The Effects of Park and Ride Supply and Pricing on Public Transport Demand

3 Study methodology

3.1 A methodology has been developed to respond to the objectives by combining outputs from secondary research with conclusions from new primary research that has been tailored to fulfil the study objectives. Choosing a railway station or bus based park and ride as part of a journey is influenced by a complex set of variables, including the cost and availability of car parking and the rail or bus journey options available in terms of speed and frequency which help to attract passengers. The car parking availability and the attractiveness of the onward public transport can impact on demand, but there is relatively limited guidance to understand how these variables interact in terms of:

  • driving to the station, park and catch a train
  • driving to an off-site car park, park and catch a train
  • drive to an alternative station and catch a train
  • use an alternative access mode (such as public transport, cycling or walking - or obtaining a "kiss & ride" lift) to this or an alternative station, and catch a train
  • use a car (or possibly another mode such as bus) for the whole journey

3.2 There is a limited understanding of the overall impact of these variables, so the study methodology combines primary and secondary data for a number of important reasons:

  • there was some uncertainty whether analysis of secondary ticket data would be adequate to identify trends, hence the requirement for additional primary data
  • results from the interview surveys were used to understand responses to a range of policy choices, and some data was incorporated in the models
  • the two datasets offered an independent validation of each other
  • the combined datasets helped to generate a statistically robust dataset

Secondary research

3.3 Several existing data sources were reviewed including historic rail journey patterns, parking availability at stations, a range of socio-economic data, plus various monitoring reports relating to bus based park and ride. This was to provide background information and to populate the forecasting model. Further details of the data sources used are given in Chapters 4 to 6.

Primary research

3.4 Econometric modelling has been completed to determine the effects of parking provision, prices and policy directly on the demand for travel. Demand models have been developed that link observed and stated behavioural responses to changes in parking provision, quality and prices. The econometric models use the base number of rail trips, plus other factors to estimate demand impacts. The impact of parking policies is then overlaid, in terms of the number and change in parking availability and charges, plus the quality and security of these facilities to examine a range of user responses. Further details of the modelling approach are presented in the Appendices.

3.5 A case study approach has been adopted for the primary research. This includes rail case studies at Bridge of Allan, East Kilbride, Perth and Kirkcaldy (and control sites at Stirling and Falkirk High) and bus park and ride case studies at Ingliston (Edinburgh) and Bridge of Don (Aberdeen). A further case study - Cross Forth - examines competition between bus based park and ride at Ferrytoll and rail at Inverkeithing. More information is provided on these case studies in Chapters 4 to 6. The primary case studies have been carefully selected, to ensure the results are sufficiently useful and applicable to help evaluate proposals in other parts of Scotland. This transferability is a fundamental aspect, providing a good indicator if other proposals might be successful, subject to fulfilling specified criteria.

3.6 Surveys were carried out with existing users of the case study sites. The face to face interviews were conducted throughout the day on both weekdays and weekends. The initial questionnaire was piloted and amendments completed based on the feedback. Initial screening questions were presented to potential respondents to ensure their travel characteristics were relevant to the survey. The surveys covered topics including gender, age, journey purpose, ticket type, parking costs and attitudinal responses to facilities at the car park. Copies of the survey questionnaires are presented in Appendix A6.

3.7 The surveys were conducted in accordance with Market Research Society guidelines and administered using Personal Digital Assistants (PDA) and took a maximum of 15 minutes for the rail and bus surveys, and 15 minutes for the Ferrytoll interviews. A broadly equal number of male and female respondents were interviewed. There was no bias in favour of interviewing either gender, with the sample influenced by who had time to stop and be interviewed. The sample rate of one interview per two or three people was estimated by the interviewers, although a higher sample rate was needed at the less busy stations. Two interviews from the bus surveys were not completed and these were excluded from the overall dataset. The total number of incomplete surveys from the rail and Ferrytoll interviews was 23 and 15 respectively. Table 3.1 confirms the number of interviews for existing users.

Table 3.1: Summary of completed interviews (existing users)
Rail Status Number of interviews Bus Number of interviews Cross-Forth Number of interviews
Kirkcaldy Case study 101 Ingliston 138 Ferrytoll 87
Bridge of Allan Case study 115 Bridge of Don 112 Inverkeithing 72
East Kilbride Case study 107
Perth Case study 36
Falkirk High Control 64
Stirling Control 64

Source: Accent

3.8 The responses were collated and used to help populate forecasting models. To supplement the existing user surveys presented above, interviews were also completed for respondents not currently using park and ride who were interviewed in Edinburgh and Aberdeen city centres who could potentially switch from their existing mode. A total of 120 interviews were conducted, 67 in Edinburgh and 53 in Aberdeen with non users to understand the characteristics of their journeys and the factors which may influence the likelihood of switching modes.

3.9 The following summarises the age and gender characteristics of the sample interviewed. More detailed technical description of the methodology is contained in the appendices.

Rail case studies

3.10 The gender of respondents is presented in Figure 3.1. An equal split of men and women were surveyed at East Kilbride, with a significantly higher percentage of women interviewed at Kirkcaldy and Bridge of Allan. At Falkirk High, Stirling and Perth, the proportion of men interviewed was higher. However, very few female respondents were surveyed at Perth, whereas the majority of people interviewed at Kirkcaldy and Bridge of Allan were female. Overall, 52% of the sample was female, with males accounting for 48%.

Figure 3.1: Gender of respondents

Figure 3.1: Gender of respondents

Source: Arup analysis of Accent data. Sample sizes are shown adjacent to each bar

3.11 The vast majority of respondents were aged between 30 and 59 years old. East Kilbride had the highest proportion aged between 16 and 29 accounting for 28% of respondents, whilst Stirling had the highest proportion of people aged over 60 (19%), as shown in Figure 3.2.

Figure 3.2: Age of respondents

Figure 3.2: Age of respondents

Source: Arup analysis of Accent data, sample size shown

3.12 Rail ticket data, plus other economic information (GDP, employment, population) and the availability of parking information was incorporated into a model. Some of the results from the primary data collection were then used to estimate the demand impacts from the additional parking availability and attitudinal responses to the availability of lighting and security. Further details of the methodology used are included in Chapter 4 and Appendix A1.

Bus case studies

3.13 The majority of male respondents were interviewed at Ingliston, whereas most of the females were surveyed at Bridge of Don. Almost 60% of respondents were aged between 30 and 59 years, as shown in Figure 3.3.

Figure 3.3 Gender and age characteristics

Figure 3.3 Gender and age characteristics

Source: Arup analysis of Accent data, sample size shown

3.14 Similar to the rail model, results from the primary research were incorporated into a forecasting model to understand the impact of parking availability on demand. A Revealed Preference model7 was created for existing users, with a Stated Intention8 survey undertaken with non-users. The results from this primary research were incorporated into the model. Further details of the methodology are presented in Chapter 5 and Appendices A2 and A4.

Cross Forth case study

3.15 The purpose of this Stated Preference (SP)9 exercise was to assess the relative attractiveness of bus and rail based park and ride using Inverkeithing and Ferrytoll. It was beyond the resources of this study to identify and interview a robust sample of current car users for whom Inverkeithing and Ferrytoll would be realistic alternatives for their existing journeys. As a result, the extent of bus or rail improvements needed to attract existing car users has not been quantified. Forecasting models were built for each mode.

3.16 A sample of existing users was approached in the car parks at Ferrytoll and Inverkeithing. A brief interview was conducted about their current journey and followed by a SP exercise describing alternative travel choices. These included changes to the daily return fare, the journey times and service frequencies. Variables were assigned to attempt to induce changes in behaviour in order to reliably estimate the impact of behavioural responses. A range of scenarios were presented, with rail journeys generally assumed to be faster but generally more expensive and less frequent than bus. The actual access and egress times (time spent getting to the final destination from the bus stop or railway station) were also included in the modelling, although these parameters were fixed. A total of 159 interviews were completed, with 72 at Inverkeithing and 87 at Ferrytoll.

3.17 Similar to the bus based surveys discussed above, females accounted for a larger proportion of the overall total (60%) of interviews. Respondents aged between 30 and 59 years accounted for almost two-thirds of the total and this result is comparable to the respondents surveyed as part of the bus sector. Figure 3.4 presents the results.

Figure 3.4: Summary of the age / gender profile

Figure 3.4: Summary of the age / gender profile

Source: Arup analysis of Accent data, sample size shown

Consultation with First ScotRail and Regional Transport Partnerships

3.18 To supplement the primary research, discussions with First ScotRail and Regional Transport Partnerships were held as shown paragraph below. The support for expanding car park availability at stations was examined, along with the role of parking to grow demand. The opportunities and issues associated with expanding parking availability were also explored.

3.19 The emerging results from the bus analysis were discussed with some Regional Transport Partnerships. Feedback from was received from TACTRAN and SESTRAN. Many of the RTPs are supportive of park and ride, and this can be demonstrated by the preparation of overarching strategy documents10. These discussions helped to supplement some of the emerging analysis from the literature review presented in Chapter 5 to understand the relative performance of existing schemes.