currently underway to consider performance
indicators that would help monitor the impact of policies by area and by social
groups.
3.6
Whilst there is no formal policy requirement, there was also a desire to monitor the
take-up of multi-travel tickets which generally benefit regular users and those making
connections between services. The use of these tickets appears to be growing, and
as will be seen later, this can add to operators’ difficulty in estimating patronage.
“It would be useful to know about trends in the use of multi-travel
tickets, travelcards, etc.” (DfT policy officer)
“We need to understand levels of season ticket use to qualify fares
indices; the typical cost of travel may be falling with season tickets,
even though the single ticket price is rising.” (DfT policy officer)
3.7
There is a growing interest/need for local level information to feed into Best Value
Performance Indicators (BPIs), local Public Service Agreements (PSAs) and the
Local Transport Plan (LTP) process.
3.8
We feel that as this sort of information would be outside the general remit of the
national statistics. For instance, any study of the costs and benefits of LTP
investment would need to include information on other local measures aimed at
encouraging bus use/restraining car use, levels of operator investment and changes
to routes and timetables. This would be better undertaken by a local authority or a
research project looking at selected authorities as case studies.
“We want to know where patronage growth is happening and see if
it’s happening in areas that are targeted for investment.” (Scottish
Executive)
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Passenger Transport Executives & Local Authorities
3.9
Consultation with transport authorities showed that they make little use of the
national statistics. Some Passenger Transport Executives (PTEs) and local
authorities look to the national-level data for general trends (ie increasing patronage)
to compare with changes in their own area. The PTEs use the aggregated
metropolitan area statistics for background information and occasional
benchmarking.
3.10
The local authorities interviewed made little reference to the aggregated shires or
regional level statistics. They tend to use data specific to their area gathered from
local operators and their own surveys2 and they wanted data for other local authority
areas to enable comparisons. The focus is on patronage and modal split to evaluate
the success of their LTPs and their bus strategies, and to report on outcomes in their
Annual Progress Report (APR) to Government.
3.11
There was no common approach to conducting modal split
surveys among the PTEs consulted. Some have considered
using NTS booster samples3, but rejected these on the grounds
that they are too expensive, or could not be completed within
the required timescale. Contrary to Government advice, some
have opted for their own surveys and used the opportunity to
ask questions on attitudes to buses that would not be covered
by the NTS and gather essential baseline information on levels
of walking and cycling. (A summary of the survey
methodologies is included in the Annex.)
3.12
PTEs survey patronage to identify the proportion of concessionary fare users,
investigate the use of supported services and help allocate travelcard revenue
between operators. The findings4 are mainly used to compare against operator data
and provide some assurance of value for money, but they also help to understand
the effect of price changes on travel patterns and assist in planning future service
levels.
3.13
There was considerable interest in comparisons of the unit cost of supported services
between local authorities. Atkins is currently monitoring bus tender prices on behalf
of DfT, however, no decision has been taken on whether this information will be
published. As the agreed price for providing services is likely to be a function of local
circumstances (including levels of congestion, density of population, competition
between operators, etc), and these are likely to vary between areas, we would not
recommend that DfT publishes comparative tables in the Bulletin.
2
SYPTE is doing its own
travel surveys so it can
ask questions related to
social inclusion and
segregate
between
urban, rural and coalfield
areas.
The PTEs tended to be more successful than local authorities at gathering local data from operators,
possibly because they tend to be served by larger operators who have the resources to extract data
or they are more likely to have invested in measures to improve bus services (including electronic
ticketing machines that have made it easier to collect data). Despite the powers under the Transport
Act 2002, some local authorities are still unable to get local information from operators. The
consultation with operators showed that they only really collect patronage and veh-kms and some do
not have the technical capabilities or resources to split data on cross-boundary routes.
3 Local authorities can request, for a fee, that additional households be included in the NTS. The
returns from such booster samples are not included in the analysis of the general NTS survey.
4 The findings are a rich source of local information that have been used in academic studies.
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3.14
PTEs and local authorities include veh-kms as an indicator of supply in their APR, but
tend to investigate network coverage and the frequency and hours of operation of
services using map-based analysis5 to allow them to identify gaps in commercial
provision. Issues of accessibility and social exclusion also arise when operators
withdraw commercial services and the authorities have to consider the need to
contract a replacement.
3.15
They record the implementation of new bus stops and bus lanes for inclusion in their
APRs. There were some instances of PTEs collecting before and after data on
patronage and passenger attitudes to monitor the impact of infrastructure
improvements and major changes to services.
3.16
Overall, PTEs and local authorities make limited use of national statistics because of
their focus on their local area, the lack of opportunity for benchmarking against other
areas (apart from a small number of authorities that are actively involved in
benchmarking groups) and lack of awareness of what data are available and how
these could be used. We understand that the DfT is, however, taking steps to raise
awareness among these authorities of the availability of bus-related statistics.
Operators
3.17
CPT undertakes it own statistical analysis of the DfT’s data for monitoring and
lobbying purposes. For example, it uses the passenger receipts data from local and
non-local services to investigate what percentage of revenue comes from farebox,
subsidies and other sources and compares the UK with other parts of Europe.
3.18
Operators’ use of national statistics is largely confined to providing contextual
information on general trends. As with the local authorities, this may be partly
because of the low levels of awareness; several operators asked for regional-level
data which are already supplied in the Bulletin and on the DfT website.
3.19
Patronage is a key indicator of business performance. Whilst some operators
contacted during the study were actively benchmarking patronage growth between
operating centres within their organisation, few undertook external comparisons.
3.20
There was some interest in information on the local population and travel patterns
that could assist them to increase patronage and/or revenue. A small number of
operators had used the NTS findings to identify the national characteristics of
frequent and infrequent bus users. Though there was very little interest in funding or
part funding NTS boosters.
3.21
There was also interest in trip generation effects associated with changes in fare
levels, particularly associated with concessionary and discounted tickets. We feel
that elasticities are likely to depend local characteristics and are better suited to a
local study, than consideration as part of national statistics.
5
Some use a Geographical Information System (GIS).
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Researchers
3.22
Given that researchers have a primary interest in monitoring the impact of
government policies and in reviewing the effectiveness of these policies, it is not
surprising that their needs broadly mirror that of government.
3.23
The PSV data on patronage are widely used to monitor progress towards the 10 Year
Plan target and changes in operating costs, veh-kms, to investigate the effects of
deregulation and continuing changes in the bus sector.
3.24
NTS data on modal share, trip rates and average trip lengths are used to investigate
the potential for modal shift, compare bus usage between Britain and other parts of
Europe, etc. The NTS has also been used to identify the characteristics of people
with varying levels of dependency on buses and the extent to which these groups
have been affected by deregulation to inform research into accessibility and social
exclusion.
3.25
The two datasets (PSV and NTS)6 have been combined to calculate passenger
kilometres (pass-km) to give a measure of demand for bus travel in modelling
exercises. Steps have to be taken to reconcile the different survey methodologies; for
example, the NTS counts ‘stages’ and the PSV concerns passengers boardings, and
the NTS does not include certain passenger groups (see later).
3.26
Disaggregated PSV patronage and veh-km data have been used to investigate the
effects of deregulation, calculate elasticities and estimate the demand for future
services. But generally it is the more local level data that is needed. For example, the
DfT’s programme of multi-modal studies require area-specific data on:
 Patronage;
 Fares;
 Passenger kilometre (pass-km); and
 Capacity – for instance, seat kms that would reveal the scope for modal
switch.
3.27
This means that the national statistics would only be used in conjunction with local
data to investigate consistency between national and local trends.
3.28
Given the policy objective to increase patronage, there is interest in information on
the effectiveness of initiatives such as bus priority measures and quality partnerships
(QPs) which are designed to increase the attractiveness of buses amongst
researchers and Departmental officers. We feel that the outputs and outcomes of
these interventions are likely to be localised and inappropriate as national statistics.
3.29
There was also interest in particular issues, for example, the rising price of tenders
for supported services, and whether increasing competition for revenue support
within local authorities is leading to the withdrawal of marginal services. As discussed
earlier, these topics could not be informed by national statistics and research would
be better undertaken at the local level.
6
NTS is a household survey of travel behaviour, whereas the PSV is a survey of operators.
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CURRENT METHODOLOGY
PSV Survey
3.30
The sample8 of operators is stratified according to the number of discs held and
Government Office region. All large operators (with 30 or more discs) are included
along with a stratified random sample of smaller operators, as indicated in Table 2.1.
Table 3.1 – Structure of PSV Sample
No. Discs
% of Local Supply
(Veh-kms)
% of Non-local
Supply
Sampling
Fraction
No. Operators
(Active 1/4/01)
(Veh-kms)
1
}
3
5.0
2215
2
} 1
5
7.5
1878
3
}
3
10.0
608
4
}
3
15.2
473
5
0.5
4
20.0
371
6–9
1.5
15
30.3
889
10 – 14
1
15
39.3
512
15 – 19
2
10
50.0
279
20 – 29
3
11
62.5
255
30 plus
91
31
100.0
346
Source: A Bulletin of Public Transport Statistics, DTLR 2001
3.31
The methodology was reviewed in 1997 and the resulting sample frame was a
compromise between the optimal designs for surveying local and non-local services9.
Given the continuing changes in the structure of the bus and coach industry and the
trend towards a smaller number of larger operators, we investigated the case for
excluding the smallest operators.
3.32
Operators with just one disc (who can only operate one vehicle at any given time)
make up less than 1% of local bus and 3% of non-local mileage. They tend to be less
stable than the larger operators, with companies frequently setting up and going out
business.
3.33
They have fewer staff and they are much less likely to have electronic systems to
record patronage, veh-kms, etc, and so the burden of filling in a survey form is
heavier on them and the quality of their returns is questionable. In addition, the
response rate from the smaller operators is low. This places a burden on DfT to
chase up non-respondents and increases the size of the sampling error.
8
The PSV survey also covers the two remaining traditional street-running tram services in Blackpool
and Great Orme as well as the light rail operators and the Glasgow underground.
9 The large operators provide the majority of local services, so a local bus survey could include a
smaller sample of small and medium sized operators. However, these small and medium operators
provide the majority of non-local services and need to be represented in a local and non-local survey.
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3.34
Fig 2.1 overleaf shows the distribution of operators (both local and non-local) across
Britain by number of discs. The data suggests that small operators are likely to play a
significant role and so we recommend that they are retained in the sample.
“We should keep the smaller operators in panel. We need the data to
represent the whole industry, particularly for calculating operating
costs.” (CPT)
NTS
3.35
There was criticism from Government representatives and researchers about the size
of the survey, though this has been addressed by increasing the sample from
approximately 5,000 to 15,000 households. In previous years there were typically
3,300 responses but in 2002 there could be three times as many (actual sample size
in 2002 was 7,400).
3.36
There was some confusion over the comparability of the patronage data from PSV
returns and that derived from the NTS. Essentially, NTS counts the number of
‘stages’ that comprise a total ‘trip’. Each stage constitutes the component of a
journey made using a specific mode, and in the case of bus travel, one stage can
comprise one or more bus boardings. As the NTS estimates pass-km on a stage
basis, it is likely that a simple multiplication of PSV survey ‘boardings’ with NTS stage
km averages would give an over-estimate of pass-kms. However, experienced
practitioners are able to reconcile the two datasets11.
3.37
Whilst this difference in methodology is noted in the Bulletin, we would recommend
that it is reinforced by emboldened text or repetition beneath the relevant tables.
11
As an illustration, if NTS average stage length is 4.4 km and the boarding to stages ratio is 1.1,
then average ride after each boarding is 4.0 km. Assuming operator boardings and NTS boardings
are the same, 4,000 m operator boardings would then give 16,000 m pass-km.
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Figure 3.1 – Distribution of PSV Sampling Frame
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QUALITY ISSUES
Accuracy
Different data collection methodologies
can lead to significant discrepancies in
patronage derived from ticket sales and
local authority counts. For example, Travel
West Midlands use a 100% sample from
their electronic ticket machines, whilst the
PTE (Centro) uses a 25% sample and
grosses up the numbers and so the data is
subject to sampling error.
3.38
Most consultees had reservations about the
accuracy of the PSV returns, particularly
concerning the patronage data. But while
discrepancies in ticket sales and actual ridership
were felt to be significant at the route and the
local authority level, they were considered to be
acceptable at the regional and national levels for
monitoring trends.
3.39
We understand from discussions with operators that the patronage figures supplied
as part of the PSV survey are subject to qualification. There are a number of factors
which contribute to deviation from estimates of the ‘true’ level of patronage. These
factors include:
 Drivers failing to register passengers with pre-paid tickets - this may be
growing problem as more of these ticket types are used;
 Drivers failing to register children with season tickets or passes for home to
school transport travelling on local buses;
 Difficulties in splitting patronage on cross-boundary routes between different
local authorities (see section on burden later); and
 Smaller operators’ reliance on paper-based, rather than electronic ticketing
machines (ETMs).
 Differences among operators in defining ‘local bus’ patronage. For instance,
by the inclusion or exclusion of registered sections of non-local routes
“We are confident that our patronage figures are reasonably
accurate. There are just some problems to do with driver discipline.”
(Small operator)
“We are putting a lot of effort into getting the numbers right…we are
taking steps to ensure there is minimal under-recording. For
example, passenger boardings are audited and driver activity reports
from the ticket machines are monitored and checked against ‘normal’
activity reports for the shift. Drivers suspected of under or over
recording will be interviewed by their manager.” (Large operator)
3.40
Because operators are aware that there may be under-reporting caused by drivers
failing to register all boardings, they sometimes add in a grossing-up factor to take
account of ‘missing’ passengers.
3.41
DfT statisticians are aware of these problems and conduct a number of cross-checks
to uncover clear cases of error, for instance, by comparing patronage data with
receipts and fares information to highlight inconsistencies within the returns provided
by individual operators.
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3.42
However, we suggest that DfT consider undertaking a study into the growing use of
multi-travel tickets and the impact of this on the accuracy of the patronage figures.
3.43
A possible long term solution to improving the accuracy of patronage information
(and also possibly providing pass-kms and other data) appears to lie in the use of
smartcards. To date, the take-up has been slow, with just a few examples of PTEs
and major operators introducing trial schemes.
3.44
The operators consulted during this
study cited constraints associated
with high costs (see panel),
competition (as they did not want to
invest in one sort of system, if the
local authority is going to introduce
another), and reservations about the
capability and reliability of the current
technology. All these suggest that the
use of such systems will not be
widespread for some time yet.
However, we recommend that the
opportunities for data provision
arising from this source are
monitored in the future.
3.45
Smartcards vs Magnetics
Solent Blueline use magnetic cards for prepaid
tickets and season tickets in preference to
smartcards. Amongst the main reasons are:
- magnetic cards are cheap and so they can be
used for day tickets;
- they can be sold on the bus without the driver
being responsible for their intrinsic value; and
- the ticket type can be printed directly onto the
card - this is a real advantage given the
increasing number of products available from
operators.
There were fewer concerns about the accuracy of the veh-kms data as most
operators are now using odometers – electronic hub meters – and computerised fuel
monitoring system for FDR purposes and there are audits of their quarterly returns.
Similarly, there were few concerns about the accuracy of passenger receipts
because of operators’ own interest in collecting accurate information.
Metropolitan Areas
3.46
Breakdown of PSV data can show small year-on-year differences in the level of
patronage within individual metropolitan areas. These changes can be attributed to
market forces and inconsistencies in reporting.
3.47
There are also differences in patronage estimates produced by the PTEs and DfT
estimates derived from the PSV survey.
“Our figures have been declining whereas the national statistics for
our area have been going up!” (PTE)
3.48
The PTEs are concerned about the accuracy of DfT data at the PTE level, especially
if the data is used to appraise their performance in delivering their LTPs. We suggest
that there is a need to investigate the causes of these variations.
3.49
Part of difference may be attributable to differences in sampling methodologies. The
DfT’s approach includes all operators with 30 or more disks plus a stratified sample
of smaller operators. If these smaller operators occupy an important share of the
local market then stratified random sampling may not be able to offer a reliable
estimate of patronage.
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3.50
We also suggest that the DfT consider using the patronage data collected by the
PTEs directly from operators (under Section 143 of the Transport Act 2000) and
through their own on-board surveys to cross-check the PSV survey12. This study did
not investigate the robustness of PTE data, however, our consultation suggests that
reasonably sound approaches are being used (see Annex).
Relevance
Service Availability
3.51
The Government has set an over-arching objective of improving accessibility. There
is a target relating to rural service availability which is to achieve a one-third increase
in the proportion of households in rural areas within a 13-minute13 walk of an hourly
or better bus services by 2010.
3.52
The NTS provides data on the proportion of the population living within certain walk
times of a bus stop and the results from rural areas are aggregated to monitor
progress towards the target. The data are also used to monitor service availability in
other types of areas and these are published in the Bulletin on Personal Travel.
3.53
Some Departmental policy officers questioned the robustness of the rural availability
indicator, though we understand that the reliability of the results should improve with
the increase in NTS sample size.
3.54
DfT policy officers and local authority representatives identified a clear need for
additional measures of availability, particularly to investigate issues of social
exclusion. Work is currently underway by the Social Exclusion Unit to identify other
measures and this may lead to additional Best Value or APR indicators that would
better meet these needs.
3.55
The sorts of indicators that are being considered include:
 % people within 5 minutes walk of a 15-minute bus service;
 % people within 10 minutes walk of an hourly bus service;
 % fully accessible services on these routes;
 % people who can get to key employment locations within 45 minutes, by
public transport;
 Proportion of households within 45 minutes of their local hospital by public
transport;
 Proportion of people within 30 minutes (by public transport) of a supermarket
or affordable, good quality food shop; and
 % of people unable to work due to transport difficulties getting to work.
12
Transport Studies Group, Westminster University, conducted an exploratory comparative exercise
between PSV patronage data and patronage data produced by two PTEs. Differences appeared to be
relatively small but in some cases opposite trends can be apparent in year-on-year estimates.
13 Respondents are asked to state the time taken or to estimate using time bands; 0-6, 7 -13, 14-26
minutes etc, so as to get people to think of actual distances travelled.
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3.56
We therefore suggest that the DfT investigates the basis for collecting relevant
statistics, once the SEU study has reported.
Vehicle Kilometres
3.57
There is a fear expressed amongst all tiers of Government that the bus use target
may be compromised by operators withdrawing services on unprofitable routes and
reducing the overall supply of services. The DfT, Scottish Executive and local
authorities felt that new indicators to describe network coverage, service frequencies
and places served were needed to complement veh-kms.
3.58
DfT policy officers identified a need for local data that would assist with responses to
public complaints about service withdrawals and Ministerial enquiries about the ease
of reaching key destinations.
“[Vehicle] mileage is going up but suspect I that the area being
covered is declining. This is intuitive feeling at present. I want data to
back that up.” (Scottish Executive)
“We need a better measure [of supply]; one that would incorporate
accessibility or the density of the network to complement vehiclekilometres. Breaking this down to the local authority level would help
it to make sense.” (CPT)
“Vehicle kilometres is one of DfT’s recommended indicators for
monitoring LTPs. But why? It’s meaningless. The Audit Commission
have dropped it from the Best Value indicators.” (Local authority)
3.59
Frequencies and routeings are largely a matter for
commercial operators and there was reluctance amongst
those contacted during the study to provide data for any
additional surveys addressing network coverage. In any case,
there appear to be no clear methods of aggregating service
frequencies or destinations served to provide meaningful
indicators at the local authority level, other than some
measure of the proportion of the local population within a set
walk distance of a route with certain levels of frequency. The
increasing use of Geographical Information Systems (GIS)
will make this easier in the future14.
3.60
Notwithstanding the general interest in network coverage monitoring, this is not an
area that is central to the national statistics series. We would suggest that DfT
continues to collect veh-kms as a summary indicator of service provision (as it is
readily available from operators). Consideration should be given to the potential of
the recommendations of the SEU study to meet users’ needs for network coverage
information. Given the local orientation of the likely indicators for service availability,
these would be better published as part of the proposed ‘Neighbourhood Statistics’
series.
14
“I am generally wary
of providing statistics to third parties;
it’s spending my
time or my staff’s
time to allow other
people to secondguess our business.”
(Medium
sized
operator)
London Borough of Croydon have produced accessibility profiles to highlight sub-areas of public
transport deprivation
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3.61
This sort of information is already becoming available from local sources; for
example, operators registering a local bus service must provide a route and outline
timetable to the Traffic Commissioner in their area (see panel on TANBS overleaf)
and a full timetable to the relevant local authorities. Local authorities and operators
are increasingly placing timetable information on their websites to deliver the DfT’s
PTI2000 initiative15.
3.62
Academics and consultants use veh-kms in transport modelling “for want of
something better”. There is concern that the trend of increasing veh-kms is
misleading; the capacity of the bus system is not increasing at the same rate, and
much of the growth is associated with higher frequency midibuses replacing larger
vehicles.
Burden
3.63
There was some resentment that the PSV forms ask operators to repeat some
information that they already supply to other sources, but generally they accepted
that it was easier for DfT to gather data directly from them.
3.64
The first sections of the PSV form
– covering the bus fleet, staff and
operating expenditure – were
considered to be relatively quick
and
easy
to
complete.
Determining payments in the form
of contract payments from local
authorities,
public
transport
subsidies and concessionary
fares reimbursement is more
onerous because it involves
aggregating income from several
different sources. However, it is
the final section of the form that
asks for a breakdown of
patronage, veh-kms and receipts
by local authority that presents a
real burden to operators (see
panel) and is a source of error in
the returns.
3.65
The DfT is unable to disclose the information provided by individual operators16 and
so no local authority-specific data are published. All the data are aggregated to:
 “In all it takes about a day to complete the PSV form. It’s all
duplicating information that is known by different sources;
how many discs is known by the Traffic Commissioners,
concessionary fares payments is known by local authorities,
FDR is know by a Government Department.” (Medium sized
operator)
 “Repeating the provision of data for different administrative
levels – it’s a nuisance!” (Small operator) “It’s hard work to
split commercial and subsidised mileage; we have to go
through the timetables…and calculate how many journeys
are contracted for what proportion of their length.” (Medium
sized operator)
 “Providing data with geographical breakdowns is horrendous
– we do not collect data on that basis!” (Large operator)
 “Service-kms is ‘guestimate’. We have details of total
distance operated, but this is not broken down by local
authority boundary and so we split this through combination
of electronic mapping and rolling a wheel on a map.”
(Medium sized operator)
 Metropolitan areas (and London);
 Government Office regions; and
 Shire counties (including unitaries) for publication.
15
16
A national passenger transport information service
The Statistics of Trade Act aims to retain confidentiality and guard commercial sensitivies.
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Statistics from the Traffic Area Network
The Traffic Area Network (TAN) is responsible for licensing PSV operators, registering local buses
and ensuring compliance with standards for punctuality, roadworthiness and driver conduct. Ahead
of the merger with the Vehicle Inspectorate, TAN has introduced a new electronic system (TANBS)
for storing licence and registration data, exchanging data between organisations (and PTI2000) and
making on-line payments.
The database will hold information on:
Licences
- name of operator;
- fleet size and classification of vehicles (not mandatory);
Registrations
- local bus route number and start/end points;
- date service commenced or was last amended;
- service type (includes dial-a-ride, hail-and-ride);
- times and days of operation and timing points (but not a full timetable);
- route length, whether it is subsidised or included in a statutory QP; and
- route maps.
Resource constraints have meant that only skeleton details for all registrations throughout the
country have been entered. As registrations are updated the majority of data fields will be
populated, however, this will take a considerable time to do. Furthermore, some areas are relatively
stable, so registrations are unlikely to change and the routes will not be entered. In the Western
Area, for example, about 60% of registrations have not changed in the last three years.
There are currently no plans for making the database more comprehensive, as the next priority is to
set up TransXChange over the next 3-5 years. This will allow operators to submit registration details
and full timetables electronically to the Traffic Commissioners and local authority, make changes to
existing registrations on-line, and then automatically update PTI2000.
TransXChange has the potential to address some of the need for more local data that has been
highlighted by the bus and coach review but cannot easily be met by national statistics. For
example, each bus stop will have a geographical reference and can be located on a map, services
stopping at that stop can be identified along with the frequency and times of operation and services
can be mapped to investigate network densities.
However, electronic submission is not mandatory, and operators will be able to continue to submit
hard copies of their registration details. The timetables and maps will be scanned so that they can
be viewed through the system, but it will not be possible to include them in any analysis and
therefore the database will not be comprehensive.
Associated with the introduction of TANBS has been a data cleansing exercise to ensure that
recorded registrations reflect actual services, as there is an on-going problem of operators failing to
inform the Commissioners of changes and cancellations. There is also a new website at
www.tan.gov.uk.
P:~ FINREP
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
3.66
The consultation has highlighted that relatively little use is made of the ‘regional’ and
‘shires’ data, mainly because these areas are characterised by differing settlement
densities which limits their applicability for benchmarking. To reduce the burden on
operators and provide more useful local level information, we considered aggregating
local authorities into sub-regional clusters – five or six authority areas - with similar
characteristics (for example, predominantly rural areas, sub-urban and small urban
centres, etc).
3.67
Operators would then be asked for data relating to a cluster of authority areas and
there would be fewer occasions of routes crossing boundaries. Data could also be
published at this level of aggregation as there would little potential for identifying
individual operators. However, we have not recommended this approach as we feel
that many operators would be additionally burdened by local authorities then
requesting data for their area (under Section 143 of the Transport Act 2000) for their
LTP monitoring.
3.68
We recommend that the Department keeps under review the burden being placed on
operators to complete departmental forms and those arising from local authorities’
surveys.
Timing
3.69
Some local authority representatives questioned the timing of the availability of the
returns. The Bulletin is published in October, however, APR that would benefit from
the latest National Statistics have to be submitted at the end of July.
ADDITIONAL NEEDS
Disaggregation of Published Data
3.70
Throughout the study there have been requests from consultees for more local level
data. For example, DfT policy officers wanted data split by local authority area or
sub-area (such as homogeneous clusters of neighbouring authorities) to give a more
detailed picture of trends, monitor the impacts of LTPs, respond to Parliamentary
Questions (PQs), inform Ministerial visits and help MPs respond to letters/complaints
from the public. The Social Exclusion Unit was interested in any data that could help
to investigate the impact of policies by local authority area or on certain groups within
these areas.
3.71
Academics and consultants need local patronage and fares data over time to derive
elasticities for modelling purposes. Local authorities want demand and supply data
for their area to monitor the impacts of their bus strategy, changes in level of
provision, etc. Some authorities felt that the DfT should provide them with data for
their area to relieve them of having to do their own surveys and overcome isolated
problems where local authorities are unable to obtain information from operators18.
18
Some operators already supply data to local authorities under the Transport Act 2000, however,
difficulties arise when authorities ask for data specifically relating to their area (as this require
estimating patronage, etc on routes that cross boundaries) or for data to be supplied in a specific
format. A lack of technology and administrative burden may limit the potential for smaller operators, in
particular, to provide local level data.
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3.72
The local authorities contacted were particularly interested in patronage on supported
services, typical levels of reimbursement for those with concessionary passes, and
comparative data on the cost of ‘socially necessary’ services to confirm that they are
getting good value for money.
3.73
The DfT are unable to disclose the PSV returns and publishing data at the local
authority level may allow the identification of individual operators and their trading
conditions. Disaggregated data would also be subject to greater sampling errors.
3.74
Some of the sorts of data requested by local authorities consulted during the study
are already available from alternative sources. For example, patronage on local
buses, veh-kms and the cost of subsidised bus services per passenger journey are
Best Value indicators and are available on www.bvpi.gov.uk Consideration could be
given to using data collected by local authorities as a further cross-check on PSV
data.
A Better Measure of Passenger Kilometres
3.75
In monitoring the 10 Year Plan the Government is committed to monitoring the modal
share for passenger journeys by car, public transport, walking and cycling. There is
currently no agreed definition of mode share; the share of passenger-kilometres
(pass-kms) is more appropriate for monitoring motorised transport, whereas the
share of trips – or stages – is more appropriate for considering all modes, because of
the shorter distances typically travelled by non-motorised means. Until a definition is
agreed, DfT policy officers need a measure of pass-kms and journeys by mode.
3.76
DfT and researchers also want pass-kms to describe the overall demand for bus
travel in modelling exercises and how this compares with cost or journey time.
Currently pass-kms is estimated from patronage data (‘boardings’ from PSV) and
average distance (from NTS, though a more accurate measure of pass-kms in
London is collected by TfL via a rolling programme of on-bus surveys).
3.77
Increasing use is being made of electronic ticketing
systems and this suggests that operators should be
able to identify boarding and alighting fare stages and
calculate approximate pass-kms in those cases where
there are cash paying passengers. However, where the
fare stages are wide or fares are capped (for example,
Travel West Midlands offer a maximum off-peak fare), it
would difficult to estimate the distance travelled with any
accuracy.
3.78
3.79
P:~ FINREP
Furthermore, we have only been able to identify a few
operators that are able to manipulate Wayfarer or
another ETM to any extent, with most saying that they
do not have the software or resources to do this.
A further constraint is that the systems tend to record
the boarding and alighting fare stage of the outward
journey, but only the origin of the return trip, or any
21
 “We are not in a position to
provide this data accurately.”
(Large operator)
 “The figures would be
meaningless where there are
high numbers of pre-paid
tickets.” (Large operator)
 “We have origin data, but no
destinations due to the simple
fares structure in London.”
(Major London operator)
 “A gated bus would be a
disaster – the issue in London is
to develop a cashless bus to
speed up boarding.” (Medium
sized operator)
QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
subsequent trips made on a multi-travel ticket.
3.80
Discussions with operators suggested that there is limited potential for smartcards to
record origins and destinations. Passengers would need to enter a destination upon
boarding or additionally to ‘swipe’ the card upon exiting and this has implications on
boarding and alighting times.
3.81
We therefore recommend that the DfT considers the need for changes to the NTS to
improve the accuracy of passengers’ estimates of trip distances. There may be
potential for geo-coding journeys on the NTS diary or providing participants with GPS
handsets. Alternatively, independent bus passenger surveys could provide a more
accurate estimate of pass-kms, particularly if pass-kms are to be used to monitor
modal share.
Use of Various Ticket Types
Whilst there is no
target to increase the
use of pre-paid tickets,
there is a policy
interest in monitoring
the relative proportions
of different ticket types
used, particularly to
consider the implications on the ease of
using public transport
and aspects of social
exclusion19.
Tickets used in London
30%
Passenger Journeys by Ticket Type (5)
3.82
25%
20%
15%
10%
5%
0%
Period Bus
Singles & Saver Freedom Pass
Period Tickets
One Day Bus
Daily Tickets
3.83
Passes
etc
Passes
There
was
some
1995/96 2001/02
interest within DfT in
having patronage by
Source: TfL
ticket type to help
interpret the fares
indices, particularly as single fares have been increasing in recent years, whereas
the cost of multi-travel tickets and season tickets have remained about the same or
even gone down in price. We also discovered some interest in ticket types used
amongst academics, for example, to use in comparing the UK with continental
Europe where there is perceived to be much greater use of season tickets and this
has impacted favourably on operating costs (through a reduced number of ticket
staff) and hence reduced fare levels.
3.84
Operators tend to monitor the impact of new ticket types to see how well they are
being taken up by users, and some (if not most) are also able to disaggregate
farebox information by ticket type. But there would be additional burden on operators
to group these tickets into appropriate categories for publication in the Bulletin.
19
Season tickets offer reductions on the cost of regular travel, however, those on the lowest incomes
cannot afford to pay for travel in advance and so they do not benefit from these discounts. Recent
trends have seen single fares increase while multi-travel tickets have remained about the same or
even gone down in price.
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
3.85
The NTS currently collects information on ticket types used, but this is not published
at present. We therefore recommend that Transport Statistics Personal Travel
(TSPT) officers liaise with NTS officers about the potential for including ticket type
information in the Bulletin, acknowledging that it would not be comprehensive
because of the exclusion of certain passenger types, for example, overseas visitors,
from the sample.
Park and Ride
3.86
Given the Government objective of improving multi-modal integration and the policy
interest in the impacts of park-and-ride, some DfT officers suggested that patronage
on park-and-ride services be published in the Bulletin.
3.87
Previous studies by Atkins20 and TAS21 have highlighted the variation in how such
schemes operate; some allow local residents to pay to use bus services, some only
issue tickets for parking and provide transit free of charge, some are integrated with
the local bus network, etc.
3.88
This suggests that it would be difficult to identify true park-and-ride passengers, and
in any case, estimates of annual usage at each site are published in the regular TAS
publication Park and Ride Great Britain.
Quality Partnerships & Contracts
3.89
Some DfT officers are interested in the take-up of statutory QPs and quality contracts
(QCs), to investigate the benefits of these new delivery mechanisms, and inform the
need for better promotion, more guidance or other support to local authorities.
However, others felt that QPs, in particular, would become the ‘norm’ and so
monitoring would add little value.
“We are interested in seeing the proposals for Quality Bus Contracts
and the progress that is being made.” (DfT policy officer)
3.90
Information on the number of statutory QPs should be available from the Traffic
Commissioners who have been charged (under the Transport 2000) with ensuring
compliance. They plan to map the areas affected by partnerships on TANBS once it
has GIS capability.
3.91
Local authorities require Government approval to set up QC schemes to procure
services over a wider area, and so the numbers of applications and schemes granted
will be available within DfT.
3.92
As there is currently some interest in take-up and the data should be relatively easy
to collate, we suggest that DfT consider publishing information on QPs and QCs.
20
Good Practice Guide edited by Atkins and published jointly by DTLR and the English Historic Town
Forum, 2000, and Travel Effects of Park and Ride, Atkins, 1999.
21 Park and Ride Monitor, TAS Partnership, 2000.
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RECOMMENDATIONS
22
(i)
Note the different methodologies adopted by the NTS and PSV survey
beneath the relevant tables in the Bulletin (Paras 2.36 – 2.37).
(ii)
Consider undertaking a study into the growing use of multi-travel tickets and
the impact of this on the accuracy of the patronage figures (Paras 2.39 2.42).
(iii)
Monitor opportunities for improving the accuracy of data and ease of data
provision through the application of new technologies (Para 2.44).
(iv)
Investigate causes of differences between PTE and PSV patronage estimates
to determine if changes in the PSV sampling methodology are required (Para
2.48).
(v)
Consider the recommendations of the Social Exclusion Unit’s report on new
indicators of service availability for their applicability to national statistics
(Paras 2.54 - 2.56).
(vi)
Continually review the burden being placed on operators to participate in
departmental and other organisations’ surveys and the potential for
integrating the data provided (Paras 2.63 -2.68).
(vii)
Use BV data collected by local authorities to cross-check PSV returns (Para
2.74)
(viii)
Consider ways of improving the accuracy of passengers’ estimates of
journeys lengths in the NTS22 to provide a more accurate estimate of bus
pass-kms, particularly if pass-kms are to be used to monitor modal share
(Paras 2.77 – 2.81).
(ix)
Liaise with NTS officers about the potential for including ticket types used in
the Bulletin (Para 2.85).
(x)
Consider publishing information on the number of QPs and QCs in the
Bulletin (Paras 2.89 – 2.92).
The geo-coding trial may lead to improved measures of distance
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
4.
Non Local Travel
DATASETS
 Data on passenger receipts and vehicle-kilometres (veh-kms) are collected
annually through a stratified sample survey of operators holding Public
Service Vehicle (PSV) operator’s licenses.
 Data on passenger journeys, travel distance and time, trip rates and the
socio-economic characteristics of coach/non-local bus users are collected by
the NTS, but the sample is small.
USERS’ NEEDS
Government
4.1
There was an identifiable need for patronage data to understand the relative
importance of non-local buses and coaches compared with other modes. There is a
particular interest in:
 Scheduled coaches – which were perceived to be important in both shortdistance travel on sections of routes that are registered as local buses (for
example, the Scottish Executive estimates that 70% of coach-kms are
registered), and longer distance travel.
 Data on patronage – which would have been useful to inform recent analysis
of the implications of extending concessionary fares to coach travel, relaxing
the rules on eligibility to FDR, and making FDR payments in relation to
patronage, rather than mileage operated.
 School and works services - to measure the effectiveness of new policies
such as travel plans and initiatives associated with the School Travel Advisory
Group (STAG).
 Demand responsive transport (DRT), community transport and other services
including hospital transport and voluntary schemes – there is growing policy
interest in how these tackle social exclusion and contribute towards public
transport integration.
4.2
In addition to patronage, some consultees felt that it would be useful to have
scheduled coach pass-kms (for example, to compare with rail services), and
patronage split by journey purpose (for example, for use in multi-modal modelling).
4.3
There was less interest in private hire and excursions, other than their contribution to
the economy, for example, through tourism.
4.4
Veh-kms data is provided by the PSV datasets and in the absence of patronage data,
this is used to provide a broad indication of changes in the relative importance of
non-local bus use.
National Express carries out annual passenger
4.5
The PSV survey also provides
information on operating costs and
revenue streams, but the lack of
P:~ FINREP
25
surveys to assist with network planning and
marketing. These have shown that coach travel
is particularly important to those without a car,
those on lower incomes ands the young and
older age groups. Typically:
 50% of passengers do not hold a driving
licence
 70% are not in full-time employment
 38% are retired or not working
 30% are aged 25-49
 23% are students.
QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
associated patronage data severely curtails the applicability of this information.
Passenger Transport Executives & Local Authorities
4.6
While PTEs and local authorities are primarily interested in local bus use, there was
interest in obtaining information on the use of non-local services for commuting and
hence their potential for addressing peak period traffic congestion.
4.7
Some authorities have conducted studies to investigate coach and other public
transport use, for example, to inform consideration of the potential implications of
congestion charging schemes, and the potential for express buses to complement
local services.
“Leeds had a representation from coach operators and this led to the
introduction of additional coach stopping areas. We didn’t realise so
many people were coming into the city by coach.” (Local authority)
“Longer distance buses carry lots of commuters into Manchester and
these are unlikely to be included in local authority’s surveys.” (PTE)
“The coach market is growing, particularly for inter-city travel and
commuting like Edinburgh to Fife, because of the perceived road and
rail congestion…We want more information on coach travel to
understand changes in behaviour over time.” (Local authority)
4.8
Contact with local authorities through this and other studies suggests that most are
now targeting the school run as a means of tackling peak period traffic congestion
and reducing car dependency amongst young people. They tend to have information
on travel patterns at schools involved in Safe Routes to School projects, but there
was need for more comprehensive information on modal shares for LTP monitoring,
etc.
4.9
Revenue constraints have led some authorities (such as Nottinghamshire) to reduce
their discretionary school transport provision, which has in turn contributed to a rise in
the number of children being driven to school by car. Previous research24 has shown
that dedicated school buses can help to reduce the school run and PTEs/LAs are
interested in having patronage or modal share over time (and ideally cost
information) to help justify need to fund school services.
4.10
There was some interest in data on DRT and community transport for contextual
purposes, however, there was a greater need for information on best practice in
setting up and running such schemes.
Operators
4.11
CPT felt that coaches were a neglected sector in Government policy and national
statistics. It felt that there would be value in having patronage and mileage data for all
non-local services to understand their role, modal shares and contribution to the
economy.
24
Assessment of Attitudes to, and Potential take-up of, Additional Home to School Transport, WS
Atkins Report for DTLR, 2001.
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
4.12
National Express is the main provider of scheduled long distance coaches25, though
scheduled services are only a small proportion of the whole non-local sector. It was
interested in comparing patronage and mileage data to understand its market share.
4.13
Other operators consulted during the study did not express a strong interest in
getting any information on non-local services.
Researchers
4.14
There is a perceived need for more information on patronage for all forms of nonlocal travel. However, there was only a clearly identifiable need for patronage on
scheduled services for use in multi-modal modelling, and variations in the provision
and usage of school services for policy research.
4.15
With increasing focus being placed both by government and local transport
authorities on DRT and community transport, there was some interest in obtaining
more information on how and where these services operate and the levels of usage.
4.16
There was selected interest in private hire – for example, the number of contracts
running and approximate patronage – to determine how many employers are
providing works buses to encourage employees to reduce their car use, or whether
private hires are catering for the same social needs as conventional bus services.
CURRENT METHODOLOGY
4.17
Patronage on non-local services was removed from the PSV survey form in the early
90s because of poor response rates and difficulties in estimating ridership,
particularly on contracted services where operators receive payment for the hire of
the vehicle irrespective of the number of passengers carried.
4.18
The survey is still used to gather information on veh-kms, operating costs and
revenue. The returns cover all non-local services and are not separated by type of
service (eg express bus, dial-a-ride) or purpose (eg school bus, works bus). The
operators consulted during the study felt that it would be possible to provide some
form of breakdown, for example, to separate information on express services and
contract work, but it would add significantly to the burden of completing the PSV
form. Data are unlikely to be held in the required format and there may be a need for
operating centres to gather data from their depots.
4.19
The operators were also unsure why this sort of information was needed and what
use would be made of it, to justify the burden of providing it.
25
National Express is estimated to carry about 12m passengers per annum on scheduled services.
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
The NTS can provide
an
estimate
of
patronage and modal
share of non-local
services, but there are
concerns about the
relatively small sample
size, particularly for
long distance trips
(see
panel).
The
sample
has
been
increased to 15,000
households in 2002,
but consultees felt that
this would still yield too
few respondents to
adequately
reflect
coach travel, and DRT
and community bus
use which are more
prevalent in rural areas.
Long Distance Mode Shares (1992/2000)
350 and over
250 to under 350
150 to under 250
Mileage
4.20
100 to under 150
75 to under 100
50 to under 75
0
10
20
30
40
50
60
70
80
90
100
% of Trips
Bus & Coach
Car
Rail
Air
Other
Source: NTS, 1998/2000
4.21
The NTS excludes people from overseas who are likely to comprise a significant
proportion of the patronage on excursions.
4.22
There were also concerns about how lesser used categories are coded in the NTS
returns. For example, dial-a-ride services can be registered, but in NTS all journeys
on DRT are put into miscellaneous ‘non-local bus’ or ‘other public’26 categories
(depending on the table).
4.23
Similarly, the Scottish Executive’s Household Survey27 has a sample size of 15,500
households and is not large enough to capture sufficient coach users. Whilst it asks
about school journeys, there are doubts about children’s interpretation of the ‘school
bus’.
“If you say ‘school bus’ as a category, respondents may think you are
talking about the ordinary bus.” (Scottish Executive)
QUALITY ISSUES
4.24
None.
26
Essentially public transport modes other than rail, local bus, scheduled bus services, excursion
buses and taxis and minicabs.
27 The Scottish Household Survey is questionnaire, rather than diary-based, as in the case of the
NTS.
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ADDITIONAL NEEDS
4.25
There is no active Government policy to promote coaches, but there is a policy
interest in the provision of non-local services to help tackle traffic congestion,
particularly associated with the school run and commuting, and address social
exclusion, for example, with DRT in rural areas.
4.26
The non-local sector is perceived to be growing through a combination of factors
including travel plans, grants for innovative services and perceptions of poor quality
of rail services. The Swarmms and Orbit multi-modal studies, for example, have also
identified a much greater role for express bus services in the future as part of areawide transport strategies.
4.27
However, operators are not so confident; we undertook a telephone survey of 16
operators that run commuter coaches into London, as part of this review. We found
that there have been reductions in provision of scheduled coach services in recent
years. For example, Reading Buses has withdrawn its coach service to London,
which included 15 coaches in the morning peak, because of a combination of traffic
congestion, competition from improved rail services and a drop in off-peak demand.
4.28
The absence of patronage data from the PSV survey and limitations associated with
the NTS currently constrain:
 the calculation of modal share that would indicate the importance of the nonlocal sector; and
 any analysis of changes in patronage over time to highlight the effectiveness
of policy initiatives.
4.29
The aggregation of non-local mileage and financial data in the PSV survey and
aggregation of lesser used modes in the NTS constrains any analysis of the relative
importance of the different types of non-local services to influence policymaking.
4.30
We therefore feel that there is a need for better information on the supply and use of
non-local services, but with the problems associated with data collection, we suggest
that this should focus on areas where there is a clear policy need, namely:
 Scheduled (long distance and express) services;
 School services; and
 DRT and community transport.
4.31
Approaches to data collection are considered in the following sections.
Scheduled Services
4.32
About 700 coaches are used for scheduled long distance and express coaches in
Britain; National Express runs about 450 of these under contract and the rest are
provided by a variety of PSV operators.
4.33
National Express is able to provide patronage from fare box data supplied by its subcontractors. It is able to avoid double-counting passengers on registered sections of
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
non-local routes by excluding certain fares. It can also estimate veh-kms from
timetables and/or FDR returns.
4.34
This data will provide an accurate picture of patronage on about 65% of scheduled
coach and express bus network and replace the need for the DfT to rely on the
surveys of departures that are currently undertaken at Victoria Coach station.
4.35
About half of the operators contacted via our telephone survey said that they would
be willing to submit patronage figures to the DfT on an annual basis, but many of
them do not use electronic ticket machines, and so the data would be based on
revenue, estimated occupancies or manual counts. Again, they would be able to
estimate veh-kms from timetables and/or FDR returns.
4.36
These operators would already be captured by the PSV survey and so we suggest
that the form is amended to include three main sections:
(i)
local scheduled services;
(ii)
non-local scheduled; and
(iii)
other non-local (private hires, excursions, school and works contracts).
4.37
The non-local scheduled section could include questions on patronage and veh-kms.
Clear definitions would be needed to ensure that the information only related to
scheduled long distance coaches and express buses, and not excursions, seasonal
services such as Christmas shopping services, infrequent services to holiday
destinations, and contracts such as services to local shopping centres.
4.38
We feel that the amount of local patronage on the registered sections of express
routes is small, compared to overall volumes carried, and that these passengers are
largely excluded from the estimates currently provided in the PSV survey. To reduce
the burden on operators, we suggest that the amended form asks for total patronage
on the whole of these routes. (This issue of splitting local and non-local data is likely
to be less important in the future if the rules on eligibility to FDR change.)
4.39
We do not recommend that operators be asked to split patronage between local
authority areas, because of the confusion and burden this would add, particularly
when considering long-distance services.
4.40
There was no clear need or interest in financial information directly relating to
scheduled services and so we do not suggest that questions relating to passenger
receipts and operating expenditure are included. Especially since there is already
resentment amongst operators about having to provide income and expenditure
information.
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School Travel
4.41
The collection and publication of patronage data relating to school travel is
complicated by the variety of services available. For example, schoolchildren may
travel on:
 Local education authority (LEA) home to school transport (where the authority
owns and operates it own fleet) that may or may not be registered;
 LEA contracted services that are registered as local buses (these tend to look
like buses and usually do not have seat belts);
 LEA contracted services that are not registered local services (for example,
yellow buses);
 Local bus tickets funded by the LEAs;
 The above are generally run for statutory scholars29, though spare seats may
be sold to pupils who live outside the statutory maximum walking distances.
 Local authority contracted services (using discretionary powers under the
Transport Act 1985);
 Commercial services which are registered as local buses;
 ‘School specials’ provided by operators in addition to the regular schedule
which may or may not be registered;
 Services that are organised by a school or a group of parents – these are
unlikely to be registered; and
4.42
4.43
4.44
 Services that have been initiated by a school or group of parents but are run
by an operator under a revenue guaranteed contract and may or may not be
registered.
The complexity in the provision of these  “Information on the mode of travel for
schoolchildren would be useful. We are
school related services and suggests that
currently deciding whether to renew
gathering patronage data is a complicated
school contracts and need to understand
task. Statutory scholars using home to
the effects on existing local buses and on
school transport should be available from
traffic if the services are terminated.”
the LEAs, rather from operators, as the
(PTE)
latter would have been contracted to run a

“We need school mode share at the
service and not take payments.
Government Office level for strategy
development and LTP monitoring. (Local
Pupils using local buses will have already
authority)
been included in the PSV survey, though

“Some trips on registered LEA services
this is likely to under-estimate those with
are likely to appear in the private bus
season tickets or LEA passes because the
categories.” (Academic)
drivers often neglect to register these as
they board.
 “You can have dedicated services which
carry schoolchildren and then there are
Local authorities should be able to provide
those who travel by local bus. Shouldn’t
patronage on general contracted services,
all trips be referred to as journeys by
but would be unlikely to be able to split this
school bus?” (Local authority)
29
Current legislation requires local education authorities (education authorities in Scotland) to provide
free home to school transport to compulsory school age pupils if they live more than two miles (pupils
aged 5-7) or three miles (pupils aged 8-16) to their nearest suitable school.
P:~ FINREP
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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between journey purposes to identify schoolchildren. Although they do not have
patronage data per se, the Traffic Commissioners do have records of services that
are not available to the general public and from which school related patronage could
be inferred, but these records have yet to be input to the TAN database.
4.45
If there is a need for patronage relating to school travel, we suggest that a study is
undertaken to investigate the feasibility of collecting data from the range of sources
listed above.
4.46
However, we perceive that the key policy need is modal share information. This
suggests that a simpler approach would be to adapt the NTS to give better coverage
of schoolchildren and revise the categories of bus travel.
4.47
In general, surveys of school travel are complicated by respondents’ lack of
knowledge about who runs a service, whether it is available to the public and whether
it is a bus or a coach. For example, while home to school transport is generally
accurately referred to as a school bus, people tend to think that a schools special is
also a school bus, even though it may be registered and available to the general
public.
4.48
The NTS currently classifies trips as:
 Local bus;
 Private bus – a service which is not open to the public ie a school bus; and
 Other – such as express bus and long distance coach.
4.49
Any reference to ‘school bus’ is likely to be classified as a private bus (or non-local
bus). We suggest that the TSPT liaises with the NTS team to aggregate all forms of
school travel into a single category, and publishes this at the national and regional
level for primary and secondary school age children.
Demand Responsive & Community Transport
4.50
There were mixed views on the need for information on
DRT and community transport at both the central and local
government level. Most consultees acknowledged that this
was an important policy area, even though the levels of
patronage on these services are likely to be very small.
4.51
Flexible services were considered to be particularly pertinent because of the changes
in the rules on registering services and the potential for patronage growth in the
future.
4.52
The main area of interest was in patronage, and split by journey purpose, if possible.
There was some interest in the understanding the coverage of these services (and
this would be addressed by the availability indicators mentioned earlier). Veh-kms
would be meaningless because of the amount of ‘dead mileage’.
P:~ FINREP
The Community Transport
Association estimates that
there are over 100,000
minibuses serving 10 million
passengers each year.
“We are trying to encourage demand responsive transport as an
alternative to standard buses. It may appear that total bus use is
declining in the future, if we didn’t include these passengers.” (DfT)
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“It shouldn’t be too difficult to collect patronage and costs. The data
exists – it just needs collating. The DfT should issue a pro-forma.”
(Local authority)
“Community transport is an increasing issue. We are interested in
knowing details of the number of schemes, passenger numbers, etc.”
(PTE)
4.53
The NTS is unlikely to cover sufficient DRT or community transport users to give a
picture of how frequently services are used. Unlike school travel, trip rates are likely
to grow and so there is need for patronage, rather than mode share, information.
4.54
DRT (and flexible services) can be registered and so the PSV returns may already
include some patronage on these services. There may be potential for separately
identifying ridership on these services on the PSV form, but we have not explored
this option with operators. Whilst community transport services can also be
registered, they tend to be operated by local authorities, community groups, schools,
charities and health authorities which would not included in the PSV sample.
4.55
It may be possible to identify DRT and community transport providers through the
Traffic Commissioners and other authorities that can issue permits30; these comprise
local authorities, the Community Transport Association (CTA) and designated local
bodies such as Age Concern and the Salvation Army. There are two main types of
permits:
(i) Section 19 permits – these vehicles are not available to the general public; and.
(iv)
Section 22 permits – these cover voluntary non-profit services run by
unpaid volunteers and registered as local buses.
4.56
TAN is able to identify community buses (‘large buses’ under s19(1) of the TA 1985)
and should be able to provide information on permit holders once data has been
migrated to TANBS. The latest estimates suggest that this will be in approximately
six months time, but in the longer term TAN will also be able to identify DRT in the
database and supply details of the relevant PSV operator or permit holder.
4.57
A feasibility study would be needed to investigate the potential for extracting valid
information on smaller schemes that have been issued permits by other sources. The
permits do not have an expiry date and many providers may no longer be operating
services.
4.58
Many community bus providers only have one or two buses and so it will be
necessary to adopt a sampling framework. Few providers have ticket machines and
so patronage data is likely to be based on fairly crude estimates.
4.59
We suggest that the Department liaises with the CTA on this issue as it had some
interest in taking forward this proposal, and even undertaking its own feasibility study.
30
Permits cannot be issued to vehicles with fewer than 9 seats.
P:~ FINREP
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RECOMMENDATIONS
(i)
Make changes to the PSV form to identify patronage and veh-kms by scheduled
long-distance and express services (Paras 3.32 – 3.36).
(ii)
If there is a need for patronage relating to school travel, commission a study into the
feasibility of collecting data from service providers (Paras 3.41 – 3.45).
(iii)
Alternatively, adapt the NTS to give better coverage of schoolchildren and revise the
categories of bus travel (Paras 3.46 – 3.49).
(iv)
Commission a feasibility study to investigate the potential to identify DRT and
community transport providers and obtain patronage data from these sources (Paras
3.50 – 3.59).
P:~ FINREP
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5.
Fares
DATASET
 Fare indices derived from a quarterly panel of 90 large operators in England
and Wales and 15 large operators in Scotland. The data feed into the Retail
Price Index.
 Experimental Corporate Price Index for bus and coach hire published by
ONS.
USERS’ NEEDS
Government
5.1
DFT policy officers compare the national fares index and retail price index to
ascertain the relative rate of growth in bus fares compared to the general cost of
living. Rises in bus fares are also compared against changes the cost of travelling by
other public transport modes such as rail and taxi.
5.2
Informal comparisons are made between the cost of car and bus travel, though these
are complicated as car travel can be priced in terms of full or marginal costs.
5.3
Given the importance of bus travel for people who are on low incomes, there is a
particular interest in comparing changes in fare levels with changes in levels of social
benefits such as income support schemes. Travelling expenses can assume a
relatively high proportion of expenditure amongst people on low incomes.
5.4
DfT monitors fares changes against supply (veh-kms and accessibility are discussed
in Chapter 2) to respond to concerns that, since deregulation, fares have gone up,
but the provision of services has fallen .
5.5
There was general satisfaction with the fares indices published in the Bulletin as a
data series, but there is concern about the reliability of the prodedures being used by
operators to estimate price changes.
5.6
There was some interest in the ONS corporate services price index for bus and
coach hire, mainly to see if this followed the trends in bus tender prices and operating
costs. However, this was not considered to be a measure of public transport prices
and there were some concerns about the sample size and geographical coverage.
PTEs & Local Authorities
5.7
P:~ FINREP
PTEs and local authorities were interested in monitoring how price changes in their
areas compared against national and, ideally, regional indices. However, they rarely
embarked on these sorts of exercises because of:
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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 the complexity of local fares tariffs and differential rates of increase
(especially between single and multi-travel tickets);
 the cost of collecting fares information, particularly as operators were
generally reluctant to release this data; and
 the lack of comparable information for other local areas or the Government
Office region.
“We used the index in comparative exercises to monitor the cost of
travelling by bus, rail and car and proved that travelling by car was
very cheap in real terms.” (PTE)
Operators
5.8
CPT makes use of the price indices to monitor economic changes in the bus and
coach sector. It felt that the corporate price index was potentially useful, but there
were concerns about the sample size.
5.9
Some operators were interested in benchmarking their own fares increases against
the national average. National Express, for example, was interested in comparing
their price changes against other bus and rail operations.
5.10
However their primary interest was in bus fare elasticities. They wanted data that
would inform differential pricing strategies for different customer segments and
routes, rather than price indices alone. Transport economists have published
research in this area and this is widely used in framing fares strategies.
“Published elasticities are incredibly important. Published price
trends are not!” (large operator)
“The biggest factor affecting elasticities is the price of parking – and
no one monitors the cost of parking.” (large operator)
Researchers
5.11
Researchers noted that price is an important determinant of usage and so they
monitor how changes in the cost of bus travel compare with other modes. This
analysis can then inform research into the potential for Government to achieve its
objective of reducing car dependency.
5.12
There was a lot of interest in using the data to derive demand elasticities which are
then used by operators in establishing their own pricing strategies.
5.13
Research work on bus fare elasticities carried by University of Westminster31 used
patronage and receipt information collected through the PSV survey to estimate bus
journey costs. However, other demand modelling exercises, for instance by LEK32,
used data provided by PTEs and stated preference surveys to estimate elasticities.
31
Bus Fares Elasticities, Dargay and Hanly, University College London (2002)
Part of an on-going study into the impact of transport policies on modal switch and social exclusion
(2002)
32
P:~ FINREP
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5.14
The published fares indices did not appear to be used in formal modelling exercises.
CURRENT METHODOLOGY
5.15
We are concerned that the local bus fares survey form does not give operators any
guidance on how they should derive a single estimate of their fares
increases/decreases in an area or in all areas served. Our consultation has identified
a number of different approaches, ranging from relatively systematic approaches,
which are not always rigorous, to the application of ‘informed judgement’.
“The quarterly return is ambiguous as to what has to be filled in. I
don’t know if concessionary fares should be included…There is
definitely a need for better guidance.” (Large operator)
“There have never been any instructions issued and we are not sure
if we are answering the question that they are asking. I guess
everybody fills the form in differently.” (Large operator)
“Fares increases are designed to yield a bottom line percentage and
so that is the figure we quote.”(Medium sized operator)
“The bulk of our traffic is single fares – about 83% - and so we
provide just the rise in single fares.” (Medium sized operator)
5.16
Recent years have seen the introduction of a much wider range of ticket types. Some
operators are weighting their fare increases according to patronage on their most
popular tickets to determine an overall increase. Others are just quoting the change
in single fares which tends to over-estimate the overall increase, as single fares tend
to be rising faster than multi-travel and season tickets.
5.17
We therefore feel that there is a need for better guidance on exactly which fares
should be included in the survey, whether to include concessionary fares and child
fares, and how to combine these to produce a single estimate. A more prescriptive
approach will yield a more representative and consistent measure of change.
5.18
Any new methodology will need to address the complexity of bus industry tariffs and
pricing strategies:
 The importance of cash fares varies considerably between operators and
areas, with metropolitan areas having a high proportion of receipts derived
from multi-travel and season tickets.
 The number and length of fare stages also varies between operators and
areas. Though we know that some of the major operators have tried to
simplify their fare structures, for example, through introducing zonal fares.
 There is wide variety of multi-travel tickets used including day, week, monthly
and family tickets as well as school passes (with differing age eligibility), and
transfer tickets allowing interchange between operators. Return tickets have
been withdrawn in some areas.
P:~ FINREP
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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 Fares can vary by time and day of week, and multi-travel tickets can have
differing periods of validity.
 Operators employ a variety of pricing strategies, for example, raising prices in
some areas relative to other areas for similar route lengths - or changing the
relative price of cash fares compared to multi-journey tickets.
 Operators may increase the prices of multi-journey tickets but at the same
time extend the geographical distances covered compared to the earlier
fares.
 There is increasing use of multi-modal tickets combing tram, bus and heavy
rail.
Basket of Fares
5.19
Given the complexity of ticket types, we considered an alternative ‘basket of fares’
methodology for deriving a more accurate fares index. Essentially this would entail
identifying a range of key tickets including single fares, concessionary fares and
multi-journey tickets and weighting the price changes according to sales for each
operator surveyed.
5.20
Additional feasibility work is needed to establish how this could work in practice. The
key issues are:
 identifying what sorts of tickets are used;
 determining their relative importance in terms of sales - the most commonly
used could then form the basis of the basket;
 determining whether operators would be able to classify their tickets
according to the categories used in the basket; and
 whether they could calculate the increase in fares associated with these
tickets, given that rates may vary by trip length and area.
“We would find the basket approach easier because our internal
reporting system takes into account the weight of different tickets.”
(Large operator)
“Single fares based on half-mile stages – it’s quite an exercise to
calculate passengers journeys and average fares across the city
centre…you have to print out the Wayfarer data and go through it
with a highlighter pen.” (Medium sized operator)
5.21
P:~ FINREP
Preliminary research suggests that cash fares are a particular problem because of
different lengths of fare stages. One approach would be to identify a representative
range of typical cash fare trips (defined by length and broad location: city centre,
suburban, rural etc.) to be included in the basket. There was a mixed response to this
amongst consultees; some felt that it would be straightforward to apply, others noted
that fare increases vary between routes even within the same sub-area. We therefore
suggest that a more basic approach would suffice.
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Revenue / passengers
5.22
A simple simulation exercise (shown in Table 4.1 overleaf) suggests that increases in
the price of a representative ‘basket’ yields the same average increase as that
derived from dividing receipts by patronage. Indeed this approach is used by
academics who have little confidence in the current STATS 30A approach, but it
does not account for people travelling with concessions or free passes (such as older
people in London), changes in service quality or changing trip lengths.
5.23
The price obtained from the receipts/patronage approach will diverge from that
obtained by the basket approach, if the number of trips associated with multi-journey
tickets varies over time. For instance, if ticket prices are increasing, but trip rates are
increasing faster on multi-journey tickets, average fare prices derived using the
receipts/patronage approach could actually show a decline over time. In contrast, the
basket price would show an increase, irrespective of the variation in the number of
trips being made. Any divergence could nevertheless be ‘corrected’ by adjusting for
the impact made by changes in trip numbers on multi-journey tickets.
Combined Approach
5.24
An alternative approach would be to combine the basket of fares and
receipts/patronage approaches. Firstly, obtain an average price for all single fares by
dividing receipts by total ticket sales. Secondly, identify the price changes that have
occurred on the basket of multi-journey tickets and thirdly apply the weights
associated with all single ticket sales and the basket of individual multi-journey
tickets.
5.25
Using single fare receipts/patronage it would be possible to obtain an average fare
that could then be compared year on year to provide a reasonable approximation of
changes. This could also be used for other purposes, for example, benchmarking
fares levels and informing the need for concessionary fare schemes.
5.26
One possible source of error could arise if people were making increasingly longer
trips and consequently receipts could increase without the price actually changing.
This could nevertheless be monitored through surveys. Another approach could be to
substitute each operators’ minimum fare for the cash fare prices, although this would
require research into how representative that would be of cash fares in general33.
5.27
Another difficulty to be considered when using a basket or combined approach is the
impact of people making more use of multi-travel tickets. Re-weighting of the basket
of tickets to reflect changing ticket use (towards higher priced tickets, such as
weekly passes) will have the effect of unduly increasing the average ticket price. In
that case, the current weights could be retrospectively applied to the original prices in
order to isolate the price change effect. Although not shown in the table, this latter
approach has the effect of generating a price change of about 2% on the basket of
fares.
33
Comments on an earlier draft suggested that minimum fares can be relatively volatile owing to, for
instance, marketing campaigns and disproportionate impacts of fare restructuring on cash fares.
P:~ FINREP
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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Table 5.1 - Price Change Simulation
Constant Basket Weights
Weight1
Price
Period 1
Price
Period 2
Period 1
Average
Trips
Period 2
Average
Trips3
Period 1
(£)
(£)
(%)
Single
1.00
1.20
30
1
1
Daily
3.00
3.30
20
3
3.3
Weekly
7.00
7.00
50
15
16
Weight
Period 2
(%)
Period 1
Average
Trips
Period 2
Average
Trips3
Price Change (P1-P2)2:
Basket Approach
2.7%
Receipts/Patronage (Assuming constant P1 average
trips on multi-journey tickets)
2.7%
Receipts/Patronage (Reflecting actual change in
average trips on multi-journey tickets between periods)
- 1.9%
Varying Basket Weights
Price
Period 1
(£)
Price
Period 2
(£)
Weight
Period 1
Single
1.00
1.20
30
20
1
1
Daily
3.00
3.30
20
20
3
3.3
Weekly
7.00
7.00
50
60
15
16
(%)
Price Change (P1 – P2)2:
Basket Approach (Change in P1 weighted prices and
P2 weighted prices)
15.9%
Receipts/Patronage (Assuming constant P1 average
trips)
- 0.6%
Receipts/Patronage (Reflecting actual change in
average trips between periods)
- 7.0%
Notes:
P:~ FINREP
(1) Weight of ticket type as a proportion of total ticket sales
(2) P1 and P2 refer to periods 1 and 2 respectively
(3) These values are used to illustrate the impact that varying trends in trip rates have on bus travel cost
estimation and do not necessarily reflect actual outcomes. The increase in trip rates here could follow
from people increasingly using the bus for journeys that they would have formerly made by car
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
5.28
The preceding discussion has served to draw out some way of improving the current
approach. We feel that further research is needed to consider the feasibility of these
alternative approaches37 and this should be informed by the work carried out by the
Strategic Rail Authority in devising a new rail fares index38.
NTS
5.29
The NTS is a potential source of information on the types of tickets used and the
prices paid for weekly and other tickets, but with the likely exception of concessionary
and other discounted tickets. Being a weekly diary, it could provide information on trip
rates associated with daily and weekly passes, although care would have to be taken
to ensure that similar travel cards were being used in estimation.
QUALITY ISSUES
5.30
Problems associated with the data collection methodology and doubts about the
robustness of the ONS corporate services price index for bus and coach hire have
been described above.
5.31
The Corporate Services Price Index is used as part of the estimation of the National
Accounts and by industry associations such as the CPT. It is considered to be one of
the “stronger” industrial indices with a relatively good response rate. The sample size
has been increased and the indicator is being re-based to the year 2000. The
‘experimental’ qualification to the indicator in being dropped in future reporting.
ADDITIONAL NEEDS
Disaggregation of National Data
5.32
Fares indices are published for Britain as a whole, England, Scotland and Wales, and
disaggregated into London, English metropolitan areas and English shire counties.
Consultees expressed a need for more local data to:
 Help DfT to understand changes that are occurring around the country;
 Help respond to enquiries by MPs and complaints from the public;
 Inform local authorities’ decisions on the need for concessionary fare
schemes or changes to the amount of discount associated with existing
schemes;
 Inform local authorities’ decisions on the need for QCs to control fares and
improve service quality with respect to fares; and
 Derive local elasticities of demand.
37
First Group and Travel West Midlands are particularly interested in developing a new approach to
monitoring fares increases and volunteered to participate in a pilot study.
38 A description of this was published in the SRA’s ‘National Rail Trends’ Issue 1 2002/03.
P:~ FINREP
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5.33
Currently the survey covers a panel of about 90 operators in England and Wales. We
understand that there is good geographical coverage and so it should be feasible to
produce indices for each Government Office region. It may also be worth
investigating the feasibility of a more detailed geographical breakdown. However, we
feel that the most useful comparisons are likely to be drawn between London and the
combined areas outside of London, and so we recommend that just these indices are
published.
5.34
The academics and local authorities consulted during the study were keen to have
average fares levels data (by region, sub-region or local authority area). The data
would allow them to benchmark their area against others, investigate how
competition between operators can affect ticket prices and also compare the cost of
travel in urban and predominantly rural areas.
5.35
However, we are concerned that this data would be misinterpreted. Fares are set in
relation to local circumstances and these would not be reflected in benchmarking
tables. Previous studies have shown that key influences are local car parking
charges, traffic congestion and the quality of the bus service.
“Costs are not that important; people are more interested in reliability
and punctuality.” (Local authority)
5.36
We note that publishing sub-regional or local authority-level data would also affect
commercial confidentiality. However, local authorities have the power to request this
information from operators.
RECOMMENDATIONS
(i)
Amend the STATS 30A form to include a list of the sorts of tickets that should be
included and excluded from the survey (Paras 4.15 - 4.16).
(ii)
Provide guidance on how to derive a single estimate where fares increases vary
between ticket types and routes/areas (Para 4.17).
(iii)
Investigate the feasibility and relative merits of improving the comprehensiveness of
the fares indices through either introducing a basket of fares, receipts/patronage ratio
or a combined approach (Paras 4.19 – 4.28).
(iv)
Consider publishing fare indices for London and areas outside London only (Para
4.33)
P:~ FINREP
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6.
Passenger Satisfaction
DATASET
 Continuous survey of passengers’ ratings of aspects of bus travel in London,
commissioned by TfL.
 Quarterly survey of passengers’ ratings of aspects of bus travel in other parts
of England, commissioned by DfT.
USERS’ NEEDS
Government
6.1
Policy officers use the data to monitor progress towards a new target – agreed with
the bus industry – to achieve year-on-year improvements in passenger satisfaction
with information at bus stops during the 10 Year Plan period. This data, and levels of
satisfaction with other aspects of bus services, are used in considering the national
impact of policy measures and to inform the potential for encouraging modal shift to
buses.
6.2
The data are considered to provide “interesting background information”, but there
was a general feeling that satisfaction surveys are limited in what they can tell policy
makers. Improvements tends become the norm soon after their implementation and
passengers’ expectations rise, so they become increasingly dissatisfied with areas
that have not been improved. Possibly the best measure of satisfaction is rising
patronage.
“People’s perceptions vary according to what they are used to. The
Japanese are the least satisfied with their railways – and yet they are
the best in the world!” (DfT policy officer)
6.3
P:~ FINREP
The
results
demonstrate that
passenger
satisfaction with information at bus stops
is typically poor
(see panel), and
that ratings for
other aspects of
bus services are
higher. Generally,
levels of satisfaction with on-bus
safety and security
and
driver/conductorbe
haviour receive the
best ratings.
Satisfaction with Bus Stop Information
West Midlands
East of England
East Midlands
North East
South West
South East
North West
Yorks & Humb
London
0
25
50
75
Avg Satisfaction Rating
Source: Bus Quality Indicators, DfT, Jan-Mar 2002
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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6.4
The Social Exclusion Unit was particularly interested in the potential differences in
satisfaction ratings between socio-economic groups and urban/rural communities
and we understand that Mori have undertaken research into attitudes towards public
services in areas with different socio-economic characteristics.
6.5
The Scottish Executive undertakes its own Scottish Bus Satisfaction Survey, based
on the questions included in English survey, to inform policy and help to target
investment. The survey includes a comparison of passenger satisfaction and the
actual characteristics of the local network and services to assess the impact of
improvements and identify the sorts of measures that can encourage increased
patronage.
PTEs & Local Authorities
6.6
The PTEs contacted during the study were particularly interested in satisfaction
surveys to help to target investment, assess the impact of changes and monitor the
Best Value indicator on posted timetables39.
6.7
They conducted their own surveys on a regular basis and were working with local
operators to raise satisfaction through infrastructure and service improvements (see
Annex). They also commission sub-area surveys to measure satisfaction with quality
bus corridors and other measures.
6.8
There was little interest in benchmarking against the national figures, largely because
levels of satisfaction were perceived to vary with the quality of service provision and
area type. Aggregated statistics would be meaningless because there was no way of
relating the findings to the existing levels of service or public expectations.
“There is only a point in doing [surveys] if we can balance
expectations and satisfaction.” (PTE)
“You get people in rural areas, who are lucky to have a pole in the
ground, more satisfied with their bus stop than those [in PTE areas]
where they have super-duper glass shelters with a telephone.” (PTE)
6.9
There was some interest in benchmarking between similar PTE areas, but in practice
this was constrained by the regularity with which surveys are conducted and the
differing survey methodologies employed.
6.10
In London, performance indicators relating to aspects of passenger satisfaction are
included in operating contracts. TfL produces league tables from the results of the
continuous surveys and feeds this information back to the operators.
6.11
Some local authorities were carrying out their own countywide surveys for LTP
monitoring and Best Value, but there was more interest in investigating perceptions
of different routes and monitoring the impact of QPs at the very local level.
Consultees were aware that national data exists but they felt that it was not relevant
39
Proportion of bus stops that display a current and clearly readable timetable for bus services
stopping at that stop
P:~ FINREP
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QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
to them because of the aggregation of area types and the perception that the likely
small sample sizes (drawn from their areas) would limit the value of local area
analysis.
Operators
6.12
Some of the larger operators conduct
passenger surveys to monitor the
performance of the business as a whole,
and to make internal comparisons
between
operations.
They
were
interested in the national statistics to
provide a comparative context to their
own surveys, but they were not able to
undertake any true benchmarking
because of different methodological
approaches. These differences tended to
concern the attitudinal scales used,
rather than the sort of questions included.
CustomerFirst
First undertakes an annual UK-wide survey of 1,500
passengers to gauge attitudes to services. The
results are used to benchmark performance in key
areas (such as reliability, frequency, drivers, buses,
fares, routes and information), identify priority areas,
and improve overall passenger satisfaction
CustomerFirst has now entered its fourth year and
the latest survey showed that 95% of interviewees
travelled by bus at least once a week and 88% rated
their most recent journey as a “good experience”.
6.13
Some of the London operators undertake their own surveys to compare/complement
TfL data. They had little interest in information for areas outside London.
6.14
There was some evidence of other operators carrying out satisfaction surveys in
relation to particular schemes or initiatives, sometimes in association with PTEs/local
authorities, but this was not considered to be relevant to the national figures.
“We collect very little information; we tend to spot sample a service or
vehicle, otherwise you can fill an office full of print out in no time and
we haven’t got the people.” (Medium sized operator)
Researchers
6.15
There was a general interest among researchers about how bus services are
perceived to be performing and so the English satisfaction survey is used for
contextual information.
6.16
There was also an interest in evaluating how policy measures impact on satisfaction
levels and how changes in satisfaction relate to changes in patronage. The surveys
have not been running for long enough to be useful for monitoring these changes,
though there was an expectation that the satisfaction data would become more
useful in time.
6.17
Since a primary objective of government policy is to encourage a shift from car travel
to bus use, researchers and other consultees suggested that greater account should
be taken of the views of people who do not travel regularly on buses. We understand
that the views of non-users were investigated in July’s ONS Omnibus survey and the
results are expected to be useful in considering ways of making bus travel more
attractive.
P:~ FINREP
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CURRENT METHODOLOGY
6.18
The English passenger satisfaction survey was generally considered to be suitable
for monitoring the bus industry target, but that its potential for wider application is not
being realised.
6.19
A number of consultees felt that the quarterly data should be aggregated to derive
annual results. They also wanted the sample size to be increased to give better
coverage of different parts of the country. The results could then be used to compare
different regions or clusters of local authority areas (see later), thereby increasing the
usefulness of the survey.
Survey Frequency
6.20
The survey is currently deliberately pitched at large-scale national coverage; NOP
identifies 400 stops outside London and carries out up to 20 interviews with
passengers coming off buses.
6.21
The surveys were introduced on a quarterly cycle as seasonal factors were expected
to influence the ratings. However, there appears to be little seasonal variation in the
findings which suggests that there is limited value in conducting quarterly waves.
However, a periodic survey is easier to administer than an one-off national survey. It
also allows regular reporting to the government committee charged with appraising
bus use and so we recommend that the quarterly approach be retained.
Rating Scale
6.22
The methodology for the DfT survey was aligned with the London surveys to allow
comparisons with London Buses. Passengers are asked to rate aspects of the
service using a numeric scale of 0 (extremely dissatisfied) to 10 (extremely satisfied)
which is converted to 0 - 100 to give a satisfaction score for publication.
6.23
We feel that a semantic scale would be more transparent than a numeric scale, but
there are difficulties associated with translating one into the other to make
comparisons. Any significant change in scale would therefore undermine the value of
the dataset as a time series.
6.24
There is a view that the 11-point numeric scale may encourage clustering of
responses around 7-8, whereas a five point semantic scale, for example, may lead to
lower average scores being obtained. We understand that questions are to be
included in an Omnibus40 survey to test respondent scoring according to differing
scales.
An Omnibus survey can either be the ONS Omnibus survey or a market research company’s
omnibus survey.
40
P:~ FINREP
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QUALITY ISSUES
Relevance
6.25
Differing methodologies are constraining opportunities for benchmarking the results
of operators’ and local authorities’ surveys against the national statistics. We feel
there is a role for DfT in standardising the approach to passenger satisfaction
surveys, for example, in making the survey form available to other parties that are
considering undertaking their own surveys.
Burden
6.26
There is some duplication between the DfT’s survey and similar exercises carried out
by PTEs/local authorities and operators. We feel that there is limited potential for:
 Replacing the national survey with data collected more locally because of
differing survey methodologies.
 The Department increasing the number of survey points and passengers
interviewed to provide local authorities with data for their areas.
6.27
About 200 interviews would be needed in each local authority area, or about 500 in a
sub-regional cluster of authorities with similar characteristics, to give a robust base.
Whilst this approach would allow investigation of the links between levels of
satisfaction and the quality of the local bus network, it would still not satisfy local
authorities’ and operators’ desire to investigate the impact of particular changes or
ask specific questions about local conditions.
Availability
6.28
There was some interest amongst researchers and local authorities in comparing the
regional satisfaction scores with the Best Value indicator on bus stop information and
general satisfaction with local buses. There is poor awareness of the Best Value
database (www.bvpi.gov.uk) and this information could usefully be referenced or
published in the Bulletin.
“It’s a bit galling that we collect this [Best Value] information, but it
never seems to go any further. It should be put together as a useful
comparator.” (Local authority)
ADDITIONAL NEEDS
Disaggregation of Data
6.29
P:~ FINREP
Little use appears to be made of the regional level satisfaction data. There was more
interest amongst Departmental officers, academics and local authorities in having
data for rural and urban areas to account for the differences in passenger
expectations.
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6.30
Collecting rural data raises some notable practical issues:
 Passengers from a variety of area types are included in the survey, but it is
unlikely that the interviewers would capture sufficient quota of people from
rural areas. This would mean that the survey would have to be expanded
considerably and this would have budgetary implications.
 Placing interviewers at rural bus stops is unlikely to be cost effective.
 Interviewers at stops in urban areas could ask passengers to describe
whether they boarded in an urban or rural area, or provide an actual location
so that the interviewer could decide the appropriate category. In both cases
this is would be a subjective judgement.
Mystery Shopper
6.31
Any significant changes to the format of the existing survey, including changing the
attitudinal scale would introduce inconsistency into the dataset and undermine its
usefulness as a time series. However, it would be possible to add to the existing
survey without compromising its basic format.
6.32
The consultation identified concern about the relative subjectivity of the passenger
satisfaction survey and the influence of peoples’ expectations and actual service
levels on satisfaction. Although it can be still subject to degree of subjectivity
(depending on the attribute looked at), a Mystery Shopper Survey is frequently
employed to obtain get more objective views on key service attributes. These could
include overcrowding, driver behaviour and cleanliness.
6.33
There is potential for the interviewers that carry out the existing English satisfaction
survey to rate selected attributes. These would have to be accessible from the bus
stop, but could include aspects of the bus stop environment, the type of bus and
whether it is low floor, etc.
Priority Ranking
6.34
There was a diversity of views of over the value of adding additional questions to the
survey to ascertain the relative importance of the service attributes. Some consultees
felt that ranking would allow the derivation of a quadrant matrix (see example
displayed in the panel overleaf) and help to focus investment in the factors that have
greatest impact on satisfaction.
6.35
However, others felt that the attitudinal surveys by the Commission for Integrated
Transport41 (CfIT), PTEs and operators have already shown that frequency and
reliability are the most important factors. Indeed, the DfT’s own regression analysis of
the survey results identifies these as being among the most significant attributes in
relation to passengers’ scoring on overall satisfaction.
6.36
Ranking would reveal what weight in policy terms should be attached to factors other
than frequency and reliability/punctuality. The Social Exclusion Unit was interested in
whether some attributes are weighted differently by certain socio-economic groups or
communities.
The Scottish Bus Satisfaction Survey
attempts to link satisfaction and local
circumstances by mapping the characteristics
41 Annual surveys of attitudes towards transport are carried out
by Mori – see www.cfit.gov.uk
of the bus system such as interchanges,
P:~ FINREP
48
frequencies, etc and relating these to the
attitudes of local residents. This approach
highlights changes in levels of satisfaction
arising from improvements to local services.
QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
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Example of a Quadrant Matrix
The passenger transport authority in Munich produces a quadrant matrix of passenger satisfaction and importance to help
prioritise improvements.
Satisfaction
4
Appearance
Security
Information
Vehicle
Supply
3
2
0
0.25
Acceptable
0.5
Needs to be Changed
System-wide monitoring shows that the highest levels of satisfaction are with security and appearance (including cleanliness and
comfort). However, passengers feel that there is a need to address 'vehicle' aspects such as slow speeds and interior capacities.
“It would be useful…I don’t know if we should do it on a regular
basis.” (DfT)
“I am unsure about need for this as it would make the survey longer
and…we don’t need to repeat other similar research.” (CPT)
“Lack of weighting is a weakness of the current survey…However, it
is difficult to actually appreciate the importance of some aspects. For
instance, reliability can be related to feelings of security ...There is a
need to understand these rankings.” (Large operator)
6.37
P:~ FINREP
Aside from ranking, consideration could also be given to an approach which
compared expectations to actual performance. However, it was argued by some
consultees that, since passengers’ expectations are likely to be strongly influenced
by local conditions, especially the frequency and reliability of the bus service, it would
be inappropriate to undertake a nationwide survey that aggregated areas which have
different levels of service.
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6.38
P:~ FINREP
We suggest that the DfT consider further the need for ranking. Additional questions
to the satisfaction survey could be included once every three or five years.
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Perceptions of Non-Users
6.39
The perceptions of non-users was considered to be an important policy area
amongst DFT officers and we understand that this will be addressed by the addition
of relevant questions in an Omnibus survey.
6.40
Our consultation suggested that this information would not be appropriate for a
monitoring exercise, but would be useful to inform travel awareness campaigns such
as TravelWise. The results would be a useful addition to the Bulletin.
RECOMMENDATIONS
(i)
Agree and promote a standardised approach to passenger satisfaction surveys to
enable comparisons to be made (Para 5.25).
(ii)
(iii)
Consider referencing Best Value website (Para 5.28).
(iv)
Investigate the feasibility of ranking service attributes in terms of their importance
(Paras 5.34 – 5.38).
(v)
Include perceptions of non-users from the results obtained form the relevant
Omnibus survey (Paras 5.39 – 5.40).
P:~ FINREP
Investigate the feasibility of introducing mystery shopping survey to complement the
existing satisfaction survey (Paras 5.31 – 5.32).
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7.
Reliability
DATASETS
 Scheduled mileage lost from a continuous survey of operators in London,
undertaken by TfL
 Scheduled mileage lost from a quarterly panel of 100 large operators for
English areas outside London, commissioned by DfT
 Data on passenger satisfaction with reliability covering London and areas in
England outside London from passenger surveys undertaken by Tfl and DfT
 Data on perceptions of reliability from the NTS
Reliability and Punctuality
7.1
For the purposes of the study ‘reliability’ generally measures incidences of where the
bus did not run or only partially run or was so late that it was effectively replaced by
the following service. Reliability thus defined differs from ‘punctuality’ which,
according to this study’s view, measures the extent to which a particular bus service
adheres to the schedule. The primary source of reliability data is the lost mileage
returns made by operators.
7.2
Reliability and punctuality are related to local traffic conditions and operating
practices (for example, scheduled running times and speeds, length of layover time,
etc). Discussions with local authorities and operators during this study highlighted the
changes to timetables that have been made, following the introduction of the Traffic
Commissioners’ punctuality target. We therefore note that high levels of reliability and
punctuality do not necessarily indicate a good quality of service, as the service
frequency may have been reduced to ensure compliance with the published
timetable, or journey times may be slow to build in some contingency against late
running.
USERS’ NEEDS
Government
7.3
The lost mileage data was considered sufficient for monitoring the recently amended
target that operators should run at least 99.5% of their scheduled timetable
(excluding lost mileage due to factors outside their control such as adverse weather,
major traffic accidents, and unplanned roadworks).
7.4
There was confidence in the accuracy of the information supplied because many
operators use odometers for recording mileage for FDR purposes and they
themselves use lost mileage as a key performance indicator.
7.5
Lost mileage was seen as being much more reliable as an indicator than subjective
measures such as passenger satisfaction. However, it was noted that the 10 Year
Plan also contains an aspiration to improve punctuality and there is currently no
appropriate indicator for monitoring this.
P:~ FINREP
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7.6
Participants felt reliability and punctuality measures would be more valuable if they
could be split between high and low frequency services or time of day, but
recognised that it would be onerous on operators to supply this data.
7.7
The Social Exclusion Unit was interested in having a geographical breakdown of the
data to determine whether some communities are more adversely affected by poor
reliability than others. This was considered to be important because poor
performance may put the jobs of bus dependent employees at risk. However,
disaggregation of the data would impact on operator confidentiality.
PTEs & Local Authorities
7.8
PTEs and local authorities collect lost
mileage information for contracted services
and supported routes to ensure that they are
getting good value for money. Some
authorities have included local targets on
reliability and, to a lesser extent, punctuality
in their LTPs. They use lost mileage, number
of services cancelled, average bus speed
and other indicators to monitor progress
using data from their local operators or
derived from their own surveys.
7.9
Punctuality is perceived to be particularly important as a way of identifying specific
problems on the network, determining the benefits of bus priority measures and
prioritising areas for investment in new infrastructure or traffic management. For
example, Warrington did its own punctuality monitoring using the Traffic
Commissioners’ 6-minute window (see below) and face to face interviews with the
public. This found that 60% of interviewees judged timeliness to be “good” or “very
good”.
7.10
Market research by South Yorks PTE showed that reliability is the most important
issue amongst all passengers, but on frequent services, punctuality was more
important. If one bus is running early and the next one running late the resulting long
gap in headways is frustrating for users who expect the service to arrive at regular
and short intervals.
7.11
TfL has a roadside team to monitor reliability and punctuality of services operated on
its behalf at 200 sites in London.
West Midlands PTE (Centro) is setting up a
reliability monitoring programme for commercial
buses. This involves on-street monitoring at
timing points along 10 corridors on three
weekdays, Saturdays and Sundays for 12 hours
per day. Centro expects to calculate vehicle
speeds and investigate the effects of new bus
priorities, etc. The information will be made
available to operators, the Traffic Commissioner
and relevant local authorities.
Operators
7.12
Lost mileage is an important indicator used to identify poor performance and
problems such as labour shortages, mechanical problems, etc. Operators tend to
benchmark between operating centres but some also use the national statistics.
7.13
Operators are particularly interested in monitoring punctuality because of the recent
changes in the powers of the Traffic Commissioners which allow them greater
P:~ FINREP
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flexibility in setting financial penalties and imposing fines for a wider range of
circumstances.
7.14
Although the availability of resources limits the scale and frequency of the surveys
that operators can carry out. When they do monitor punctuality, operators undertake
manual comparisons for the most part of actual arrival or departure times against
scheduled times. Progress is nevertheless being made in developing electronic
monitoring systems. For example, Arriva is introducing GPS in Liverpool and First is
piloting handheld data recorders.
7.15
Punctuality information is being used to improve internal operations, adjust
timetables to better meet service delivery, and raise awareness of particular highway
problems with local authorities.
Researchers
7.16
Lost mileage statistics are used for contextual purposes, for example, when
considering the impact of labour shortages on the operators’ ability to meet 10 Year
Plan targets. National level data has limited application in modelling as they are
generally too aggregate to be meaningful.
“The problem with modelling bus reliability is that it is so particular; it
comes down to constrictions on particular routes.” (Academic)
7.17
There was interest in a measure of punctuality at the national level and especially at
the local level for modelling the impacts of specific measures to improve bus times.
Traffic Commissioners
7.18
The Traffic Commissioners are
charged with ensuring compliance
against timetables. The nationwide
punctuality target states that over 95
per cent of bus services should
operate no more that one minute
early or five minutes late.
7.19
Operators were critical that the target was not related to differing traffic conditions in
different areas and that trying to meet the target may have adversely affected
passengers.
“Unless the traffic congestion is unanticipated, the
operator should consider changing the registered
particulars, because it is the operator’s timetable, and
not that of the Traffic Area Network…the public is
entitled to know when a bus is due to arrive and
depart, and to be confident that a bus service will run
on time.” (Traffic Commissioners Annual Report 2001)
“We are having to build additional time into schedules to be able to
cope with every contingency. This means that the frequency of
service to customers has actually declined.” (Large operator)
“Buses are parked up more now because we have to build in catchup time.” (Medium sized operator)
7.20
P:~ FINREP
Local area surveys are prompted by complaints rather than being planned on a
systematic basis and so the findings are not representative of all bus services.
Monitoring is undertaken by Vehicle Inspectorate (VI) staff and the Commissioners
can request that surveyors look at particular routes, operators or all services within
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an area. However, they have limited resources – there is only funding for 12
surveyors to cover England, Scotland and Wales – and so some surveys have been
undertaken jointly with PTEs to increase the coverage and share costs.
7.21
TANBS will be able to provide data on the number of complaints received and acted
upon, but a rising trend may be the result of increasing awareness of the complaints
procedure rather than worsening quality of service. Reports on VI surveys will be
scanned into the system and so they can be viewed but not interrogated by an
analysis programme.
CURRENT METHODOLOGY/QUALITY ISSUES
7.22
There were no real concerns about the approach or quality of the reliability data. The
consultation tended to be dominated by the need for a punctuality indicator (see
later).
Relevance
7.23
Reliability (and punctuality) is closely related to traffic congestion. We understand
that the Department is currently investigating a general measure of congestion which
may be relevant to explaining local bus performance. We suggest that the DfT
consider the appropriateness of including this data in the Bus Quality Indicators
Bulletin.
Burden
7.24
Operators currently record total mileage run and lost mileage for FDR purposes and
so there is no additional burden in supplying these data for reliability monitoring.
They also tend to monitor the causes of the lost mileage for their own purposes.
7.25
Stagecoach is now requiring depot managers to split the findings of reliability surveys
to reflect high frequency (4+ buses per hour) and low frequency routes. There may
be potential for gathering similar data from other operators and using case studies to
satisfy DfT policy officers’ interest in disaggregated data.
7.26
However, it is unlikely that sufficient operators will be able to provide this sort of
information to give nationwide or even regional coverage so that the findings could
be included in the national statistics.
P:~ FINREP
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ADDITIONAL NEEDS
A Measure of Punctuality
7.27
The Department has a policy need for punctuality data for monitoring the 10 Year
Plan. The findings may also have powerful marketing applications in raising public
confidence in buses and encouraging modal switch.
7.28
At a recent Bus Forum, operators indicated that they would publish route
performance data and agree to “sensible” targets that reflected passenger priorities
and the Traffic Commissioners’ remit. However, we perceived that operators would
only be willing to hand over information if this would be used to prove that the Traffic
Commissioners’ target was unrealistic or to pressure local authorities into delivering
bus priority/traffic restraint measures. Clearly they would be reluctant to release data
that would lead to them being penalised42.
“I don’t see why us making greater efforts to monitor our systems
should be held against us. If we are trying to introduce quality checks
and find that things are not as good as we would like, we run a risk of
making a rod for our back.” (Medium sized operator)
“Punctuality and frequency are key customer concerns. It should be
taken as granted that we are trying to improve these. So why should
we provide punctuality data to Government?” (Large operator)
7.29
Consultees felt that any measures of punctuality should take into account differing
levels of service frequency, as this was perceived to impact on passengers’
expectations. Operators also felt that it was important to put the findings into context
by describing traffic congestion and traffic speeds, “otherwise you just see that buses
are getting slower, and not that traffic is getting heavier”. This suggests that
punctuality should be measured locally, and there would be the added advantage
that the data could be used to investigate the benefits of priority measures, QPs,
better enforcement of bus lanes, etc.
Using Local Data
7.30
We thus perceive that there would be more value in aggregating local data, where
possible, to develop a national measure, rather than conducting a national survey
based on a sample of routes and corridors. Aside from its local application, Ministers
would be able to report on overall changes in terms of the number of areas where
punctuality had improved according to local monitoring statistics.
7.31
We would argue that a national survey which was capable of reliably measuring
punctuality data using a sample would be prohibitively expensive. Such a national
survey would entail a complicated sampling approach, possibly an initial sample of
localities based on bus network and service characteristics and then possibly, within
those localities, a sample of corridors and routes by hour of the day (and by day of
CPT have prepared a paper ‘Better Buses’ (June 2002) which advocates locally-agreed targets
between operators and LAs in place of the Traffic Commissioners’ national targets. The recent Select
Committee Report also supports use of more appropriate local targets.
42
P:~ FINREP
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the week) and then a sample of particular services (high and low frequency). Care
would also have to be taken about the selection of the actual observation points used
to monitor bus services.
7.32
Monitoring even one route is expensive. For example, consider a service which
operates every 10 minutes between 6 a.m. and 6 p.m. 6 days a week. To monitor 5%
of its journeys (which may be required to generate sufficiently reliable data) there
would need to be in excess of 1000 observations each year for this service alone.
Possible Indicators
7.33
A number of suggested indicators were identified by consultees. These included:
 Excess wait time;
 Average headway divided by timetabled headway43;
 Delay divided by journey time or total journey time (including delay and
transit); and
 The proportion of buses meeting the Traffic Commissioners’ target.
7.34
TfL classifies services according to high frequency (headway of 12 minutes or less)
and low frequency (headway of 15 minutes or more). It uses excess wait time to
monitor high frequency services and the proportion of buses running on time (defined
as between 2 minutes early and 5 minutes late) to monitor low frequency services.
7.35
A nationally consistent approach would require agreement on what measure or
measures to be used. It is likely that a study exploring the merits and applicability of
the different measures will be required.
Data Collection - Working with PTEs
7.36
We suggest that PTEs (in partnership with local bus operators) offer the best local
sources of punctuality data. There would be a number of advantages to such an
approach:
 People and bus services are more concentrated in metropolitan areas;
 PTEs are interested in obtaining punctuality information. Some are already
using observational surveys, while others are introducing or planning to
introduce GPS and other technologies to undertake monitoring; and
 PTE data could be used to improve local services in a way national data
cannot.
7.37
There are significant cost implications, but the scale of the sampling exercises could
be limited to key corridors to keep costs within available budgets. There would be an
opportunity to build on current investment into Real Time Information (RTI) systems
and electronic run-time monitoring by the PTEs. (Nexus, for example, is installing a
RTI system and are piloting a GPS-based run time monitoring system. West
Yorkshire are also looking to invest in reliability monitoring systems).
43
This is effectively another way of representing lost mileage as, if an operator is scheduled to run 10
journeys in one hour, the timetabled headway is 6 minutes. If all 10 run, the average headway is also
6 minutes, even if they are bunched erratically.
P:~ FINREP
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7.38
A measure of metropolitan punctuality (that could be used as a national proxy) could
then be derived by getting source data from the PTEs and weighting it to derive an
overall index of punctuality. Rural bus punctuality could be also incorporated into this
measure by using the results of specific survey or by working with local authorities
which have a significant rural bus service component.
7.39
We suggest that there is an important role for the TSPT team within the Department
to advise on the approach and help ensure the consistency of the results. This could
include specifying the indicator to be measured, sampling approaches and the use of
new technologies (ie what sampling should be done in respect of databases derived
from automatic monitoring and what complementary observational surveying may be
required).
RECOMMENDATIONS
(i)
Consider the appropriateness of publishing a future congestion indicator in the Bus
Quality Indicators Bulletin (Para 6.23).
(ii)
Promote the development of an agreed national indicator for punctuality (Paras 6.33
– 6.35).
(iii)
Advise on a common indicator for punctuality, sampling methods and use of
technology for collecting and analysing data (Para 6.39).
(iv)
Investigate how data derived from PTEs (in partnership with local operators) could be
used to produce a punctuality indicator for metropolitan areas (Paras 6.36 – 6.39).
P:~ FINREP
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8.
Other Themes
SAFETY & SECURITY
Dataset
 Quarterly data on staff assaults from a panel of 120 large operators
 Annual estimates of type and cost of vandalism from the operator panel
 Annual data on passenger assaults from a panel of police forces
 Perceptions of safety and security at bus stops an on-board from the
passenger satisfaction survey
 The British Crime Survey’s investigation of occupational security
 Health and Safety Executive RIDDOR44 data on accidents at work
Users’ Needs
Government
8.1
Some policy officers are interested in trends in the number of assaults on staff and
passengers to respond to Ministerial enquiries concerning the personal security on
buses and consider the potential for encouraging modal switch to meet the 10%
growth in patronage target. The panel data are used to monitor these trends but
there are concerns about the quality of the passenger figures.
8.2
Public perceptions of safety and security associated with different modes are
considered to be more important than actual statistics in influencing modal choice.
The national statistics address this through the satisfaction survey and new questions
about barriers to bus use were added to the July 2002 Omnibus survey.
8.3
Policy officers will use the findings to consider the relationship between perceptions
and actual incidents to inform the whether policies/initiatives should be aimed at
reducing actual incidents or addressing misperceptions.
8.4
There was interest in segmenting the existing data or collecting additional data to
investigate whether particular socio-economic groups or communities are more likely
to experience assaults than others, or indeed to perceive themselves to be at greater
risk. We suggest that the SEU and the TSPT liaise over the potential for interrogating
the database and discuss with the police whether it would be possible to add socioeconomic questions to the form.
8.5
There is a general policy interest in monitoring vandalism, but little use appears to be
made of the relevant statistics.
Reporting of Injuries, Diseases and Dangerous Occurrences Regulations 1995
P:~ FINREP
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PTEs & Local Authorities
8.6
PTEs and local authorities are concerned with incidents in their areas so that they
can take steps to address on-going problems. They obtain their data through their
own staff (for example, GMPTE has a safety officer that monitors crime at bus
stations), reports from operators, notices of service withdrawals from the Traffic
Commissioners, and liaison with the police.
8.7
Some authorities have undertaken surveys into people’s attitudes towards safety and
security and how these influence travel patterns so as to inform local policy making
and the design of public transport infrastructure.
8.8
National statistics cannot satisfy the need for local data and there is little interest in
benchmarking against other areas but there is a keen interest in any good practice
learnt from particular schemes and initiatives.
Operators
8.9
Operators systematically monitor incidents involving staff, passengers45 and vehicles.
They tend to pass information onto the PTEs, as a matter of course. Depending on
the seriousness of the incident and the potential for apprehending an offender, they
would also inform the police. This suggests that the police data is not comprehensive
and would under-estimate crime associated with using public transport.
8.10
Some operators consult the national statistics to compare against national trends, but
generally they do not have any real need for the national data.
8.11
There was particular concern over the rising cost of insurance and more effort is now
going into gathering evidence through drivers’ records and on-bus CCTV which
suggests that their data better reflect conditions on buses.
8.12
Generally their monitoring did not extend to people’s perceptions of safety and
security risks using buses. Operators tended to see public transport related-crime as
a problem with society, rather than solely a transport problem. There was some
interest in having more information on fear of crime, particularly to understand the
effectiveness of measures such as CCTV, but this is better covered by a research
project than national statistics.
Researchers
8.13
45
Personal security data does not generally figure in modelling exercises, but there is
widespread interest in crime and fear of crime as a deterrent to public transport use.
There was interest in the effectiveness of measures to address people’s perceptions
of risk, but this is not a topic that could easily be covered by the national statistics.
Some incidents between passengers are not reported to the operator
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Current Methodology
8.14
The quality of the assaults data relies on the incidents being reported to the police
and the co-operation of the different forces to fill in the TSPT survey forms. The
response rate varies across the country; for example, the West Midlands and
Metropolitan Police do not file returns because of a lack of resources.
8.15
We understand that Ministers have taken a particular interest in safety and security
and that the Department has reconvened a group (STOP) to investigate issues
relating to crime on public transport.
8.16
There is clearly a need for appropriate statistics and we feel that further work is
needed to determine more efficient and effective means of collecting data from the
police. There is limited potential for reducing reliance on the police by using
operators’ data as drivers’ records only cover on-bus incidents and operators are
often not made aware of incidents at bus stops and stations.
Quality Issues
Accuracy
8.17
Consultees had doubts about the accuracy of the vandalism costs largely because a
proportion of remedial work such as cleaning graffiti is often undertaken as routine
maintenance. In addition, operators argued that reported costs do not reflect the
knock-on effects of service interruption and how this influences perceptions and
future usage of buses.
“Our estimates [for vandalism] are not very reliable. (Medium sized
operator)
“Vandalism would be noted because the vehicle had to be withdrawn
from service. We would not log cleaning to remove graffiti, etc. and
so vandalism figures are under-estimates.” (Medium sized operator)
“We ask the garage how much it costs for repairs and we produce
figures for the insurers. This just covers the cost of reinstating a
vehicle and not the future loss of passengers who have been put off
because of smashed windows, or loss in service because it has
taken 45 minutes to get a replacement bus out.” (Medium sized
operator
Relevance
8.18
Operators were generally happy to provide vandalism information to indicate the
rising challenge (and cost) of delivering bus services, but they were unsure how it
was used by Government. We appreciate that vandalism can impact on fares, bus
usage, etc but our consultation did not show that the data was being widely used.
8.19
We therefore recommend that the DfT reappraises the need for collecting information
on vandalism to buses, taking into consideration actions that are likely to be
necessary to improve the accuracy of the data.
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Burden
8.20
Whilst there is no real difficulty associated with completing the staff assaults reporting
form, operators felt that there was a duplication of effort in completing similar forms
for internal documents, insurance returns, industrial injury forms and, in metropolitan
areas, for PTE monitoring purposes.
8.21
We investigated the potential for collating information directly from insurance forms,
but concluded that this approach would not provide a complete picture of all assaults
on staff or passengers. Not all incidents are reported to insurers and not all provide
the level of details requested in the DfT form.
8.22
As the data is only published annually, we recommend that the DfT considers
reducing the frequency of the survey from quarterly to annually to reduce the burden
on operators. Operators generally maintain databases containing this information and
therefore they should be able to produce annual reports with relative ease.
Additional Needs
8.23
P:~ FINREP
None.
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VEHICLE STOCK
Dataset
 DVLA data on number, age and size of local buses and coaches.
 PSV operator returns on number and type of vehicles and aspects of
accessibility.
Users’ Needs
Government
8.24
Policy officers were interested in the size of the total PSV fleet, as an indication of
investment in new vehicles, and in the composition of the fleet to understand how
operators were responding to passengers’ preferences.
8.25
There is a policy interest in the average age of the fleet as this is perceived to
influence the attractiveness of public transport. Until now DVLA data has been used
to monitor average age, but the CPT has committed its members to reducing the
average age of the bus and coach fleet to eight years or less and has agreed to
supply annual survey returns to support this.
8.26
However, there is some concern that the CPT figures does not cover all vehicles and
the exclusion of school buses, in particular, would impact on the average age. We
understand that comparisons will be made with the DVLA data to clarify the
discrepancies between the datasets.
8.27
Policy officers use age as a proxy for the quality and accessibility of the fleet, though
the PSV survey form has now been amended to incorporate questions on low floor
design and accessibility to wheelchairs.
8.28
There was a policy need to disaggregate the age and accessibility data to the
regional, or ideally, the local authority level to identify where slow progress was being
in reaching the target.
8.29
There was interest in public attitudes towards the age and appearance of buses and
we understand that relevant questions have been added to an Omnibus survey.
PTEs & Local Authorities
8.30
The PTEs have a particular interest in the composition of the bus fleets operating in
their areas and the extent to which they incorporate accessibility features and clean
engines. Some PTEs have databases of information acquired from operators, but
they note that the contents change as vehicles are moved between depots.
8.31
There is concern that operators invest in new vehicles to serve London (as part of
TfL contracts) and cascade older buses to the rest of the country. There is a desire to
see progress in modernising local fleets and the national statistics are used for
benchmarking.
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8.32
Some local authorities are interested in the composition
and emissions characteristics of local fleets to inform
their local bus strategies and air quality management
strategies. Currently they get this information from local
operators, but they felt that there was potential for the
national statistics to fulfil this need. Returns from the
PSV survey could give a snapshot of the regional fleet,
but we feel that further disaggregation would be
constrained by commercial sensitivities.
8.33
There was less need for vehicle age information as this was not considered to be a
good indicator of quality, particularly because of differential ageing effects on
different types of vehicles. There were concerns about the age of school buses, but
this could be addressed through LEA contracts.
GMPTE maintain a database of
buses containing vehicle age,
design (low floor and wheelchair
accessible) and compatibility
with Euro emission standards.
The information is gathered from
a survey of operators and is
used to get a picture of the
quality of buses in local use.
“Customers value modern buses but that is only part of the equation
– cleanliness of a bus whether old or young is probably more
important.” (Local authority)
Operators
8.34
Operators have no particular need for national statistics on vehicle stock. They felt
that age was a crude measure for quality.
8.35
There was some concern that the new age target encompassed all types of vehicles.
Minibuses and midibuses age faster than larger vehicles, and quality and condition
tended to be related to maintenance, rather than age.
“Age statistics would not account for older vehicles that have been
retrofitted.” (CPT)
“A reconditioned 10-year old bus can be better than a 5 year old.”
(Medium sized operator)
8.36
They have a passing interest in changes in the composition of the bus fleet.
Researchers
8.37
Academics and researchers use the national statistics on the age and composition of
the bus fleet for background information for prefacing studies on the bus industry and
bus use. These factors are considered to influence the attractiveness of local buses.
Current Methodology
8.38
The DVLA age and fleet size data is taken from the information on ‘active’ vehicle
licences. Licences that have been that have not been renewed after three months
are removed from the analysis.
8.39
The annual PSV survey provides vehicle type and accessibility data from a stratified
sample of operators. The returns do not cover community buses that are not
registered, and there may be under-reporting of vehicles that are held at depots but
are no longer in use. Also, the overall response rate for small operators is poor (as
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discussed in Chapter 2), but the survey is generally perceived to provide a useful
cross-check against DVLA derived data.
8.40
There is a discrepancy between the two datasets; the DVLA data shows that the total
fleet has about 86,000 vehicles, whereas factoring up the PSV survey suggests that
there are 80,000.
8.41
There are a number of other sources of fleet information, but we do not consider that
these have the potential to replace these two existing datasets. These include:
 CPT – the annual membership returns provide the total number of vehicles,
average age (which will used for monitoring the new target) and type of
vehicle, classified as small (9-25 seats), full size bus and full size coach. CPT
estimates that while its members own the majority of the national bus fleet,
they own less than half of the coach and minibus fleets, and so it would not
give a full picture of the PSV fleet.
 Traffic Commissioners - records of the number and type of vehicles (less than
17 seats, single deck and double deck) are submitted on applications for PSV
operators’ licenses. Historic data has not migrated to the TANBS and it will be
some time before the Traffic Commissioners have a comprehensive picture of
the PSV fleet.
 SMMT – the industry organisation only has records of new vehicles.
 TAS – the fleet information is bought for the PSV Circle (an informal industry
group). The Monitor specifically targets operators with 50+ vehicles and so
the data only covers about half of total British fleet.
Quality Issues
8.42
Issues about accuracy and the relevance of the datasets have been covered in the
previous sections.
8.43
We were concerned about the burden associated with completing the ‘vehicle fleet’
section of the STATS100/A/B forms and the apparent duplication with application
forms for licensing and registering vehicles, membership of CPT, responses to local
authority surveys, etc. However, operators reported that this was easy and quick to
fill in.
Additional Needs
Engine Cleanliness
8.44
Reducing the environmental impact of transport is a Government objective and there
was interest amongst DfT policy officers and PTEs/local authorities in having data on
the engine cleanliness to inform air quality strategies.
8.45
This would also inform the Treasury decision on whether to vary the tax on buses;
currently buses are taxed on the basis of seating capacity, whereas other vehicles
are taxed according to environmental factors.
8.46
The DVLA registration form asks for information on compatibility with Euro standards,
but the questions are not mandatory and so the database is incomplete. There is
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scope to link vehicle registration data with the type of vehicle and emissions/engine
type information held by the Vehicle Certification Agency. However, as all engines
will eventually incorporate these standards, we do not feel that it would be worthwhile
to specifically monitor progress.
Disaggregation of Data
8.47
There is no clear way of deriving the average age of the fleet by region from the
DVLA or CPT data.
8.48
However, it would be possible to manipulate the PSV returns to derive regional
statistics on:
 composition of the fleet (minibus, single deck, double deck);
 proportion of low floor vehicles;
 proportion of regional fleet fully accessible to wheelchairs; and
 proportion of fleet compatible with Euro emission standards (if possible).
8.49
We therefore recommend that the DfT consider publishing these data in the Bulletin.
The regional fleet is likely to change because of movement between depots and we
suggest that the published tables note that the data are intended to give a snapshot
only and should not be used for time series analysis.
Size Banding
8.50
Over time there have been changes in manufacturers’ design and specification of
vehicles such that the current size banding may need to be reviewed to better reflect
current bus characteristics. We appreciate that DfT would have to co-ordinate with
the DVLA definitions, but we would suggest that the definitions be amended as
follows:



P:~ FINREP
a minibus has 9-24 seats;
single deck 25-39 seats; and
single deck 40 plus seats.
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LIGHT RAIL STATISTICS
Dataset
 Light rail and tram annual returns from relevant operators. The data covers
patronage, route length, number of stations, staffing, pass-km, receipts and
construction costs.
Users’ Needs
Government
8.51
The data published in the Bulletin is used to monitor the 10 Year Plan target of
doubling light rail patronage by 2010. Patronage, pass-kms and cost data are also
used to compare bus, guided bus and light rail systems to evaluate value for money
and consider bids for new schemes.
8.52
Policy officers were interested in the potential for encouraging modal shift to light rail
and needed information on previous modes used by current passengers. There was
interest in identifying the characteristics of light rail users to inform social inclusion
policies. Some of this sort of information is already available from market research
undertaken by the operators and we feel that it would be better suited to a research
study than national statistics.
PTEs & Local Authorities
8.53
PTEs have a direct interest in obtaining performance information for their systems
and comparing trends with other systems. Benchmarking is limited by the differing
characteristics of each scheme; route, density of stops, types of areas served, etc.
Operators
8.54
Some bus and coach operators expressed an interest in information that could be
used to allow for performance appraisal between buses and light rail. This is not
currently possible using national statistics and we would suggest that further work is
undertaken on the potential for including reliability and passenger satisfaction data in
the Bulletin.
Researchers
8.55
Many of the light rail systems have only been recently introduced and/or extended
which limits the availability and consistency of trend data. There is an interest among
specialist researchers in obtaining more specific operational data that would support
an assessment of the likely impact that the systems will have in meeting national
transport objectives and the opportunity costs involved.
Current Methodology
8.56
P:~ FINREP
The NTS is now gathering information on light rail usage, however, the relatively
small sample is unlikely to capture much usage and so the DfT survey will remain the
primary source of information.
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Quality Issues
Robustness
8.57
There is some concern about the different count methodologies; for example,
patronage on the Croydon Tramlink is derived from infra-red counters, some systems
use counts derived from ticket sales and Centro has replaced its ticket machines and
now uses conductors to estimate passenger numbers on the Midland Metro.
8.58
Whilst it should be possible to account for travelcards and multi-travel tickets through
operator surveys, non-payment of fares (either through fare evasion or ticket
machine malfunction) could lead to an under-estimation of ridership. There have
been particular problems associated with ticket machines malfunction on the
Manchester Metrolink and Midland Metro.
Accessibility
8.59
There appears to be a lack of knowledge, rather than information, about light rail
statistics. Few consultees outside DfT were aware of the data published in the
Bulletin. This is not helped by the index in Annex B referring to Table 5: Rail Systems
in GB.
Additional Needs
8.60
We understand that Ministers are interested in the cost-effectiveness of light rail,
especially compared to busway schemes, and there would be value in collecting
information on operating costs and profit levels. Currently this sort of information is
contained in the TAS Rapid Transit Monitor. Whilst the DfT may have more
confidence in figures derived from its own survey, we do not feel that this is an area
for national statistics.
8.61
There is some interest in comparative fares levels that would assist consideration of
the relative attractiveness of bus, guided bus and light rail schemes. Currently, a
proxy measure derived by dividing total receipts by pass-kms or patronage is used
but this does not account for concessionary fares and discounts. Given the limited
number of systems, it should be relative easy to collate tariffs and provide
comparative fares and trend information, but this would only have value if equivalent
data was available for buses.
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RECOMMENDATIONS
Safety & Security
(i)
Liaise with SEU and police over the potential for segmenting the passenger assaults
data to enable analysis of socio-economic characteristics (Para 7.4).
(ii)
Investigate new methods of collecting data on passenger assaults from the police to
improve coverage and accuracy. (Paras 7.14 – 7.16).
(iii)
Reappraise the need for data on vandalism to buses, taking into consideration
actions that are likely to be necessary to improve accuracy (Paras 7.18 – 7.19).
(iv)
Consider reducing the frequency of the staff assaults survey from quarterly to
annually (Paras 7.20 – 7.22).
Vehicles
(v)
Consider publishing regional statistics on the composition of the fleet, proportion of
low floor vehicles and proportion of fleet fully accessible to wheelchairs in the Bulletin
(Paras 7.47 – 7.49).
(vi)
Review the DVLA size banding to better reflect the industry’s classification on bus
types (Para 7.50).
Light Rail
(vii)
Investigate the potential for including reliability and passenger satisfaction data in the
Bulletin (Para 7.54).
(viii) Consider ways of raising awareness of light rail statistics (Para 7.59).
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9.
Summary of Recommendations
GENERAL
9.1
The review has shown that generally there are high levels of satisfaction with the
national statistics on buses, coaches and light rail. There are some concerns about
accuracy and sample sizes. There were also requests for additional information
which have been noted in the relevant chapters and are summarised in the next
section.
9.2
We feel that operators are generally unaware of the importance of the data they
supply to DfT for inclusion in the national statistics. We strongly recommend that the
introductory letters that are issued with the forms are revised to stress that the
information is used by Ministers in policymaking. The targets to increase patronage
and improve the quality of bus services will benefit their business and time series
data is crucial for monitoring progress.
9.3
We also feel that there is lack of awareness amongst local authorities of the sorts of
information that is available, particularly concerning the light rail statistics. We
suggest that there is a case for re-launching the publications and explaining how the
data can be relevant to local authorities, for example, in benchmarking local data
against national figures. The Passenger Transport Executive Group (PTEG) is
beginning to co-ordinate information sharing among PTEs and may be one vehicle to
help achieve this.
9.4
Some changes are also needed to avoid possible confusion:
 There is potential for improving the presentation of the tables on the DfT’s
web site to improve clarity.
 The PSV survey forms need to clarify who should complete the form. For
example, should National Express answer on behalf of its contractors?
9.5
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theme. Possible methodologies and cost implications for the suggested feasibility
studies are included in the Annex.
QUALITY REVIEW OF BUS , COACH AND LIGHT RAIL STATISTICS
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THEME-SPECIFIC RECOMMENDATIONS
Local Bus Use
1. Note the different methodologies adopted by the NTS and PSV survey
beneath the relevant tables in the Bulletin (Paras 2.36 – 2.37).
2. Consider undertaking a study into the growing use of multi-travel tickets and
the impact of this on the accuracy of the patronage figures (Paras 2.39 2.42).
3. Monitor opportunities for improving the accuracy of data and ease of data
provision through the application of new technologies (Para 2.44).
4. Investigate causes of differences between PTE and PSV patronage estimates
to determine if changes in the PSV sampling methodology are required (Para
2.48).
5. Consider the recommendations of the Social Exclusion Unit’s report on new
indicators of service availability for their applicability to national statistics
(Paras 2.54 - 2.56).
6. Continually review the burden being placed on operators to participate in
departmental and other organisations’ surveys and the potential for
integrating the data provided (Paras 2.63 -2.68).
7. Use BV data collected by local authorities to cross-check PSV returns (Para
2.74)
8. Consider ways of improving the accuracy of passengers’ estimates of
journeys lengths in the NTS47 to provide a more accurate estimate of bus
pass-kms, particularly if pass-kms are to be used to monitor modal share
(Paras 2.77 – 2.81).
9. Liaise with NTS officers about the potential for including ticket types used in
the Bulletin (Para 2.85).
10. Consider publishing information on the number of QPs and QCs in the
Bulletin (Paras 2.89 – 2.92).
Non-Local Bus Use
11. Make changes to the PSV form to identify patronage and veh-kms by
scheduled long-distance and express services (Paras 3.32 – 3.36).
12. If there is a need for patronage relating to school travel, commission a study
into the feasibility of collecting data from service providers (Paras 3.41 –
3.45).
13. Alternatively, adapt the NTS to give better coverage of schoolchildren and
revise the categories of bus travel (Paras 3.46 – 3.49).
14. Commission a feasibility study to investigate the potential to identify DRT and
community transport providers and obtain patronage data from these sources
(Paras 3.50 – 3.59).
47
The geo-coding trial may lead to improved measures of distance
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Bus Fares
15. Amend the STATS 30A form to include a list of the sorts of tickets that should
be included and excluded from the survey (Paras 4.15 - 4.16).
16. Provide guidance on how to derive a single estimate where fares increases
vary between ticket types and routes/areas (Para 4.17).
17. Investigate the feasibility and relative merits of improving the
comprehensiveness of the fares indices through either introducing a basket of
fares, receipts/patronage ratio or a combined approach (Paras 4.19 – 4.28).
18. Consider publishing fare indices for London and areas outside London only
(Para 4.33)
Bus Passenger Satisfaction
19. Agree and promote a standardised approach to passenger satisfaction
surveys to enable comparisons to be made (Para 5.25).
20. Consider referencing Best Value website (Para 5.28).
21. Investigate the feasibility of introducing mystery shopping survey to
complement the existing satisfaction survey (Paras 5.31 – 5.32).
22. Investigate the feasibility of ranking service attributes in terms of their
importance (Paras 5.34 – 5.38).
23. Include perceptions of non-users from the results obtained form the relevant
Omnibus survey (Paras 5.39 – 5.40).
Punctuality
24. Consider the appropriateness of publishing a future congestion indicator in
the Bus Quality Indicators Bulletin (Para 6.23).
25. Promote the development of an agreed national indicator for punctuality
(Paras 6.33 – 6.35).
26. Advise on a common indicator for punctuality, sampling methods and use of
technology for collecting and analysing data (Para 6.39).
27. Investigate how data derived from PTEs (in partnership with local operators)
could be used to produce a punctuality indicator for metropolitan areas (Paras
6.36 – 6.39).
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Safety & Security
28. Liaise with SEU and police over the potential for segmenting the passenger
assaults data to enable analysis of socio-economic characteristics (Para 7.4).
29. Investigate new methods of collecting data on passenger assaults from the
police to improve coverage and accuracy. (Paras 7.14 – 7.16).
30. Reappraise the need for data on vandalism to buses, taking into
consideration actions that are likely to be necessary to improve accuracy
(Paras 7.18 – 7.19).
31. Consider reducing the frequency of the staff assaults survey from quarterly to
annually (Paras 7.20 – 7.22).
Vehicles
32. Consider publishing regional statistics on the composition of the fleet,
proportion of low floor vehicles and proportion of fleet fully accessible to
wheelchairs in the Bulletin (Paras 7.47 – 7.49).
33. Review the DVLA size banding to better reflect the industry’s classification on
bus types (Para 7.50).
Light Rail
34. Investigate the potential for including reliability and passenger satisfaction
data in the Bulletin (Para 7.54).
35. Consider ways of raising awareness of light rail statistics (Para 7.59).
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SUPPLEMENTARY INFORMATION
106738135
QUALITY REVIEW OF BUS , COACH AND LIGHT RAIL STATISTICS
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A Participants in In-Depth Interviews
Bruce
Allen
Stockport BC
Laurie
James
Surrey CC
John
Bannister
DfT/TAN
Tom
Killick
DfT
John
Bird
Centro
Christine
King
SYPTE
Hugh
Brennan
Kent CC
Mike
Lambden
National Express Group
Spencer
Broadley
DfT
Andrew
Ledger
DfT
David
Brown
London General
Natalie
Lethbridge
DfT
A
Bryce
Wilts and Dorset
Catherine
Mason
Arriva
Bill
Buckley
TAN
Ross
McKenna
TfL
Bill
Campbell
Lothian Buses
Sharon
McNair
TAN
Miranda
Carter
DfT
Phil
Morgan
DVLA
Chris
Cheek
TAS
John
Nelson
University of Newcastle
Vince
Christie
LGA
Keith
Oates
SYPTE
Steve
Cosby
GMPTE
Paul
O'Hara
DfT
Joyce
Dargay
Peter
Openshaw
DfT
Friedrich
Demmer
University College
London
LEK Consulting
John
Pepper
DfT
Roy
Desouza
Warrington Council
Mike
Power
Traction Group
Frank
Dickson
Scottish Executive
John
Preston
University of Oxford
Paul
Dodson
Cambridgeshire CC
Fiona
Raje
University of Oxford
Phil
Dykins
DfT
Richard
Rampton
Travel West Midlands
Juliet
Eyeions
East Sussex CC
Nick
Reeve
WYPTE
Dave
Farmer
DfT
David
Rodgers
NOP
Richard
Gravatt
Essex CC
Tom
Rye
Napier University
Steve
Grayson
DfT
Dorothy
Salathiel
DfT
Ravi
Gurumurthy
SEU
Christian
Schmidt
GMPTE
Martin
Hancock
Travel West Midlands
Peter
Shelley
Solent Blueline
David
Harley
CPT
Jonathon
Simmons
LEK Consulting
Ray
Heyward
Leeds CC
Jamie
Singleton
Derbyshire CC
John
Hibbs
Graham
Sutton
Wellglade
John
Hodgkins
University of Central
England
Bucks CC
Max
Thompson
Edinburgh City Council
Graham
Hogg
First Group
Andrew
Thompson
London Bus
Torben
Holvad
University of Oxford
Mark
Threapleton
Stagecoach
Tim
Hughes
TAN
Bill
Tyson
GMPTE
Peter
Impett
Dorset CC
Pat
Waterman
The Big Bus Company
Peter
White
University of Westminster
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B The Review Board
 Hilary Hillier, Chief Statistician, Transport Statistics Personal Travel, DfT
 Peter Openshaw, Team Leader, Buses and Taxis Division, DfT
 David Harley, Economist, Confederation of Passenger Transport
 Martin Higginson, Corus (formerly with TRL)
 Andrew Thompson, TfL
 Catherine Mason, Arriva
 Professor Peter White, University of Westminster
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C Passenger Transport Executive Surveys
INTRODUCTION
There are three main reasons why transport authorities need to know about the travel
patterns of their passengers and the use of different ticket types:
Passenger Transport Executives (PTEs) have a statutory requirement in the large
urban areas to reimburse bus and train operators for carrying concessionary
passengers including children, older people and people with disabilities.
Some Executives also administer travel passes and multi-journey tickets and so
need ticket use information in order to share out ticket sales revenue among the
operators.
Patronage data are also used to help in planning tendered bus services
supported by the Executive. The details of passengers’ full journeys are important
in assessing the service level requirement of various sections of route.
The following sections summarise the approach taken by the PTEs, relying heavily on
documents and notes supplied by the PTEs themselves. Both Metro and GMPTE submitted
the most detailed descriptions of their methodologies and these are reported in-depth.
For the most part, the methodology used for estimating patronage consists of drawing up a
sampling frame of departures or ‘duties’ stratified by peak/off-peak hours; day of the week;
and operator. Where it can be established, the actual proportion of bus services sampled by
PTEs varies from about 0.3% to 2%. On-board surveys of passengers are undertaken on the
targeted services and the results of these surveys are then grossed up using an expansion
factor (usually based on a ratio of overall revenue to on-board ticket sales) to get overall
patronage for the service network in the area. The data are sometimes cross-checked
against patronage data supplied by the operators.
WEST YORKSHIRE (METRO)
A sample level of 0.3% of all bus departures over Monday to Saturday is undertaken. On
Sundays the sample level is higher mainly because the weekday work dictates the number
of staff required in the team. The survey is undertaken quarterly.
Selecting the Bus Sample
In order to ensure that the sample of bus journeys surveyed is representative, targets are
calculated for the various time periods for groups of bus service. The time periods have been
defined to reflect different traffic levels so that the passenger loads on surveyed buses within
a time period can reasonably be expanded to represent non-surveyed buses. Ten time
periods are used (divided between peak/off-peak periods, day and evening, weekday and
weekends).
Bus services are classified into services with similar passenger characteristics in similar
geographical areas so that the sampling can be made more manageable. In this way over
900 separate services can be grouped into about 300 service groups, which together with
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the 10 time periods, makes for about 3000 cells to be targeted for sampling (over a year this
can entail 10,000 and more bus departures being sampled).
A computer timetable database is used to calculate the number of bus hours scheduled in
each service group and time period cell. The sample rate is then applied to give the quarterly
target bus hours for each service group and time period.
The target bus hours are calculated on a quarterly basis but the work is phased over specific
weeks for smaller operators for two reasons. Firstly to ensure that any missed surveys due
to staff illness or vehicle breakdown can be scheduled again in the same quarter. Secondly,
for operational reasons it is impracticable to survey small targets less than about two hours
in a duty.
The surveyor’s duties are built using a computer program which primarily draws upon the
bus workings data (know as the bus running boards). The program is used to select bus trips
to survey which have not recently been used.
Collecting the Passenger Data
Information about passenger journeys is collected by interviewing passengers on the
vehicle. To speed-up the interview process the data are recorded electronically using a
hand-held data recorder and a bar-code wand.
At the start of each bus journey the relevant trip details are entered onto the recorder using
the keypad (and bar codes where appropriate). However, passenger interviews are entered
into the recorder solely using the bar-code reader and code sheet. Passengers are asked for
the following information:
The point at which they boarded the bus (recorded to the nearest previous Fare Stage);
The point at which they intend to leave the bus (recorded to the nearest Fare Stage);
Type of ticket;
Fare paid.
On buses it is usual for the one surveyor to interview all the passengers. However, if
passengers are missed, the number of lost interviews is recorded together with the fare
stage number for later use in analysis.
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Calculating the Bus Revenue
The principle of reimbursement is to establish how much each bus passenger would have
paid if they had not been using a concessionary ticket or travel pass. In order to do this,
tables of fares for each service operating in West Yorkshire are maintained on the computer
database. This is then used to establish the equivalent fare that the passenger would have
paid within the area for which the Executive is responsible.
Bus Patronage
The sample data are expanded to give total patronage estimates in four stages:
Sample group times periods, which for various reasons have not data or insufficient data,
can have data brought forward from a previous month or the scheduled time can be
switched to another cell.
Sample data are expanded by the primary grossing factor of scheduled bus hours: surveyed
bus hours per time period per service group.
The primary grossing factor is also used to expand the surveyed cash fares i.e. the cash
paid to the driver on the vehicle.
The final stage of grossing is based on the comparison between estimated cash (from
expanding surveyed cash) and the revenue actually received from on-vehicle sales.
This comparison is used to correct the primary grossing factor for final results calculations.
The level of correction represents a measure of how representative the survey was i.e.
whether a typical mix of passenger loads was observed.
The expanded results enable patronage to be estimated for an operator or service group
showing passenger distribution by class of ticket or time of day. For reimbursement
purposes the average fares are calculated for peak and off-peak periods. The average fare
and number of passengers forms the basis of payment although for concessionary fares the
scheme in force takes account of the generation effect of reduced fares.
Staffing
A team of 25 surveyors, supported by staff in the office provide the data for reimbursement
and planning purposes for a bus operation carrying 200 million passengers per year and a
rail operation with 18 million passengers.
Funds amounting to about £40 million pa are being distributed to bus and train operators
using the sampling method.
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GREATER MANCHESTER (GMPTE)
Introduction
The count passenger sample (CPS) is primarily used to reimburse bus operators for carrying
passengers at concessionary fares and apportion off-bus sales revenue between bus
operators.
Data Collected
The survey method involves a data collector following a bus driver on his duty. All
passengers on the bus are given a short interview which records the following information:
Boarding stage;
Alighting stage;
Age of passenger (within broad bands);
Ticket type.
The information is recorded on a portable computer. The data collector presses a button
when the bus passes each stage. This enables the boarding and alighting stage of each
passenger to be matched to a time of day of travel.
Boarding and alighting stages have unique codes on each bus service. However, a look-up
table is maintained between bus stops in the GMPTE network database containing servicespecific stage numbers. This can be used to build up a stop-to-stop matrix of bus trips,
although it should be remembered that the bus stop to which a stage is allocated may not be
the bus stop actually used by the passenger. Bus stops on the GMPTE bus network
database have Ordnance Survey Grid References (OSGRs) recorded, thus enabling the
matching of stage-to-stage information to geographical locations.
Where a cash fare is paid, the boarding/alighting stage information is matched with fare
tables stored on computer to calculate the fare paid for each trip. This enables cash revenue
for the sampled duties to be estimated for expanding the sample.
Sampling
A stratified random sample of drivers’ duties is selected at quarterly intervals. Approximately
0.3% of duties are sampled (approximately 3000 duties in a year, more than 12,000
departures). The sample is stratified according to:
Type of duty (early, middle, late, etc.);
Operator - small operators are combined into groups for sampling and expansion;
Day of the week; and
Garage for large operators.
Sampling is roughly in proportion to the number of duties available for sampling in each
stratum.
Although not formally part of the stratification process, an effort is made to sample duties of
any one operator/group evenly throughout each quarter.
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Expansion
Expansion involves estimating cash revenues across all bus departures sampled for each
quarter and expanding up to the operator’s reported cash revenue for that quarter.
To estimate total patronage, it is most accurate to sum the estimates of patronage for each
operator. The estimated number of passengers over any three month period will be:
R(R)/R(S)}]o
o
Where:
T is the number of passenger trips recorded in the sample for an operator in the quarter.
R(R) is the reported cash revenue for an operator in the quarter.
R(S) is the estimate cash revenue from surveyed duties for an operator in the quarter.
denotes summation across operators.

Expansion factors may be attached to individual records of passenger rides.
There is a further stage to the expansion process carried out at duty level, which essentially
involves re-weighting the data in favour of trips where cash recorded in the driver’s waybill is
high relative to the estimated cash revenue recorded from matching survey trip information
to fare tables. This has little practical effect in aggregate.
Using CPS for Transport Planning.
The perceived limitations of the CPS are that:
It records passenger rides not passenger trips;
It is recorded at stage level;
Low sample size; and
It is a random sample of driver duties, not of passenger trips.
The last point limits the efficiency of the sample, especially when the locations of
passengers’ boardings and alighting points are important. The tendency for bus duties to
comprise series of end-to-end runs on a particular bus route increases the scope for the
characteristics of the passenger trips recorded in the sample to diverge form those of the
population in any one sampling period. The limitation of the sample become less significant
where CPS is used for recording large movements (e.g. across a cordon or screenline) using
data collected over a long period (e.g. 1 year).
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Boundary Issues
Many passenger rides with just one trip in the county and some passenger rides with both
trips ends in the county will not be sampled. Operators of journeys whose duties are not
surveyed send GMPTE their cash revenues returns for the routes concerned. The element
of this revenue deemed to represent Greater Manchester travel is incorporated in the
expansion factor applied to the sample.
While these procedures are appropriate for the purpose of determining concessionary
reimbursement to bus operators, they cause problems for using the data for transport
planning purposes. Some passenger trips will be over-expanded while other passenger trips
(mainly those near the Greater Manchester boundary) will be missing entirely.
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TYNE AND WEAR (NEXUS)
A sample frame is created for each operator ranking services type by depot. This frame
contains the peak vehicle requirements for each service by day type for morning and
afternoon peaks as well as evening. This equates to the notional population of driver duties.
The statistical auditor (Southampton University, Dept of Social Sciences) estimates the
number of duties to be sampled in a given period for the size of the operator. Nexus staff go
through the sample frame picking every Nth (total duties/ sample duties) duty from a
randomly selected starting point.
Nexus creates a driver’s duty for the surveyor to work from the vehicle selected. The
surveyor collects an inspector’s ticket at the start of each journey. They input the ticket
numbers into their hand held terminal and this acts as a control value.
The surveyor attempts to interview all passengers boarding with them or subsequently on
the journey. On completion of the journey the end ticket number is input. A scaling factor is
then calculated (= no. tickets issued/ no. tickets surveyed). This factor is applied to all of the
passenger information on that particular journey.
A file is created for each bus service noting the number of journeys scheduled to operate by
hour of the day Monday-Friday, Saturday and Sunday. These are accumulated by operator
and into time periods. These periods reflect the different travel patterns associated with
particular passenger types e.g. commuters & pensioners.
Nexus compares the number of surveyed journeys for each operator in each time period with
the scheduled journeys and scale up the data accordingly. This then gives an estimate of
total patronage.
As information on the fares paid by passengers is collected as well as ticket type, origin and
destination, they can estimate total fare box cash take by the operator.
A final factor can then be calculated (total fare box/ estimated fare box) When this is applied
they obtain a reliable estimate of total patronage.
Nexus consider that this estimation process is best used globally but the methodology can
be used for smaller scale work. However it does require proportionally more sampled
departures, to ensure that the error level is within acceptable limits.
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WEST MIDLANDS (CENTRO)
Centro calculates the amounts to be reimbursed to bus operators for carrying passengers
holding senior citizens concessionary passes (Centrocard, Busmaster and any other multioperator ticket administered by Centro). It uses a rolling programme of on-bus surveys
sampling (approximately between 1% and 2%) of duties. Passengers are counted and asked
about their alighting stop and ticket type.
Bus operators provide patronage data to Centro on a 4-weekly basis. Once this is
reconciled to figures derived from the on-board surveys, this is then analysed to provide an
annual figure.
Centro's patronage data was originally produced via a continuous on-board survey (COBS)
and operators’ 4-weekly returns. However, the rolling bus passenger survey (RBPS) system
is replacing this and patronage will be obtained from RBPS in the near future. The RBPS is a
refinement of the COBS approach, which aims to get more accurate information on specific
concessionary groups and which also incorporates a revenue correcting factor to improve
overall accuracy.
COBS, the previous system of surveys, became less reliable as the survey resources were
stretched to include a number of smaller operators as well as the major operator which it had
covered alone.
RBPS has been developed by MVA, Transport Consultants, reporting to a Joint Steering
Group (Centro and bus operators). It differs form COBs in two main ways (i) more surveyors
- usually 2 per bus (unless fewer than 50 passengers expected) and (ii) a 2 stage expansion
approach.
COBS used one stage of expansion from sample data to total population - the ratio of
operator declared total revenue for the period to the total revenue from the sample was used
to multiply up the OAP sample numbers.
RBPS uses 2 stages which should weight things more satisfactorily. Samples are first
stratified i.e. split into day types (Monday to Friday, Sat and Sun) and duty types (Early,
Middle, Late, Splits) for each operator - where the travel patterns within each of these type
combinations are thought to be more similar that between them.
The first stage of expansion multiplies each sample's results by the ratio of the total numbers
of duties, per period, in each type combination to those sampled and then the results of each
type combination are added together. (Thus if there are 300 Monday-Friday Middle duties
and 10 are sampled, the results are multiplied by 30 and so on for each other type
combination).
The second stage of expansion involves comparing the total on-bus revenue from cash
passengers as estimated from the survey so far with the revenue declared by the operator
for the period. The two should be quite close in general, with discrepancies mainly due to
more/fewer buses running than timetabled and these are allowed for by multiplying the
survey OAP numbers by the ratio of operator revenue to survey revenue.
During the transition between the two systems patronage is being obtained via attributing the
trend from operators’ 4-weekly data to the previous year’s total annual patronage.
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The RBPS methodology does not include all bus operators as some of the smaller operators
are unable to supply accurate patronage data. However, this only applies to a small number
and an estimate based on fleet size operated and registrations is possible. Centro is
confident that this provides them with an accurate number of bus passenger journeys.
SOUTH YORKSHIRE (SYPTE)
SYPTE perform a large (19k pa) number of surveys on bus, tram and train for concessions
monitoring purposes and this is used to form patronage estimates.
Basics
For concessionary fare reimbursement they use the on-board surveys to calculate the ratio
of concessionary to non-concessionary patronage and apply this factor to meet the claims of
the bus operators.
Detail
Patronage/concessionary estimation is seen to be sensitive to two main factors - the
coverage of the survey programme and the accuracy of the claims.
Coverage was found to be a problem and an adjustment was made which brought the value
to between +/- 3.5% of the value shown in the DfT's Bulletin. 2000/01 and 2001/02 the DfT
figures climbed while SYPTE’s continued to fall (albeit shadowing). So there is a problem of
consistency between the two sources.
There are 2 factors which may effect on current accuracy:
Because their survey is adjusted according to DfT results, if there are any errors in the
results these are likely to replicated in their own analysis. SYPTE would like to know how the
DfT data are obtained (for example whether all operators supply data, or how such
allocations as patronage on cross-boundary services are made).
The structure of the sample itself. However, SYPTE have made substantial changes this
year to improve this.
As a backup, SYPTE have requested operator data, but they have found that delays in
getting the data makes the cross checking process difficult.
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MERSEYSIDE (MERSEYTRAVEL)
Data are collected by a dedicated team of 40 surveyors, who do count and origin/destination
surveys on buses across Merseyside. The survey is used to reimburse operators who
participate in their concessionary and prepaid travel schemes, and so only those services
that accept these passes are surveyed. However, there are very few services operating
which do not fall into this category, so the PTE continues to use the surveys as a way of
estimating patronage.
The data are grouped by operator, and time of day, for each financial year. The PTE knows
the scheduled vehicle mileage from their service database, and they compare this with the
surveyed vehicle mileage for the same period to get an expansion factor. The PTE knows
the number of passengers surveyed, so they multiply this by the expansion factor to get an
estimate of the total number of trips that would have been made during the year. The same
applies to the passenger mileage, which is derived from the o/d data.
The process is computerised. The sample is geared to reimbursement, which is a continual
process, and the main reason for collecting the data. The methodology in calculating the
payments takes into account the fact that it is a small sample, and is not designed to be
accurate over limited time periods. However, it is currently their best tool for estimating
patronage.
STRATHCLYDE
Bus patronage statistics is an area that is not fully addressed by the PTE. While most PTEs
get patronage figures from the various operators in their area Strathclyde only get those
relating to supported services.
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D Outline Methodologies & Costs
INTRODUCTION
The following section outlines possible methodologies and associated costs for the feasibility
studies recommended in the main report.
LOCAL BUS USE
Use of Multi-journey Tickets
A need for a study to examine the use of multi-travel tickets was identified. The results of this
study are also likely to inform on methods of patronage and fares estimation.
Study Option:
Analysis of NTS diary data to get some information on broad types of tickets being used over
time.
Review of PTE/London Bus passenger surveys. These authorities are often collecting
information on the use of tickets by passengers over time.
Survey of operators.
Study Costs
The NTS could possibly be the cheaper option, mainly requiring NTS staff time. The review
of PTE/London bus data could also be relatively cheap, just requiring TSPT staff time,
although it may be difficult to group the actual tickets types used into standard categories.
Both these sources have the advantage of offering some basic time series analysis.
The survey of operators, while possibly having limited time series value, could provide useful
information on the types of tickets used, the conditions of use, and plans for the future etc. It
could be accomplished with 50 large operator interviews as well as a number of interviews
with smaller operators. The fieldwork and analysis could cost in the region of £30,000 to
£50,000 depending whether a face-to-face or telephone based methodology was employed.
The survey could be tied into the feasibility study on deriving a new fares index – see below.
Measurement of Bus Journey km
It is difficult to obtain reliable bus journey km information given that NTS participants
generally estimate the distance travelled themselves. This survey is, nevertheless, the best
current source of this information.
Study Options
The NTS results could be improved by geo-coding the individual legs of bus journeys – if
these are to be post codes this is likely to be a relatively onerous task. Alternatively,
respondents could use hand held GPS devices for either measuring distances or getting
geo-code co-ordinates or both.
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PTE bus passenger surveys offer an alternative means of gathering this information.
Generally these surveys note the stage at which people have embarked and alighted. An
analysis could be conducted of data produced by these sources although the feasibility of
obtaining reliable and representative data would need to be established.
Study Costs
Obtaining more reliable distance information (especially through geocoding) is already being
looked into by the NTS team. Additional costs are likely to be incurred through the analysis
of the codes generated. If GPS hand-held devices are to assist in estimating km/coordinates, these are likely to cost in the region of £70 each, with perhaps a total of 200
required at any time. This equipment could therefore cost £14k alone.
An examination of the feasibility of using PTE/London Bus surveys would cost about £2000.
NON-LOCAL TRAVEL
Feasibility Study of Estimating School Patronage
This feasibility study would look into the range of funding agencies and service providers
which account for school patronage and determine whether a reliable means could be
employed to estimate the patronage of buses by school children.
Study Approach
There are a wide range of authorities involved in providing bus services for school children
either directly or indirectly. For instance, local education authorities (LEAs) provide fully paid
and subsidised tickets for schoolchildren to travel on local buses while local authorities can
contract operators to provide dedicated school bus services.
An audit would be required to identify providers/funders involved in school transport that
would be willing to participate in a study (the types of organisations have already been
identified in the main study). Next it would be necessary to evaluate the quality of the data
that these organisation can provide and the likely share of patronage for which each of these
sources account. This information would probably be best obtained through a series of faceto-face interviews.
Study Cost
Assuming that about 50 interviews were undertaken, the study would be likely to cost in the
region of £50k.
Feasibility Study into DRT and Community Transport Patronage Estimation
This feasibility study would investigate how patronage associated with these services could
be reliably estimated.
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Study Approach
In practice, it would be possible to work closely with the Community Transport Association to
establish the extent to which particular organisation are issuing permits; the extent to which
issues permits issued are no longer being used; what journeys are being made; what
patronage data is being kept, whether there is a need for a central registry etc.
The feasibility study could focus on a number of specific (representative) geographical areas
so as to get an in-depth appreciation of issues and would be likely to entail mix of face-toface and telephone interviews.
Study Cost:
Assuming approximately 25 telephone interviews and 15 face-to-face the study would cost in
the regions of £20 k.
FARES
Feasibility Study to Investigate Derivation of New Index
This feasibility study would investigate how a reliable index of fares could be generated
which more accurately reflects changes in the price/cost of bus travel.
Study Approach
In the first instance the study would require a survey of the kind of ticketing structures that
operators employ. This part of the feasibility study could be done as part of the study into
types of tickets being used (see above) and would entail specific questions on what price
changes have been made on the different types of tickets; operators’ knowledge of the
number of trips being made on-multi-journey tickets; the pricing strategies that are being
employed; and future plans. This stage of the study could also incorporate a review of the
indexing of bus fares in other countries.
On the basis of the initial results, desk research would be undertaken to model some index
options that could then be tested. A limited number of these options could then be field
trialled by obtaining the responses of groups of selected operators to the new data collection
forms and also by ascertaining the views of expert practitioners.
Study Costs
The study consists of approximately three phases: an initial fieldwork stage (including a
literature review); a modelling phase and a trialling phase. The costs of these phases could
amount to (a) £30k (b) £15k (c) £25k respectively, leading to an approximate total of £70k.
PASSENGER SATISFACTION
Mystery Survey
The objective of the proposed mystery survey would be to give a more ‘objective’ measure of
bus service standards.
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Study Approach
The study could be undertaken on a similar basis to the existing satisfaction survey with a
number of sampling points distributed around England and Wales. These sampling points
are likely to be the departure points for particular bus services. Sampling points could be
stratified according to a number of characteristics including settlement density and car
ownership while the bus services would be stratified according to time of day and
weekday/weekend service.
Study Costs
Assuming that a bus could be ‘observed’ for £15 and that it was decided to undertake 5000
observations, the total cost, along with the inclusion of sampling, administration and
reporting costs would be in the range of £100-£150k.
IMPORTANCE RANKING
This study would be undertaken to inform on people’s attitudes towards the relative
importance of bus service attributes.
Study Options
It could be done as part of the existing satisfaction survey (probably only on a proportion of
the questionnaires since these attributes are do not appear to vary greatly over time). This
additional element could be undertaken annually or over longer intervals.
A separate survey could be conducted annually or for a longer interval (this could be
telephone based).
Study Costs
The key determinant of survey costs are the sample size and the complexity of the sampling.
Option (a) would possibly be cheaper for any given size since it would take advantage of the
survey already taking place. The additional costs of a sample of 2000 interviews enclosing
ranking questions (adding perhaps 3-4 minutes onto the questionnaire) in addition to the
analysis and reporting would approximate to £25k. Option (b), an independent survey of
2,000 bus users, could cost upwards £40k to undertake and report.
RELIABILITY
Feasibility Study of PTE Generated Punctuality Data.
This study would investigate the potential for collecting reliable bus punctuality data from
PTEs and TfL. These authorities are increasingly looking at the application of new
technologies to monitor bus service reliability, although, in some instances these systems
are being independently established by operators (Merseyside). As most bus users are
concentrated in metropolitan areas, the aggregated data from the PTE/London Bus areas
would provide a reasonable proxy of ‘national’ bus reliability.
Study Approach
The study would comprise in-depth face-to-face interviews with PTE/London Buses officers
as well as a number of operators (who are likely to be interested in collaborative ventures if
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punctuality information is not to be used to penalise them). The interviews would seek to
discuss their views concerning punctuality monitoring; their capacity to carry out surveys of
punctuality; what plans are being made to introduce automatic systems (or other
procedures) to monitor punctuality; and what resourcing would be required to implement a
standardised, approach etc.
The study would also investigate the potential for actions to be taken to ensure a consistent
approach to monitoring punctuality across the PTE/London areas, what technologies, for
instance, could be applied etc..
Study Cost
There are 8 metropolitan transport planning authorities (PTEs and TfL).
About 40 interviews should be undertaken with officers drawn from these organisations as
well as with operators and technical specialists. The study would be likely to cost in the
region of £35k.
SAFETY AND SECURITY
New Approach to Collecting Passenger Assault Data
There is a need to investigate new methods of collecting data on passenger assaults from
the police and/or other sources.
Study Approach
The focus of the study would be to identify an effective data collection methodology that
would generate more accurate and complete results. It would include determining whether
police reporting forms could be improved so as to better identify the location of street/public
transport assaults and assessing the quality of the databases being used by the various
police forces. Alternative sources would also be investigated, for instance, whether the data
should be collected through an enlarged British Crime survey which would put street/public
transport crime data in a wider context.
The study would be done through a literature review and interviews with the police,
criminologists, etc.
Study Costs
The study would entail approximately 40 interviews most of which are likely to be face-toface as well as a literature review on the methods used elsewhere. The study could entail
testing of options. The estimated cost for this study would be £40k.
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ANNEX C
WS ATKINS RECOMMENDATIONS
Priority
H/M/L
(2) Consider undertaking a study into the H
growing use of multi-travel tickets and the
impact of this on the accuracy of the patronage
figures (Para 2.42).
(4) Investigate causes of differences between H
PTE and PSV survey patronage estimates to
determine if changes in the PSV sampling
methodology are required (Para 2.48).
(5) Consider the recommendations of the H
Social Exclusion Unit’s report on new
indicators of service availability for their
applicability to national statistics (Para 2.56).
(6) Continually review the burden being placed H
on operators to participate in departmental and
other organisations’ surveys and the potential
for integrating the data provided (Paras 2.63 2.68).
(7) Use BV data collected by local authorities H
to cross-check PSV returns (Para 2.74)
(15) Amend the STATS 30A (changes in bus H
fares) form to include a list of the sorts of
tickets that should be included and excluded
from the survey (Paras 4.15 - 4.17);
(16) Provide guidance on how to derive a H
single estimate where fares increases vary
between ticket types and routes/areas (Paras
4.15 – 4.18).
(17) Investigate the feasibility and relative H
merits of improving the comprehensiveness of
the fares indices through either introducing a
basket of fares, receipts/patronage ratio or a
combined approach (Paras 4.19 – 4.28).
(18) Consider publishing fare indices for H
London and areas outside London (Paras 4.33
– 4.36)
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Action proposed/in hand
To be part of a research project
on establishing a new bus fares
index. In the interim, DfT to issue
guidance
to
operators
on
treatment of these tickets when
calculating passenger journeys
for the PSV survey return.
DfT to establish programme of
visits to PTEs and to consider
further
action
once
visits
completed.
Newly
established
DfT
neighbourhood statistics branch
to progress; proposals on
indicators expected to emerge as
part of guidance for next set of
Local Transport Plans
Accepted, this is anyway part of
the National Statistics code of
practice
DfT will examine sources of LA
level data and attempt to
improve their presentation and
accuracy. This will involve
discussions of differences with
LAs and operators.
DfT will commission a research
study in 2003/04 to establish a
more robust local bus fares index
which will take into consideration
all the Review recommendations.
See (15) above.
See (15) above.
See (15) above.
QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
(21) Consider referencing Best Value website H
(Para 5.28).
(25) Promote the development of an agreed H
national indicator for punctuality (Paras 6.32 –
6.34).
(26) Advise on a common indicator for H
punctuality, sampling methods and use of
technology for collecting and analysing data
(Para 6.39).
(27) Investigate how data derived from PTEs H
(in partnership with local operators) could
collect punctuality data for use in producing a
national indicator (Paras 6.35 – 6.38).
(28) Liaise with SEU and police over the H
potential for segmenting the passenger
assaults data to enable analysis of socioeconomic characteristics (Para 7.4).
(29) Investigate new methods of collecting data H
on passenger assaults from the police to
improve coverage and accuracy. (Paras 7.14 –
7.16).
(30) Reappraise the need for data on H
vandalism to buses, taking into consideration
actions that are likely to be necessary to
improve accuracy (Paras 7.18 – 7.19).
(31) Consider reducing the frequency of the H
staff assaults survey from quarterly to annually
(Paras 7.20 – 7.22).
(32) Consider publishing regional statistics on H
the composition of the fleet, proportion of low
floor vehicles and proportion of fleet fully
accessible to wheelchairs in the Bulletin (Paras
7.47 – 7.49).
(34) Investigate the potential for including Light H
Rail reliability and passenger satisfaction data
in the Bulletin (Para 7.54).
(1) Note the different methodologies adopted M
by the NTS and PSV survey beneath the
relevant tables in the Bulletin (Paras 2.36 –
2.38).
(3) Monitor opportunities for improving the M
accuracy of data and ease of data provision
through the application of new technologies
(Para 2.44).
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To be included in DfT local
project - see (7) above
DfT will be working on this
the next year as part of the
target monitoring process.
DfT will be working on this
the next year as part of the
target monitoring process.
data
over
PSA
over
PSA
DfT will be working on this over
the next year as part of the PSA
target monitoring process.
The newly created Safer Travel
on buses and coaches Panel
(STOP) will address all the
recommendations under this
heading
The newly created Safer Travel
on buses and coaches Panel
(STOP) will address all the
recommendations under this
heading
The newly created Safer Travel
on buses and coaches Panel
(STOP) will address all the
recommendations under this
heading
The newly created Safer Travel
on buses and coaches Panel
(STOP) will address all the
recommendations under this
heading
DfT
to
consider
whether
meaningful and reliable data can
be produced from the DVLA
database.
DfT will be working on this over
the next year as part of the PSA
target monitoring process
DfT to add text to relevant
Bulletin tables
DfT to collect information about
areas with smart card schemes
and assess the quality of the
information available from smart
cards and judge whether there is
QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
(8) Consider ways of improving the accuracy of M
passengers’ estimates of journeys lengths in
the NTS to provide a more accurate estimate
of bus pass-kms, particularly if pass-kms are to
be used to monitor modal share (Paras 2.75 –
2.81).
(9) Liaise with NTS officers about the potential M
for including ticket types used in the Bulletin
(Paras 2.82 – 2.85).
(11) Make changes to the PSV form to identify M
patronage and veh-kms by scheduled coach
services (Paras 3.32 – 3.36).
(12) Consider if there is a need for patronage M
relating to school travel, if so, commission a
study into the feasibility of collecting data from
service providers (Paras 3.41 – 3.45).
(13) Alternatively, adapt the NTS to give better M
coverage of schoolchildren and revise the
categories of bus travel (Paras 3.46 – 3.49).
(14) Commission a feasibility study to M
investigate the potential to identify DRT and
community transport providers and obtain
patronage data from these sources (Paras 3.50
– 3.59).
(22) Investigate the feasibility of ranking M
service attributes in terms of their importance
(Paras 5.34 – 5.38).
(23) Include perceptions of non-users from the M
results obtained form the relevant Omnibus
survey (Paras 5.39 – 5.40).
(35) Consider ways of raising awareness of M
light rail statistics (Para 7.59).
(36) Investigate consistency of trip length M
estimates
(10) Consider publishing information on the L
number of QPs and QCs in the Bulletin (Paras
2.89 – 2.92).
(19) Investigate the feasibility of introducing L
mystery shopping survey to complement the
106738135
scope for improving existing
statistical series and creating
new series. This will be kept
under review as use of smart
cards
becomes
more
widespread.
Accepted, DfT is considering, in
the longer term, ways of
improving estimates of journey
length, for example, through geocoding.
Included in annual Bulletin of
Public Transport Statistics from
November 2002
DfT to design questions in
conjunction with Confederation
for Passenger Transport
Accepted, DfT also considering
the way data on school travel are
collected in NTS.
See (12) above, DfT to consider
for the 2004 NTS.
Need to delay until results of DfT
consultation
on
extending
FDR/BSOG
to
Community
Transport are known and the
implications assessed
DfT to consider periodic separate
surveys to establish importance
of different attributes (although
can be done by analysing
existing results).
DfT to include in next annual
Bulletin (November 2003).
DfT to pursue and to include bus
and coach statistics as well.
DfT to clarify with light rail
operators
Has been considered, but
thought not to be meaningful
given the wide range in the
scope of these arrangements.
However, DfT will continue to
publish research findings.
DfT will not be implementing this
recommendation as it is not an
QUALITY REVIEW OF BUS, COACH AND LIGHT RAIL STATISTICS
Final Report
existing satisfaction survey (Paras 5.30 –
5.31).
(20) Agree and promote a standardised L
approach to passenger satisfaction surveys to
enable comparisons to be made (Para 5.25).
(24) Consider the appropriateness of L
publishing a future congestion indicator in the
Bus Quality Indicators Bulletin (Para 6.22).
(33) Review the DVLA size banding to better L
reflect the industry’s classification on bus types
(Para 7.50).
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application used for National
Statistics.
DfT to add to Local Transport
Plan guidance.
DfT
will
consider
which
publication best suited for this
purpose.
DfT will investigate whether any
action is necessary.