University of Groningen Bicycle Sharing System Wiersma, Bouke

University of Groningen

Bicycle sharing system Wiersma, Bouke

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Download date: 11-02-2018 Abstract

This thesis investigates the role and effects of a bicycle sharing system, and studies the feasibility of such a system in Plymouth. The research consists of a literature review, policy discussion, case studies, and a detailed assessment of the local demand by performing interviews, focus groups and a survey. This study concludes that a bicycle sharing system in Ply- mouth is at the moment very unlikely to become successful, in terms of attracting significant numbers of users, achieving substantial modal shift and reducing CO 2 emissions. One of the main reasons for this is the cycling-unfriendly situation on the road: there is a lack of high- quality cycling infrastructure, few restrictions on motorized traffic, and not enough consideration is given to cyclists by drivers. Furthermore, individuals experience social norms unsupportive of cycling, while few incentives exist for individual modal change. There is no strong policy support for cycling, and Plymouth’s size does not seem to be optimal for bicycle sharing. Elsewhere, bicycle sharing has led to a sudden increase in numbers of cyclists, which had several reinforcing effects as cycling became more mainstream, social norms changed, and drivers became more aware of cyclists. It is not entirely clear to what extent bicycle sharing in general has been a vital part of increasing levels of cycling elsewhere, and taking into account its high costs it represents a very improbable policy alternative for Ply- mouth at this moment.

Contents

ABSTRACT 1

CONTENTS 3

ACKNOWLEDGEMENTS 5

1 INTRODUCTION 7

1.1 INTRODUCTION TO THIS STUDY 7 1.2 RESEARCH GOALS 8 1.3 METHODOLOGY 9

2 LITERATURE REVIEW 15

2.1 INTRODUCTION 15 2.2 INTRODUCTION TO BICYCLE SHARING SYSTEMS 15 2.3 THE ADVANTAGES AND DISADVANTAGES OF CYCLING 17 2.4 THE DETERMINANTS OF BICYCLE USE 19 2.5 DETERMINANTS OF BICYCLE USE : IDENTITY AND ATTITUDES 23

3 PHYSICAL AND POLICY CONTEXT 27

3.1 INTRODUCTION 27 3.2 NATIONAL POLICY 27 3.3 LOCAL POLICY 28 3.4 LOCAL CHARACTERISTICS 29

4 CASE STUDIES 31

4.1 INTRODUCTION 31 4.2 PARIS 31 4.3 BRISTOL 32 4.4 CARDIFF 33 4.5 BLACKPOOL 34 4.6 DIJON 34 4.7 KEY POINTS 35

5 THE INFLUENCES ON A LOCAL SCHEME’S SUCCESS 37

5.1 INTRODUCTION 37 5.2 CYCLING -UNFRIENDLY SITUATION ON THE ROAD 37 5.3 HILLINESS 38 5.4 INTERNAL BARRIERS TO ACTION 38

5.5 HABITS 38 5.6 BICYCLE SHARING -SPECIFIC CHARACTERISTICS 39 5.7 OTHER INDIVIDUAL ATTITUDES 39 5.8 EXTENT OF LOCAL INTEREST 40

6 DISCUSSION 43

6.1 INTRODUCTION 43 6.2 MAIN RESULTS 43 6.3 APPLICATION TO PLYMOUTH 47 6.4 LIMITATIONS OF THIS RESEARCH 50 6.5 FUTURE RESEARCH 51

7 CONCLUSIONS 53

REFERENCES 55

APPENDICES 63

A MAP OF PLYMOUTH 63 B CALCULATION OF MODAL SHARE 64 C THE QUESTIONNAIRE 65 D STATISTICAL PROCEDURES 71 E SUMMARY OF SURVEY RESULTS 72 F PROPOSAL FOR BICYCLE SHARING SYSTEM IN PLYMOUTH 75 G MAPS CREATED DURING FOCUS GROUPS 77 H CALCULATION OF CO 2 EMISSION REDUCTIONS 78 I CALCULATION OF BENEFIT-COST RATIOS 79

Acknowledgements

This thesis was written as part of the MSc Energy & Environmental Sciences at the Univer- sity of Groningen. It was created in the period from December 2009 to July 2010, during a work placement at the Sustainable Transport Team at Plymouth City Council. It served as a feasibility study for the Local Transport Plan 3.

I would like to thank my excellent and patient supervisors Henk Moll, Jon Shaw, and Jennie Middleton for their superb support and their elaborate and constructive comments throughout the thesis process. Also, I am grateful to all my colleagues at Plymouth City Council who helped me with producing this document in many ways, and provided me with invaluable work experience. Finally, thank you to all participants and respondents for taking part in my interviews, focus groups and survey.

1 Introduction

1.1 Introduction to this study Increasing levels of cycling has become a policy priority in many countries. Reasons for this include the health benefits, low environmental impact, noise reduction and cleaner air associated with cycling (Tolley, 2008). In the United Kingdom (U.K.), 26.5% of national CO 2 emissions originate from road transport (Department of Energy and Climate Change, 2009); offering considerable opportunities for CO 2 reduction by encouraging sustainable modes of travel. The urgency for this is highlighted by the tendency of emissions from transport to grow, in contrast to declining emissions from other major sources, such as industry and power generation (Anable & Shaw, 2007) . The potential for increasing cycling rates is evident, since 56% of all car trips made in the United Kingdom in 2008 covered a distance below five miles, according to the 2008 National Travel Survey (Department for Transport (DfT), 2009a); a distance that can very well be covered by bicycle. Moreover, the number of bikes approximately equals the number of cars present in the United Kingdom (Cairns, 2001).

An increase in bicycle use can be achieved in many ways; for example by improving cycling infrastructure, marketing its benefits, or discouraging higher-impact modes of transport (Mai- bach, Steg & Anable, 2009). A practice which has proved to be rather popular in recent years is to provide a bicycle sharing scheme, also known as community bicycle systems, public bicycles, or smartbikes (these terms are used interchangeably in this thesis). A bicycle sharing system covers a part of the city with a number of automated docking stations, at which subscribers can conveniently pick up or drop off one of the available public bicycles. Advan- tages of this system include that it is not necessary for users to buy, store and maintain their own bicycle or worry about theft, that it improves integration between different transport modes, and that it enables one-way only trips, since users are enabled to leave the bicycle at another docking station. Generally, usage is very inexpensive, with the first half hour of each trip being free, and an average annual fee of around €20 (£17). The scale of existing bicycle sharing systems differs greatly; in Paris, up to 1451 stations and 20600 bicycles have been available throughout the city centre (Vélib’, 2007), while in Bristol the sharing scheme consisted of 8 stations and 16 bicycles (OBIS, 2009). Today, over 200 sharing schemes exist throughout the world, by far most of which in Europe, and for 2010 many more are planned to be implemented.

In Plymouth, United Kingdom (for a map see Appendix A, p.57), mode share for cycling is about 1% (Appendix B, p.58). Nationally, despite the setting of ambitious targets in the mid 1990s, levels of cycling have remained unchanged at 1.5% ever since. Currently local authorities are required to set their own targets regarding bicycle use; Plymouth City Council (PCC) is currently meeting its own target of a 1% annual increase. The most important local plan regarding cycling is the Local Transport Plan 2 (LTP2). In 2011, the new LTP3 will be completed, setting out policy for the period 2011-2026. For the future policy on cycling, set out in the LTP3 document, PCC aims to find out about the opportunities offered by a bicycle

7 sharing scheme. This has provided the direct incentive for this study; however, the absence of academic research on bicycle sharing schemes in mid-sized cities, the factors determining their success or failure, their main effects, and their role in a transition towards sustainable transport was an equally important reason for conducting this investigation. So far, some research has been done on the factors determining the success of bicycle sharing schemes. The available studies focus almost exclusively on the large and well-known schemes, such as the ones in Paris, Lyon and Barcelona, for their evidence base. This may bias their conclusions; a notion of particular relevance for mid-sized cities such as Plymouth. So, it is relatively well- understood how sharing schemes can be successful in big cities, but their success or failure in smaller cities has not been considered at all. This is rather more striking when one considers that no mid-sized city has created a sharing scheme with user rates as high as in the major schemes. One notable exception is the European OBIS project (Optimising of Bike Sharing in European Cities), which reviews bicycle sharing practice in ten different countries. The project will “identify good practices, success factors, limits and market potentials by analyses, demonstrations and optimised strategies” (OBIS, 2010). However, the OBIS research results were not going to be available on time to be of any value for Plymouth’s LTP 3, and lacked case-specific focus. Therefore, this thesis served as a feasibility study for implementing a bicycle sharing scheme in Plymouth, focusing on whether and how such a scheme could be successful, and what the environmental and monetary costs and benefits could be. With an eye on the wider relevance of this study, the focus was widened to discuss the effects and role of bicycle sharing schemes in general.

1.2 Research goals This research was guided by two main research goals. First of all, the objective was to explore whether and how a bicycle sharing scheme can be successful in Plymouth. Secondly, this study aimed to review the role and effects of bicycle sharing systems in general. To provide a basis for understanding this subject, this study firstly examined the existing body of literature on the determinants of bicycle use. The focus here was on cycling for transport, as opposed to leisure cycling. The reason for this was that most bicycle sharing schemes are aimed at utility journeys rather than leisure journeys. Also, their pricing structure encourages short trips, which makes it less attractive to use the bicycles for longer leisure trips. While public bicycles are ideal for tourists exploring the city, it is likely that this group represents a small proportion in Plymouth. The review of determinants of bicycle use highlighted the potential role of providing bicycle sharing facilities, as well as the relation to providing other, additional incentives to cycle. From this discussion, an overview was acquired of the factors influencing bicycle mobility. Secondly, the current transport and cycling context in the United Kingdom and Plymouth was described, focusing on national and local policy, and summarizing the city’s relevant characteristics. This was particularly relevant in order to make any implementation of public bicycles successful in Plymouth. Also, it was significant in terms of understanding the current (low) levels of cycling and possible opportunities or constraints related to a bicycle sharing scheme. Furthermore, it was important to acknowledge that Plymouth was not the first city considering implementing a public bicycle scheme. Some predecessors have created very successful schemes, while others schemes failed. To understand the factors influencing the success or

8 failure of various previously constructed schemes, and the role and effects of bicycle sharing in these cases, a number of them were studied.

The next aspect of this study attempted to estimate the demand for a bicycle sharing scheme in Plymouth. Clearly, the success of a scheme is determined by whether people are actually interested in using it regularly. Although current cycling levels are low, this does not necessarily mean that there is no potential for cycling. This section tried to establish which barriers to cycling people in Plymouth perceived, the differences in cycling behaviour and attitude between various groups (male/female, employed/unemployed/student) and the extent to which the local residents indicated to be interested in the scheme. The findings from these parts of the study were used next to identify the opportunities for a bicycle sharing scheme in Plymouth. This answered the question whether and how a sharing scheme could increase cycling rates in Plymouth. This involved a proposal of the most suitable locations to position the docking stations, as well as recommendations with regard to the priority a sharing scheme should receive in policy, and the role it could play in encouraging cycling in Plymouth. Also, the benefits of a public bicycle system in terms of CO 2 emission savings were quantified, along with an assessment of its benefit-cost ratio.

1.3 Methodology In this study a multi-method design was chosen, including both quantitative and qualitative methods, as this allows for one method to compensate for the weaknesses of the other (Gray, 2009). A literature review was conducted as a starting point for understanding cycling behaviour in general and related to bicycle sharing schemes. The relevance of a literature review has been pointed out by Gray (2009), as it provides an up-to-date understanding of the subject, identifies key gaps in knowledge, and guides the development of the study. To find literature, ISI Web of Knowledge was used in the period between November 2009 and April 2010, with combinations of key words including ‘smart bikes’, ‘bicycle sharing’, ‘public bicycles’, ‘attitude to cycling’, ‘determinants of cycling’, ‘cycling behaviour’, ‘cycling to work’, ‘bicycle commuting’ and other similar terms. However, due to the limited amount of academic research on sharing schemes, a similar search with the same terms was conducted online using Google, in order to find government or consultancy reports on the subject. Ref- erences from articles and reports found were also used to find more relevant literature.

Secondly, the discussion of the local context was mostly descriptive in nature, and relied on government policy and statistics. Selection of relevant literature for this section was supported by the relevant PCC officers. The section on national policy was largely based on the DfT website (DfT, 2010a), while LTP 2 and its supporting documents were used to inform the section on the local context. Surveys such as the 2001 national census (ONS, 2001) and the 2008/2009 Plymouth school census (PCC, 2009) were key documents for providing an overview of the levels of cycling in Plymouth. For this part of the study, the input from PCC staff was important, as they were the main audience for the results of this study, and they are fully aware of the important issues of influence for this study.

In the following part of the research, a number of cases were studied to find out why some of them succeeded and others failed. Case studies are often used when a ‘why’ or ‘how’ ques-

9 tion is being posed, and when the focus is on a contemporary phenomenon in a real-life context (Yin, 2009), which is the case in the current study. Next to this, the main reason for including case studies in this thesis was the lack of specific research into bicycle sharing schemes. Even though many different schemes exist at the moment of writing, few of them have been reviewed in-depth. Moreover, generally speaking, only the very successful, large- scale schemes such as those in Paris and Barcelona have been studied before in a way useful for this research. As noted earlier, the lessons learnt from these schemes may very well not be applicable to Plymouth, as the city size is completely different. Another reason for studying other cases has been that it could provide very useful qualitative data, for example on implementation strategies and the philosophy behind the spatial lay-out of the scheme. In this study, multiple cases have been studied, as it is difficult to generalize from one specific case (Yin, 2009). The case studies were primarily informed by internet research, mostly using the same key words as with the literature review. In some cases, this was supplemented with individual contact with directly involved officials. The selection of cases to be studied was based on similarity to Plymouth, size of the city and scheme, and the availability of information. Also, it was considered essential to include both successful and less successful schemes. The case studies were conducted in a qualitative way, covering a range of topics as wide as possible. With all cases, an emphasis was placed on the number of hires per bicycle per day (with higher use rates indicating success), and the relation between this and the city’s and scheme’s size. One of the factors reviewed with specific interest for all cases was the design philosophy behind the spatial distribution of the stations: this might be of particular relevance in case only a limited number of docking stations can be funded. The collection and analysis of data was focused on answering these questions.

The case studies were followed by an estimation of the local demand for a public bicycle scheme, for which a survey, two focus groups and four interviews were carried out. One of the reasons for organizing focus groups and interviews is that surveys generally tend not to capture the underlying meaning of attitudes and behaviour of involved individuals (Lewis- Beck, Bryman & Futing Liao, 2004). Being more qualitative in nature, focus groups allow for a variety of views to emerge, while group dynamics can often encourage the stimulation of new perspectives (Gray, 2009). Two focus groups were organized in April 2010; one session was held with the bicycle user group (BUG) of PCC, and one with the BUG of the University of Plymouth. Four people attended the PCC focus group (three male, one female), and three people attended the University focus group (all female). This way, experiences from long- standing cyclists were included in this study to get a feel of the broader issues relating to cycling and bicycle sharing in Plymouth. The focus groups had two main objectives; creating a proposal for the locations of the docking stations, and to learn from accomplished cyclists’ experiences of cycling in Plymouth. For the proposal, an A1-sized map of the central part of Plymouth was provided to the participants, on which the locations for the stations could be drawn. The map did not show all of Plymouth, because bicycle sharing schemes generally are focused on the central part of the city, as most trips take place in that area, but also because this part of Plymouth is the least hilly. The participants were also informed about the assumptions that the scheme is most likely to succeed in the central and flat area shown on the map, and that the number of docking stations PCC can afford is finite. For the rest, they were free to indicate where stations should be located according to them.

10 Both sessions were recorded using the voice recording option on a mobile phone. These re- cordings were used to create a list of the most relevant statements and opinions expressed. Some issues identified in this list were new to the research and were therefore copied into the survey, while others were categorized into main factors influencing the success of any public bicycle system in Plymouth. Particularly issues which were mentioned often or issues which were agreed on by multiple participants were considered important and were used to identify key issues associated with bicycle sharing and cycling in Plymouth. The advantage of organizing a focus group with PCC officers, who both cycle to work and work with transport on a daily basis, is an awareness of current issues and opportunities. The other main result of the focus groups, two maps proposing key locations for docking stations, were not processed, but were used as a basis for a final proposal. The problem with using only BUG members was that they only involve members of the workforce who cycle regularly. While employed persons may have different views on cycling to start with, another problem was that the scheme should attract new cyclists, rather than replacing already existent cycling trips. Therefore, it is important to speak to those other groups as well.

For this reason, in April 2010 a number of students were recruited from the psychology participant pool, which consists of all undergraduate psychology students, who have to partici- pate in a set number of studies as part of the curriculum. Due to the ending of the academic year few students were available and the number of interviewed students totalled four, which were, probably due to the skewed demographic of the psychology courses, all females aged 18-29. These students were interviewed one at a time, which enabled them to fully express their opinions and experiences. They were asked open questions about their experience of cycling in Plymouth, their interest in using a possible bicycle sharing scheme and the motiva- tions for that, and under what circumstances they would like to use the scheme. Notes were made during the interview. The data gathered this way was processed in a way similar to the focus group data analysis. It was used to get a feel of which issues spring to mind in non- cyclists when presented with information about a bicycle sharing scheme, as well as any reasons for (not) using the scheme. The notes taken were not systematically analysed, rather key issues which arose during the interviews were used to both inform the questionnaire and shape the overview of influential factors. The participants were also asked to complete a first version of the questionnaire, as a pilot study to check whether the questionnaire measured what it intended to measure, and whether the questions were formulated in a clear and under- standable way. Some changes in the phrasing of questions were made as a result of this. These focus groups and interviews were conducted prior to the survey, as they directly informed the questionnaire, by helping to create a map containing a proposal and by identifying key issues to be included. The map was considered crucial in order for respondents in the survey to assess whether they would be interested in using it. Also, the ideas and discussions from the focus group helped to identify key issues to be included in the questionnaire. Includ- ing the knowledge and experience of the city’s cycling context from regular cyclists is a particularly important part of designing appropriate policies (Pucher, Dill & Handy, 2010).

Next, the survey was performed, aiming to quantify the interest in using a bicycle sharing scheme in Plymouth, to explore which group is most interested, and to identify the main barriers to cycling in Plymouth. A survey was considered to be the appropriate method, as a large quantity of data was required for a generalization towards the wider population. Also,

11 surveys are generally used for predictive purposes, focusing on the general population, rather than on a limited number of individuals (Kitchin & Tate, 2000). Qualitative research methods, such as in-depth interviews, are not suitable for making a generalization towards the wider population, as they do not provide the rather large amount of data required for this. Next to estimating the local interest in using a scheme, aims of the survey included among others measuring attitudes to cycling, identifying the type of trip purpose for which the scheme would potentially be used, and examining the key areas where the scheme could be expanded. All aspects and variables included in the questionnaire were included based on the expectation that they influenced the interest in using a bicycle sharing scheme. The questionnaire used consisted of four parts, and can be found in Appendix C (p.59). The first part concerned basic personal characteristics, such as gender, age, income, and bicycle ownership. The second part related to travel habits, asking about mode of travel to work or city centre, distance of daily commute, and frequency of bicycle use. In the third part, respondents indicated to what extent they agreed (1 = totally disagree, 5 = totally agree) with 20 statements measuring their attitude towards cycling. The final part evaluated their interest in using the proposed bicycle sharing scheme in Plymouth, after introducing the respondent to the basics of such a scheme. Participants were recruited using two methods. These methods were chosen based on their expected relatively high response rates, compared to telephone or mail surveying, and the low costs associated with it. First of all, participants were recruited in the city centre, in an attempt to reach all sections of the population. Passers-by were asked to complete a paper questionnaire, which took each respondent about 10 minutes. Talking the participants through the questionnaire individually and writing down the answers, would easily take 20 to 30 minutes, an amount of time few people are presumably willing to spare. Moreover, keeping the time it takes to complete the questionnaire relatively short reduced the risk of participants losing interest. Interviewer variability, such as asking questions in a different sequence or way, was absent, and the number of open questions was kept to a minimum, as they are likely to reduce the response rate and cause analysis problems (Bryman & Teevan, 2005). Two open questions were included to interpret the responses on closed questions, make an assessment of data quality, and enable respondents to fully express themselves. Shortening the questionnaire was considered not to be desirable, as the amount and diversity of information acquired would have been drastically lower. In total, 62 questionnaires were completed in the city centre, of which one case was removed due to unreliable data. The second data collection method involved PCC staff. Officers within the development team were approached by hand- ing them questionnaires in person, or via their respective secretaries, ensuring a very high response rate. 110 questionnaires were returned, of which eight were removed, due to either the physical inability to cycle or data quality concerns. The data collection methods produced complementary samples; for example, the lack of 30-49 years olds and full-time employed persons in the city centre was compensated by the PCC sample, providing a balanced dataset which included reasonably sized groups from every section of the population.

The data was processed using SPSS version 16.0. A number of modifications have been made to the data. Two of the attitude scales (‘I have got the required skills to ride a bicycle safely’ and ‘It is unlikely that I will use the scheme at all’) were reversed for compatibility with other variables. A ‘general interest’ variable was calculated by adding all five interest-related questions (see Appendix D, p.65), in order to simplify the analysis. This was supported by the use

12 of a data reduction technique, factor analysis, which classified the five variables into one group, indicating they measure the same underlying construct (Brace, Kemp & Snelgar, 2009; see Appendix D, p.65). Together they explained about 63% of the variance.

Some of the questions from the attitude scale in part three were categorized as external barriers to cycling and internal barriers to cycling. External barriers to cycling relate to factors outside of the individual, such as cycling infrastructure, hilliness and weather. Internal barriers on the other hand, are personal factors such as being unconfident on a bicycle or perceiving a social norm in which cycling is abnormal. A factor analysis has been carried out, using the methodology from Timmerman and Stuive (2007), which confirmed that these variables were categorized in the appropriate group. To determine the effects of internal and external barriers to cycling on demand for the scheme, the respective variables were recoded into groups: resulting in both an internal barriers variable and an external barriers variables con- sisting of five groups ranging from very high to very low barriers. The two datasets were considered separately in the analysis phase, as data collection location and demographic characteristics of both samples were rather different. The PCC data can be considered to represent those who work in the city centre, while the other dataset is more representative for the group who come into the city centre for non-work reasons.

Throughout this research, all descriptive statistics from the survey concern both datasets combined, unless stated otherwise. Also, when the results on a particular variable differs significantly between the two datasets, this will always be mentioned; if this is not mentioned, the results do not differ significantly. For example, regarding the results on part three of the questionnaire (the attitude Likert scales), only two out of 20 differed significantly between the two datasets, indicating that despite their methodological and demographical differences, the actual results are rather similar. In Appendix E (p.66), the datasets are presented together to limit the amount of data and present a comprehensable overview of the results. The statistical analyses were performed using non-parametric tests, as all dependent variables were ordinal, and all independent variables were either ordinal or nominal. In case the dependent variable had two possible values, the Mann-Whitney test was used; with more than two possible values, the Kruskal-Wallis test was used. A 95% confidence interval was used; all p-values were two-tailed unless stated otherwise. It was made clear to all participants (in focus groups, interviews, and survey) that their par- ticipation was voluntary, they could end their cooperation at any stage, and that any data they provided would be completely anonymous. The interviewed students, which were interviewed individually in a designated room, signed informed consent forms which made the aforementioned things clear to them.

In the following chapter, results are integrated to inform the discussion. This discussion, in turn, informed a final section which proposes how a scheme should be implemented in Ply- mouth. The proposal is based on the main lessons learned in the first parts of this chapter and was informed particularly by the ideas proposed in the focus groups. This proposal was used to calculate the impact of a bicycle sharing scheme, in terms of CO 2 emission reductions, value for money, and changes in modal share. The reductions in CO 2 emissions were based on modal shift data from other cases and the survey, and statistics on the average emissions

13 for each mode. Finally, a benefit cost ratio for the scheme was calculated based on an earlier appraisal estimating the cost and benefits of increased cycling levels in Plymouth.

The next chapter introduces the basics of bicycle sharing and reviews existing literature. Chapter 3 discusses the local physical and policy context, while chapter 4 contains studies of five different cases. In chapter 5 the focus groups, student interviews and survey results are discussed, structured by their main findings. Chapter 6 contains a discussion of the results, followed by a proposal for a bicycle sharing system in Plymouth and its main effects. It also discussed limitation of this study and suggestions for future research, while the final chapter details the conclusions.

14 2 Literature Review

2.1 Introduction This chapter focuses on previous research on cycling, in order to provide a firm foundation on which the rest of the study can be based. First a basic introduction to bicycle sharing systems will be presented, followed by an overview of the advantages and disadvantages of cycling in general and bicycle sharing in specific. The extensive amount of research on the factors influencing bicycle use is summarized in sections 2.4 and 2.5, in order to gain insight into how to get people cycling.

2.2 Introduction to bicycle sharing systems In this study, a bicycle sharing scheme will be defined as: a system offering short-term urban rental bicycles available at a network of unattended locations. This definition should help to select appropriate cases to study in chapter 4, and to acquire a relevant overview of current schemes. Also, in order to determine the success factors of these schemes, it is crucial to compare schemes which are similar. The definition is particularly appropriate for this study, as it excludes many schemes which are undeniably bicycle sharing schemes as well, but are not of immediate relevance for the current study. This group of excluded schemes includes bike-and-ride schemes (which provide rental bicycles at railway stations; such as the OV Fiets scheme in the Netherlands), rural tourism-oriented schemes (Nextbike, Neusiedler See, Austria), sharing schemes with manned stations (often found in Spain), community-based schemes (which are found in a range of North American cities, such as Bike Share in To- ronto) and first generation-type schemes which do not limit the duration of use or lock the bicycles (such as the Amsterdam White Bicycles plan).

Three generations of bicycle sharing systems have been identified (DeMaio, 2003, 2009; DeMaio & Gifford, 2004). The first generation of bicycle sharing came into existence in Am- sterdam in 1965, and consisted of ordinary bicycles painted white. The bicycles could be used by anyone and left anywhere, as long as they were available for the next potential user, which meant they were never locked. Due to problems with theft and vandalism the programme was very unsuccessful. A more recent attempt to provide a first generation bicycle sharing scheme was made in Cambridge in 1993, however, this scheme ended in a similar vein as the White Bicycle Plan (Transport for London (TfL), 2008). The second generation of bicycle sharing systems first emerged in Denmark in the 1990’s; the first large-scale scheme being implemented in Copenhagen in 1995. Using the bicycles now required a 20 DKK deposit (€2,70; £2,25), to be returned after the journey, and was allowed only within the city centre. The bicycles were designed specifically for this purpose; being sturdy and able to cope with heavy use and being outside all year. Even though De- Maio (2009) notes that the scheme experienced problems with theft due to the anonymity of the user, the scheme still operates in the same fashion today, and is one of the longest running schemes of all.

15 The third generation of bicycle sharing systems emerged in 1996 at Portsmouth University, United Kingdom, where students could rent a bicycle by using a magnetic stripe card. This tackled the crucial issue of anonymity, as one would have to register to become a cardholder. Also, the bicycles were now locked to the stations. Since then, a range of technological addi- tions have been made to the concept, including electronically-locking racks or bike locks, telecommunication systems, mobile phone access, and on-board computers (DeMaio, 2009). The vast majority of currently operating systems use third generation technology. The fourth generation of bicycle sharing has been envisioned to give users the freedom to park the bicycles anywhere they like by providing bicycles with their own locks (Haverman, 2010), and to be characterized by improved efficiency, sustainability, and usability (DeMaio, 2009).

The second part of previous research on bicycle sharing systems, next to the classification outlined above, concerns the factors influencing the success of the systems. In their study on the factors critical for success for a bicycle sharing scheme in the United States, DeMaio and Gifford (2004) identify five main factors; there needs to be a customer demand for the bicycles, sufficient bicycle infrastructure and cyclist safety should be provided, limited profitabil- ity of the systems should be tackled by providing additional income (for example via advertising), theft and vandalism should be minimized, and finally a good multimodal connectivity is required, by strategically locating the docking stations. DeMaio (2003) adds that bicycle sharing systems should be implemented simultaneously with a range of bicycle facility improvements for all cyclists, such as cycle lanes, storage, and a general philosophy which pri- oritizes cyclists. This conclusion is shared by Midgley (2009), who also emphasizes the importance of a bicycle friendly topography and climate.

Bührmann (2007) names four key conditions for implementation: a strong commitment to sustainable urban transport planning and to the promotion of cycling as a serious transport mode, a minimum standard of bicycle infrastructure for safe and convenient cycling, sufficient resources for a large scale scheme to achieve a real impact, and sufficient space for racks/parking to guarantee the accessibility of bicycles. Other aspects to take into account, following Bührmann (2007), include city size (cities of at least 200,000 inhabitants are deemed most suitable), topography (hilliness could deter potential users; something which has been countered in some cities by providing electrically assisted bicycles), and distance between docking stations (which should not exceed 300-500 meters). Feasibility studies carried out by a number of large cities throughout the world (London, New York, Melbourne, Philadelphia and Vancouver) all agree with this distance between the stations (TfL, 2008; TransLink, 2008; NYCDCP, 2009; City of Philadelphia, 2010). Although most of these studies do not present general findings, because they have a very specific purpose, there are some aspects worth mentioning. For example, the London feasibility study states that “the scale of any scheme is critical to its likely success” (Transport for London, 2008, p.5), implying that a modest scheme in a small city may never work. The New York feasibility study adds that “small programs do not work” (NYCDCP, 2009, p. 6). However, it should be noted that there is a difference between the density of a scheme (i.e. the distance between stations) and the size of the scheme (number of station and bicycles). The New York study highlights the importance of both, noting that successful sharing programs depend on a high density as well as a widespread coverage. On the other hand, these findings are from reports tailored to large-

16 city situations, and therefore any conclusions should be drawn with caution. What is true for dense agglomerations such as London may not be true for a medium-sized city like Ply- mouth. In terms of user characteristics, CityRyde (2009) states that although bicycle sharing members are very diverse, the typical member can be defined by the following characteristics: 18 – 34 years of age, high level of education, require high level of mobility, and awareness of environmental and social issues. This is confirmed by the scheme in Lyon, where as much as 33% of all subscribers are students (TfL, 2008). To complement this review of previous research, the next section takes a bigger perspective and focuses on the factors influencing levels of cycle in general.

2.3 The advantages and disadvantages of cycling From a government’s point of view, planning for cycling provides a range of advantages, summarized by Tolley (2008): it contributes to energy saving, is healthy, is inexpensive compared to other modes, makes efficient use of space, is an equitable, quick, reliable and benign means of transport, which provides mobility to almost everyone, and finally, appropriate government planning for cycling can cut accident rates among cyclists. It could be argued there also are some disadvantages attached to cycling from a government’s point of view. Perhaps the most important one is that interventions which encourage cycling, and especially those discouraging car use, can be very unpopular. However, as Albalate and Bel (2009) argue on the case of congestion charging, public support may increase according to the quality of the plan and the investment area of the revenues. Furthermore, some are physically unable to cycle, while conflicts between pedestrians and cyclists possibly increase in areas where they share space. Advantages and disadvantages of cycling from an individual’s point of view are partly different from those mentioned above, and are summarized in Table 2.1. Advantages Disadvantages - Health improvements - (Perceived to be) dangerous - Fun - Weather-dependent - Being outside - Inconvenient - Flexibility - Uncomfortable - Relaxing - Tiring - Environmentally friendly - Uncharacteristic mode - Cheap - Difficult to carry loads - Control - Difficulties with trip-chaining - Predictability - Slow mode in rural areas - Freedom - High maintenance - Quick mode in urban areas - Storage at home - Exciting - Need for specialist equipment - Lack of stress - Convenient Table 2.1 Advantages and disadvantages of cycling from an individual point of view (from: Gatersleben & Appleton, 2007; Anable & Gatersleben, 2005; Heinen, Van Wee & Maat, 2010)

17 The advantages and disadvantages of bicycle sharing schemes are to a great extent similar to those of cycling in general. However, TfL (2008) identifies four additional advantages of bicycle sharing systems. First of all, it provides a new individual transport mode, which improves accessibility, connectivity with other modes, resilience to the public transport network, and the variety of options available to users. It would also serve to raise the profile of cycling and to demonstrate political commitment to cycling. Secondly, it removes some of the barriers to cycling: bicycle ownership, maintenance and theft. This not only leads to higher levels of cycling; experience elsewhere suggested that bicycle sharing schemes have also encourage people to use their own bicycles more (TfL, 2008). Thirdly, a bicycle sharing scheme can help to create momentum to implement additional cycling measures, leading to a much more cycling and walking-friendly city. Fourth of all, a scheme can promote tourism, as visitors are offered an attractive and low-cost new way of discovering the city. As Sherwin and Parkhurst (2009) note, it prompts individuals to try cycling, while creating a culture of cycling. It may create what is often called a critical mass; when the number of cyclists becomes high enough, a virtuous cycle starts, in which car drivers become more aware of cyclists, cycling becomes mainstream, and consequently more people take up cycling. Several more advantages can be added to this. Public bicycles enable one-way trips to be made, which offers users great freedom and flexibility. The location where one cycle trip was ended does not necessarily have to be the starting point for the next trip. Furthermore, where individually owned bicycles are mostly used only twice a day for commuting, the public bicycles can be used up to 10 times a day.

On the other hand, a range of shortcomings has been associated with third generation bicycle sharing systems (Haverman, 2010; Maartens, 2008). First of all, space for the docking stations is generally limited in city centres. Secondly, the bicycles need to be redistributed constantly to prevent empty stations, the costs of which are “enormous and increasing” (Haverman, 2010). Thirdly, most bicycles are not equipped with an individual lock (rather they are locked to the docking stations), which means it is not possible to go anywhere; users are confined to the network of stations. Some more disadvantages of bicycle sharing can be added to this. It is rather unpredictable; even though users can check current availability of bicycles online, one can never be entirely sure a bicycle, or an empty docking point, will actually be available at the right time and place. Booking a bicycle in advance is not possible, and this would have made the scheme even less reliable and flexible for those using it irregu- larly or spontaneously. Furthermore, in most cases a docking station will not be located exactly at the destination, leaving users to walk the last few hundred metres. When no bicycle or docking point is available at the preferred docking station, the user will need to find another station. Especially in schemes where the distance between docking stations is quite big this could be a problem. Moreover, seeing that some schemes experience relatively high levels of theft and vandalism, it could be argued that a scheme represents a waste of energy and materials. When the same bikes would have been owned and stored individually, their life- time would have been much longer, and also no fossil fuels would be required for the redistribution. One might say the private bicycle will probably perform better on these aspects.

18 2.4 The determinants of bicycle use The body of literature on the factors influencing bicycle use is extensive, and therefore provides an excellent starting point for understanding cycling behaviour. It was unrealistic to include every article dealing with this subject in this section; therefore a selection of key studies was included, seeking to incorporate all the main findings into this study. This section is structured by a classification used by Heinen, Van Wee and Maat (2010), distinguishing five groups of influences on bicycle use: built environment, natural environment, socio- economic factors, psychological factors, and cost, travel time, effort, and safety.

The first group of determinants of cycling mentioned by Heinen and colleagues (2010) concerns the built environment, of which the first factor is urban form. This includes one of the most evident aspects: trip distance. The higher the distance, the less likely people are to cycle. Data from the National Travel Survey 2008 (DfT, 2009a) illustrate this; 87.6% of all bicycle trips in the United Kingdom cover less than five miles. With regard to density, the majority of studies showed that a denser urban area is related to higher cycling rates (e.g. Parkin, Ward- man and Page, 2008; Pucher & Buehler, 2006). Also, Pucher, Komanoff and Schimek (1999) argued that small, compact cities are most suitable for cycling since more destinations are accessible within a short ride, while traffic volumes are lower as well. No city of over 2 million inhabitants has a cycling mode share of over 10%, and most of the cities with the world’s highest mode share (such as Groningen) are small or mid-sized cities. For network layout within an area, which could be fine-grained or instead consist of very few roads, no uniform relation with cycling rates has been found over several studies (e.g. Moudon et al., 2005). Furthermore, there is a consensus that a mixture of functions increases levels of cycling (Cervero & Duncan, 2003; Pucher & Buehler, 2006). The second aspect within the built environmental category is bicycle infrastructure. A preference for separate, off-road cycling facilities exists among inexperienced cyclists (Hunt & Abraham, 2007; Daley, Rissel & Lloyd, 2007) and women (Garrard, Rose & Lo, 2008). However, the improvement of cycling infrastructure in general has also been found to increase cycling rates (Parkin et. al, 2008), though possibly rather modest (Wardman, Tight & Page, 2007). In their study of Dutch, Danish and German cycling policies, Pucher and Buehler (2008) argued that the extensive provision of cycling infrastructure has been fundamental in increasing levels of cycling in these countries. It should be noted that this was ac- companied by additional measures, such as marketing and car-discouraging policies. In a study monitoring the route choice of cyclists in Portland, United States, it was found that they use specific bicycle infrastructure for about 50% of their distance travelled, even though this infrastructure only made up eight percent of Portland’s total network (Dill, 2009). This finding again highlights the preference of cyclists for separate cycling infrastructure. Two studies using stated preference techniques in Graz (Austria) and Edmonton (Canada) have found their participants indicating a strong preference for bicycle lanes and paths as well (Hunt & Abraham, 2007; Titze, Stronegger, Janschitz & Oja, 2008). The quality and design of the bicycle infrastructure also plays an important role; for example, Rietveld and Daniel (2004) have found that fewer people cycle in cities with a higher number of stops on cycling routes. Also, the continuity of cycling infrastructure is considered very important, especially by inexperienced cyclists (Stinson & Bhat, 2005). The quality of the infrastructure involves many more aspects, such as road surface quality, intersection design

19 and cyclist priority at traffic lights. A final component of infrastructure is additional facilities, such as safe parking and showers at the destination of the bicycle journey. People especially value safe bicycle parking highly (e.g. Hunt & Abraham, 2007; Martens, 2007), while the evidence for the effect of showers at work is mixed. In one of very few remarks on bicycle sharing schemes found in this vast range of work on mode choice and encouraging cycling, Daley and colleagues (2007) found that non-cyclists would like to have the possibility to try out cycling without having to make a big investment; something which a bicycle sharing scheme would ideally cater for.

The next group of factors identified by Heinen and colleagues (2010) is natural environmental factors. First of all, the evidence for the negative effect of hilliness is overwhelming (e.g. Parkin et al., 2008). Even the Netherlands-based study by Rietveld and Daniel (2004) found a significant relationship between hilliness and levels of cycling. While Moudon and colleagues (2005) surprisingly did not find this effect, this is most likely explained by the large proportion of recreational cyclists in their sample; a group which possibly even prefers cycling on a challenging, hilly terrain. It seems unlikely that this finding also applies to the daily commute by bicycle. Furthermore, the seasons have been found to influence cycling; in winter, people are less in- clined to cycle than in summer (Stinson & Bhat, 2003). No research could be found on the influence of climate, although it does make sense that countries with high cycling rates, such as the Netherlands, Denmark and Germany, have a temperate climate. Within the UK, a higher temperature is associated with higher cycling rates (Parkin et al., 2008); however this finding is unlikely to be universal. According to Heinen and colleagues, there are no uniform findings concerning rain, however, it seems plausible that the majority of people would dis- like cycling in rainy conditions. Also, on the effect of wind, little is known, although it clearly has an impact on the amount of effort required during cycling (Parkin, Ryley & Jones, 2007).

The third major category consists of socio-economic factors. There is ample evidence that men are more likely to cycle than women (e.g. Rietveld & Daniel, 2004; Stinson & Bhat, 2005). However, this particularly seems to be the case in countries with low cycling levels, whereas in countries with high levels, cycling is equally popular among men and women. Intuitively, the relationship with age seems to be clear-cut, but the evidence is ambiguous, which leads Heinen and colleagues (2010) to conclude that while there certainly is a relationship between cycling and age, this might not be a universal one. Also, the effect of income is unclear, as some studies indicate a positive relationship, others find a negative association, and some do not find any significant effects at all. Increased car ownership seems to have a negative effect on cycling levels, although Parkin and colleagues (2008) found that in Eng- land and Wales, cycling rates among households without a car are lower than in households owning one car, while it decreases again in households owning multiple cars. Increased bicycle ownership is expected to increase the probability of cycling, as the availability of a bicycle in a household is the strongest predictor of utility cycling (Cervero et al., 2009). In past decades, the UK has witnessed an increase in bicycle ownership; however, this was related to an increase in leisure cycling rather than an increase in commuting by bicycle. Studying why the increase in leisure cycling has not resulted in a subsequent increase in commuter cycling, Gardner (1998) found a discrepancy between the image of leisure cycling as calm, peaceful

20 and liberating, and of commuter cycling as dangerous, demanding, stressful, and as requiring major self-discipline. However, Gardner does also note that many of the people who currently cycle to work indicate that leisure cycling did encourage them to try to cycle to work as well. This means that leisure cycling can play a role in encouraging utility cycling, and is therefore worth supporting. Employment status has also been found to predict bicycle use, as Boumans and Harms (2004) found part-timers to be more likely to cycle. According to Ryley (2006), household structure also exerts a significant influence on bicycle use: individuals without children, students, people in between jobs and part-timers without children are more likely to cycle than other categories. Heinen and colleagues (2010) indicated that being physically active increases the odds of a person cycling. Moreover, some studies point out that on average highly educated people cycle less (e.g. Parkin et al., 2008; Rietveld & Daniel, 2004).

Fourthly, Heinen and colleagues (2010) summarized a series of psychological factors. First of all, attitudes play an important role in determining whether people cycle or not. In general, attitudes towards car use are more positive than those towards bicycle use, while having a positive attitude towards cycling increases the likelihood of commuting by bicycle (Dill & Voros, 2007). On the other hand, cycling itself improves attitudes towards cycling (Gatersle- ben & Appleton, 2007). Also, social norms may have an influence on cycling behaviour; when social norms approve of cycling, individuals are more likely to cycle. Social norms may be opinions expressed by persons, as well as actual behaviour. Furthermore, individuals with more deeply held environmental beliefs use public transport more often, and Hunecke, Blöbaum, Matthies and Höger (2001) argued that the same is likely to be true for non-motorized modes of transport. Next to attitudes and social norms, habits also influence cycling behaviour. In most mode choice research, the role of habits is not included, as they mostly focus on a more or less rational choice of individuals between the various modes (Heinen et al., 2010).

The fifth and final category consists of utilitarian aspects: cost, travel time, effort, and safety. Cost, travel time, and effort are variables which are to be minimized by the traveler, in order to make a particular journey as efficient as possible. It should be noted that cost not only concerns the costs of cycling itself, but also the cost of competing transport modes (e.g. Rietveld & Daniel, 2004). According to Bamberg, Ajzen and Schmidt (2003), providing free public transport reduces cycling rates. Wardman and colleagues (2007) showed that paying people to cycle to work could double the amount of people cycling. Effort required to travel a particular journey is influenced by factors such as wind, hilliness, and number of stops. Safety, finally, can be split into actual safety and perceived safety. Actual safety is based on number of accidents, for example, while perceived safety is not necessarily equal to actual safety. Providing separate bicycle infrastructure increases perceived safety, but it is not clear whether actual safety is improved as well. In a study by Gatersleben and Appleton (2007), people who tried commuting by bicycle for the first time over a weekly period evaluated safety of cycling much better after having cycled than before, indicating that perceived safety increases with experience. Moreover, an overall increase in cycling results in an improvement in actual safety (e.g. Jacobsen, 2003; Pucher & Buehler, 2008).

21 Although useful for structuring this section, the rather broad categorization of variables by Heinen and colleagues (2010) is replaced by a different division in the rest of this research. This new classification is more policy-orientated, which is important since this study is to be used by Plymouth City Council. So, in the rest of this research, the factors influencing bicycle use are subdivided into two main categories: policy-influenced and non policy-influenced. The former consists of three subgroups: physical infrastructure, non-physical context, and individual characteristics. Physical infrastructure concerns for example interventions to improve cycling paths and lanes or facilities at the destination. Non-physical context measures include strategies such as pricing policies to reduce the attractiveness of the car, or providing better legal protection to cyclists. The policies aimed at individual characteristics concern social factors such as attitudes and habits. The factors under non policy-influenced are not considered to be realistic to include in policy, or the effect of including it in policies is not as straightforward as suggested. For example, while cold or wet weather negatively affects cycling levels, it is not a feasible policy to counter these effects by providing heated or covered cycle lanes. The non policy-influenced variables are mostly of value to estimate the demand for cycling in a given area. This does not mean that in hilly cities, such as Plymouth, there is no demand for cycling; however, it does suggest the maximum amount of people regularly using a bicycle is lower than in flat areas. Table 2.2 summarizes the factors mentioned in this section. Not all variables are included; cost and effort are excluded because they are the result of other factors which are included in the overview. Also, leisure cycling is not directly included in this overview, as this is both a predictor of utilitarian cycling, as well as a result of cycling interventions. Despite not being mentioned directly in any of the studies discussed in this section, bicycle sharing schemes can be added to this overview of influences. Some of the aspects which can be added to this overview are bicycle training and the protection of cyclists in law, as is the case in some other countries (Pucher & Buehler, 2008).

Policy-influenced Non policy-influenced Physical infrastructure - Hilliness - Urban form (trip distance, density, mixture of - Weather / Climate (wind, functions) rain, temperature) - Cycling infrastructure - Seasons - Design of infrastructure (continuity, number of - Gender stops, cyclist priority, etc.) - Age - Bicycle parking - Income - Bicycle sharing system - Employment status Non-physical context - Household structure - Social norms - Costs (of both cycling and its alternatives) - Safety (both perceived and actual) - Giving cyclists protection in law - Education (training cyclists, informing car-users, etc.)

22 Individual characteristics - Bicycle and car ownership - Frequency of physical activity - Level of education - Attitudes - Deeply held environmental beliefs - Habits - Identity Table 2.2 Overview of factors related to bicycle use.

While in this section the focus has been on identifying single determinants of bicycle use, it should be stressed that each of these factors alone are not likely to have a significant effect on cycling levels. Many authors have argued that the best opportunity for increasing levels of cycling lies in the application of a comprehensive approach, which tackles many issues at once (e.g. Pucher & Buehler, 2008; Wardman et al., 2007).

Another issue concerns the relative importance of each individual variable. The study by Titze and colleagues (2008) found bicycle lane connectivity and social support to be the most important factors influencing bicycle use, while Hunt and Abraham (2007) find the most important measure to be the provision of safe parking facilities at the destination. Others argue that cycling is only moderately related to a supportive bicycle infrastructure, and more to individual characteristics (Moudon et al., 2005). Anable and Gatersleben (2005) provided evidence that rational, instrumental factors are more important to individuals when considering transport modes than subjective, affective factors. This is supported by De Geus, Bour- deaudhuij, Jannes and Meeusen (2008), who state that individual factors were more important than the environmental determinates in their sample from Flanders. However, the authors stress that this effect is likely to be dependent on the presence of adequate bicycle infrastructure. In short, despite all research it remains complicated to determine the relative effectiveness of each kind of intervention.

2.5 Determinants of bicycle use: identity and attitudes The emphasis of many studies, and of the previous section, is on technical, physical, and rational aspects. According to Spinney (2009), due to the weight placed in many studies on rational and instrumental aspects of cycling, it has failed to capture the wide range of ways in which cycling can become meaningful to its practitioners. This includes the affective experiences derived from the journey itself, which can be experiences such as pleasure, freedom, relaxation, or simply being outside. Moreover, cycling can be meaningful as an expression of political activism, as an instrument of communication or as a source of identity. So, as cycling is not merely a means of getting from A to B, and thereby not only touches upon rational aspects as costs and travel time, it is important to also place emphasis on the affective, non-instrumental factors related to cycling (Anable & Gatersleben, 2005; Spinney, 2009).

On the importance of identity, Skinner and Rosen (2007) state that “identity is an important facet of how people make sense of their own mobility choices and behaviour”. With regard to

23 how non-cyclists make sense of cyclists, the authors add that in the U.K. cyclists are, depending on the positive or negative angle, often considered to be brave, fit and unconventional, or foolish, inconsiderate and selfish in posing a hazard to others. This image of cycling as a rather alternative subculture may present a significant barrier for people to take up the practice. Horton (2007) adds that a fundamental ‘fear of cycling’ is one of the most important barriers to cycling; however, this barrier does not only consist of fear of accidents, it also comprises fear of becoming a cyclist, and thereby adopting the cyclist identity. It seems clear that the cyclist identity perceived by non-cyclists in the U.K. is not particularly desirable. This discourse is reaffirmed and strengthened by various factors, such as the spatial margin- alization of cycling, and the representation as car travel as normal and cycling as deviant in the media. This results and is reinforced by the current low levels of cycling, and quite possibly is also influenced by government’s attempts to encourage cycling and reduce car use, which makes people fear they have to become a cyclist as well (Horton, 2007). Lorenc, Brunton, Oliver, Oliver and Oakley (2008) identify five main explanations for transport choices, derived from a review of earlier work on the subject. At this point, one of these five is particularly relevant: culture of car use. This explanation includes the perception of cars as more convenient than walking and cycling, as ‘cool’, and the view of car ownership and car use as part of a normal adult lifestyle, all of which discourage active modes of transportation.

Rietveld and Daniel (2004, p. 545) link cycling levels to ‘cultural tradition’, by finding that in the Netherlands the native population demonstrates higher cycling rates than non-natives. Translating this finding to the U.K., one might argue that the national cultural tradition is not particularly receptive to cycling, given the low levels of cycling in past decades. Research by Anable and Gatersleben (2005) showed that cyclists valued cycling to work higher on 9 out of 11 indicators (cost, predictability, environment, health, no stress, control, freedom, relaxation, and excitement) than car drivers valued their car journey to work (they highly valued the flexibility and convenience of their mode). This illustrates the opportunities offered by cycling to individuals. However, the same study found that car users value cycling rather low on various indicators, on which cyclists themselves value the bicycle quite high (e.g. convenience, no stress, freedom). This shows the potential difficulties in persuading car users to take up cycling, or for that matter, another sustainable transport mode. It also provides some indicators for the direction sustainable transport policy could take: improving people’s perceptions of the bicycle’s convenience, or decrease the car’s flexibility or convenience. It could be that once a car driver tries a bicycle sharing scheme, his attitudes change as the experience turns out to be rather relaxing and convenient. But, it is unlikely that an inexperienced cyclist will enjoy riding a shared bicycle very much as long as the city is rather cycle-unfriendly. One could argue bicycle sharing is likely to improve the convenience of cycling, as some of the more troublesome aspects are eliminated (storage, theft, maintenance).

Social norms also influence people’s decisions whether to cycle or not, even to a great extent when cycling levels are low, according to Sherwin and Parkhurst (2009). As mentioned in the previous section, De Geus and colleagues (2008) argue that marketing seeking to increase cycling levels should focus on creating social support for cycling. Titze and colleagues (2008) found that next to bike lane connectivity, individuals consider social support to be the

24 most important variable related to their cycling behaviour. Increasing social support can for example be achieved by increasing the number of cyclists, which represents cycling as normal rather than a mode of transport for ‘others’. Next to the lack of attention for affective, non-rational factors and attitudes in previous mode choice research, it can be argued that there is a similar absence of attention for habits (Gär- ling & Axhausen, 2003). According to Thøgensen and Møller (2008), travel mode choices are highly influenced by habits, which implies that higher levels of cycling are unlikely to be attained by improving the rational attractiveness of cycling alone. In a study by Garvill, Ma- rell and Nordlund (2003), simply asking car drivers to deliberate their mode choices reduced car use, at least on the short-term. Fujii and Kitamura (2003) offered a one-month free bus pass to a group of car users, which led to an increase in bus-use, also one month after the bus pass had expired, an improvement in attitudes towards the bus, and the car use choices being less habitual. However, while Thøgensen and Møller (2008) find the same effects, they also note that after four months these effects were no longer present, indicating that in many cases habitual mode choice may be similar to mode choice based on a rational decision-making process after all. The authors argue this could be due to the lack of quality offered by the alternative; the breaking of the car habit did lead to some consideration, however, this rational choice process supposedly evaluated the car as being the best mode. This emphasizes the importance of combining marketing strategies aimed at breaking habits with improvements in the rational attractiveness of cycling (i.e. provide cycling infrastructure, making car travel expensive).

This chapter has highlighted the possible reasons to actively encourage cycling, the success factors identified by previous work on bicycle sharing systems, and the role of a range of factors, identity and attitudes within increasing bicycle use. However, the effects and role of bicycle sharing are still unclear, as is the importance of the factors influencing bicycle use in Plymouth. The following chapter will explore the local context in order to identify any strengths and weaknesses which influence the potential success of bicycle sharing in Ply- mouth.

25 26 3 Physical and policy context

3.1 Introduction This chapter discusses the local situation of Plymouth, both in terms of policy as well as by describing the local transport network and statistics. This is crucial in order to make a comprehensive assessment of the opportunities for a successful bicycle sharing system in Ply- mouth. With regard to policy, a distinction is made between national and local policy. Plymouth is a unitary authority, which means that, while it is located within the county of Devon, Devon County Council does not influence Plymouth policy. Even though the most important transport document, the Local Transport Plan, is produced by the local government, the national government does play an important role. Therefore, first the national policies will be summarized in section 3.2, while the local policy is discussed in 3.3. Section 3.4 examines the local cycling context.

3.2 National policy Although preceded by some earlier policy notes, the encouragement of cycling in national policy did not take off in any meaningful way until 1996, with the publication of the first Na- tional Cycling Strategy (Department of Transport, 1996). It included targets to double the number of trips made by bicycle by the end of 2002, and doubling them again by 2012. De- spite these goals, the share of trips made by bicycle remained relatively stable at 1.5% in the period after 1996 (DfT, 2009b). One of the explanations for this might be that the targets stated in the 1996 National Cycle Strategy were abandoned in 2004 with the publication of the White Paper ‘The Future of Transport’. Local councils have been responsible for their own target setting since. Nevertheless, the 1996 National Cycling Strategy did mark a significant change in national policy, as the policy in the preceding decades did generally not support cycling. In fact, the difference in cycling rates between the United Kingdom and countries as the Netherlands and Denmark is largely attributable to differences in transport policies since the 1970’s, according to Pucher and Buehler (2008). But while those countries started planning for cycling in the 1970’s, the official position of the DfT in 1991 was still not to encourage cycling because of the alleged safety hazard of cycling in traffic. Moreover, for most of the post-war period, the decrease in cycling, from 15% mode share in 1950 to the current 1.5%, has not been countered by the government; instead it has been exacerbated by their policies, according to Lumsdon & Tolley (2001).

However, currently the DfT is actively encouraging cycling in a number of ways. In 2005, the DfT set up Cycling England, an independent body which aims to “get more people cycling, more safely, more often” (DfT, 2010b). Working with an initial annual budget of £6 million (€7.17 million), its two main initiatives were Bikeability, and the Cycling Demonstration Towns project.

27 Bikeability aims to provide cycle training, mainly to children but also to adults. The scheme is currently adopted by half of all local authorities in England, including Plymouth, and by 2012, half a million children are scheduled to have taken part in Bikeability training (DfT, 2010c). In the Cycling Demonstration Towns project, six towns, with a size varying between 65,000 and 250,000 inhabitants, were collectively allocated a total funding of seven million pounds over three years, which was match-funded by the local authorities. Investment levels in these six towns were now closer to ‘European levels’ of investment of around £10 (€12) per capita per year, rather than the average English level of around £1 per capita per year (DfT, 2010d). In the four-year period from 2005 until early 2009, this investment programme resulted in a total increase in cycling of 27% (according to automatic counters), or 16%, based on manual counts (Sloman, Cavill, Cope, Muller & Kennedy, 2009). When in 2008 the DfT allocated £140 million (€167 million) to Cycling England for the next three years, the Cycling Demonstration Towns programme was extended to include 11 more towns, and one city. Plymouth has not applied to become a Cycling Demonstration Town, at least partly due to difficulties with match-funding the Cycling England grant, which was one of the requirements. Furthermore, in cooperation with the Department for Children, Schools and Families (DCSF), the DfT targets all schools to have a School Travel Plan by 2010. However, in Plymouth school related car use has remained relatively stable despite the city-wide implementation of School Travel Plans. Further measures to encourage cycling from the DfT include the Na- tional Business Travel Network, which aims to discuss sustainable travel options with and between businesses, and the Cycle to Work Guarantee, to which businesses can sign up to commit to facilitating more employees to commute by bicycle, partially funded by tax ex- emption. Finally, the role of the DfT is to provide guidance and best practice advice to local governments.

Next to national government policy and funding, the situation for local authorities is also influenced by a number of national organisations, including the charities Sustrans and Cam- paign for Better Transport, the national cyclists’ organisation CTC, and British Cycling (the national governing body for cycle sport). Sustrans, for example, is involved in educating and training schoolchildren the skills they need to cycle to school, as well as aiming to create a national network of traffic-free cycle routes.

3.3 Local policy Within this national policy context, Plymouth City Council’s transport policy revolves around the Local Transport Plan (LTP). Since 2000, local authorities are required to create their own LTP. Currently, LTP 2 is the relevant plan on which transport measures are based. It sets out the transport strategy and implementation programme for Plymouth from 2006 to 2011. Its seven main objectives are generically formulated and leave plenty of room for implementation of cycling policies. Next to these objectives, LTP 2 also contains four ‘key principles’, and a number of ‘key strategy elements’. They will not be presented here in detail, but it should be noted that cycling is again not mention at all; which is striking as public transport is. ‘Key principle’ 1 is ‘the importance of public transport’, and includes the statement that “improvements to the reliability and capacity of public transport lie at the heart of the strategy” (PCC, 2006). Also,

28 the following three pages in this chapter of the LTP 2 elaborate on specific public transport- related measures. This illustrates the plan’s principal focus on public transport rather than on other, arguably more sustainable modes such as walking or cycling.

One of the supporting documents to the LTP 2 is the Cycling Strategy (PCC, 2005), which sets out the cycling measures in more detail. It contains three main objectives, which can be summarized as follows: to maximise the role of cycling as a transport mode, to develop infrastructure which is better for walking, cycling and public transport, and to ensure that cycling policies are fully integrated in other plans. With regard to the first objective, maximising the role of cycling as a transport mode, a more specific target is set as part of seven supporting targets: to increase the number of cycling trips in the city by 1% per annum. Given the level of cycling in Plymouth (about 1% of all trips are made by bicycle) this is not a particularly ambitious target. Other targets aim to increase the proportion of schoolchildren cycling to school (among others by means of the aforementioned School Travel Plans), reduce the number of cycle casualties, and to reduce rates of cycle theft. Subsequently, the section on delivery of objectives focuses on three main strands of interventions: engineering (provision of cycling infrastructure), encouragement, and education. The annual cycling budget in Plymouth is approximately £250,000 (€300,000), which is about £1 (€1.20) per capita per annum, a level similar to most other English cities. However, it is expected that this figure will increase in the coming years, as a result of enlarged commitment to cycling within the council. Currently, none of the council’s employees is dedi- cated to cycling full-time; but everyone partly working on cycling equals approximately 1.5 full-time cycling officers (this excludes engineering and construction). The efforts to heighten levels of cycling in the city are centred around the Strategic Cycle Network, a framework map which details the desired cycle routes throughout Plymouth, to be provided in the future. The network distinguishes between cycle routes suited for experienced (mostly direct, on-road routes) and ones for non-experienced cyclists (away from traffic, focus on safety and leisure).

3.4 Local characteristics Plymouth is a seaside city in Devon, in the south-west of England, located between the Tamar estuary in the west, and the river Plym in the east (map of Plymouth see Appendix A, p.57). The climate is temperate with an average winter temperature of eight degrees Celsius, and an average summer temperature of 19 degrees Celsius. Average annual rainfall is approximately 900 mm (BBC, 2010a). Its population size is around 250,000 inhabitants; the University of Plymouth is home to over 31,000 students. Plymouth offers 42km of cycle paths (off-road), 17 km of cycle lanes (on-road), and 8 km of bus lanes, on which cyclists are also allowed throughout the city. The city centre is largely pedestrianized, and in this area cycling is prohibited. Some streets in the western end of the city centre have been re-opened to cars recently in an attempt to revitalize the area. In the rest of the city, a minority of the streets have a 20 mph speed limit, and there are only a few streets designated as home zones. Even though it is rather hard to compare with other cities, it is safe to say that Plymouth is a very hilly city. Most routes are constantly going up and down, although exceptions are some

29 of the routes near the seaside and rivers. An additional problem is that most of the main roads are located where the hilliness is minimal, which means that cycling on the flattest route also means cycling along busy roads. Although no data for the modal share of cycling in Plymouth is available, it can be assumed that it is approximately equal to or a bit lower than the rest of England, based on two other data sources. According to the 2001 national census, 2,806 persons (2.6% of all workers) regularly cycle to work in Plymouth, compared to 2.8% for England (ONS, 2001). 62% use car for journey to work (61% nationally), 13% use bus (8% nationally), 7% work from home (9% nationally), 13% walk (10% nationally), 2% use motorcycle (1% nationally), and 0% uses the train (7% nationally) (ONS, 2001). Moreover, the 2008/2009 Plymouth School Cen- sus indicated that 0.68% of all school pupils regularly cycle to school (PCC, 2009); compared to 1.9% nationally (DfT, 2009a). Plymouth City Council is led by 57 elected councillors, of which 36 are Conservative, 20 Labour, and one independent, who decide on council spending.

Now the scene has been set in specifying the local situation regarding cycling, and the factors influencing bicycle use in general, the focus of this research can now narrow again towards bicycle sharing schemes. It has remained unclear so far what exactly the effects of bicycle sharing systems have been in other cases, and which role they can play in the transition towards a higher modal share for cycling. The next chapter discusses some of the cases in which bicycle sharing systems have been implemented, to further explore these issues.

30 4 Case studies

4.1 Introduction This section studies five cases, in order to enhance understanding of their effects, the factors influencing their success, and differences between bicycle sharing in very large cities and in mid-sized cities. First of all, the Vélib’ scheme in Paris is discussed, as this is the scheme which has arguably had the greatest influence on the popularity of bicycle sharing schemes, and has experienced the highest use rates of all. Although Vélib’ has inspired the design of many other schemes, in terms of a tailored approach to bicycle sharing for smaller cities, it can be questioned whether these rules also apply here. For this purpose, the schemes in Bris- tol, Cardiff and Blackpool are studied in this chapter as well. These are the three small currently running schemes of relevance in the U.K., and are in cities of comparable size to Ply- mouth, and with a similarly low level of cycling. Finally, the Velodi scheme in Dijon is discussed as a fairly large scheme in a small city, to establish whether bigger scheme have a similar impact in smaller cities. For comparability’s sake, the analysis will focus on the following aspects for each case, which are related to the success of the scheme: city size, scheme size, use rates, type of user, and spatial distribution of the stations.

4.2 Paris The city of Paris has approximately 2.2 million inhabitants, while over 11 million live in its metropolitan area. The scheme in Paris, named Vélib’, started in July 2007 and consists of 1,150 docking stations and 13,500 bicycles available on the street (OBIS, 2009). Vélib’ was set out to be even bigger: 1,451 stations and 20,600 bicycles, but it remains almost three times the size of the second-largest one, Bicing in Barcelona, which offers 400 docking stations. Vélib’ covers the central area of Paris, an area of about 12 by 12 km. Within this area, the density of docking stations is very high, approaching an average distance of about 300 metres between each station. The size of the scheme can be explained by the intense competition between outdoor advertisers JC Decaux and Clear Channel, who were caught in a bid- ding war to operate the Paris scheme (Nadal, 2007). As with schemes in many other cities, the company runs the scheme in exchange for the lucrative outdoor advertising contract. This way the local council doesn’t pay anything for the scheme directly, but does so indirectly. Total investment and maintenance costs for Vélib’ over a 10-year period is expected to be €300 million, or €30 million per year, which is about €1 (£0.80) for each trip made. While the scheme’s size is likely to have played a role in the scheme becoming this popular, reports suggest that the costs of the scheme are higher than expected, at least partly due to theft and vandalism, leading JC Decaux to state they can no longer afford to operate the system (BBC, 2010b). According to OBIS (2009), the number of hires per bicycle per day in Paris is among the highest of all schemes, at 6.4 hires per bicycle per day (86,600 per day in total). To put this into perspective; other high performers are Barcelona (5.4), Stockholm (2.2), and Milan (2). However, of the 28 schemes for which this data is available in the OBIS study, 16 experience

31 rather low use rates (under 1 rent/bike/day), of which the worst include Goteborg (0.06), Bristol (0.09), Karlsruhe (0.15), and Chalon-sur-Saone (0.17).

In the period between 2001 and 2006, Paris had already witnessed an increase in bicycle use of 48%, which coincided with a comprehensive effort to improve the context for cycling in the city. This effort for example included an increase in the amount of bicycle infrastructure from 8.2 km in 1995 to 370.9 km in 2006, while traffic calming measures were also intro- duced on a rather large scale (Mairie de Paris, 2007). According to DeMaio (2009), cycle mode share increased from 1% in 2001 to 2.5% in 2007, the year of Vélib’s start. According to CityRyde (2009), 58% of users are male, and 67% live in the city centre. 23% of its users are between 16 and 25 years old, 39% are 26-35, 21% are 36-45, 10% are 46-55, and 7% are between 56-65 years old. The scheme is effectively targeting the group who considers cycling but need some incentive to do so; the ‘near market’ (Transport for London (TfL), 2008). The influence of Vélib’ has been evident, as all major feasibility studies cite Vélib’ and copy its spatial layout; the dense network of docking stations, as well as other features, such as price, technology, and distinctive bicycles (City of Philadelphia, 2010; NYCDCP, 2009; TfL, 2008; TransLink, 2008). Some of these features, such as pricing structure and attractive design of the bicycles, will also apply to schemes in smaller cities; crucially, however, others will not.

4.3 Bristol Bristol is a city located towards the south-western part of England, with a population of about 600,000 inhabitants, with about 1 million people living in its urban area. The bicycle sharing system in Bristol was terminated during this study, due to a lack of funding and commitment from the local council. It operated from October 2008 until May 2010, and was operated by the U.K.-based company Hourbike. The Bristol scheme was a partnership between Bristol City Council, Hourbike, the University of the West of England (UWE), and public transport operator First Great Western. It consisted of eight docking stations: four in the city centre, three at the UWE, which is about seven kilometres north of the city centre, and one at Bristol Parkway railway station. The number of bicycles was small at 16, and use rates have been very low, at about 2 per day (OBIS, 2010), which equals to an average number of hires per bicycle per day of 0.09. The small size of the scheme could be attributed to financial pres- sures. According to Sherwin and Parkhurst (2009), the idea was to let the scheme grow by itself, as new institutions joined, each paying for their own docking station and bicycles. The revenues from membership, advertising and hire fees were considered unlikely to cover the costs, so each of the main partners paid a certain amount for their stands and bicycles, which could be used by any member of the scheme. Out of the 106 persons who pre-registered their interest in the scheme, 8% indicated they never really cycled before, 34% were regular cyclists, while 58% classified themselves as occasional cyclists. Although Bristol has been given Cycle City status and consequent funding, as part of the national Cycle Demonstration Towns programme, the bicycle sharing scheme was not part of this. According to the operator (personal communication, 2010), they invested part of their own money in the scheme, in the hope that Bristol City Council would be interested in investing in an expansion of the scheme in a later stage. However, the funding Bristol obtained

32 from their Cycle City status (from the Cycling Demonstrations Towns project), will be mainly used to provide cycling infrastructure.

4.4 Cardiff Cardiff, located in south Wales, has a population of about 325,000; or 840,000 in its larger urban area. The Cardiff bicycle sharing scheme was launched in September 2009 and operates 70 bicycles at 9 stations, and is operated by OYBike Systems Limited. The stations are located in the city centre and at Cardiff Bay, an important tourist destination. The design philosophy of the positioning of the stations was based on connecting the railway station with the city centre and Cardiff Bay, targeting commuters and tourists. The route between Cardiff Bay and the railway station has proven to be the busiest route for public bicycles. An expansion is on its way; the number of additional stations is yet to be decided by the operator. It will probably cover an additional handful of stations in district centres and tourist destinations, such as the traffic-free Taff trail, a cycle route. The council has no commercial input in the running of the scheme and there are no ongoing annual running costs to Cardiff council. The basis for tendering for the provision of the Car- diff Bike Scheme stated that the scheme had to be cost neutral to Cardiff Council. The scheme will be funded by OYBike by a combination of sponsorship sales, scheme member- ships and hire charges beyond the initial 12 month period. As part of the agreement, which runs for 3 years, the Council funded a limited number of costs for the scheme. This included £3,500 for the installation of 35 docking points, £2,300 for the preparation of legal agree- ments, and £63,000 for the sponsorship of 70 bikes for a period of 12 months. The funding for the scheme was received as part of the Cardiff Sustainable Travel City revenue funding, which is additional funding to the Council from the Welsh Assembly Government. The main role for the council is to provide public space near cycle infrastructure and promoting the scheme. The use rates vary between 2 and about 12 a day, for the entire fleet of bikes. Although these use rates are over 50 times lower than the use rates in the Vélib’ scheme (which is about 8 hires per bike per day), according to the local Council (personal communication, 2010), it is similar to other schemes of the same size, and therefore the scheme meets expectations. It was launched in September 2009, so it is very well possible that use rates have suffered from the winter weather. There are signs that now the winter has passed usage is increasing. OYBike, the scheme’s operator, indicates that they have learnt two main lessons from their previous bicycle sharing experiences. Firstly, it is more likely to work when there are problems with public transport (either bad provision or overcrowded), and secondly, a mixed city centre with lots of residential buildings also increases chances of success. This particularly applies to cities with over 200,000 inhabitants. It seems clear that these variables are not favourable in Plymouth, as the centre is largely non-residential, and public transport is functioning reasonably well. Other aspects such as rising fuel prices are expected to influence favourably on public bicycle use. The launch of the bicycle sharing scheme in London in July this year, should also impact on the UK’s small schemes, as the advertising budget in London is much bigger. Therefore, the future of the scheme in Cardiff is viewed rather positively by those involved.

33 4.5 Blackpool Blackpool is a city of about 150,000 inhabitants in the northeast of England, which attracts many tourists in the summer season, mainly to its promenade along the seaside. The bicycle sharing scheme in Blackpool started in the summer of 2009, and is operated by Hourbike. It consists of about 50 bicycles and 9 stations, but it will be expanded to 500 bicycles at about 78 stations. The scheme started as part of the general objective of their Cycle Demonstration Town status: to get more people cycling more often. An important part of the funding was obtained from their Cycle Demonstration Town status, although the local NHS (National Health Service) also provided £400,000 of the £1 million required for the first three years of the scheme. Unlike OYBike, Hourbike does not offer advertising space on individual bicycles. The majority of the stations were located along the promenade, near the Blackpool Pleasure Beach amusement park. The reasons for it being rather small include limited availability of time and bicycles, and (temporarily) suitable locations. Therefore, the scheme so far has not been a fully-fledged, finished scheme; rather it was a small pilot. At its peak in summer, use rates were about 1.5 hires per bicycle per day, with 40 to 50 bicycles available on street. However, during many other periods of time, this number was around 1, sometimes dropping to about 0.3 (Blackpool Council, 2010). This was also influenced by the decision to remove many bicycles from the streets in winter, to minimize the impact of the weather on the bicycles. Many of the sub- scriptions were handed out for free. This made the scheme almost entirely free to use, as the first half hour of use was free as well. The scheme was primarily used for leisure trips, and generally attracted people who didn’t cycle previously. The goal of the scheme in its first year was to simply get cycling more visible in the city, not to achieve significant mode shift. So the scheme was used to get cycling off the ground, rather than as the climax of years of investment in cycling, as was the case in Paris. The expansion which is taking place this year was based on the satisfaction of the users so far, rather than on use rates. It includes expanding to about 78 stations, of which 30 stations along the seaside promenade, which stretches for about 6 miles along the entire city, and also accommodates a tramway and a regular road. In total, 46 stations are categorized as leisure, 14 residential, 11 at employers, and 7 in the town centre. Some of the stations are placed at the town’s car parks, catering for the significant number of visitors to Blackpool, while other stations are located in the outskirts of the town, at some 800 metres away from the nearest other station (personal communication, 2010). It should be kept in mind that the Blackpool system has been set up as a pilot scheme, and that its results so far are only predictive for any Plymouth scheme up to a certain extent. It confirms the strong seasonality effect, and shows that a pilot scheme can be useful, as long as it is not used to estimate demand, but to gain insight into the experiences from its users.

4.6 Dijon The Velodi scheme in Dijon started in February 2008, and consists of 35 docking stations and 400 bicycles. It is operated by Clear Channel, who pays for and maintains the scheme. Dijon is a mid-sized city in central France, with a population of about 150,000 within the city; or 240,000 in the greater urban area. In terms of bicycles and stations per inhabitant, the scheme

34 is very dense, at 2.31 bicycles per 1000 inhabitants. Although this figure is about 6 in Paris, the majority of the schemes reviewed by OBIS have densities of under 1 (OBIS, 2009). This can be explained by the fact that this contract was made before the economic crisis, in a context of high competition between Clear Channel and JC Decaux (Dijon Local Authority; personal communication, 2010). As with almost all advertiser-run schemes in France, the spatial layout of Velodi is focused on the city centre, with some stations available at radial routes coming into the centre. The distance between stations is also close to 300 metres. The scheme has clearly been influenced by the Vélib’ design mould. The total area covered by stations is approximately 2 by 2 kilometres, so the scheme does not particularly cater for longer journeys. According to the local authority (personal communication, 2010), an average of 1506 hires per day was made during 2008. Most trips were made between 12 am to 8 pm, with peaks at 8am (80 hires), 12am (110), 5pm (130) and 6pm (130). This equals 3.8 hires per bike per day, which is very high for a mid-sized scheme, compared to data presented by OBIS (2009). The typical user is young, equally a woman or a man, employed and rather well-educated: In 2008 52% of users were from 14 to 33 years old (40% from 18 to 28 years old).

4.7 Key points These cases confirmed some of the findings mentioned earlier: big schemes in big cities can achieve very high use rates and convince non-cyclists to take up cycling, while small schemes very often fail to attract significant numbers. Alternative explanations for systems with higher use rates have been suggested to be a congested public transport system and a mixed functions city centre. A key difference between big and small schemes is the distribution of the docking stations: big schemes often aim to cover an area with a consistent grid of stations, while small schemes tend to focus on a few important locations. Possibly this can be explained by the different mobility patterns from each type of city: in big cities such as Paris, mobility takes place in virtually every direction within the big central area, while in smaller cities as Plymouth, mobility is much more one-sided, as functions are concentrated in the city centre. Therefore, in the big urban areas the more or less random distribution of mobility ensures demand for public bicycles will be randomly distributed as well, whereas in smaller cities the demand will be more focused on certain areas. Another key point has been the difference in role of bicycle sharing. In Paris, Vélib’ has been implemented after years of investment in cycling infrastructure, when levels of cycling were already on the rise, where in the U.K. cities this was not the case. This might partly explain the difference in success. Fi- nally, it should be noted that there might be a cultural difference between France and the U.K., which has supported the higher use rates in French scheme in this study. When the bigger schemes in the U.K. will be implemented in the future, it might give an answer to the extent of which the U.K. can possibly have a truly successful scheme. Now the local situation and the application elsewhere seem to suggest the chances for a successful bicycle sharing system in Plymouth are rather low, it is time to look into the local demand for a bicycle sharing scheme.

35 36 5 The influences on a local scheme’s success

5.1 Introduction In this chapter the main influences on the success of a bicycle sharing system in Plymouth are discussed. Some of these influences also apply to cycling in general. These main themes were identified based on two focus groups, four student interviews, and one survey, the details of which can be found in the methods section in chapter one. Each section in this chapter presents one major theme, and discusses the evidence from the three research methods. In Ap- pendix E (p.66), a descriptive summary of the survey’s dataset can be found. As mentioned in the method section, the survey results are based on both samples, unless there is a significant difference between the samples for that particular variable.

5.2 Cycling-unfriendly situation on the road One of the main themes which appeared during the focus groups and interviews was the road situation, which was widely considered very cycling-unfriendly and dangerous. The participants of the focus groups, which were all experienced cyclists, all agreed with this, and indicated even they avoid some of the inner city roundabouts and intersections, as they are very dangerous for cyclists. At was argued that in some places, cycling infrastructure is available, but this is often of poor quality or even dangerous. These points were confirmed by the student non-cyclists which were interviewed; all four agree the situation on the road is too unfriendly to cyclists. While two out of four are tentatively interested in using a bicycle sharing system in Plymouth, both indicate the road situation will probably prevent them from actually trying it. One of them stated she would possibly like to use the scheme when there would be no or very little traffic. Both focus group sessions pointed out that the ban on cycling in the pedestrianized parts of the city centre did not help either; although all participants in one of the focus groups indicated they all still cycle in this area. The unsafe road situation was illustrated by one participant, who started cycling in London and then after a few years moved to Plymouth. She indicated she would never have started to cycle in Plymouth, and she was actually quite scared to cycle in Plymouth initially, despite being an experienced cyclist.

Overall, cycling in Plymouth was described as being ‘hard work’, as one has to be very aware of the traffic, which is indicated not to care much for cyclists. Also, it was indicated that the car is widely prioritized, and that a major culture change is required to make cycling more attractive and to increase cycle rates. In the survey, the most important barriers to cycling were found to be a lack of cycle lanes (47% agreed), feeling unsafe while cycling (46% agreed), and too much traffic in the city (46% agreed); all suggesting the road situation is a major problem for cycling in Plymouth. While these percentages do not represent majorities, it should be noted that in most cases the indifferent proportion is rather large, which means that the 46% agreeing is much larger than the proportion disagreeing. With regard to infrastructure, a lack of cycle parking was not widely perceived a problem (27% agreed, 20% disagreed).

37 5.3 Hilliness Plymouth’s hilliness would intuitively be an important influence on the success of cycling, and this effect is confirmed by this research. Especially in the focus groups, hills were consistently mentioned as a main barrier, even though the participants themselves did cycle. This is complicated by the position of the main roads, which often follow the least hilly routes. This leaves cyclists with a dilemma: either ride the flatter but busy roads, or choose the quieter but hillier roads. In the survey, surprisingly, neither the city centre nor Plymouth and its surrounding urban area were judged to be too hilly to cycle; only minorities agreed with these statements. Overall, the effect of hilliness should be somewhat limited within the context of the bicycle sharing system, as it should be focused on the flatter parts of the city.

5.4 Internal barriers to action Internal barriers to action are related to barriers which exist within an individual rather than outside of the individual (which are external barriers), such as an individual’s perception of social norms. In the interviews this came to the surface twice, as two participants indicated they would only like to use the scheme if many others did so as well, preferably their friends or other students. This may indicate individuals consider cycling as something strange, which is a clear internal barrier. In the PCC focus groups, one participant suggested he believes many people may consider cycling a sport rather than a mode of travel. However, in the survey only 6% of respondents agreed with this, making it not the most likely or important barrier. In the survey, an internal barriers variable was calculated by adding the scores from other statements, and categorizing these scores into five groups, running from very low to very high. The survey showed that those with high internal barriers to cycling have significantly less interest in using the bicycle sharing system than those with low internal barriers, which was true for the overall dataset (p = .001), as well as the individual PCC dataset (p = .045) and city centre dataset (p = .015). With regard to the individual attitude measures from the questionnaire measuring internal barriers to action, there was no overwhelming effect for these. The only statement with which more people agreed (36%) than disagreed (31%) was ‘most people I know would never consider cycling’, indicating social norms unsupportive of cycling. Similarly, 28% indicated that their friends and family would find it very uncharacteristic if the respondent was to cycle; however, 49% disagreed with this. The other statements did not yield prominent results: 19% would feel uncomfortable on a bicycle, 15% feels not fit enough to cycle, while 19% believe they do not have the skills required to ride a bicycle safely.

5.5 Habits Attracting new cyclists inevitably involves modal change, which relates to individual habitual mode choices. The students interviewed all walked everywhere in Plymouth, primarily because all their destinations are within walking distance and they enjoy it. Moreover, all four interviewees predicted this mobility pattern to be the same for most other students as well. So, it might be difficult to persuade this group into changing transport mode.

38 However, those who already cycled occasionally, particularly within the city council, were far more interested in using the scheme than those who did not. Also, those who cycle very often are not at all interested, as they prefer to use their own bicycle. This effect is illustrated in Figure 5.1; where the vertical axis displays the score on the general interest variable; the lowest possible score would be five on this variable (as it consists of the score of five variables on which the lowest possible score was one). The scores do not reflect an absolute value of any meaning, rather this graph illustrates the relative differences between the groups; as the averages for the groups varied roughly between 10 and 20 this was chosen as the range for this graph. These findings were confirmed by evidence showing that those who use their bicycle to come into the city centre (either to work or not) are the least interested in using the bicycle sharing scheme, while train users are the most interested.

Figure 5.1 Interest in using a bicycle sharing scheme in Plymouth, according to frequency of non-leisure cycling among PCC staff.

5.6 Bicycle sharing-specific characteristics Theoretically, bicycle sharing systems tackle a number of barriers to cycling, by shifting responsibility of ownership away from the user. In the survey it was examined whether some of these were seen as a problem at the moment in Plymouth. Bicycle theft was considered the most important problem, with 42% agreeing and 15% disagreeing. Other barriers were not commonly perceived: 19% thought buying and maintaining a bicycle is expensive, while only 7% thought it is a lot of work. In the focus groups and interviews participants were generally very positive about the concept of bicycle sharing. One interviewee who was interested in using the scheme, indicated she especially liked that the bicycle is not the user’s responsibility anymore, in terms of theft and maintenance. A shortcoming mentioned by a focus group participant was that the bicycles do not come with a helmet, which could be a problem as two out of three participants indicated they would never cycle without a helmet.

5.7 Other individual attitudes Within the survey, the attitude scales (part three) revealed having to wear different clothing while cycling was the most widely agreed barrier (62% agreed); however, PCC staff overall perceived this barrier significantly more than city centre respondents (p = .001). This could be explained by the requirement of wearing smart clothing at the workplace for this group,

39 which is to some extent incompatible with cycling. Moreover, in general, due to the hills cycling requires much more effort, which is an important difference with the Netherlands, where everyone simply wears their everyday outfit while cycling. Another reason might be that cyclists need to wear high-visibility gear as motorists are not accustomed to cyclists on the road, and the clothes forms a precautionary measure. Whatever the reasons, it remains that bicycle sharing systems are designed to be used quickly and spontaneously, and this does not match with the need to change clothing every time one wants to use a public bicycle. By focusing on the flat parts of the city, these problems may be partly alleviated. Elsewhere in the survey results, 65% indicated they liked cycling, indicating a significant potential, while 22% thought the weather in Plymouth is not suitable for cycling.

5.8 Extent of local interest Generally, all focus group participants and interviewees were very positive about bicycle sharing as a concept. However, its chances of becoming successful were estimated to be very low. One of the focus group participants stated that it is “very hard to imagine how it would work in Plymouth”. Also, despite their positive comments, most participants also indicated they did not want to use the public bicycles themselves.

According to the survey, on the other hand, interest in the scheme is considerable. Out of the total 162 cases, 57% indicate they would like to try out the scheme at least once, 32% indicate they are interested in using it a couple of times a month, 11% a couple of times a week, 4% on a daily basis. Although this pattern is similar for both datasets, it should be noted that the city centre dataset was consistently more interested, measured on these four indicators, as well as with regard to trip purpose. This is illustrated in Figure 5.2 below; the only group even less interested than PCC staff are unemployed persons. It should be noted that, as with Figure 5.1, the values on the vertical axis do not represent values with an absolute meaning, rather they have a comparative purpose. The method of calculation for these scores can be found in Appendix D (p. 65).

Figure 5.2 Interest in using a bicycle sharing scheme in Plymouth per occupational group.

40 Overall, respondents indicated they were most likely to use the bicycles for leisure/social trips, and least likely for the journey to and from their bus stop, shopping, and their daily commute. Only on the use of the bicycles for business trips did the PCC dataset yield more positive results than the city centre one. Asked where the respondents would like to see more docking stations, Mutley/Mutley Plain was the most common answer, while for the other options no clear preference was identified (Appendix E, p.66).

With regard to type of user, both datasets were analysed separately. First of all, among PCC staff, no significant differences were found for most of the variables from part one and two of the survey (e.g. gender, income; see Appendix C, p.59), or for external barriers to action. However, those working with sustainability on a daily basis were significantly more interested (p = .004), and those cycling more often for leisure trips and non-leisure trips were also more interested than those who never did so (p = .008 and .003, respectively). Finally, respondents who indicated they did consider cycling for non-leisure purposes were significantly more interested in the scheme as well (p = .000). Secondly, in the city centre dataset no significant effects were found either for most of the variables from the first two parts of the survey. Also, there was no significant difference between those working with sustainability and those not working with it on a daily basis, and also not for the frequency of either leisure or non-leisure cycling. Nevertheless, the significantly higher interest of those who already considered non-leisure cycling more often was also found in this dataset (p = .030). More- over, young people were found to be significantly more interested in the scheme (p = .039), with the interest gradually decreasing with higher age groups.

Based on this survey, this scheme is most likely to attract those who already cycle occasionally, are young and perceive limited internal barriers to action. Those who never cycle at the moment are unlikely to try out the scheme. Individuals perceiving internal barriers to action (i.e. feel uncomfortable on a bicycle, perceive cycling as something which is done by ‘others’), are very unlikely to use the scheme. The evidence for students using the scheme is mixed, as they are the most interested group in the survey, but meanwhile the interviews draw a very negative image. Furthermore, it is striking that a significant proportion does own a bicycle but (almost) never use it. This might indicate that there are apparently many barriers to cycling to which having access to a bicycle does not make a difference, implying that a bicycle sharing system could have a limited impact.

41 42 6 Discussion

6.1 Introduction The chapter draws together and elaborates upon key findings from the previous chapters. Its structure is based on answering the two main questions: the first part of 6.2 focuses on whether and how bicycle sharing can be successful in Plymouth, while the second part deals with the role and effects of bicycle sharing in general. Next, the main lessons are applied to a proposal for a bicycle sharing scheme in Plymouth, which not only represents a practical application of the findings, but also generates some final data on the effects of a bicycle sharing scheme. Lastly, limitations of this research are highlighted and suggestions for future research will be made.

6.2 Main results With regard to whether a bicycle sharing system can become successful in Plymouth, there are reasons to be optimistic and reasons not to be. In some aspects, Plymouth offers great opportunities for cycling in general and implementation of a bicycle sharing scheme as well, many of which have been mentioned before in earlier chapters. First of all, Plymouth has the ideal city size for cycling (Pucher et al., 1999), as most destinations are within cycling distance and there is not too much traffic on the road. It also meets the one of the criteria for a successful scheme suggested by Bührmann (2007); a minimum city size of 200,000 inhabitants. Its temperate climate provides supportive conditions for cycling in general. The spa- cious lay-out of the city, in particular the city centre, means that it should not be a problem to find space for the docking stations or cycle lanes, as is the case in London (TfL, 2008). Also, despite being very hilly in many parts, there is a significant east-west oriented flat area in the southern part of the city, including and surrounding the city centre. While Plymouth certainly does not have a cycling culture, this does not necessarily have to be a problem; levels of cycling in Paris prior to Vélib’ were only slightly higher as current levels in Plymouth, while mode share in Barcelona before their successful Bicing scheme was even lower at 0.75% (Romero, 2008). One could argue that there is an enormous potential to increase cycling, as so few people do so at the moment. The survey produced very favourable results, with 57% of respondents wanting to try out the scheme at least once, and 15% indicating they would like to use it at least once a week. Finally, as car users value the bicycle low on convenience, no stress, and freedom (Gatersleben & Appleton, 2007) - factors on which bicycle sharing arguably scores well - it might represent a good opportunity to get car users into cycling.

On the other hand, there are many barriers to a successful public bicycle scheme. The main barrier seem to be the particularly cycle unfriendly situation on the road. In the literature review the major importance of cycling infrastructure was demonstrated (Parkin et al., 2007; Pucher & Buehler, 2008). However, the local context showed that although there is some cycling infrastructure in Plymouth, it is a rather modest amount, and the focus groups indicated in some places infrastructure quality was very poor. This can be explained by the lack

43 of policy emphasis on cycling, which is illustrated by the ban on cycling in the city centre. The focus groups participants added that car drivers do not give cyclists anywhere near enough consideration. Also, cars have priority at many intersections, while cyclists are largely marginalized. The interviewed students even conveyed a fear of cycling on the roads in Plymouth, while the experienced cyclists from the focus groups also avoided many difficult crossings and described cycling in Plymouth as ‘hard work’. The survey confirmed these findings, as some of the biggest barriers to cycling were a lack of cycle lanes, feelings unsafe while cycling and too much traffic being present in the city. Also, according to the survey, a significant proportion already owns a bicycle but apparently perceives a sufficient amount of barriers to never actually use it.

Plymouth’s hilliness seems to be a major barrier to cycling in general, although the survey failed to show these results. However, previous studies have uniformly found a big effect of hilliness, and the focus groups indicated its importance as well. It is not entirely clear why the survey did not particularly show this effect, however the overall evidence seems to confirm this effect. However, this factor can be minimized, as the scheme should be focused on the flatter parts of Plymouth. Next to these physical issues, internal barriers to cycling seem to be commonly present. Iden- tity (Horton, 2007; Spinney, 2009) and social norms (De Geus et al., 2008; Sherwin & Park- hurst, 2009) have been shown to play an important role in shaping mobility. The low level of cycling in Plymouth (1% modal share) represents a culture or social norm in which cycling is not normal, while two of the four interviewees even pointed out that they would only like to use public bicycles if many of their friends did so as well. The survey confirmed the strong effect of internal barriers, finding a significant negative effect of high internal barriers on the interest in using public bicycles in both datasets. The survey suggests there is a broad demand for public bicycles in Plymouth, as 15% of respondents want to use it at least once a week. However, in the interviews and focus groups participants were also very enthusiastic about the idea of a scheme, but when asked they did not have the intention to actually use it. This attitude-behaviour gap may also apply to the survey respondents; also simply because travel mode choices are highly influenced by habits (Thøgensen & Møller, 2008), and therefore the actual switch to another mode of travel is not easily made. Furthermore, the public bicycles were expected to be used most for leisure/social trips, which suggests people would potentially want to cycle in their leisure time, but do not consider actually changing the way they travel on a daily basis.

Other problems with any scheme in Plymouth would be that cycling’s alternatives are also rather attractive (e.g. Rietveld & Daniel, 2004): public transport is functioning well, while lack of serious congestion and a generally car-friendly urban environment makes the car rather attractive as well. In big urban areas, on the other hand, congestion provides a strong incentive to cycle; in Plymouth this incentive is clearly missing. With regard to another factor possibly leading to success, a mixed functions city centre (Cervero & Duncan, 2003; Pucher & Buehler, 2006; casestudy Cardiff in section 4.4), Plymouth does not score very well with its very non-residential centre. Furthermore, theoretically, in a dense, heavily-used, and mixed-functions city centre, like Paris, journeys are made all across the area throughout the day in every direction; while in Plymouth there is primarily the daily commute going in and out of the city centre. Bicycle sharing systems are not able to cope with sudden booms in de-

44 mand, as their capacity is limited; rather, they function optimally when demand is spread evenly in time and space. This limits potential for use in Plymouth, as the one-sided mobility will lead to bicycles being used closer to twice a day than to ten times a day. What adds to the appeal of bicycle sharing in big cities is that space is limited for individual bicycles; many may live in apartments, which makes it harder or less convenient to store private bicycles. For smaller cities such as Plymouth this most likely does not apply.

Furthermore, it could be argued a public bicycle is not really suitable for commuting, as commuting requires reliable transport. One can never be entirely sure there is a bicycle available at the preferred station, even though it is possible to check online. Having to check for availability every time before you go out is not exactly convenient, especially since the absence of bicycles requires finding another mode of travel to work. Since 67% of all journeys are commuting to work or school (DfT, 2009a), this does limit the potential for the scheme significantly, unless the sheer size of the scheme ensures there are simply so many stations, availability of bicycles is almost guaranteed. The survey showed low interest in using the scheme for commuting as well; and the high interest in using it for leisure may be potentially indicate that cycling is seen as something for leisure rather than part of daily travel, or that people did not entirely understand the bicycles are intended for short trips.

The second part of this research goal was how a scheme could be successful in Plymouth. First of all, it is important to address the points outlined above which indicated why it is not likely for a scheme to work. This implies improving all aspects of the current situation on the road, ensuring cycling is represented as normal, for example in marketing. Many other measures should be included, such as interventions aimed at breaking habits, preferably reducing the attractiveness of car travel, paying extra attention to safety issues, as well as availability of route signage and maps (Cycling England, 2010; TfL, 2008). In short, a bicycle sharing scheme should not be used instead of these measures, rather it should be part of an integrated set of interventions. Furthermore, in terms of implementation of the actual scheme itself, many aspects come into play. The basic technology should be third generation (swipe cards etc.), while the bicycles should be sturdy and able to cope with being outside all day. Next to this, spatial distribution of the stations is important: not only to cover the appropriate locations, but also in terms of covering an appropriately sized area with a suitable density of stations. This is particularly relevant when due to budget limitations only a limited number of stations is available. Also, with tight budgets, it is important to strike a balance between covering a sufficiently big area while also providing a sufficiently high density. The former enables trips of the distance that is ideal to cycle (1 to 5 km, roughly), while the latter ensures users can always find a bicycle or available docking point, possibly at a station next to the first-choice station, when that isn’t available. Furthermore, it is important to provide docking stations at transport hubs, businesses, and other key locations. The local ferry landings may represent a particular opportunity, as the ferries provide substantial shortcuts compared to alternative land-based routes; providing bicycles greatly decreases overall journey time for trips which are combined with the ferries. Also, local businesses could contribute to the costs of locating a station at their office. Another specific feature for smaller cities such as Plymouth is that mobility is largely restricted to the twice-daily commute in and out of the city. In big cities such as Paris, mobility is much more random, as functions are well-mixed throughout the covered area. Small

45 cities should try to reduce their dependency on the twice-daily traffic rush; this puts a strain on the low-capacity system as mobility is so one-sided. For this reason, the scheme should cater for shoppers, short social/leisure trips, as well as business trips. More details on how a scheme in Plymouth could be implemented can be found in section 6.3.

The second goal guiding this research concerned the role and effects of bicycle sharing systems in general. With regard to its role in terms of tackling barriers to cycling, bicycle sharing address entirely different barriers than most other measures. According to the survey, bicycle theft is a rather serious risk, and bicycle sharing does provide a solution for this. One of the interviewees also specifically mentioned the lack of responsibility for the bicycles as a main advantage. However, other barriers which are supposed to be tackled are not considered important barriers in Plymouth, as 19% think buying and maintaining a bicycle is expensive, and only 7% think it is a lot of work. Furthermore, public bicycles make it much easier to get out and try cycling without having to make a serious commitment. As the act of cycling has been shown to improve attitudes towards it (Gatersleben & Appleton, 2007), this might be one of its key benefits. On the other hand, many respondents did own a bicycle but never used it, and attitudes to cycling are already quite positive, as 65% indicated they liked cycling.

In the transformation towards a more sustainable transport sector, with higher levels of cycling, bicycle sharing systems seem to be able to play a specific role. In cities such as Paris and Barcelona, significant improvements to the cycling situation preceded the implementation of the bicycle sharing scheme (DeMaio, 2009; Mairie de Paris, 2007; Romero, 2008). Consequently, cycling levels were also already increasing gradually, and the sharing systems were implemented as a culmination of cycling improvement interventions. This resulted in a sudden boost in numbers of cyclists, by attracting many new cyclists at once. So, the main role for a bicycle sharing scheme seems to have been to give cycling a one-off boost, once the on-road situation is already quite receptive to cycling but modal share is not quite picking up. In other words, when the external barriers to cycling are being tackled (i.e. the situation for cycling is good), but internal barriers prevent people from cycling (as it is for example perceived as not normal, or something for others), bicycle sharing addresses this. It simply makes cycling very accessible to everyone, without any major barriers; even use is almost free.

Next to the role a bicycle sharing scheme can play, it seems not too much is known about the effects of bicycle sharing in general. It is well established that, at least in big cities, levels of cycling have picked up, and in Paris new people have started cycling and even started using their own bicycles more (TfL, 2008). The sudden increase in numbers of cyclists on the streets has been termed critical mass (Sherwin & Parkhurst, 2009). When a critical mass of cyclists is achieved, this in turn would have reinforcing effects as car drivers become more aware of cyclists, social norms change favourably, political support can grow, and momentum for cycling will be created. However, the extent of these effects is not known in detail, and this is true for many other things as well. For example, little is known about the CO 2 emission reductions due to bicycle sharing. While cycling undoubtedly has a low environmental impact, bicycle sharing most commonly attracts those who used to walk or use public transport (Anaya, 2009; Dector-Vega & Baster-

46 field, 2009). Therefore, reductions in CO 2 emissions may be limited. Moreover, redistribution of the bicycles is often done by fossil-fuelled vehicles, and high levels of theft and vandalism mean a relatively high input from a materials point of view. The net result of these effects has not been quantified to date. Another issue surrounding by a degree of uncertainty is the long-term effect on levels of cycling. In order to find out more about the possible effects of bicycle sharing, and how a scheme should be implemented, the next section details the application of bicycle sharing to Plymouth.

6.3 Application to Plymouth Implementation This section presents a proposal of how a bicycle sharing scheme could be implemented in Plymouth. This is not to say it is a good idea to implement a scheme; the purpose is to explore how it could work and what the consequences would be. First of all, the scheme is assumed to work best with contemporary third generation technology, as used by most present systems (swipe cards, electronic locks to the docking station, automated hire; see section 2.2). It does not fall within the scope of this study to go into this in more detail. Given the balance between tight budgets and the need for a rather large scheme, it was decided to aim for a compromise option of 40 docking stations (with up to 10 bicycles at each station), covering the city centre and the surrounding area, as shown in Fig- ure 6.1 (a bigger map can be found in Appendix F, p.69).

Figure 6.1 Proposed location of docking stations in Plymouth

47 The locations of the docking stations are largely based on the maps created during the two focus groups sessions (Appendix G, p.71), with a number of stations added at primarily residential and intermediate locations. In the same appendix an overview of the reasons for each station’s location can also be found. The proposal aims to strike a balance between two requirements which are difficult to meet both. First, a scheme needs to cover a large enough area to enable longer trips. This particularly concerns trips between 1 and 5 km, as shorter distances are generally walked, and longer distances can be covered quicker with other modes of transport. Second, the scheme needs a sufficient density of docking stations to give users the security that within the scheme’s area they will be able to find a place to pick up or drop off a bicycle. Also, if at the preferred station no bicycle or open docking point is available, it is important to have another station nearby. Another starting point was that the concentration of mobility in rush hours is more noticeable in Plymouth than it is in big cities such as Paris. This means that demand for the bicycles will be concentrated in both time and space. Therefore, efforts have be made to counter this effect by placing stations in such as way that shopping, short leisure and business trips are also catered for. Also, Parkin, Ryley and Jones (2007, p.12) note that “it is important for cycle planners to recognize that cycle journeys are most likely to take place between a home origin and destination located in an urban centre or at a public transport node, such as a railway station”. This confirms the importance of spreading the stations over a large enough area to also cover residential areas, and include both origin as destination locations. In addi- tion to this, the survey showed how the public bicycles were considered most attractive for leisure and social trips; to accommodate this demand it is also important to provide stations at popular leisure locations such as the Hoe and the Barbican. Although in the survey Mutley was indicated as the most popular area to expand the scheme, due to its hilly topography and the limited number of stations available, it was decided not to include Mutley in the proposal at this point.

In the current proposal, the city centre is the central part of the scheme, as mobility is concentrated in that area. The central ‘spine’, stretching from the railway station to the seaside at the Hoe, is covered by stations as this is a wide, traffic-free, recognizable and quick route. Even though cycling is prohibited on major parts of this stretch, it is assumed that with the implementation of this scheme this ban will be lifted. This general lay-out is complemented by a specific focus on coverage of public transport hubs. The railway stations and bus station are covered, as well as the three local ferry landings (Cremyll, Torpoint and Mount Batten). The ferries offer a particular opportunity, as they provide considerable shortcuts compared to the car or bus route into town, and mostly only transport pedestrians (with the exception of Torpoint Ferry). The total duration of the ferry/walking journeys to the city centre can be decreased significantly by offering public bicycles for the trip from the ferry to the centre. The distance from Mount Batten Ferry to the city centre is about 1 km, from Cremyll Ferry to the city centre is about 2 km. Distances to the railway station or the university are even bigger, so there is a great opportunity for time saving. At the moment, the scheme is not specifically aimed at a certain demographic group, however this could still be done in the future. Students are already catered for by placing some docking stations at the campus (both university and halls of residence).

Costs The costs for the scheme are dependent on the method of funding. Many French cities have coupled the scheme with outdoor advertising rights; they don’t directly spend any money on the scheme, they miss out on their advertising revenue instead. The costs of this are not entirely clear, as in most cases the outdoor advertising companies decide which scale of the scheme they consider feasible in exchange for the income the get from the advertising contract. Although this method of funding has been used for Vélib’, it is rejected by most recent feasibility studies (e.g. TfL, 2008, TransLink, 2008). Alternatively, PCC could opt for commercial operators such as OYBike or Hourbike, in which case costs are directly related to the number of bicycles and stations. Assuming 40 stations and 400 bicycles, the initial investment costs would be between £40,000 and £475,000, while the annual maintenance costs would be between £200,000 and £360,000 (Hanning, 2009; Hourbike, 2010). Alternatively, the Bixi scheme in Montreal charges about $78 (£51) for the annual membership, and according to NYCDCP (2009) is aiming to become profitable. This would keep the costs for the council down, although there is no guarantee the scheme will continue to exist on the long- term. Given the current cycling budget of about £250,000, the costs for a scheme of this size seem to be much too high. Unless PCC could negotiate a deal in which there are no ongoing costs for the council, in a way similar to Cardiff, it seems unlikely the scheme could go ahead without external funding or grants.

Results The most important indicator of the scheme’s performance is its usage. Based on chapter 4 and data from OBIS (2009), the number of rents per bicycle per day could be anywhere between 0.3 and 3.8; 0.3 being the lowest use for a big or mid-sized scheme (Berlin), and 3.8 being the highest for a mid-sized scheme (Dijon). The survey indicates considerable enthusi- asm for the scheme, however, previous sharing schemes in the U.K. have not achieved high use rates. Moreover, the student interviews suggested an attitude-behaviour gap, implying the survey results do not necessarily lead to actual high levels of usage. Taking the hostile situation on the road and the effect of internal barriers to action into account, the figure seems more likely to be close to 0.3 and 3.8. Assuming a use rate of 0.3, modal share for cycling would increase from 1% tot 1.01%; for a use rate of 1 it would be 1.06%, for 3.8 it is 1.22%. In terms of modal shift, experience elsewhere suggests public bicycle users will primarily come from walking and public transport. According to Anaya (2009), in Barcelona, only 10% of users came from private motorized vehicles, while customer research in London showed this figure is less than 7% (Dector-Vega & Basterfield, 2009).

Also, it is unclear to what extent bicycle sharing contributes to emission reductions. Anaya (2009) labels it as a myth due to the emissions from redistributing the bicycles over stations, however to the author’s knowledge no quantitative research has been done into this. It seems, however, that as long as a bicycle sharing scheme results in a wider increase in cycling – in Barcelona, the scheme is attributable for only one-third of the increase in cycling – this will have all of the positive effects of cycling identified in chapter 2. Based on the assumptions of

49 low (0.2 rents per bicycle per day), medium (1) and high (3.8) use rates of a sharing system, CO 2 emission reductions from cycling could be anywhere between 4 and 74 tonnes per year (see Appendix H, p.72). However, as this calculation does not take into account the extra emissions associated with bicycle sharing, it is hard to draw conclusions based on this.

Based on PCC (2010), an analysis of the costs and benefits of increasing cycling levels in Plymouth, the societal benefits of one cyclist to cycle for one year (220 trips per year) are about £400 (€477). These benefits are primarily due to physical fitness improvements, and to a lesser extent to congestion reduction, reduced absenteeism and greenhouse gases emissions reductions. When a comprehensive investment programme in cycling would be started in Plymouth, these benefits would ensure a benefit cost ratio (BCR) of anywhere between 15:1 and 32:1 (PCC, 2010). These very high BCR’s are confirmed by a study by the Government Office for the South West (2010), where the median BCR of a number of UK cycling projects was found to be 19:1. Assuming low, medium and high use rates (0.2, 1 and 3.8 rents per bicycle per day), the BCR of a bicycle sharing scheme in Plymouth will not be anywhere near as high as it could be with other cycling measures (see Appendix I, p.73). In the low success scenario the BCR is as low as 0.3:1, while even in the most successful scenario the BCR is not higher than 5.6:1. This clearly demonstrates that investing in a bicycle sharing scheme represent a big financial risk, also due to the uncertain benefits. While it might just attain a positive BCR, clearly investment in traditional cycling interventions such as cycle lanes, parking, and marketing is far more cost-effective than bicycle sharing in its current form.

6.4 Limitations of this research Some limitations are associated with this research. First of all, it seems that the survey results are too optimistic. Not only did respondents identify fewer barriers to cycling than everyone else in the interviews, focus groups, and any informal discussions throughout the research process; also as much as 15% would like to use it at least once a week. This may be explained by the fact that respondents did not have an outspoken opinion about cycling, possibly because they never cycle or even consider doing so. This explanation is also supported by the fact that on some questions in the attitude scale 40% of respondents was indifferent to a statement. This also explain why the barriers which appeared most important still only were perceived by a minority (such as the 46% agreeing that there are not enough cycle lanes). Another reason for the positive outcomes of the survey could be that personal interest in using the scheme was estimated based on a hypothetical situation, while it is likely there is a difference between stated preference and actual behaviour. Moreover, despite efforts to explain bicycle sharing properly, one can never be sure all respondents fully understood the concept. The open questions were used as interpretations for this, to be able to remove cases with unreliable data. This study might have had a deeper foundation, had more literature been available on bicycle sharing. A lack of reliable data also played some part in the case studies, as it was difficult to obtain data on use rates of schemes, and even impossible to check for the reliability of this data. When depending on operators or local authorities for this data, there is a risk of being provided with overly favourable data. Given its strikingly high use rates, this may have been the case for Dijon. Due to a lack of data availability, the case studies have not been as in-

50 depth as might have been desirable. However, by using a multi-method design, it was attempted to get a comprehensive answer to the study’s main questions.

6.5 Future research Despite this study’s efforts, some important issues remain. Most importantly, as sharing schemes are a relatively recent phenomenon, little is know about their long-term viability. Vélib’ has been extremely successful in the short run; however, it can be questioned whether it is the most cost-efficient option to maintain in the long run. This is particularly relevant given that each trip made by Vélib’ bicycles costs about €1. It could be very interesting to see how many Vélib’ users continue to cycle would the scheme be terminated. If this proportion is very high, as might be expected as regular users apparently liked cycling, it might actually be beneficial to stop Vélib’, and invest the money in other cycling measures, improving cycling for everyone in the city. The role of successful schemes supposedly has been to create a cycling culture, momentum, and all the corresponding beneficial effects. However, as modal share for cycling in Paris already increased 48% in the six years prior to Vélib’, it is unclear what would have hap- pened if it had not been for Vélib’. It is likely that cycling levels would have continued to increase, as the cycling context continued to improve. From this point of view, it is unclear to what extent Vélib’ has been of crucial importance, while also questioning the supposed general impact and purpose of bicycle sharing.

With regard to the future of bicycle sharing, it can be questioned what the role of bicycle sharing will be in the latter stages of the transformation to high cycling levels. After all, the role of bicycle sharing in countries with a high modal share for cycling such as the Nether- lands is minimal. This leads to the question whether there is a place for bicycle sharing systems in its current form in the latter stages of the transformation towards a high modal share for cycling. From this perspective, it almost seems that bicycle sharing is just a very expensive way to temporarily speed up the transition to high cycling levels. While it has been argued to create a critical mass and get cycling out of its obscure sub-cultural corner, there is actually no proof that this can be attributed to bicycle sharing at all. Since public bicycle systems represent significant investments, and may form the bigger part of the entire local cycling budget, it is of great importance for future research to look into the issues mentioned above.

One strand of research which could be added to this would be to examine the environmental sustainability of bicycle sharing. While cycling is undeniably a sustainable mode of travel, bicycle sharing has some rather environmentally unfriendly elements: high rates of vandalism and theft, as well as the redistribution of bicycles, which often happens with petrol-fuelled vehicles. As modal shift from the most polluting mode of travel, private motorized vehicles, is very limited, environmental benefits may be limited as well. The overall accumulated effects of this have never been quantified, but this would certainly make a strong contribution to the arguments either in favour of or against the practice of bicycle sharing, and is definitely worth future study.

52 7 Conclusions

This study’s first goal was to explore whether and how a bicycle sharing scheme can be successful in Plymouth. At this point, it seems highly unlikely that a scheme will become successful in terms of achieving significant use rates or modal shift. The main reason for this is the cycle-unfriendly situation on the road: a lack of good quality infrastructure, poor driver consideration towards cyclists, and few restrictions on car mobility throughout the city. Cy- cling has been found to be something which people are fearful of, and a significant proportion of the population does not even consider using the bicycle as a mode of travel. Although Plymouth’s hilliness is a big factor in the city’s overall potential for cycling, its effect could be minimized by focusing bicycle sharing on the flatter parts of the city, in and near the city centre. Another important factor which lessens the potential for bicycle sharing is that widespread internal barriers to cycling were found. It was indicated people only want to use the public bicycle once many of their friends or peers do so as well, while evidence was found for people feeling uncomfortable on a bicycle as well. Moreover, social norms have been found to be unsupportive of cycling, among others due to the low levels of cyclists at the moment. It should be noted that in other countries bicycle sharing has been successful even though modal share for cycling was very low, so that does not necessarily have to be the biggest barrier. What can be added to this is that Plymouth is a rather small city, which is good for cycling in general, but is not ideal for bicycle sharing, which requires high levels of mobility in both time and space. In Plymouth, this is not the case, partly due to the lack of mixed functions in its centre, and partly due to its limited size. The alternatives to using the bicycle are very attractive; there is only limited congestion and public transport is functioning well. There is no strong policy support for cycling at the moment, and cycling is not even permitted in the car-free city centre. Also, this study found bicycle sharing in Plymouth to be perceived most attractive for leisure and social trips, which means people do not consider it as a serious alternative to their daily non-leisure travel. Finally, so far no scheme in the U.K. has been successful in attracting substantial numbers of cyclists. Overall, despite its temperate climate, success of bicycle sharing in Plymouth does not seem to be evident.

However, assuming funding would become available to implement a public bicycle system, there are some basic points as to how it could be successful in Plymouth. First of all, the barriers mentioned above should be tackled; one cannot expect inexperienced cyclists to start cycling as long as the roads are cycling-unfriendly. Furthermore, a small scheme should definitely not be used; no small scheme has ever attracted significant numbers of new cyclists. Given that funding will be limited, a balance should be struck between adequately dense coverage and covering a big enough area to cater for longer trips (over 1 km), and thereby offering real time savings to users. After all, short trips are walked just as easily; it is only with somewhat longer trips that the benefits of cycling start to apply. Third generation technology should be used, such as user registration and swipe cards. A local scheme should cater for as many trip purposes as possible, because the daily rush of commuters is too concentrated in time and direction to be focusing on. Providing for leisure and shopping trips is therefore an

53 important part of trying to achieve higher use rates. Also part of this would be to include local hubs, such as the ferry landings and the railway station. The second goal of this study was to review the role and effects of bicycle sharing in general. First of all, the role of bicycle sharing within cycling policy is very specific, as it addresses entirely different barriers than most other interventions. It removes the responsibility of ownership and maintenance from the user. Therefore, risk of theft, costs and maintenance work are not a barrier anymore, even though out of those three only risk of theft is commonly perceived as a barrier in Plymouth. Also, it should be noted that the majority of barriers to cycling are not tackled by bicycle sharing. Therefore, it should always be implemented as part of a comprehensive programme of measures. The role of bicycle sharing is to make it in- credibly easy to just try cycling, without having to make any commitment to it. The act of cycling has been shown to improve attitudes towards cycling, implying a straightforward effect. On the other hand, attitudes have been shown to already be quite positive, as many indicated they liked cycling; also, a significant proportion already owned a bicycle but never used it. Elsewhere, bicycle sharing has been used successfully as additional intervention following major investments in the basic cycling situation. In other words, it has been most successful in those cities where the on-road situation is already fairly receptive to cycling but modal share is not quite picking up.

Ideally, the effects of bicycle sharing in these cases include a sudden boost in number of cyclists, creating what is often referred to as a critical mass. This has several reinforcing effects on cycling, as car drivers become more aware of cyclists, social norms change favourably, political support can grow, and momentum for cycling will be created. It has also been argued bicycle sharing schemes successfully increase numbers of people using their own bicycle as well. However, very little is known about the exact effects; for example, in many cities the infrastructural improvements already led to an increase in levels of cycling. It could be that levels would have continued increasing to current levels anyway, and bicycle sharing is only a way to speed up this process. With regard to other main effects, modal shift from private motorized vehicles tends to be minimal, as most users used to walk or use public transport. This suggests the potential for CO 2 emission reductions is limited as well; also because vehicles are needed to redistribute the bicycles over the docking station, and material requirements due to high levels of theft and vandalism. Although little is known about the quantified effects, evidence from Plymouth suggests the likely CO 2 savings are negligible.

Overall, not only does it seem highly unlikely a scheme will attract significant numbers of users in Plymouth, it is also unclear to what extent bicycle sharing in general is preferable over other interventions which focus on improving the general cycling context. This is em- phasized by the difference in likely benefit-costs ratio: while traditional cycling interventions often achieve a ratio of 19:1 or more, for bicycle sharing in Plymouth this is more likely to be 1:1. Considering all requirements for a successful sharing system – either those mentioned by other authors or the ones pointed out by this study – it is clear that Plymouth does not score well on any of these. It will first have to address the barriers outlined above in order for any bicycle sharing system to work successfully.

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61 62 Appendices

A Map of Plymouth

63 B Calculation of modal share

As no specific data for the mode share of cycling in Plymouth is available, the following calculation has been used to acquire an estimate. Accurate data is only available for journeys to work and journeys to school.

According to the DfT’s National Travel Survey 2008, in the U.K. 1.6% of all journeys was made by bicycle. In the table below can be seen that cycling levels in Plymouth are 13% to 74% lower than national averages, based on the two available data sources. Based on this the modal share of cycling in Plymouth is estimated to be about 1%.

Type of trip % of all trips % using bicycle for this % using bicycle for this journey (U.K. figure) journey (Plymouth figure) Commuting 16% 2.83% 2.49% To school 11% 1.9% 0.68%

Based on the calculations below, this equates to about 2,480,000 cycle trips per annum in Plymouth.

Annual number of trips in Plymouth: Population * average number of trips per person per annum in the U.K (from National Travel Survey 2008, Table 4.7). 250,000 * 992 = 248,000,000

Annual number of cycling trips in Plymouth: 248,000,000 * 1% = 2,480,000

64 C The questionnaire Note: original layout has been very slightly adapted to fit the questionnaire on these pages.

Questionnaire bicycle sharing scheme May 2010 This questionnaire consists of four parts and will take about 10 minutes. Any information which you provide will be kept strictly confidential. Please read the questions carefully and ask the researcher in case anything’s unclear.

Part 1: Basic information 1) What’s your gender? male female

2) What’s your age? under 18 years 50-59 18-29 60-69 30-39 70+ 40-49

3) What are the first four figures of the postcode of your current address?

4) If employed: What is your employer’s postcode or address?

5) If student: where is your school/faculty located? Main university campus on North Hill/Drake Circus College of Art at Tavistock Place Derriford other:………………………………………..

6) What’s your occupation? student full-time job part-time job unemployed retired

7) What is your current annual net income? under £10,000 £10,000 - £19,999 £20,000 - £29,999 £30,000 - £39,999 £40,000 or more

8) Is environmental sustainability a major theme in your particular job/study? yes no n/a

9) Do you currently own a bicycle, which is available for you to make your trip to work/school/do shopping here in Plymouth? yes no

65 10) Do you own a car, which is available for you to make your trip to work/school/the shop here in Plymouth? yes no

Part 2: Travel habits Question 11 and 12 are only for employed persons and students.

11) What is the approximate distance of your daily commute? …………………………………………….. miles

12) What is your usual mode of travel to work/school? (if you use more than one, use the one which covers the greatest distance) walking car bus train bicycle other: ………………………………………………………

13) What is your usual mode of travel to the city centre? (if you use more than one, use the one which covers the greatest distance) walking car bus train bicycle other: ………………………………………………………

14) Do you ever consider cycling to work/school/do shopping? never rarely sometimes often

15) How often do you cycle for fun/leisure? never couple of times a year once or twice a month about once a week multiple times a week

16) How often do you use the bicycle for non-leisure travel (i.e. journey to work or school, or for shopping)? never about once or twice a month about once a week multiple times a week (nearly) always

66 Part 3: Attitude towards cycling Please indicate to what extent you agree with the following statements about cycling. Please read the statements carefully. Totally Disagree Neither Agree Totally disagree disagree agree nor agree 17. I am not fit enough to cycle to 1 2 3 4 5 work/school/the shop. 18. There is not enough cycle 1 2 3 4 5 parking throughout Plymouth. 19. Cycling is good for the envi- 1 2 3 4 5 ronment. 20. There are not enough cycle 1 2 3 4 5 lanes throughout Plymouth. 21. Cycling is a sport, not a trans- 1 2 3 4 5 port mode. 22. My friends and family will find it very uncharacteristic if I were 1 2 3 4 5 to cycle to work/school/shops. 23. The city centre is too hilly to 1 2 3 4 5 cycle. 24. I have got the required skills to 1 2 3 4 5 ride a bicycle safely. 25. I would feel unsafe while cy- 1 2 3 4 5 cling through Plymouth. 26. I would feel uncomfortable on 1 2 3 4 5 a bicycle. 27. Most people I know would never consider cycling in Ply- 1 2 3 4 5 mouth. 28. Cycling is healthy. 1 2 3 4 5 29. Owning and maintaining a bi- 1 2 3 4 5 cycle is a lot of work. 30. It is expensive to buy and 1 2 3 4 5 maintain a bicycle. 31. I like cycling. 1 2 3 4 5 32. Plymouth and its surrounding urban area are too hilly to cy- 1 2 3 4 5 cle. 33. There is too much traffic in the 1 2 3 4 5 city to cycle. 34. Bicycle theft is a serious risk 1 2 3 4 5 for bicycle owners. 35. The weather in Plymouth is not 1 2 3 4 5 suitable for cycling. 36. I have to wear different clothes 1 2 3 4 5 to cycle. Please make sure you have responded to each statement!

67 Part 4: Interest in bicycle sharing scheme

Bicycle sharing schemes exist in about 150 cities (among which are Paris, Bristol, Cardiff). Plymouth City Council is currently assessing the feasibility of such a scheme in Plymouth.

Main characteristics of bicycle sharing:

- public bicycles, available at docking stations (see picture) - you can quickly collect a bike at one docking station and drop it off again at any other docking station in the city - annual subscription fee of about £20 - use is free for first 30 minutes of each trip; £1 for each extra 30 minutes - maximum allowed use is 4 hours per trip - ideal for short, one-way trips: you are expected to return your bike to any docking station immediately after you’ve completed your trip, so that someone else can use the bike again - only to be used in the area covered by docking stations

A proposal for the lay-out of such a scheme in Plymouth is shown on this map, with the black squares indicating locations of docking stations (40 in total). The map covers the area from Devonport on the left to Laira Bridge on the right, with the city centre in the middle.

69 Please indicate to what extent you agree with the following statements. Please read the statements carefully.

Totally Disagree Neither Agree Totally disagree Disagree agree nor agree 37 I would like to try out the proposed 1 2 3 4 5 scheme in Plymouth at least once. 38 I’m interested in using the scheme 1 2 3 4 5 at least a couple of times a month. 39 I’m interested in using the scheme 1 2 3 4 5 at least a couple of times a week. 40 I’m interested in using the scheme 1 2 3 4 5 on a daily basis. 41 It is unlikely that I will use the 1 2 3 4 5 scheme at all. I would potentially use a bicycle sharing scheme in Plymouth for: 42 My daily commute 1 2 3 4 5 43 Shopping trips 1 2 3 4 5 44 Leisure/social trips 1 2 3 4 5 45 Journeys from and to the railway 1 2 3 4 5 station 46 Journeys from and to my bus stop 1 2 3 4 5 47 Business trips within Plymouth 1 2 3 4 5 48 Other city centre trips, 1 2 3 4 5 namely:………………………… 49) Why are you (not) interested in using a bicycle sharing scheme in Plymouth? ………………………………………………………………………………………………… ………………………………………………………………………………………………… ………………………………………………………………………………………………… ………………………………………………………………………………………………… …………………………………………………………

50) In which area of the city, located on or near the map, would you like to see (more) docking stations? (tick one or more boxes)

Mutley / Mutley Plain St. Judes / Mount Gould Cattedown / Prince Rock area Stonehouse / Union street Devonport the Victoria Park area none of the above others: ……………………………………………………………………………..

51) Do you have any final comments? ………………………………………………………………………………………………… ………………………………………………………………………………………………… …………………………………………………………………………

Thank you for participating in this study

70 D Statistical procedures

The factor analysis has been executed using the following command in SPSS, the results of which can be found in the tables below. The five items were classified into one group, indicating they measure the same construct.

FACTOR /VARIABLES TRY_ONCE COUP_MON COUP_WEEK DAILY NOT_AT_ALL /MISSING LISTWISE /ANALYSIS TRY_ONCE COUP_MON COUP_WEEK DAILY NOT_AT_ALL /PRINT INITIAL EXTRACTION ROTATION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /CRITERIA ITERATE(25) /METHOD=CORRELATION. Total Variance Explained

Com- Initial Eigenvalues Extraction Sums of Squared Loadings

ponent Total % of Variance Cumulative % Total % of Variance Cumulative %

1 3,292 65,831 65,831 3,292 65,831 65,831

2 ,977 19,546 85,377

3 ,388 7,756 93,133

4 ,201 4,023 97,156

5 ,142 2,844 100,000

Extraction Method: Principal Component Analysis.

Component Matrix a

Component

TRY_ONCE ,786

COUP_MON ,922

COUP_WEEK ,863

DAILY ,665

NOT_AT_ALL recoded ,797

Extraction Method: Principal Compo- nent Analysis.

a. 1 components extracted.

The general interest variable was calculated with the following command:

COMPUTE General_Interest=TRY_ONCE + COUP_MON + COUP_WEEK + DAILY + NOT_AT_ALL. EXECUTE.

71 E Summary of survey results

Variable Location PCC City centre N 102 60 Gender Male Female N 88 70 Age 18-29 30-39 40-49 50-59 60-69 70 or older N 62 36 29 23 11 1 Other within Ply- Other outsi- Postcode zone PL1 PL4 mouth de Plymouth Visitor N 14 30 81 26 3 UoP cam- City Colle- School location pus ge N 17 3 Full-time Part-time Occupation Student job job Unemployed Retired PCC N 23 15 6 7 6 102 £10,000 - £20,000 - £30,000 - £40,000 or Income <£10,000 £19,999 £29,999 £39,999 over N 30 35 37 31 20 Is sustainability a major theme in work/study? yes no n/a N 89 55 10 Bicycle ownership yes no N 67 95 Car ownership yes no N 110 51 Distance daily commute (one- 1.5 and way, in km) under 1,51 - 5 5,01 - 10 10,01 - 25 25,01 - 50 over 50 N 34 50 35 19 10 2 Mode of travel to work/school Walking Car Bus Train Bicycle Motorcycle N 43 58 28 4 11 4 Mode of travel into the city centre (if unemployed or re- Not applica- tired) Walking Car Bus ble N 5 2 6 148 Does respondent ever consider cycling to n/a (cy- work/school/shops? Never Rarely Sometimes Often clists) N 86 22 30 9 14 Couple of Once or Multiple times a twice a Once a times a Frequency of leisure cycling Never year month week week N 65 53 21 14 8 Once or Multiple Frequency of non-leisure cy- twice a Once a times a (Nearly) cling Never month week week always N 126 15 6 4 9

72 St. % % di- Variable name N Mean dev. agree sagree 17 Not fit enough to cycle 162 2,06 1,17 15% 70% 18 Not enough cycle parking in Plymouth 160 3,08 0,99 27% 20% 19 Cycling is good for the environment 162 4,33 1,13 86% 8% 20 No enough cycle lanes in Plymouth 161 3,52 1,06 47% 13% 21 Cycling is sport, not transport mode 162 2,00 0,93 6% 75% My friends and family would find it very 162 2,67 1,27 22 uncharacteristic if I were to cycle 28% 49% 23 City centre is too hilly to cycle 162 2,35 1,02 15% 60% 24 I've got the required skills to cycle* 161 3,83 1,21 73% 19% 25 I would feel unsafe while cycling 162 3,12 1,20 46% 33% 26 I would feel uncomfortable on a bicycle 161 2,36 1,18 19% 62% Most people I know would never con- 161 3,02 1,04 27 sider cycling 36% 31% 28 Cycling is healthy 161 4,47 0,85 93% 4% Owning and maintaining bicycle is a lot 162 2,30 0,84 29 of work 7% 64% Buying and maintaining bicycle is ex- 162 2,54 0,97 30 pensive 19% 54% 31 I like cycling 161 3,70 1,07 65% 15% 32 Plymouth is too hilly to cycle 162 2,92 1,05 32% 36% 33 Too much traffic in the city 160 3,24 1,02 46% 28% 34 Bicycle theft is a serious risk 161 3,34 0,81 42% 15% Weather in Plymouth is not suitable for 162 2,72 0,99 35 cycling 22% 45% 36 Have to wear different clothes to cycle 162 3,64 0,99 62% 14% * values were reversed for comparability with means of other variables

City % agreeing with these statements PCC Centre Overall Like to try at least once 54% 63% 57% Like to use at least couple of times a month 31% 34% 32% Like to use at least couple of times a week 11% 12% 11% Like to use scheme on a daily basis 1% 8% 4% Unlikely to use the scheme at all 41% 33% 38%

City % agreeing with these statements PCC Centre Overall My daily commute 11% 22% 15% Shopping trips 12% 29% 19% Leisure/social trips 46% 59% 51% Journeys to and from the railway station 27% 33% 29% Journeys to and from my bus stop 8% 15% 11% Business trips within Plymouth 29% 19% 25%

Where would you like to see (more) docking stations? % yes % no Mutley / Mutley Plain 36% 64% St. Judes / Mount Gould 17% 83% Cattedown / Prince Rock area 11% 89% Stonehouse / Union street 14% 86% Devonport 11% 88% the Victoria Park area 11% 89% None of the above 10% 90%

74 F Proposal for bicycle sharing system in Plymouth

Station locations and purpose:

1) Torpoint Ferry 2) Devonport residential area 3) Intermediate station / residential area 4) Brickfield recreation ground and community centre

75 5) City College Plymouth 6) Royal William Yard (residential and cafes) 7) Stonehouse residential area / naval base 8) Cremyll Ferry (to Mount Edgecumbe & Cornwall) 9) Intermediate station / residential area 10) Cathedral / intermediate station / residential area 11) Victoria Park 12) Intermediate station / residential area 13) West Hoe residential / tourist area 14) Citadel Road residential / tourist area 15) City Centre 16) City Centre 17) The Hoe / leisure, tourist area 18) Intermediate station / leisure, business, residential area 19) City Centre, Plymouth City Council, Civic Centre 20) City Centre 21) City Centre 22) City Centre 23) Railway station 24) University campus 25) University campus 26) City Centre 27) City Centre 28) City Centre 29) Barbican, leisure / tourist area 30) Barbican, leisure / tourist area 31) University campus 32) Intermediate station / residential area 33) Bretonside bus station 34) Intermediate station / business area 35) University 36) Beaumont Park / residential area 37) Barbican Leisure Center 38) Residential area 39) Residential area 40) PCC depot / business area

Note: intermediate stations are provided to link up areas; to ensure distances between stations are not too high, providing adequate density of coverage.

76 G Maps created during focus groups

Top map: focus group PCC BUG, bottom map: focus group university BUG.

H Calculation of CO 2 emission reductions

Low success (0.2 rents per bicycle per day) Medium success (1 rent per bicycle per day) High success (3.8 rents per bicycle per day)

Assumptions Number of bicycles on street: 400 Modal shift: CO 2 emissions per km [kg] From bus: 50% 0.19 Walking: 40% 0 Car: 5% 0.33 Private bicycle: 5% 0 Average trip distance with public bicycle 1.2 km

Scenario 1 Total trips 29,200 New modal share cycling 1.01% Total km travelled 35,040 Total bus km replaced 17,520 CO 2 savings 3,329 kg Total car km replaced 1,460 CO 2 savings 482 kg Total annual savings 3,811 kg

Scenario 2 Total trips 146,000 New modal share cycling 1.06% Total km travelled 175,200 Total bus km replaced 87,600 CO 2 savings 16,644 kg Total car km replaced 8,760 CO 2 savings 2,891 kg Total annual savings 19,535 kg

Scenario 3 Total trips 554,800 New modal share cycling 1.22% Total km travelled 665,760 Total bus km replaced 332,880 CO 2 savings 63,247 kg Total car km replaced 33,288 CO 2 savings 10,985 kg Total annual savings 74,232 kg

78 I Calculation of benefit-cost ratios

Low success (0.2 rents per bicycle per day) Medium success (1 rent per bicycle per day) High success (3.8 rents per bicycle per day)

Assumptions Number of bicycles of street: 400 Number of trips made per user annually 200 Benefits per cyclists* £400 * Based on: PCC, Plymouth City Council (2010). LTP cycle target setting. Internal spreadsheet. Annual cost of scheme £200,000

Scenario 1 Total trips 29,200 Number of cyclists 146 Total benefits £58,400 BCR 0.3:1

Scenario 2 Total trips 146,000 Number of cyclists 730 Total benefits 292,000 BCR 1.5:1

Scenario 3 Total trips 554,800 Number of cyclists 2774 Benefits £1,109,600 BCR 5.6:1