on the move - independent transport commission the move: exploring attitudes ... advantage...

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On the Move: Exploring attitudes to road and rail travel in Britain

APPENDIX

Contents1 APPENDIX A Interview and Questionnaire Schedules ................................... 80

2 APPENDIX B Data and Literature Review ...................................................... 84

7 APPENDIX C Discussion Group summaries ................................................ 139

8 APPENDIX D Statistical Results .................................................................... 173

80

1 APPENDIX A Interview and Questionnaire Schedules

81

ON THE Move Q1. Would you say your general travel patterns have changed in the last two years?

Yes 1 No 2

Travel more 1 Travel less 2 Travel by different modes i.e. now cycle more 3 If yes, Why Q2. Thinking about the long term future do you think you will be traveling more or less than you do now?

Travel more

Travel less

No change

In applicable

Travel in general 1 2 3 4 Work 1 2 3

4

Education Self / others 1 2 3

4

Shopping 1 2 3

4

Leisure 1 2 4 Q3. How do you MAINLY travel for these different purposes at the moment? Purpose Car as

driver Car as passenger

Train Bus/metro underground

Walk Cycle Van Other

Varies – no main

Work 1 2 3 4 5 6 7 8 9 Education Self/others

1 2 3 4 5 6 7 8 9

Shopping 1 2 3 4 5 6 7 8 9 Leisure 1 2 3 4 5 6 7 8 Q4a. What would you say are the advantages and disadvantages of travel by train? Advantage

Disadvantage

Q4b. What would you say are the advantages and disadvantages of travel by car? Advantage

Disadvantage

Q4c. Are you yourself a driver? Non driver

Provisional licence

Full licence

Licence but don’t drive

1 2 3 4

82

Q5a. How many cars in your household? None

1 One 2

Two 3

3+ 4

Q5b.If ‘no’ do you expect to have one in the coming year or so Yes 1

No 2

Maybe3

No 4

Q5c. If ‘yes’ do you see it as an important/major priority Yes 1

No 2

Maybe3

No 4

Q5d. Why do you say that? - (Q5b) you expect or not to own a car or (Q5c) that it is or isn’t a priority Q6. What do you think other groups will think about car use in the future? Will they travel more or less by car?

Travel more Travel less No change

DK

Young people 1 2 3

4

Older people 1 2 3 4 Recent migrants 1 2 3 4 Rural residents 1 2 3 4 Urban/town residents 1 2 3 4

City centre residents 1 2 3 4 Demographics 7.Sex Male Female 8. Age group: 20 and under 21 - 30 30 - 55 55 or more 9. Employment status Full time – travel to work most days 1 Full time – often work from home 2 Part time 3 Student 4 Unwaged 5 Retired 6 If working do you travel during the course of work (apart from commuting)

Yes – more than once a month

Occasionally - 3 to 12 times a year

Rarely – less than twice a year

No never travel during work

1 2 3 4 10. Occupation – now or before retirement

Code

11. Number of adults over 17 in household

Number of people under 17 in household

83

13. Were you born in the UK Yes No If ‘No’ how many years have you been in the UK

Which country were you born in? 14. Postcode (first 4 letters) 15. Type of residential area

Central/urban 1

Suburban 2

Market town 3

Rural village 4

Deep rural 5

16. Type of work/education area

Central/urban 1

Suburban 2

Market town 3

Rural village 4

Deep rural 5

12. Which ethnic group would you place yourself in?

White UK 1 Any other Black background 11

Irish 2 Asian & White 12

White European 3 Asian & Black African 13

Any other white background

4 Asian & Black Caribbean 14

Bangladeshi 5 White & Black African 15

Pakistani 6 White & Black Caribbean 16

Chinese 7 Any other ethnic group 17

Any other Asian background

8

African 9

Caribbean 10 I do not wish to disclose this 19

84

2 APPENDIX B Data and Literature Review

‘On The Move’ Changes in GB Road and Rail Travel Trends Desk-Top Research and Literature Update November 2014

85 ‘On The Move’ Changes in GB Road and Rail Travel

Contents 1 Background to Research ................................................................................... 86

2 Older People ...................................................................................................... 87

2.1 Driving Licence Holders .............................................................................. 87

2.2 Mode of Transport ....................................................................................... 88

2.3 Concessionary travel by older people ......................................................... 90

2.4 Mobility difficulties ....................................................................................... 91

2.5 Car Ownership ............................................................................................ 91

2.6 Interview focus ............................................................................................ 93

3 Black and Minority Ethnic Groups ...................................................................... 95

3.1 BME Groups and Car Ownership ................................................................ 98

3.2 BME Groups and Travel to Work .............................................................. 100

4 Migrant Groups ................................................................................................ 103

5 Business Travellers ......................................................................................... 108

5.1 Mode of transport to work ......................................................................... 109

5.2 Regional Differences ................................................................................. 110

6 Appendices ...................................................................................................... 112

Appendix 1: Age and car ownership ....................................................................... 112

Appendix 2: Car Ownership ................................................................................... 114

Appendix 3: Migration data ..................................................................................... 118

Appendix 3a: Detailed migration data to target interviews ...................................... 119

Appendix 4: Areas to which migrants have moved ................................................. 128

Appendix 5: Regional differences in car ownership, by age and sex ..................... 129

Appendix 6: Travel to Work .................................................................................... 136

Appendix 7: Labour force ....................................................................................... 138


1 Background to Research 1.1.1 The Independent Transport Commission's 2013 report series On

the Move found significant changes in travel amongst some groups.

• Men aged over 60 have reduced their annual car mileage and car use. • Women aged between 50-59 showed the largest increases in car

mileage. • Male car driving mileage is particularly affected by declining company

car ownership leading to a switch to rail for business travel. • London has patterns of travel distinct from the rest of GB. • People born in the UK drive more than those born abroad. • The growth in rail mileage is due to an expanded market base.

1.1.2 With the support of ORR and DfT, the ITC is moving into a more detailed investigation of the changes highlighted in the original report, so that planners and service providers can respond to changing demand, including incorporating the findings in national rail and road forecasting models. This investigation was conducted in a short time, as a preliminary to social research in-depth work, and is not intended as a comprehensive evaluation of all research and data available, more as an effort to find key points to help in the design of survey work.

1.1.3 There appears to be very little substantial research on changing travel patterns in the UK, particularly those associated with black and minority ethnic and migrant groups. The main sources for this desk-top research are therefore, the National Travel Survey (NTS) and the UK Census data (2001 and 2011). The NTS is the primary source of data on personal travel patterns in Great Britain. It is an established household survey which has been running continuously since 1988. It is designed to monitor long-term trends in personal travel and to inform the development of policy. The survey collects information on how, why, when and where people travel as well as factors affecting travel (e.g. car availability and driving licence holding). Since 2002, the Department for Transport (DfT) has commissioned the National Centre for Social Research to conduct the survey fieldwork. Data collection consists of a face-to-face interview and a 1 week self-completed written travel diary. In 2013, the survey coverage changed from sampling residents of all Great Britain to residents of England only.


1.1.4 This report will concentrate on demographic groups who have been identified through previous research as being under-represented in national car and rail forecasting models. These groups are:

1. Older people 2. Migrants 3. Minority ethnic groups 4. Business Travellers

1.1.5 The main objective of this desktop study is to describe shifting travel patterns as far as possible, and the secondary objective is to highlight geographical areas where there are concentrations of high car use amongst the groups of interest in order to target the qualitative and quantitative research phases.

2 Older People 2.1.1 The 2011 census reveals that 16 per cent (9.2 million) of the

population of England and Wales were aged 65 and over; this proportion was the same in 2001 (8.3 million). 90 per cent of those aged 65 and over were economically inactive in 2011. This included 86 per cent who were retired and 3.6 per cent ‘Other inactive’ (looking after home or family, long term sick or disabled, or economically inactive students). The remaining 10 per cent were economically active; the majority of these were working. The proportion of those aged 65-74 who were economically active in 2011 (16 per cent) was almost double that in 2001 (8.7 per cent), a rise in those economically active of 413 thousand people over the decade. The increased proportion of those aged 65-74 economically active reflects the larger number of older people who had continued to work beyond age 65 (ONS, September 2013).

2.1 Driving Licence Holders

2.1.1 The National Travel Surveys (1998/2000/2012) show that the proportion of adults surveyed who held a full driving licence was quite high for older age groups, dropping off for those aged 70+. It shows that the number of older drivers has increased steadily over this time period with those in the oldest category increasing from 40% of all those surveys holding a full licence to 72% in 201


2.1.2 The table below also shows that drivers in these older age categories are dominated by males for all time periods shown. However, the number of older women holding full driving licences has increased from 1998/2000 to 2013, with numbers in the oldest category (70+) more than doubling in this time period.

2.1.3 Note: The National Travel Survey from January 2013 covers England residents only. Therefore, the 2012 results presented are the final set for Great Britain as a whole.

Table 1 Full car driving licence holders (% in Great Britain)

1998-2000 (%) 2010 (%) 2012 (%) 50-59 60-69 70+ 50-59 60-69 70+ 50-59 60-69 70+ All adults 77 67 39 83 79 57 82 79 58 Males 88 83 65 90 89 78 89 89 79 Females 67 53 22 77 69 41 75 70 42

2.1.4 As table 1 shows, over the long term there has been an increase in the proportion of both males and females holding a full driving licence for older age groups. Between 1998/2000 and 2012 the proportion of people aged 70+ holding a licence increased from 39% to 58%. The increase among older women is particularly notable: 70% of women aged 60-69 and 42% aged 70+ held a licence in 2012 compared with 53% and 22% in 19998/2000 respectively. This is due to ageing of existing licence holders rather than large numbers of newly qualified drivers in older age groups (NTS 2012 Statistical Release).

2.1.5 The main reasons given in 2012 for not learning to drive for the over 60s were ‘not interested in driving’ (32%), ‘friends and family can drive me’ (18%), ‘safety concerns/nervous about driving’ (13%), ‘too old’ (13%) and ‘physical difficulties/health problems’ (7%).

2.2 Mode of Transport

2.2.1 During this same period, the main mode of transport used for older people was by car as a driver, followed by walking and then car as a passenger. The graphs below (figures 1 and 2) illustrate this. Some variations are also apparent between men and women as up to the age of 50 women made more trips on average than men of the same age, but after the age of 50 men made more trips than women. Bus use was higher for those in the oldest groups, particularly among females, reflecting the availability of concessionary bus travel for older passengers and differences in driving licence holding across age groups.


Figure 1 % Trips by Main Mode Great Britain 1998/2000

Figure 2 Figure 2: % Trips by Main Mode Great Britain 2012

2.2.2 The amount of trips broadly increases with age up to 40-49 and then decreases among older age groups. 58% of trips by men aged 70+ were made as car drivers compared with 25% amongst women in this age group (NTS 2010).

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2.3 Concessionary travel by older people

2.3.1 The Transport Act 2000 required all local authorities in England to provide a minimum standard of a half fare for women aged 60+, men aged 65+ and disabled persons. From 1 April 2003, the eligible age for these schemes was equalised to 60+ for men and women. From 1 April 2006, free local concessionary bus travel was introduced in England for disabled passengers and those aged 60+ within their local area and from April 2008 this was extended to cover bus travel throughout England. From April 2010 the eligibility in England for men and women is equivalent to the pensionable age for women, therefore gradually increasing. In Scotland and Wales the eligibility remained at aged 60 for men and women.

2.3.2 The proportion of eligible older people with a concessionary travel pass in Great Britain increased following the introduction of the minimum standard of a half fare. From 1998/00 to 2002 take-up rates among men 65+ and women 60+ increased from 49% to 58%. There was a further increase in take-up in 2006 to 62% which was associated with the introduction of free local concessionary bus travel in England and this continued to increase year-on-year until it started to level off in the last couple of years. In 2012, 79% of eligible older people had a pass (82% of females and 74% of males) (NTS 2012).

2.3.3 There is considerable variation between area types with take-up ranging from 66% in rural areas to 87% in London in 2012.

Table 2 Take-up rates for concessionary fares for pensioners (%)

Area 1998-2000 2012 London boroughs 79 87 Metropolitan built-up areas 72 84 Large urban area (population over 250k)

44 80

Medium urban area (25-250k) 44 81 Small urban area (3-25k) 39 78 Rural 30 66

Source: National Travel Survey 2012

2.3.4 Corresponding with this increase in take up of concessionary fares, the proportion of people aged 60+ who said they use a local bus at least once a week increased from 32% in 1998/2000 to 40% in 2010. Over the same period the proportion of people in this age group who said they use a bus less than once a year or never fell from 42% to 32%.


Table 3 Frequency of bus use for those aged 60 years and over: Great Britain, 1998/00 to 2010 (NTS web table NTS0621).

Year Frequency No. 1998/2000 At least once a week 32 At least once a month 11 At least once a year 15 Less than once a year or never 42 2006 At least once a week 32 At least once a month 11 At least once a year 12 Less than once a year or never 45 2010 At least once a week 40 At least once a month 15 At least once a year 13 Less than once a year or never 32

2.4 Mobility difficulties

2.4.1 The NTS asks adults (aged 16+) whether they have difficulty going out on foot or using bus services. Those who say they have difficulties travelling on foot, by bus or both are classified as having mobility difficulties. The proportion of adults with mobility difficulties increases greatly with age. Overall, 11% of adults in England reported having a mobility difficulty in 2013. 31% of individuals aged 70+ had problems walking or using a bus, compared with 3% of those aged 16-49. This increase with age is more marked among women than men, although the proportion of women 70+ with mobility problems may be increased by the higher number of women living to very old age. Those reporting mobility difficulties make fewer trips, on average, across all age groups.

2.5 Car Ownership

2.5.1 The 2001 and 2011 census provide data on car ownership by age. This shows that the proportion of people not owning a car is greatest amongst the oldest age groups (65+) for both years, but the incidence of not owning a car has declined between the two periods. Ownership of one car has also increased for each age group over this time except for 60-64 year olds who have seen an 8% drop in owning one car from 2001 to 2011 and a 12% increase in owning two. Ownership of 2 cars has also increased for each age group, most notably after the 60-64 year olds, in the 65-74 group. Appendix 1 shows a detailed breakdown of car ownership by age and gender.


Table 4 Percentage comparison of car ownership between 2001 and 2011

60-64 65-74 75-84 85+

2001 2011 2001 2011 2001 2011 2001 2011

0 cars/van 18 14 23 19 48 35 45 701 car/van 50 42 52 52 42 51 46 242 cars/vans 32 44 25 29 10 14 9 6Total 100 100 100 100 100 100 100 100

Figure 3 Car ownership by age (2001 census)

Figure 4 Car ownership by age (2011 census)

0

500000

1000000

1500000

2000000

50‐54 55‐59 60‐64 65‐74 75‐84 85+Age

No cars/vans

1 car/van

2 or more cars/vans

0

500000

1000000

1500000

2000000

2500000

3000000

50‐54 55‐59 60‐64 65‐74 75‐84 85+

Age

No cars/vans

1 car/van

2 or more cars/vans


2.6 Interview focus

2.6.1 Looking at areas which are likely to provide interview respondents for the On the Move research, Appendix 5 shows regional differences in car ownership by age and sex in the over 50s age groups. The data are based on whether or not there is a car in the household, since an individual does not need to be a driver, or the main driver, to have car as their main method of transport. The data show that car availability amongst women is slightly but not greatly lower than amongst men in all regions across the whole 50+ population. Car availability corresponds with a range of influencing factors, principally income and the availability of alternatives. Predictably, then, London has the lowest proportions of both men and women with a car or van in the household. The North East has the next lowest.

2.6.2 The more complex graphs in Appendix 5 separating out the different over 50 age groups shows very little variation among men up to the age of 75. The profiles of car availability among those aged 50 to 54, 55 to 59, 60 to 64, 65 to 69 and 70 to 74 are very similar to the profile for voer 50s overall. Car availability then falls in each successive five year age band. The profiles betwen regions are broadly similar to the overall profile, though they flatten a little, with male Londoners in older age groups not showing as sharp a difference in car availability as in the under 75s, perhaps because of historic car ownership. The other interesting variation is that car availability amongst men in the 80+ group is far higher, proportionally, in the South East and South West than the usual regional profile would lead us to expect: SRA's previous research has shown better health and higher incomes amongst older people in the South East, and it may be that the South West's offer of alternatives is lower than in some other regions.

2.6.3 The availability of cars to women has a more varied picture. Those aged 50 to 64 have higher car ownership than the average for women over 50. The 65-69 group reflects the closest to the average, and then car availability sinks steeply for each successive five year age band. Women over 85 typically are about half as likely to live in a household with a car or van available as women over 50 on average. These findings probably reflect historic car use behaviours. As with older men, car availability in London, the South East and South West is higher amongst the most elderly women than the typical regional profile.


2.6.4 The graph below shows the analysis of difference between car ownership amongst men and women over 50. This is designed to help target the research interviews, but also illustrates the truth of a broadly held perception, that relative car ownership changes steeply with age. Overall, the male car availability figure is 5%age points higher in the North East than the female, whilst the figures are quite similar for London. In the 50-54 age group, men and women are almost equally likely to have a car in the household, and in the South West the difference in negligible. At 55-59, the only region with a marked difference, but still below 5%age points, is the North East. By the age of 80 to 84, car availability amongst women is 25%age points lower than amongst men, except in London. In the oldest age group, the difference is slightly less stark, partly because car ownership amongst men aged over 85 is also quite low. The highest difference, however, is in the highest car-owning regions, South East and South West, suggesting relative mobility deprivation for very elderly women in these regions.

Figure 5 Proportions of men than women with one or more cars or vans

2.6.5 In terms of finding interview subjects who mainly use cars, the South West and South East still have the highest proportions of older women in car owning households, with the North West, West Midlands and East regions next, and the South East and South West for older men.

Higher proportions of men than women living in a household with one or more car or van

0%

5%

10%

15%

20%

25%

30%

All

Age 5

0 to

54

Age 5

5 to

59

Age 6

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64

Age 6

5 to

69

Age 7

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74

Age 7

5 to

79

Age 8

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84

Age 8

5 an

d ov

er

North East

North West

Yorkshire and TheHumberEast Midlands

West Midlands

East

London

South East

South West


2.6.6 This analysis is too broad-brush to target interviews closely, so Appendix 5 closes with rather dense tables showing the local areas with the highest proportions of car owners, men and women, in each age group. A summary of these is given below: these local areas offer the likeliest chance of finding car using respondents in older age groups, both men and women.

Table 5 The highest car areas

Hart, Hampshire Waverley (Surrey)East Dorset Mole Valley Malvern Hills New Forest South Bucks

3 Black and Minority Ethnic Groups

3.1.1 In 2011 the majority of the UK population described themselves as belonging to the White ethnic group (87 per cent or 55 million). The remaining 13 per cent (8.1 million) belonged to a minority ethnic group, representing one person in eight of the UK population. The Asian / Asian British (including Chinese) ethnic group accounted for 7 per cent of the UK population (4.4. million people). The other minority groups were Black / African / Caribbean / Black British (3 per cent), Mixed (2 per cent), and Gypsy / Traveller / Irish Traveller / Other groups (1 per cent). Figure 5 shows the proportion of each ethnic group for the UK, comparing figures for both the 2001 and 2011 census.

3.1.2 Between 2001 and 2011, the proportion of the population identifying as White British and White Irish decreased. The remaining White ethnic groups increased; the Any Other White group had the largest increase of 1.1 million people (1.8%).


Figure 6 Ethnic Groups 2001-2011 England and Wales

Source: Census 2001 and 2011, Office for National Statistics)

1. Comparability issues exist between these ethnic groups for the 2001 and 2011 Census

2. No comparable data exists for these ethnic groups in 2001 Census

3.1.3 Table 6 below shows the top 5 regional locations by percentage of ethnic population for 2011. This shows that London has the highest concentration of all ethnic minority groups (except Gypsy/Irish travellers which seem to be most concentrated in the South East) with 40 per cent of residents in London identifying themselves as belonging to a minority ethnic group (ONS Key Statistics, October 2013).

3.1.4 The West Midlands was the second most diverse area with the White ethnic group at 79.2%. Wales was the least diverse area, followed by the South West and North East. Over 95% of the population identified as White in these areas.


3.1.5 The local authorities with the highest proportions of White British were Redcar & Cleveland and Allerdale at 97.6% each. The lowest proportions of White British were found in Newham (16.7%). Kensington & Chelsea had the highest percentage of people indentifying with Any Other White at 28.9%. Leicester had the highest percentage of those reporting to be Indian at 28.3%.

Table 6 Top 5 regional locations by percentage of ethnic population (2011)

Mixed/Multiple Asian/Asian British

Black/African/ Caribbean/Black British

Gypsy/Irish Traveller

Other

London (5%) London (18.5%)

London (13.3%) South East (0.2%)

London (3.4%)

West Midlands (2.4%)



All other regions (0.1%)


East (1.9%) Yorkshire & The Humber (7.3%)

East (2%) Yorkshire & The Humber (0.8%)

East Midlands (1.9%)



East Midlands/North West/South East 0.6%)

South East (1.9%)

North West (6.2%)

South East (1.6%)

3.1.6 An interactive map (census data 2011) showing the concentrations of different ethnic groups in England and Wales can be found at:

http://www.ons.gov.uk/ons/rel/census/2011-census/key-statistics-for-local-authorities-in-england-and-wales/sty-enthnicity-in-england-and-wales.html

3.1.7 A similar (though less diversity shown) map for Scotland can be found at:

http://www.scotlandscensus.gov.uk/ods-web/datavis.jsp?theme=Ethnicity_v3_November_2013&selectedWafers=0


3.1 BME Groups and Car Ownership

3.1.1 A question about ethnicity was first asked in the National Travel Survey in 2001. Data from the 2010 survey showed that the proportion of adults (aged 17+) living in a household with a car was highest among those from White and Asian backgrounds, in particular, those from White British (83%), Pakistani (83%) and Indian backgrounds (81%). Adults from Black backgrounds were least likely to live in a household with a car (59%). A higher proportion of Asian adults were non-drivers (25%) compared with White adults (12%).

3.1.2 The variation in car availability contributes to differing travel patterns across ethnic groups. In 2007/10 (4 years of combined data) on average, adults from a White background made the most trips (1,023 trips per person per year), compared to 865 trips by those from an Asian background, and 859 trips by those from a Black background. However, travel differences between ethnic groups may to some extent be a result of the distributions of these populations between urban and rural areas.

3.1.3 Table 7 below compares personal car access for ethnic groups in Great Britain from 2002 and 2012 (NB data was not collected for mixed ethnic groups and Black groups in 2002). These figures show that for the groups collected for both time periods, levels of car access has remained relatively stable, with only very slight decreases shown for ethnic groups compared to a very slight increase for white populations.

Table 7 Personal car access for ethnic groups in Great Britain 2002 and 2012

2002 2012 Adults in household with a car/van

Adults in household with a car/van

White 80 81 Asian/Asian British 73 71 Other ethnic groups 61 59 Mixed/multiple ethnic groups 67 Black/African/Caribbean/Black British

59

(Source: NTS 2002, 2012)


3.1.4 A more detailed breakdown within ethnic groups is given below. The figure below shows the proportions of households in each ethnic group with no car or van, 1, or 2 or more1. Across the whole population, just under 20% of households have no car or van, 39% have 1 car or van and 41.4%, the largest proportion, have 2 or more cars or vans. That is quite remarkable given that 30% of households are one-person households2.

Figure 7 Cars or vans in household, comparison between ethnic groups

3.1.5 Given that the group 'White UK' dominates the population, the figures for this group reflect the overall averages. There are differences, however: fewer White UK households have no car (16.8% White UK, 19.5% overall); fewer have 1 car or van (37.8% / 39%), and more households have 2 or more cars (44.1% compared with 41.4% overall).

3.1.6 The relatively high car ownership for White UK might lead us to expect that all other groups would have lower ownership, but it is not quite the case:

Asian/Asian British Indian households have a very similar car

ownership profile to White UK: 17.6% no car, 37.9% 1 car and 44.5%

two or more cars or vans.

1 DC4203EW ‐ Tenure by car or van availability by ethnic group [tenure not analysed, though it would provide social context ‐ d'you want it?][We also have this by region ‐ I just haven't drawn pics of it yet.] 2 DC4404EW ‐ Tenure by household size by number of rooms (tenure/rooms not analysed for this report).

Cars or vans %, by ethnic group

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Asian/Asian British Pakistani households are exactly as likely to have

no car as White UK, 16.8%, but far more have just one car or van, at

45.5%, with 37.6% having two or more.

'Other Asian' households have the next nearest vehicle ownership

profile at 26.2% / 45.2% / 22.6%, but already this is quite a gulf from

the White UK figure.

Black groups have the highest proportion of no car households, Black

African 42.2%, Black Caribbean 39.4% and Other Black 45.8%.

Single car ownership in these groups is barely higher than the overall

average and 2+ cars or vans below 20%.

Over a third of Asian/Asian British Chinese, and 'Other' households

have no car, and these groups have low 2+ vehicle ownership,

Over a third of 'Other White' households have no car, but over 50%

have 1 car or van.

3.1.7 These data tend to confirm the findings of the earlier On the Move reports. There is probably a compounding effect, however, as we have seen that migration to London predominates and no-car households are far higher in London than elsewhere because of the high availability of alternatives.

3.1.8 Appendix 2 contains data tables on car ownership by ethnic group and an analysis of which wards have the highest concentration of each BME group in car-owning households.

3.2 BME Groups and Travel to Work

3.2.1 In the 2011 census, the distance travelled to work by ethnic group was also recorded. Figure 8 shows the distances travelled as percentages of the total number captured in each ethnic group (e.g of all Asian people captured in this census, 18% of them travelled less than 2km to work). The data shows that the greatest proportion of black and other ethnic groups travelled 5-10km to work compared with the greatest proportion of white respondents who travelled 2-5km. More other ethnic groups, black and Asian respondents travelled further than the white population.


Figure 8 Distance Travelled to Work by Ethnic Group

3.2.2 Since travel patterns vary within the broad ethnic groupings above, the figures below show a breakdown.

Figure 9 Distance to work: White UK

0

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74.0%

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All <10km 10km <>30km 30km < Mainly at home Other


Figure 10 Distance to work: Excluding White UK

3.2.3 The figures above are %ages of all people travelling each distance - so 'White UK' is just over 80% of those travelling less than 10km, 'Other White' 6%, Asian 7%, etc. It is best to consider the two graphs above together. The tables are split because 'White UK' is so dominant a group that it overpowers everything else and makes it appear that there are no distinctions. The close up view provided by separating out the graphs shows:

White UK are just over 80% of the Travel To Work (TTW) population

but 84% of the 30km+ and very low on 'other' and lowish on short

distances.

White Irish, Other White, Black and Other are high on 'other' - which

presumably includes commuting from outside the UK.

Asian, 'Other White' and Black are less likely to travel 30km+ to work;

Asians slightly higher than their 'all' figure on short journeys.

Figure 11 Method of travel to work, by ethnic group

Distance to work: excluding white UK

0.0%1.0%2.0%3.0%4.0%5.0%6.0%7.0%8.0%9.0%

10.0%

White Irish Other White Mixed/multipleethnic group

Asian/AsianBritish

Black/BlackBritish

Other

All

<10km

10km <>30km

30km <

Mainly at home

Other

Mode to work %

0%

10%

20%

30%

40%

50%

60%

Work mainly ator from home

Train,underground,

metro, light railor tram

Bus, minibusor coach

Driving a caror van

Passenger ina car or van

Bicycle On foot All other

All White Multiple ethnic Asian/Asian British Black/Black British Other


4 Migrant Groups

4.1.1 Over 85% of people living in England were born here. 12% of those born outside the UK are students, many of whom will be temporary residents.

4.1.2 London has by far the highest proportion of residents born outside the UK, almost 37%, though many will be students. The North East, South West, North West and Yorkshire and The Humber have the lowest proportions of residents born outside the UK: in each of these regions, over 90% of residents were born in the UK, though some localised areas have higher migration, such as Bradford in Yorkshire and The Humber, where 17% are born outside the UK, and Blackburn with Darwen in the North West, 15%. A quarter of Manchester residents were born outside the UK, though, again, this is a University city.

Figure 12 Proportion born in the UK, by English Region

Born in the UK %

0 10 20 30 40 50 60 70 80 90 100

England

North East

North West

Yorkshire & Humber

East Midlands

West Midlands

East

London

South East

South West


4.1.3 Rates of arrival in England have been accelerating: almost as many migrants now living in England, 1.1m, arrived in 2010-2011 as in each decade from 1960 to 1990 (1.2m each), and more than from the entire period 1941-1960 (note that some migrants from that earlier periods will since have moved away or died, so this is not an absolute reflection of annual migration). The rate of growth has not been constant: the West Midlands had the highest immigration outside London in the post-war period but is now one of the lower migration regions (still with absolutely higher numbers than before; it is the relative rate of attraction which is slower). The East Midlands appears to have relatively mature migration with less acceleration, which may make it a suitable area for interviewing people in settled communities as well as newer arrivals. The South East, by contrast, is seeing more rapid acceleration even than London, with 2007-2011 arrivals outstripping 2001-2006 and equalling the two decades from 1981-2000. Appendix 3 has more detail on this.

4.1.4 In 2011, the top three countries of birth of non-UK born residents in the UK were, in descending order, India, Poland and Pakistan. Since 2001 the number of usual residents born in Poland and living in the UK has increased nearly ten-fold from 61,000 in 2001 (1 per cent of the non-UK born population) to 654,000 (8 per cent of the non-UK born population) in 2011. Poland was the most reported non-UK country of birth in both Scotland (55,000, 15 per cent) and Wales (18,000, 11 per cent), but second in England (561,000, 8 per cent) and Northern Ireland (20,000, 16 per cent). In England the most reported non-UK country of birth was India, and in Northern Ireland it was the Republic of Ireland (32 per cent, 38,000). The local authorities reporting the biggest concentration of Polish born usual residents in 2011 were Ealing, the City of Edinburgh, Haringey, Brent, Hounslow, Birmingham, Barnet, Southampton, Slough and Luton.

4.1.5 Figure 13 shows a comparison of the most reported countries of birth of non-UK born usual residents from the 2001 and 2011 census. This shows a marked decline in residents from the Republic of Ireland and a large increase of those from Poland. Increases also in those from Nigeria and China.


Figure 13 Most reported countries of birth of non-UK born usual residents (%)

4.1.6 Overall the South and South-East of England, Yorkshire and Central and Eastern Scotland had the highest levels of residents who were living outside the UK one year prior to the 2011 census. Table 8 shows the numbers of residents by region who were not living in the UK two years prior to the 2011 census. This shows that London and the South East had the highest concentrations of recent migrants with the East of England, the North West and the West Midlands also having relatively high levels of recent migrants.

Table 8 Numbers resident in the UK less than 2 years

Geography Resident in UK Less than 2 years (No. respondents)

North East 22956 North West 74516 Yorkshire and The Humber 66394 East Midlands 56340 West Midlands 70911 East 85547 London 368529 South East 130673 South West 52159 Wales 27456

0

2

4

6

8

10

12

2001

2011


4.1.7 The local areas within high migrations regions that have the highest proportions of people not born within the UK, and therefore likely to be a good ground for migrant interviews are:

East Midlands: Leicester and Nottingham have the highest

proportions of immigrants, but Wellingborough and Corby may also be

interesting as they have experienced fast growth in recent years.

Nottingham also has high recent arrivals, which may in part be related

to its being a student city.

South East: Slough and Reading are the larger migration areas

(Oxford also is, but has a large student population). Crawley and

Runnymede have experienced fast migration growth since 2001.

London: All Inner London, with Newham having the highest recent

arrivals and Westminster and Kensington & Chelsea having high

migration perhaps of a different type. In Outer London, Brent might be

of interest because it has long standing migrant residents.

West Midlands: Birmingham is interesting because it has a mature

migrant population. Coventry appears to be having the most rapid

recent growth, which may in part be related to the Universities.

East: Luton provides another example of a stable community, with

Cambridge a student area. Watford has high recent arrivals.

4.1.8 Appendix 3 shows the ten local authorities with the highest proportions of the resident population who were living outside the UK one year prior to the 2011 Census as well as the two highest contributor countries for each of these 10 local authorities. Six of these local authorities were in London: City of London and Westminster (6.4%) and Kensington and Chelsea (5.5%) were the two highest, with their two largest contributor countries in both cases being USA and France.


4.1.9 Outside London, cities such as Cambridge (4.6%), Oxford (4.4%) and Edinburgh (3.4%) had high levels, reflecting the high proportions of students in annual inflows to the UK. Forest Heath (Suffolk) also had a high proportion (4.6%), reflecting the presence of foreign Armed Forces (these were mainly US personnel and their families previously stationed in USA and South Korea). Aberdeen’s high levels probably reflect movement of oil industry workers from outside the UK. In Wales, Cardiff had the highest proportion at 1.7% (52nd within the UK). In Northern Ireland, Dungannon had the highest proportion at 1.8% (51st highest area within UK). Appendix 4 shows a map of migrant concentrations as a proportion of the usually resident populations.

4.1.10 On the Move highlighted that people born overseas tend to drive less than people born in the UK. This may correlate with incomers migrating to cities, or living in close communities where local shops cater to their requirements, and it probably varies by country of origin and by wealth - a refugee is less likely to have a car than someone from 'new Europe' (see recommendations section for further discussion of data availability on travel patterns).

4.1.11 The proposal for this current work highlighted differences in travel patterns between long established minority ethnic communities and newcomers, and between migrants from different countries and cultures.


5 Business Travellers

5.1.1 According to the National Travel Survey (2010), the estimated annual business mileage of all 4-wheeled cars fell by 48% from 1,710 miles in 1995/97 to 890 miles in 2010. For company-owned cars only, business mileage fell from 11,890 in 1995/97 to 7,490 in 2010. Business trips are defined as those made in the course of work, provided that the purpose of the trip is for the traveller to reach a destination. They do not include commercial travel, such as trips to deliver goods, or to convey a vehicle or passenger - these types of trips are not covered by the NTS. Just 3% of trips were for business purposes in 2013, however they accounted for 9% of all distance travelled.

5.1.2 In 2012, the average number of business trips per person in Great Britain was 31, travelling 606 miles. Both the number of business trips made and the distance travelled on business trips were lower in 2012 than the comparative figures for 2002 when the average number of trips per person was 34 and the miles travelled per year was 683. The drops in these figures occurred after 2007; around the time that the financial crisis occurred (NTS 2013).

5.1.3 In the NTS a commuting trip is defined as a trip from home to work, or from work to home. In 2012, 15% of trips were for commuting, while 20% of the average distance travelled per person per year was for commuting purposes. Since 1995/97, the average number of trips and average distance travelled per person per year has decreased by 12% and 4%, respectively. Commuting trips have seen a larger decrease than the average with falls of 16% and 8%, respectively.

5.1.4 On average, in 2012 a person made 146 commuting trips, travelling 1,318 miles. In 2013, for England only, these figures were 145 and 1,279. These figures are 18% and 11% lower respectively, than the same figures for 1995/97. The decrease in commuting trips has been a large contributor in the 16% fall in all trips recorded between 1995/97 and 2013. Part of this decrease is likely to be related to the increase in the proportion of people who work at home and changes in employment status.


5.1.5 Men tend to make both more commuting and business trips than women, on average making 165 commuting trips and 38 business trips per person per year in 2013, compared with 126 and 22 respectively for women. This is likely to be a result of a higher proportion of women working from home compared with men and the higher employment rate for men. Men also travel almost twice the commuting distance that women travel in a year – 1,692 miles compared with 879 miles - and over 3 times the business trip distance that women travelled – 956 miles compared with 295 miles per person per year in 2013.

5.1 Mode of transport to work

5.1.1 Most commuting and business trips are made by car. In the 2011 Census, 15.3 million people (57.5 per cent) travelled to work by driving a car or van. Walking was the next most common choice, followed by bus and then train. Figure 8 shows the method of transport used by commuting passengers in 2011.

Figure 14 Method of Travel to Work

(Source: ONS 2011 census analysis)

0

10

20

30

40

50

60

70

Percent


5.1.2 Between 2001 and 2011, driving to work decreased by 0.8 percentage points and commuting to work as a passenger decreased by 1.3 percentage points. In 2001, London had by far the lowest driver rate at 33.5 per cent. This had reduced to 26.1 per cent by 2011. The North East experienced the largest growth in workers who drove to work during this time period (ONS, 2011 travel to work census analysis). Commuting by public transport increased between 2001 and 2011, although commuting by bus or coach saw a slight decrease as shown in table 9.

Table 9 Public transport commuters, 2001 to 2011 (England and Wales)

Percentages 2001 2011 Percentage Point Change Public Transport 14.5 15.9 1.4

Light Rail 3.0 3.8 0.8 Train 4.1 5.0 0.9 Bus or Coach 7.4 7.2 -0.2

Source: 2001 and 2011 Census - Office for National Statistics

5.2 Regional Differences

5.2.1 Residents in the East of England commuted further than residents of any other English region in 2011, on average commuting 1,672 miles per person per year – 377 miles further than the average for England. They also travelled further for business compared with any other region, travelling 807 miles per person per year on average – 207 miles further than the England average. People living in the North East travel less distance for commuting than any other region (1,044 miles per person per year) which may be partly related to the fact that they also make the fewest commuting trips on average (140 per person per year). Residents of London make more commuting trips than residents of any other region, making on average 153 trips per person per year. However, residents of London travel the least distance for business. Looking at the difference between urban and rural areas, residents of more rural areas tend to commute further than those in urban areas. They also travel further for business and make more business trips on average.


5.2.2 Figure 15 shows the average distance commuted by workers resident in the nine English regions and Wales in 2001 and 2011. In both years, workers resident in the East of England had the longest average commuting distance (16 km in 2001 and 17 km in 2011). With the exception of workers resident in the North East and London, elsewhere the average distance commuted to work increased by at least 1 km. At 11 km, London residents had the lowest average commuting distance in 2011. This was up 0.9 km on the 2001 figure. Given that a large proportion of workers living in London also work in London it is unsurprising that commuting distances are shortest in this region.

Figure 15 Average Distance Travelled to work English regions and Wales 2001 and 2011

(Source: 2001 and 2011 census)

0 5 10 15 20

North East

North West

Yorkshire & The Humber

East Midlands

West Midlands

East of England

London

South East

South West

Wales

Distance (km)

2011

2001

112

6 Appendices

Appendix 1: Age and car ownership The following tables show the breakdown of car ownership by age and sex.

Table 10 Males (2001 – England and Wales)

Age No cars or

vans in household

1 car or van in household

2 or more cars or vans in household

Age 50 to 54 194,637 643,013 931,265 Age 55 to 59 169,597 585,980 701,460 Age 60 to 64 179,550 600,675 461,089 Age 65 to 74 400,330 1,171,816 452,089 Age 75 to 84 387,754 623,236 121,235 Age 85+ 136,762 90,950 18,921

Table 11 Females (2001 – England and Wales)

Age No cars or

vans in household



Age 50 to 54 230,484 676,769 896,147 Age 55 to 59 223,186 656,694 608,848 Age 60 to 64 270,008 662,199 356,592 Age 65 to 74 794,795 1,173,731 329,007 Age 75 to 84 977,759 588,640 107,613 Age 85+ 422,992 108,818 32,604

Table 12 Age structure

Age Structure 2001 Total value percent Age 60 to 64 2,544,754 4.9 Age 65 to 74 4,367,032 8.4 Age 75 to 84 2,933,337 5.6 Age 85 to 89 676,678 1.3 Age 90 and over 335,727 0.7

113

Table 13 Males (2011 – England and Wales)

Age

All categories: Car or van availability

No cars or vans in

household



All categories: Age 27,084,300 4,757,705 10,565,041 11,761,554Age 50 to 54 1,773,400 227,002 581,754 964,644Age 55 to 59 1,562,383 195,394 540,524 826,465Age 60 to 64 1,646,600 198,436 663,817 784,347Age 65 to 69 1,289,126 163,072 625,155 500,899Age 70 to 74 1,021,612 159,281 569,173 293,158Age 75 to 79 790,435 153,744 471,826 164,865Age 80 to 84 533,353 145,963 312,371 75,019Age 85 and over 369,226 165,307 171,004 32,915

Table 14 Females (2011 – England and Wales)

Age

All categories: Car or van availability

No cars or vans in

household



All categories: Age 27,986,813 5,913,611 10,917,805 11,155,397Age 50 to 54 1,807,856 243,291 600,071 964,494Age 55 to 59 1,603,262 219,826 598,066 785,370Age 60 to 64 1,711,761 256,693 768,925 686,143Age 65 to 69 1,367,040 257,440 703,594 406,006Age 70 to 74 1,134,217 305,628 606,223 222,366Age 75 to 79 949,847 359,771 470,282 119,794Age 80 to 84 739,628 390,054 290,540 59,034Age 85 and over 691,154 481,199 168,864 41,091

Table 15 Age structure 2011

Age Structure 2011 Total

value percent Age 60 to 64 3,377,162 6.0 Age 65 to 74 4,852,833 8.7 Age 75 to 84 3,115,552 5.6 Age 85 to 89 825,671 1.5 Age 90 and over 429,017 0.8

114

Appendix 2: Car Ownership Table 16 Car Ownership by Ethnic Group (England & Wales, 2001)

White: British

White: Irish

White: Other White

Mixed: White and

Black Caribbean

Mixed: White and

Black African

Mixed: White and Asian

Mixed: Other Mixed

Asian or Asian

British: Indian

Asian or Asian

British: Pakistani

Cars or vans None 4,978,780 141,414 188,726 21,265 9,352 13,823 15,149 64,263 48,449 1 8,493,131 140,606 235,320 17,561 8,185 18,172 15,525 143,083 87,537 2 or more 5,864,737 75,269 132,134 6,883 3,129 9,643 7,622 107,606 36,524

Asian or Asian

British: Bangladeshi

Asian or Asian

British Other: Asian

Black or Black

British Black:

Caribbean

Black or Black

British: Black

African

Black or Black

British: Other Black

Chinese or Other Ethnic

Group: Chinese

Chinese or Other Ethnic Group: Other Ethnic Group

Cars or vans None 26,627 21,601 125,071 82,621 15,374 22,267 27,401 1 27,879 36,768 112,720 71,434 12,262 34,519 31,664 2 or more 7,433 22,379 37,837 22,381 3,582 20,598 14,169

115

Table 17 Car Ownership by Ethnic Group (England and Wales 2011)

White: Total White: English, Welsh, Scottish,

Northern Irish/British

White: Irish White: Gypsy or Irish Traveller White:

Other White

White: Other White

Mixed/Multiple ethnic group:

Total

All categories: Car or van

20,900,820 19,608,888 299,260 20,462 972,210 301,295

No cars or vans 5,067,920 4,583,458 110,350 7,745 366,367 130,687 1 car 8,857,426 8,322,276 119,591 8,339 407,220 117,384 2 or more 6,975,474 6,703,154 69,319 4,378 198,623 53,224

Mixed/Multiple ethnic group: White and Black Caribbean

Mixed/Multiple ethnic group: White and Black African

Mixed/Multiple ethnic group:

White and Asian

Mixed/Multiple ethnic group: Other Mixed

Asian/Asian British: Total

Asian/Asian British: Indian


109,960 40,803 74,207 76,325 1,229,370 451,408

No cars or vans 51,647 19,587 26,291 33,162 349,936 105,880 1 car 41,475 15,294 30,793 29,822 527,940 183,926 2 or more 16,838 5,922 17,123 13,341 351,494 161,602

Asian/Asian British: Pakistani

Asian/Asian British: Bangladeshi

Asian/Asian British: Chinese

Asian/Asian British: Other

Asian

Black/African/Caribbean/Black British:

Total

Black/African/Caribbean/Black British:

African All categories: Car or van

276,193 104,664 136,155 260,950 731,069 348,226

No cars or vans 64,782 38,086 53,255 87,933 353,029 172,306 1 car 128,039 47,404 53,634 114,937 280,678 132,308

116

2 or more 83,372 19,174 29,266 58,080 97,362 43,612 Black/African/Cari

bbean/Black British: Caribbean

Black/African/Caribbean/Black British: Other Black

Other ethnic group: Total

Other ethnic group: Arab

Other ethnic group: Any other ethnic

group


293,367 89,476 203,490 80,658 122,832

No cars or vans 133,954 46,769 88,198 37,610 50,588 1 car 115,713 32,657 78,214 30,526 47,688 2 or more 43,700 10,050 37,078 12,522 24,556 Table 18 People in Households with 1, 2 or more cars (ethnic groups)

Asian/Asian British: Indian Asian/Asian British: Pakistani Asian/Asian British: Bangladeshi Spinney Hills (Leicester) 11397 Washwood Heath (Birmingham) 14553 Coldhurst (Oldham) 4974 Handsworth Wood (Birmingham) 8044 Bordesley Green (Birmingham) 14227 St Dunstan's and Stepney Green 4619 Rushey Mead (Leicester) 7984 Springfield (Birmingham) 12352 Aston (Birmingham) 3639 Stoneygate (Leicester) 7506 Toller (Bradford) 12012 Bromley-by-Bow 3616 Latimer (Leicester) 6776 Sparkbrook (Birmingham) 10741 East India and Lansbury 3578 Coleman (Leicester) 6309 Bradford Moor 10584 Shadwell 3498 Batley East (Kirklees (Huddersfield)) 6259 Manningham (Bradford) 9621 Mile End East 3372 Humberstone & Hamilton (Leicester) 6051 Little Horton (Bradford) 8171 Bethnal Green South 3321 Belgrave (Leicester) 5625 Hodge Hill (Birmingham) 8074 Whitechapel 3152 Rumworth (Bolton) 5111 City (Bradford) 7732 Limehouse 3103 Kenton West (Harrow) 4947 Park (Wolverhampton) 7700 Lozells and East Handsworth 3077 Lady Margaret (Ealing) 4919 Heaton (Bradford) 7682 Biscot (Luton) 2898 Keighley Central (Bradford) 6799 Mile End and Globe Town 2371 Dewsbury West (Huddersfield) 6592 Bethnal Green North 2346 Lozells and East Handsworth 6341

Milkstone and Deeplish (Rochdale) 5483

Dallow (Luton) 5470

117

Black/Black British: African Black/Black British: Caribbean Arab Thamesmead Moorings 4469 Catford South 2428 Sparkbrook 1865 Thamesmead East 2860 Thornton Heath 2363 East Acton 1371 Abbey Wood 2331 Soho (Birmingham) 2020 Burngreave (Sheffield) 1315 Peckham 2137 Handsworth Wood 2008 Hanger Hill (Ealing) 1258 Woolwich Common 2052 Bensham Manor (Croydon) 1984 Golders Green 1230 Stonebridge (Brent) 2047 Woodside (Haringey) 1766 Barnhill (Hillingdon) 1195 Glyndon (Greenwich) 1776 West Thornton 1698 Perivale 1193 Livesey (Southwark) 1770 Lozells and East Handsworth 1682 Childs Hill (Barnet) 1073 Evelyn (Lewisham) 1758 Perry Barr 1677 Nechells 988 Edmonton Green 1718 Stockland Green (Birmingham) 1545 Hendon 988 ... Aston 1525 Handsworth Wood 977 Nechells (Birmingham) 1500 Norbury 1524 Westbourne (Westminster) 973 Moss Side (Manchester) 1492 South Norwood 1519 Princes Park (Liverpool) 957 Selhurst 1518 Stonebridge (Brent) 1470 Asian/Asian British: Chinese Millwall 799 Ladywood 720 Blackwall and Cubitt Town 649 Colindale 594 Bradford 588

118

Appendix 3: Migration data

Table 19 Top ten local authorities for proportion of usually resident population with an address outside the UK one year prior to the 2011 census

Rank

Local authority Resident population

(thousands)

Previously lived abroad (thousands)

% lived abroad

Highest ranking

country of previous

residence

Number

Second highest ranking

country of previous

residence

Number

1 City of London, Westminster 227 14 6.4 USA 2,225 France 1,357

2 Kensington and Chelsea 159 9 5.5 USA 1,522 France 1,057 3 Camden 220 10 4.6 USA 1,420 France 704 4 Cambridge 124 6 4.6 USA 608 China 393 5 Forest Heath 60 3 4.6 USA 1,800 South Korea 129 6 Oxford 152 7 4.4 USA 840 Germany 443 7 Hammersmith and Fulham 182 8 4.4 Australia 1,486 France 823 8 Tower Hamlets 254 10 4.1 USA 836 France 729 9 Islington 206 7 3.6 USA 841 Australia 630 10= Edinburgh 477 16 3.4 India 1,350 China 1,331 10= Aberdeen City 223 8 3.4 Nigeria 873 Poland 608

119

Appendix 3a: Detailed migration data to target interviews Over 85% of people living in England were born here. 12% of those born outside the UK are students from outside the UK, many of whom will be temporary residents3. London has by far the highest proportion of residents born outside the UK, almost 37%, though many will be students (CT0074 is not disaggregated by region).

Table 20 Born in the UK

Table 21 Year of arrival in England

3 CT0074 ‐ Economic activity by year of arrival in the UK by passports held (national), NOMIS

Born in the UK %

0 10 20 30 40 50 60 70 80 90 100

England

North East

North West

Yorkshire & Humber

East Midlands

West Midlands

East

London

South East

South West

England %

0 0.5 1 1.5 2 2.5

Arrived before 1941

Arrived 1941-1950

Arrived 1951-1960

Arrived 1961-1970

Arrived 1971-1980

Arrived 1981-1990

Arrived 1991-2000

Arrived 2001-2003

Arrived 2004-2006

Arrived 2007-2009

Arrived 2010-2011

120

Almost as many migrants now living in England, 1.1m, arrived in 2010-2011 as in each decade from 1960 to 1990 (1.2m each), and more than from the entire period 1941-1960 (note that some migrants from that earlier periods will since have moved away or died, so this is not an absolute reflection of annual migration). Table 22 Date of arrival in the UK, by Region

That figure is too detailed to be easily read, so most of the analysis will be on the regions with higher migration. For completeness, the areas within the low migration regions which have higher migration are shown in the table below.

Date of Arrival %, Regions

0 1 2 3 4 5 6 7 8

1941

1941-1950

1951-1960

1961-1970

1971-1980

1981-1990

1991-2000

2001-2003

2004-2006

2007-2009

2010-2011

South West

South East

London

East

West Midlands

East Midlands

Yorkshire & Humber

North West

North East

England

121

Table 23 Higher migration areas in the low migration regions

Born in the UK %

North East 95.0 Newcastle upon Tyne 86.6 South West 92.3 Bournemouth UA 85.1 Bristol, City of UA 85.3 Swindon UA 87.1 Exeter 88.9 North West 91.8 Blackburn with Darwen UA 85.2 Greater Manchester Met County 88.0 Manchester 74.7 Preston 86.6 Yorkshire and The Humber 91.2 Bradford 82.8 The figure below, then, splits out the year of arrival in the UK into those regions which see most migration. It also consolidates the periods somewhat. The figure keeps the distinction between before 1960 and after, as it is interesting to see that the predominance of London as an attractor has not been a constant: London always had higher migration, but its relative rate of attraction has accelerated over the years. Figure 16 Year of arrival, higher migration regions of England

Further points to note in the figure above: The East Midlands appears to have relatively mature migration with less

acceleration, which may make it a suitable area for interviewing people in settled communities as well as newer arrivals.

Year of arrival %, higher migration regions

0 2 4 6 8 10 12

1941-1960

1961-1980

1981-2000

2001-2006

2007-2011

South East

London

East

West Midlands

East Midlands

England

122

The South East, by contrast, is seeing more rapid acceleration even than London, with 2007-2011 arrivals outstripping 2001-2006 and equalling the two decades from 1981-2000. This is probably partly a reflection of pressure on housing in London: in recent Equalities research (unpublished? the HS2 reports?? Kris?), Social Research Associates recorded a significant uplift between the 2001 and 2011 census in minority communities and social exclusion in the London periphery and Home Counties.

The West Midlands had early migration, with the largest block after London in 1941-1960.

The later arrivals, 2007 to 2011, will include a fair proportion of students and therefore may be of less interest in the interview phase of this research.

Explanatory note: these percentages are of the present population. For example, in the South East region, 87.9% of current residents were born in the UK and are therefore not shown in the above figure; 1% of the present population arrived before 1960 (a graphical error means that pre-1941 arrivals are included in 1941-1960); 2.1% of the present population arrived between 1961 and 1980, and so on up to 3% of the present population having arrived between 2007 and 2011. The same principle applies in the figures below.

The next set of figures and tables are not of interest for general reading but may help target the interviews in the social research phase which this desk research is required to inform. They show, for each region, the main migration areas and the date of arrival into each.

East Midlands:

Leicester and Nottingham have the highest proportions of immigrants, but Wellingborough and Corby may also be interesting as they have experienced fast growth in recent years. Table 24 Higher migration areas within the East Midlands region

Born in the UK % East Midlands 90.1 Derby UA 86.1 Leicester UA 66.4 Nottingham UA 80.5 Corby 86.9 Northampton 83.7 Wellingborough 87.6

123

Figure 17 Date of arrival, higher migration areas within the East Midlands region

South East:

Slough and Reading are the larger migration areas (Oxford also is, but has a large student population). Crawley and Runnymede have experienced fast migration growth in recent years - though Runnymede has a total population of only 80,000 so finding the 10% who have entered the UK since 2001 might be tricky. Table 25 Higher migration areas within the South East region

Born in the UK %

South East 87.9 Milton Keynes UA 81.5 Reading UA 75.2 Slough UA 61.0 Windsor and Maidenhead UA 82.6 Rushmoor 82.4 Oxford 71.5 Elmbridge 81.7 Epsom and Ewell 83.7 Runnymede 83.1 Woking 80.1 Crawley 79.7

Date of Arrival %, East Midlands main migration areas

0 1 2 3 4 5 6 7 8 9 10

1941-1960

1961-1980

1981-2000

2001-2006

2007-2011

Wellingborough

Northampton

Corby

Nottingham UA

Leicester UA

Derby UA

East Midlands

124

Figure 18 Date of arrival, higher migration areas within the South East region

London:

All inner London areas provide enough migrants, established and new, to make good recruiting grounds. Brent might be of interest because of the solid block of earlier migrants. Westminster may provide a different cohort of new migrants, with wealthy arrivals to the UK in recent years, as would Kensington and Chelsea. The other area of notable recent growth is Newham, which is likely to be partly because of the increased density of development with the expansion of the Docklands areas, but also because this is one of the more affordable areas of London and tends to see new waves of migrants. Table 26 Higher migration areas within the London region

Born in the UK %

London 63.3 Inner London 57.8 Camden 57.5 Hammersmith and Fulham 57.2 Haringey 55.4 Kensington & Chelsea 48.4 Newham 46.3 Tower Hamlets 56.9 Westminster 46.7 Outer London 66.9

Date of arrival %, South East main migration areas

0 2 4 6 8 10 12 14

1941-1960

1961-1980

1981-2000

2001-2006

2007-2011Crawley

Woking

Runnymede

Epsom and Ewell

Elmbridge

Oxford

Rushmoor

Windsor and Maidenhead UA

Slough UA

Reading UA

Milton Keynes UA

South East

125

Brent 44.9 Ealing 51.8 Harrow 55.2 Hounslow 56.7

Note that, in Inner London, the area with the highest proportion born in the UK, Lewisham at 66.3%, is still far lower than most of the rest of England. Figure 19 Date of arrival, higher migration areas within the London region

Date of arrival %, London migration areas

0 2 4 6 8 10 12 14 16 18 20

1941-1960

1961-1980

1981-2000

2001-2006

2007-2011 Hounslow

Harrow

Ealing

Brent

Westminster

Tower Hamlets

Newham

Kensington & Chelsea

Haringey

Hammersmith and Fulham

Camden

Inner London

London

126

West Midlands:

Birmingham is interesting because of the mature migrant population. Coventry appears to be having the most rapid recent growth, which may be related to the Universities. Table 27 Higher migration areas within the West Midlands region

Born in the UK % West Midlands 88.8 West Midlands Met County 83.4 Birmingham 77.8 Coventry 78.8 Sandwell 84.1 Wolverhampton 83.6 Figure 20 Date of arrival, higher migration areas within the West Midlands region

Date of arrival %, West Midlands main migration areas

0 1 2 3 4 5 6 7 8

1941-1960

1961-1980

1981-2000

2001-2006

2007-2011

Wolverhampton

Sandwell

Coventry

Birmingham

West Midlands

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East:

Luton provides another example of a stable community, with Cambridge a student area. Forest Heath is an anomaly in terms of this research: the large influx is constant renewals as it has a USAF base, so the travel patterns are likely to have been stable for a long time and to stay that way. Table 28 Higher migration areas within the East region

Born in the UK % East 89.0 Bedford UA 82.4 Luton UA 69.1 Peterborough UA 79.4 Cambridge 70.6 Watford 75.3 Forest Heath (Suffolk) 77.0 Figure 21 Date of arrival, higher migration areas within the East region

Date of arrival %, East main migration areas

0 2 4 6 8 10 12 14 16

1941-1960

1961-1980

1981-2000

2001-2006

2007-2011

Forest Heath (Suffolk)

Watford

Cambridge

Peterborough UA

Luton UA

Bedford UA

East

128

Appendix 4: Areas to which migrants have moved

129

Appendix 5: Regional differences in car ownership, by age and sex Figure 22 2011 Census, table DC4109EWla - Car or van availability by sex by age

Car or van in household

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

North East North West Yorkshireand TheHumber

EastMidlands

WestMidlands

East London South East SouthWest

Men 50+ Women 50+

Men living in households with 1 or more car or van

0%10%20%30%40%50%60%70%80%90%

100%

All men Age 50to 54

Age 55to 59

Age 60to 64

Age 65to 69

Age 70to 74

Age 75to 79

Age 80to 84

Age 85andover

North East

North West

Yorkshire and The Humber

East Midlands

West Midlands

East

London

South East

South West

130

Women living in households with 1 or more car or van

0%10%20%30%40%50%60%70%80%90%

100%

All wom

en

Age 5

0 to

54

Age 5

5 to

59

Age 6

0 to

64

Age 6

5 to

69

Age 7

0 to

74

Age 7

5 to

79

Age 8

0 to

84

Age 8

5 an

d ov

er

North East

North West

Yorkshire and The Humber

East Midlands

West Midlands

East

London

South East

South West

Higher proportions of men than women living in a household with one or more car or van

0%

5%

10%

15%

20%

25%

30%

All

Age 5

0 to

54

Age 5

5 to

59

Age 6

0 to

64

Age 6

5 to

69

Age 7

0 to

74

Age 7

5 to

79

Age 8

0 to

84

Age 8

5 an

d ov

er

North East

North West

Yorkshire and TheHumberEast Midlands

West Midlands

East

London

South East

South West

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Table 29 Proportion of men in households with 1, 2 or more cars or vans

Area Men 50+ Area 60 to 64 Area 65 to 69

Hart 97% Hart 98% East Dorset 98%

South Northamptonshire 96% East Dorset 98% Hart 97%

East Dorset 96% Surrey Heath 97% Broadland 97%

Wokingham 96% Broadland 97% Wokingham 97%

Uttlesford 95% South Northamptonshire 97% South Norfolk 96%

South Bucks 95% South Norfolk 97% East Hampshire 96%

Broadland 95% Wokingham 97% Rutland 96%

Surrey Heath 95% Uttlesford 97% Chiltern 96%

Mid Suffolk 95% Mid Suffolk 96% South Bucks 96%

Chiltern 95% North Dorset 96% Horsham 96%

South Norfolk 95% Horsham 96% North Dorset 96%

South Cambridgeshire 95% Wealden 96% Uttlesford 96%

Harborough 95% Chiltern 96% South Cambridgeshire 96%

East Hampshire 95% South Cambridgeshire 96% Mid Suffolk 96%

Horsham 95% Daventry 96% Wychavon 96%

Wealden 94% Rochford 96% Maldon 96%

Elmbridge 94% West Devon 96% Wealden 96%

Tandridge 94% Bromsgrove 96% Hambleton 96%

South Oxfordshire 94% South Bucks 96% South Northamptonshire 96%

Maldon 94% East Cambridgeshire 96% Babergh 96%

North Dorset 94% East Hampshire 96% South Staffordshire 96%

Waverley 94% Fareham 96% Mole Valley 96%

West Oxfordshire 94% Forest of Dean 96% Cotswold 96%

Bromsgrove 94% Rutland 96% Surrey Heath 96%

Rutland 94% Maldon 96% Sevenoaks 96%

West Devon 94% Stratford-on-Avon 96% West Devon 96%

Mole Valley 94% Cotswold 96% Rochford 96%

Blaby 94% Babergh 96% Elmbridge 96%

Cotswold 94% Harborough 96% Daventry 95%

South Staffordshire 94% South Staffordshire 96% Malvern Hills 95%

Ribble Valley 94% New Forest 96% Harborough 95% Table 30 Proportion of men in households with 1, 2 or more cars or vans

Area 70 to 74 Area

75 to 79 Area

80 to 84

East Dorset 97% East Dorset 96% East Dorset 91%Hart 96% South Bucks 94% Malvern Hills 88%Wokingham 96% Hart 94% South Bucks 88%South Norfolk 96% Chiltern 94% Mole Valley 88%North Dorset 96% West Devon 93% West Somerset 88%

Uttlesford 95% South Cambridgeshire 93% Hart 87%

Mid Suffolk 95% Surrey Heath 93% Horsham 87%South Bucks 95% Wokingham 93% New Forest 87%Maldon 95% Malvern Hills 93% East Hampshire 87%Harborough 95% Waverley 93% North Dorset 87%Chiltern 95% North Dorset 93% Surrey Heath 87%Cotswold 95% Broadland 92% Cotswold 87%Rutland 95% South Norfolk 92% Richmondshire 86%

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South Cambridgeshire 95% New Forest 92% South Norfolk 86%East Devon 95% East Hampshire 92% Ribble Valley 86%East Hampshire 95% Mole Valley 92% South Hams 86%Malvern Hills 95% Ribble Valley 92% Mid Sussex 86%Wychavon 94% Horsham 92% Wokingham 86%Stratford-on-Avon 94% West Somerset 92% Tandridge 86%Wealden 94% Mid Devon 92% Broadland 86%North Kesteven 94% South Hams 92% Wychavon 86%Horsham 94% South Oxfordshire 92% Wealden 85%Suffolk Coastal 94% East Devon 92% Bromsgrove 85%Ribble Valley 94% Eden 92% South Somerset 85%Broadland 94% Maldon 92% South Lakeland 85%West Devon 94% Uttlesford 92% West Devon 85%Surrey Heath 94% Wealden 92% Stratford-on-Avon 85%South Northamptonshire 94% Stroud 91% Daventry 85%

New Forest 94% Rutland 91% South Cambridgeshire 85%

Hambleton 94% South Northamptonshire 91% Waverley 85%

West Oxfordshire 94% Elmbridge 91% Chiltern 85% Table 31 Proportion of men in households with 1, 2 or more cars

Area 85 and over

East Dorset 76%

Malvern Hills 72%

South Bucks 72%

Cotswold 72%

Guildford 71%

South Lakeland 71%

New Forest 71%

South Hams 70%

Elmbridge 70%

Mole Valley 70%

Eden 70%

East Hampshire 70%

Surrey Heath 70%

West Somerset 70%

Waverley 70%

Rutland 70%

East Devon 69%

Dorset 69%

West Dorset 69%

North Dorset 69%

Sevenoaks 68%

Wokingham 68%

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Table 32 Proportion of women in households with 1, 2 or more cars

Area Women 50+ Area

50 to 54 Area

55 to 59

Hart 94% East Dorset 98% Hart 97%

Wokingham 93% Hart 97% East Dorset 97% South Northamptonshire 93%

South Northamptonshire 97% Uttlesford 97%

South Bucks 93% Wokingham 97% Wokingham 97%

Uttlesford 93% Rutland 97% South Bucks 97%

Surrey Heath 92% Mid Suffolk 97% South Cambridgeshire 97%

Chiltern 92% Surrey Heath 97% South Northamptonshire 97%

East Dorset 92% South Bucks 97% North Dorset 96% South Cambridgeshire 92% Uttlesford 97% Horsham 96%

Elmbridge 92% South Norfolk 97% Mid Suffolk 96%

East Hampshire 92% Chiltern 97% Daventry 96%

Mid Suffolk 91% East Hampshire 97% Wealden 96%

Harborough 91% Broadland 97% Surrey Heath 96%

South Oxfordshire 91% Mole Valley 96% South Norfolk 96%

Horsham 91% Bromsgrove 96% Broadland 96%

Mole Valley 91% Wealden 96% Chiltern 96%

Waverley 91% North Dorset 96% Cotswold 96%

Tandridge 91% South Cambridgeshire 96% South Oxfordshire 96%

Broadland 91% Horsham 96% Bromsgrove 96%

South Norfolk 91% East Cambridgeshire 96% Rutland 96%

West Oxfordshire 91% Stratford-on-Avon 96% New Forest 96%

North Dorset 91% Cotswold 96% East Hampshire 96%

East Hertfordshire 91% Harborough 96% Brentwood 95%

Bromsgrove 91% Hambleton 96% Elmbridge 95%

West Berkshire 90% Waverley 96% Maldon 95%

Wealden 90% West Devon 96% Waverley 95%

Buckinghamshire 90% Malvern Hills 96% West Devon 95%

Cotswold 90% Tandridge 96% Harborough 95%

St Albans 90% New Forest 96% South Hams 95%

Daventry 90% Fareham 96% Stratford-on-Avon 95%

Rutland 90% Stroud 96% Eden 95%

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Area 60 to 64 Area

65 to 69 Area

70 to 74

East Dorset 97% East Dorset 95% East Dorset 92%

Surrey Heath 96% Hart 95% Hart 90%

Chiltern 95% Chiltern 94% Malvern Hills 90%

Uttlesford 95% Surrey Heath 93% Chiltern 89%

Wokingham 95% South Northamptonshire 93% Waverley 88%

Hart 95% North Dorset 93% South Bucks 88%

South Bucks 95% East Hampshire 93% Horsham 88%

South Cambridgeshire 95% Maldon 93% Wokingham 88%

North Dorset 95% Wychavon 93% North Dorset 88%

Rutland 95% South Cambridgeshire 93% Cotswold 87%

Horsham 95% Mole Valley 93% Uttlesford 87%

South Northamptonshire 95% Rutland 93% Wealden 87%

East Hampshire 95% South Bucks 93% South Norfolk 87%

Wealden 95% Wokingham 93% New Forest 87%

South Norfolk 95% Horsham 93% Mole Valley 87%

Malvern Hills 95% South Norfolk 93% South Oxfordshire 87%

Harborough 95% Uttlesford 92% East Hampshire 87%

Bromsgrove 95% Mid Suffolk 92% Ribble Valley 87%

Mid Suffolk 95% West Devon 92% East Devon 87%

Hambleton 95% Stratford-on-Avon 92% South Hams 87%

Stratford-on-Avon 95% Waverley 92% South Cambridgeshire 87%

Broadland 94% South Oxfordshire 92% Tandridge 86%

New Forest 94% Wealden 92% Mid Suffolk 86%

West Devon 94% Malvern Hills 92% Rutland 86%

Mid Devon 94% Harborough 92% West Devon 86%

Wychavon 94% Bromsgrove 92% Surrey Heath 86%

Guildford 94% Ribble Valley 92% Guildford 86%

Cotswold 94% Cotswold 92% Richmondshire 86%

Waverley 94% Broadland 92% South Lakeland 86%

Tandridge 94% South Holland 91% Stratford-on-Avon 86%

Mole Valley 94% Elmbridge 91% Mid Devon 86%

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Area 75 to 79 Area

80 to 84 Area

85 and over

East Dorset 84% South Bucks 70% West Devon 45%

South Bucks 81% East Dorset 68% East Dorset 45%

Chiltern 81% Chiltern 68% South Bucks 45%

Hart 80% Elmbridge 68% Mole Valley 44%

Mole Valley 80% Malvern Hills 67% West Somerset 44%

Waverley 79% Guildford 65% Chiltern 44%

Wokingham 79% Mole Valley 65% Tandridge 44%

Malvern Hills 79% East Hampshire 65% Cotswold 44%

Tandridge 79% Hart 64% Waverley 44%

New Forest 79% New Forest 64% Malvern Hills 43%

Horsham 78% Cotswold 64% New Forest 43%

Elmbridge 78% North Dorset 64% North Dorset 43%

Surrey Heath 78% Waverley 63% Elmbridge 43%

North Dorset 78% Wychavon 63% South Hams 42%

Wychavon 78% West Devon 63% Chichester 42%

Cotswold 78% South Lakeland 63% East Devon 42%

Guildford 78% South Hams 62% Wychavon 42%

East Hampshire 78% St Albans 62% Rutland 42%

Uttlesford 78% East Devon 62% South Oxfordshire 41% South Cambridgeshire 77% Wokingham 62% East Hampshire 41%

Surrey 77% Stratford-on-Avon 62% West Oxfordshire 41%

South Oxfordshire 77% South Oxfordshire 62% Windsor and Maidenhead 41%

South Hams 77% Surrey Heath 62% Surrey 41%

Suffolk Coastal 77% West Somerset 62% Stratford-on-Avon 41%

Rutland 77% Surrey 62% South Lakeland 41%

Wealden 77% Buckinghamshire 62% Hart 41%

Stratford-on-Avon 77% North Norfolk 61% Hambleton 41%

Buckinghamshire 76% Richmondshire 61% Guildford 41%

Dorset 76% Dorset 61% Wokingham 41%

South Lakeland 76% Horsham 61% Torridge 40%

East Devon 76% South Somerset 61% West Dorset 40%

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Appendix 6: Travel to Work This series of tables is derived from NOMIS WU01EW - Location of usual residence and place of work by sex (MSOA level). The table below shows, not surprisingly, that most people work in the region in which they live. There are significant regional differences, however. In the East, South East and East Midlands especially, 10-20% work outside the region. There is permeability of work across the midland and northern regions and London is not always the main draw - indeed, almost 10% of working London residents work travel out of the region for work. That said, a larger proportion of East and South East residents travel into London to work than the proportions travelling anywhere outside their region in the North East, North West and Yorkshire and The Humber. It is the East Midlands that is the unusual case, here, with quite large proportions of out-commuting and London as the 7th ranked work destination. Table 35 Workplace of all residents

I live here I work here too

Next work region

3rd work region

4th

Work in London rank

North East 95.6% 1.78% Y&H 0.49% Scotland 0.47% N. West 0.38% 5th North West 95.6% 0.97% Y&H 0.78% W. Mids 0.76% Wales 0.38% 5th Yorkshire and The Humber 94.3% 1.77% E. Mids 1.43% N. West 0.71% N. East 0.35% 6th East Midlands 87.3% 3.15% W. Mids 2.76% Y&H 2.30% East 1.00% 7th West Midlands 92.8% 2.32% E. Mids 1.26% NW 0.99% S. West 0.69% 6th East 82.8% 13.36% London 2.16% S. East 0.87% E. Mids London 91.4% 4.75% S. East 2.89% East 0.22% S. West South East 84.6% 11.92% London 1.32% East 1.05% S. West South West 94.1% 2.93% S. East 0.98% London 0.77% W. Mids

The next three tables are from the same data source. The first two show where the men and women in each region travel to work, and the third contrasts these data. Table 36 Workplace of male residents


Next work region

3rd work region

4th

Work in London rank

North East 93.8% 2.43% Y&H 0.81% Scotland 0.65% N. West 0.45% 6th North West 94.1% 1.23% Y&H 1.10% Wales 0.99% W. Mids 0.50% 7th Yorkshire and The Humber 92.6% 2.32% E. Mids 1.80% N. West 0.83% N. East 0.46% 6th East Midlands 84.6% 3.94% W. Mids 3.21% Y&H 2.77% East 1.32% 6th West Midlands 90.6% 3.10% E. Mids 1.60% NW 1.23% S. West 0.85% 6th East 78.6% 16.21% London 2.83% S. East 1.17% E. Mids London 89.8% 5.64% S. East 3.46% East 0.26% S. West South East 80.3% 15.13% London 1.78% East 1.32% S. West South West 92.1% 3.83% S. East 1.33% London 0.98% W. Mids

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Table 37 Workplace of female residents


Next work region

3rd work region

4th

Work in London rank

North East 97.3% 1.16% Y&H 0.32% London 0.30% N. West North West 97.0% 0.72% Y&H 0.57% W. Mids 0.44% Wales 0.26% 5th Yorkshire and The Humber 96.0% 1.24% E. Mids 1.06% N. West 0.60% N. East 0.24% 5th East Midlands 90.1% 2.36% W. Mids 2.31% Y&H 1.84% East 0.68% 7th West Midlands 94.9% 1.55% E. Mids 0.92% NW 0.75% S. West 0.53% 5th East 86.9% 10.52% London 1.49% S. East 0.58% E. Mids London 93.2% 3.83% S. East 2.30% East 0.18% S. West South East 88.9% 8.75% London 0.87% East 0.79% S. West South West 95.9% 2.07% S. East 0.63% London 0.57% W. Mids

Table 38 Comparison of travel to work by men and women

Working in own region All Men Women Difference

North East 95.6% 93.8% 97.3% 3.5% North West 95.6% 94.1% 97.0% 2.9% Yorkshire and The Humber 94.3% 92.6% 96.0% 3.3% East Midlands 87.3% 84.6% 90.1% 5.4% West Midlands 92.8% 90.6% 94.9% 4.3% East 82.8% 78.6% 86.9% 8.2% London 91.4% 89.8% 93.2% 3.4% South East 84.6% 80.3% 88.9% 8.6% South West 94.1% 92.1% 95.9% 3.8% 90.9% 88.5% 93.3% 4.8% Women are far less likely to travel to work than men. Overall, the difference is 5 percentage points. In the East, only three quarters of men's jobs are within the region, whereas 87% of women's are; in the South East, 80% of men work within the region and 89% of women. The distribution of trips among men is almost exactly the same as for the total working population, but London is a more likely destination among women who travel out of the region to work.

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Appendix 7: Labour force Limited statistics were found on labour force participation. http://www.ons.gov.uk/ons/rel/census/2011-census-analysis/ethnicity-and-the-labour-market/index.html

In the 2011 Census, the Other White ethnic group (77%) had the highest employment rate of all ethnic groups (aged 16 to 64). This was the case for both men (82%) and women (72%) from this group.

The proportion of men aged 16 to 64 who were unemployed was highest in the Other Black (17%), White and Black Caribbean (16%) and Caribbean (15%) ethnic groups. For women it was highest for Black African (12%), White and Black Caribbean (11%) and Other Black (11%) groups.

The highest rates of economic inactivity for men were in the Chinese (40%), Arab (40%) and Gypsy or Irish Travellers (39%) ethnic groups. The highest rates for women were Arab (64%) Bangladeshi (61%), Pakistani (60%) and Gypsy or Irish Traveller (60%).

Of those in employment, men from the Pakistani (57%), Black African (54%) and Bangladeshi (53%) ethnic groups were most likely to work in low skilled jobs. For women the most likely were Gypsy or Irish Traveller (71%), Bangladeshi (67%) and White and Black Caribbean (66%).

Of those in employment, Gypsy and Irish Traveller men (41%) and women (18%) had the highest proportion of all ethnic groups who were self-employed.

Over half (54%) of Bangladeshi men in employment worked part-time (less than 30 hours a week) and just over 1 in 10 worked 15 hours a week or less (12%).

Bangladeshi (56%) and Gypsy or Irish Traveller (54%) women were the most likely to work part-time (less than 30 hours a week). Bangladeshi and Pakistani women had the highest proportion working less than 15 hours a week (23% and 20% respectively).

Young people (aged 16-24) from the Gypsy or Irish Travellers (14%), White and Black Caribbean (13%) and Black Caribbean (12%) ethnic groups had the highest proportion of young people who were unemployed.

Fourth National Survey of Ethnic Minorities, 1993-1994 http://discover.ukdataservice.ac.uk/catalogue/?sn=3685&type=Data%20catalogue no apparent analysis of travel, nor of work category https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/343640/data-sets.pdf useful list of datasets, but none appear to show travel patterns or employment by ethnicity (there are coarse employment figures, but showing proportions, as in the census, rather than the actual jobs). Driving licence data are available by age and sex, but not apparently by ethnicity. The series 'Taxi and private hire vehicles and their drivers' gives only the number of licences, with no characteristics of the people holding the licences.

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7 APPENDIX C Discussion Group summaries

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APPENDIX 1 On the Move – Focus Group Summaries December 2014 – March 2015 Older People

1.1 Tiverton, Devon 1.2 Hither Green, SE London 1.3 Saltburn, Redcar and Cleveland

Black, Asian and Minority Ethnic Groups 1.4 Swansea, South Wales 1.5 Leicester 1.6 Luton, Herts

Business 1.7 Leicester 1.8 Central London 1.9 Bradford/Leeds 1.10 Birmingham

Migrants 1.11 Leeds 1.12 Peterborough 1.13 Woking

OLDER PEOPLE 1.1 Older People, Tiverton, 28th January 2015 General / Introductions Older people, 10 female, 2 male. Average age of 65-70. None of the

participants worked any longer so getting around was mainly for shopping and leisure. 3 did some voluntary work, one helping to run a community car scheme and 2 others active in Devon Senior Voice (raising awareness of issues faced by older people (http://www.seniorcouncildevon.org.uk/). Whist a few did have family and/or friends living nearby who could help them get about, most did not and so were reliant on public transport. All lived close to the community centre and also further in the town centre. 2 lived in Exmouth and had travelled to the meeting by bus.

Views about different modes of transport

Car 9 of the 12 participants had driving licences but only 4 were still driving. Of those who had cars, two (women) were almost 76 years old and both acknowledged that they had lost a lot of confidence and that there would soon come a time when they would stop driving, although this was tinged with sadness as they also both commented that ‘driving is my independence’. ‘I drive a car but I know my time is coming, as you get older, you lose a bit of confidence so I think I will use the buses more in future’ (female, aged 75). 1 male was driving on a voluntary basis for a community transport

141

scheme. Even for those who did drive, they also used their bus passes, especially to go to Exeter as they felt it was too confusing driving around big cities and also they were unsure about where to park in Exeter. One person had never had a driving licence and had never had any interest in driving, she was therefore, very used to taking the bus everywhere. Buses All participants had bus passes. Largely, they agreed that they use the bus more because they have their passes, otherwise, they might limit journeys because of the expense. For many, the bus is a necessity so they would have no other choice but to pay for the bus, but most said they simply ‘wouldn’t be able to go out as often’ (female, aged 78). Another (female) commented that she often accompanied her friend to the hospital on the bus and that if she had to pay to do so, she wouldn’t be able to go with her. Another female participant commented that she would use her bus pass even more often if the buses were more convenient – at the moment, there are no services on a Sunday and usually they are only every hour, although ‘the one at 4pm is always full of school kids so you can never get on’. Some discussion arose about the much better and more frequent services in the city (Exeter), although only a few people had actually used the services to get around Exeter – one person cited anecdotes to this effect from her sister and friends who lived there. A few participants lived in the town centre so they had little need of transport as they could simply walk into town and rarely went further afield. Train Few participants used the train and the issues were twofold. Firstly, the biggest impediment was the fact that Tiverton train station is some 7 miles outside of the town and a taxi to get to train station is around £15. There is a bus service that goes to the train station, though few people seemed to be aware of this. Secondly, the train was perceived to be very expensive and this is particularly so when compared with the coach. Most who needed to travel further, such as to London (3 participants spoke about recent journeys to London) used the coach (Berry’s (http://www.berryscoaches.co.uk) which they claim can get them to London return for £18. Most participants were familiar with the railcards on offer, although some seemed interested in finding out more information about the ‘two together’ card which they were less familiar with. However, as one participant commented ‘discount cards would encourage me to use the trains more but only if I could get to the station cheaply and easily first’.

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Cycling Only one person rides a bike – one other female did ride until 12 months ago when she came off her bike and damaged her leg so she is now unable to. Generally, there was agreement that Tiverton was too hilly to ride around and also that it was not ‘bike-friendly’. Many of the roads were considered too narrow and without cycle paths, it was not felt to be safe for cyclists. Interestingly, one driver commented that she understood how difficult it was often for drivers to see cyclists and so she wouldn’t feel safe but would perhaps consider cycling if better provisions were made. For others, mobility was an issue which impeded them from cycling and they would simply not be able to despite any improvements in provision. Other forms of Transport One participant provided information on the local community transport scheme which surprisingly, few had heard of before. Many seemed interested in such a scheme, especially in light of an anecdote from another participant who recalled his driving experience helping a man visit the grave of his wife. Rather than simply driving him to the churchyard as a taxi would, he felt he was able to give a much more personal service and helped choose flowers and walked with him to the grave as the path was uneven. Interestingly, a few participants had the impression that to use such a service, you had to be frail and elderly and most often people don’t see themselves in that light. Some used taxis occasionally, although the expense prohibited extensive use.

Car as status symbol / hybrid solutions

There were only 4 drivers in this group and no sense at all that the car represented any kind of status symbol. One female (aged 76) commented ‘oh God, no, it’s my independence, we only have cars for convenience, although they are expensive to run’.

Role of technology in travel choice

As participants were mostly reliant on the local buses which they used almost daily, they had little need for technology for any travel related information. Most carried paper timetables with them although 3 people did say they had used the internet to look up buses to get to London. None used the internet for shopping either, preferring to go out themselves to do this as it is also a reason to get out of the house. None thought this would change at all in the future. Regarding schemes such as car sharing, most thought they would probably be useful for people who worked but not for them. Black boxes didn’t really feature in people’s considerations about insurance, one person had heard of them as her grandson had recently looked into getting one. One participant added ‘just occasionally, when I have done something really stupid, I think I am glad I don’t have a black box installed!’

The Future Transport does seem to feature in people’s thoughts about the future

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and also in their decisions about where to live now. One female commented ‘we haven’t had a car for so long so when we moved to Devon, we had to live somewhere where there were good transport links’ (female living in Exmouth). Another added ‘there will come a point for me when I will have to stop driving and for that reason, I bought a house in the centre of Tiverton so I could still get out and about. I don’t have a parking space there and I have to rent a space in the multi-story car park which is a 15 minute walk from my house but at the moment, that is my exercise’. Another stated that when she is no longer able to drive, she too will move into the centre of town as there is currently a ‘nasty hill’ leading up to her house which she knows she will not be able to climb up in a few years and as she doesn’t have any family nearby to help, she is totally reliant on public transport.

Other comments Most of this group were very used to the public transport system, in particular that of the local buses they use most frequently. Many had no real desire to travel further afield and used the coach when the need arose. A view reflected by many participants is that using the bus means that it is quite difficult to do a lot of shopping at one time so more frequent trips are required. However, without the expense of the bus to consider, most thought this to be positive as it meant they get out of the house more often and ‘escape the four walls which otherwise can become a prison. For our age group, that is important’ (female, aged 76). For one (female) participant who had been used to travelling by all forms of public transport for many years commented that she much preferred to do so because; ‘I have total freedom, I am always chauffeur –driven and if there is ever a problem, it is always someone else’s responsibility’. For those for whom public transport is not a choice however, views can be quite different. One female recalled a story of a friend who until recently drove everywhere but due to a stroke, has had to sell her car as it is unlikely she will ever be able to drive again – ‘it has definitely changed everything for her, she will now have to get used to using public transport’. Changing habits (male/female) Most participants were now living on their own (many widowed). One female commented that when she and her husband lived on the US, they both drove and whilst her husband had never had an accident, he could not pass the UK test and so she had to do all the driving from that point. He died before he ever managed to pass. For another female participant, she met her husband when he was still a learner driver and she already had her own car so she always did the driving. A male participant commented that when he and his wife were younger,

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he did all the driving as ‘there was no way she was going to get behind the wheel of my car! But that has changed over the years and now we share the driving’ (male, aged around 60).

1.2 Older People - Hither Green

Older people: 8 participants, 5 men and 3 women All but one car owners but also 4 cyclists. All had Freedom Passes. Teacher retired, teacher part time, local councillor, editor, manager NGO, park attendant,

carer Overall a relatively well-off group and very active in looking after grandchildren, caring

roles, voluntary work and active leisure lives. Introductions (first names only) – assure anonymity Where they live and how they mainly travel around

Although the average age of this group was 78, they were very active and used a variety of methods of transport including cycling and buses. All had smart phones and regularly used computers. They all lived in the Hither Green/Blackheath/Lee area and all had facilities for off street parking.

Views about different modes of transport – car, train, bus taxis, cycling Why they don’t use other modes – perceptions as well as objective factors such as cost What drives choices? Knowledge of advanced rail fares, rail travel cards, concessionary bus fares

Cars - often they didn’t use their cars especially for visits to Central London and local trips. Parking was a big determinant but also the weather. “We pick our grandson up from school every weekday (daughter working) and we usually take the bus but if it’s raining we drive.” They mainly used the car for longer trips but voiced concerns about whether it was worth it – on balance yes for the convenience and emergency use (grandchildren and in one case a disabled daughter). Also cars tended to be old and not worth much in terms of sale price but still reliable “modern cars are” so on balance worth hanging on to. One couple had downsized from two cars to one following retirement. Bus/local train/tube – good knowledge of London and local bus routes – disliked bad behaviour by teenagers but this was not a deterrent to use even at night “I welcome surveillance – it keeps you safe”. Huge support for Freedom Pass “we love it – the whole of London at our feet – stops me getting depressed.” Train – all had Senior Rail Cards and one person travelled with a daughter who had a Disabled Card. Good knowledge of existence of Advanced Fares but not always available to fit with travel needs. “I can’t pick and choose when the meetings are.” (Chair of NATO support group). Coach not used and poor knowledge of routes, fares, discounts, etc interested when shown route maps and prices Cycling and walking - Half the group cycled although not on busy roads and not night and only locally. Very aware of the role of cycling in keeping fit and getting around when walking too far especially when feet problems “I’ve got a fallen arch so can’t walk too far but can cycle quite long distances.” Welcomed local

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decision to introduce 20mph on wider basis in London. Car ownership as a sign of success Status symbol – aspirations to own cars – what sort of price range and models?

For 6 of the 7 car owners - certainly not – strictly utilitarian but interested in design of cars for needs of older people – e.g. no sill on boot to enable easier loading. A lot of interest in new aides to parking, safety features, etc. “Features which helped to keep you driving longer such as automatic right turning might lead me to buy a new car – I think these do exist but only on high end cars which I wouldn’t bother with.” Maybe status considerations when young “I thought I was the King of Siam in my first car.” (Humber Hawk)

Views on hybrid solutions Car clubs, shared cars, black box to drive insurance cost down. Role of technology in modal and travel choice

Technology – all had smart phones but didn’t use them much for travel information – preference to check train times for longer trips only and thought insurance costs quite reasonable anyway (all had max no claims bonus) and used internet to check best quote annually. Idea of car clubs not appealing “I’m used to my own car – I’d feel nervous getting used to a new car”.

Passing the driving test and driving skills Problems with theory test, problems of old age, couples issues (women in couple not driving and lose skill)

Some concern about future ability to drive and all very interested in the Mobility Advisory Centres. Of the three women the male partner always drove when they were a couple and one of the women hardly drove at all “We always go out together so I haven’t driven for over ten years. If he drops off his perch I’d sell the car – we don’t need it really here in London – we’re so lucky.”

The future – will they/have they consider/ed transport issues when their situation changes marry/have children/divorce, partner dies, new job etc Will they use cars more/the same or less?

It was clear that the London Freedom Pass was highly prized and a major reason for living in London at retirement. “We did think about moving to Gloucester (daughter lived there) and we would have released a lot of equity in the house swop but the thought of losing the free travel was a major decider to stay.” “Why would you move – once you have a roof over your head which has been paid for, London is cheap with its free museums, transport and even cheaper food.” The group agreed they certainly wouldn’t use cars more and depending on health and death of a partner probably less although bearing in mind that they didn’t use their cars much as it was. The main difference would be more rail for long distance and perhaps a few more taxis. There was also agreement that they might use the internet for deliveries “I do occasionally get things delivered from John Lewis and Argos and if I didn’t have the car I might get bulky food and household stuff like toilet rolls delivered too.”

Conclusion

This group were typical ‘Guardian readers’. They were very informed about transport (except coaches) and frequent users of the London Transport system. The opportunities provided by Freedom Card ownership was a major bonus and key reason for living in London and explaining travel patterns. Car ownership and use was still a feature of their travel patterns but choices were

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multimodal and even though they all had parking where they lived it would not present a major problem if they didn’t own cars.

The discussion about cycling was interesting in that it was seen as a direct alternative to walking although equally healthy. There is potential for more cycling with safer roads and the spread of 20mph zoning was a key incentive. Motivation to cycle fitted well with support within this group for the ‘green’ agenda.

Overall the group’s lifestyle confounded the image of retirement – all members of this group were making a significant social or economic contribution albeit unpaid.

1.3 Older people – Saltburn To be added

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BLACK, ASIAN AND MINORITY ETHNIC GROUPS 1.4 BAME - African Community Centre, Swansea, 29th January 2015 General Introductions

There was a wide variation in age for this group, with the youngest being below 20 and the eldest above 65. Whilst participants were recruited via the African Community Centre, this group spanned multiple ethnicities. 3 males were from Jordan, Sri Lanka and Pakistan and the 7 females were from Lebanon, Pakistan, Uganda, Nigeria and Cameroon. Whilst some had been in the UK for a few years (the longest, 13 years), others had been here 2-3 years and some had arrived only a few months ago and were seeking asylum. None in this group owned a car and all relied on buses and walking to get around.


Car No participant owned a car as it was seen as prohibitively expensive to do so. Two males had driving licences in their own countries (Jordan and Pakistan) but could not drive in the UK. One had applied for his provisional licence and is due to take the theory test next month. One other female said that she would also like to take lessons in the future but at the moment could not afford to buy a car. Bus All rely on the bus to get around as well as walking. Participants stated that they mostly needed to travel to get to shops, to the African community centre and into the city centre for free English lessons and to undertake voluntary work. Whilst all found the buses quite difficult to understand at first, they are all now much more used to them. One commented that she didn’t understand where to get on or off and when she asked the driver, he was rude to her so she asked a fellow passenger instead who helped; ‘sometimes the public are much more helpful than the drivers’ (female, aged 21-30). Another female agreed that the buses were confusing and that it is difficult to find the right information. She recalled a time recently that she had to travel to the hospital and whilst she had found out which bus to take, she did not know the direction of travel and so waited on the wrong side of the road and got on the wrong bus. One other female commented that she found it difficult to use the bus at certain times to coincide with her fasting. She had been told on a few occasions that she was not allowed to eat on the bus at the time when she wanted to break her fast. She found this all the more confusing ‘when you see all the other people eating and all the rubbish on the buses’.

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Generally, the group found local buses to be convenient, although some commented that they can take a long time and are often late because the traffic is often bad around the city. The main problem is the expense. All agreed that the price for the buses was too high and most were familiar with the Oyster system in London and thought something like that would be beneficial to them to save money by combining journeys. Also, any help in terms of discounts would be helpful as no participant was entitled to any concession. One comment which most agreed with sums this up; ‘my income is £35 per week and if I have to spend £19 on a bus pass, how can I survive?’ (male 30-65). For one elderly lady, bus travel was essential as she had to travel frequently to the surgery because of a knee problem which meant she was reliant on the bus and found this expensive. Another male participant noted that although he takes the bus quite happily, they finish too early at the weekend (11pm) which means he has to take a taxi if he is coming home later which is expensive. He also noted that because of the usually wet weather, the buses are always damp and smell bad so they are often unpleasant to take. A few in the group had taken the bus to Cardiff also to visit friends and family. One female commented that in Cardiff, ‘they put the bus timetable on the wall and maps so you can easily work out where you are going’ (female, aged 21-30). Train None of the group travelled by train, citing the expense as the biggest reason. Whilst they acknowledged that the train is easier and faster, none could afford to use the train. A couple had travelled to London previously and had taken the bus to do so, stating that Megabus offer a return fare to London for only £5. None of the participants was aware of the rail discount cards available and when explained, they appeared interested but stated that the initial fee of £30 per annum was too expensive. If something similar were available for the bus however, they would consider it. One female who did once travel by train to London had done so using a friend’s ‘family & friends’ card which saved her a lot of money. She has been in the UK for 13 years and so felt confident using public transport and stated that she knew where to find some good deals; ‘there are lots of offers but you have to know where to look’ (female, 30-65, Lebanon). Walking Most participants walked a lot to get around, especially if they did not have a weekly bus pass for a particular week. Most simply accepted this and stayed local to their homes, visiting only their local shops. Many live close to the African Community centre also, which provides a lifeline for them to socialise. One male commented that he would actually prefer to walk in any case as ‘it is not only cheaper but it is also good for your health and good for the environment’ (male, aged 30-65).

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Cycling None of the participants has a bicycle. Interestingly, this was attributed not only to the cost of buying a bike, but also cultural differences were noted; ‘we don’t really learn to ride a bike like you do here, it would be difficult for me’ (Male, 30-65, Pakistan). In addition, the hills in Swansea were noted as a barrier to cycling as well as the lack of cycle lanes. Taxi Only two participants ever used a taxi, one if he comes home later than 11pm at weekends as he says there is no choice. The other (female) stated that she uses a taxi once or twice a year on special occasions like Eid when she travels with her family to go to the mosque and to visit friends. Taking a taxi on those occasions is cheaper than paying for them all to use the bus.

Car as status symbol / hybrid solutions

Whilst not really expressed as a status symbol, all agreed that a car would be useful but only if they could afford it. One (male) participant stated that he would prefer to walk as it is good exercise and another agreed that even if he had a car, he wouldn’t always use it as parking is so difficult in the centre and also expensive.


None used smartphones (only three people owned one) to find travel information. In terms of technology helping people travel around, all agreed that voice announcements on buses (such as those used in London) signalling the name of the stop would assist them and others who struggle with the language.

Passing the driving test and driving skills

Only one person has so far investigated the UK driving system and has a provisional licence. He is feeling confident about taking his theory test next month, largely because he has been driving for 30 years in Pakistan and since they drive on the same side of the road as the UK, he doesn’t envisage any problems.

The Future

Whilst two people in the group felt secure enough to think about taking driving lessons and passing the driving test, most others felt that their futures in the UK were too uncertain to think far ahead; ‘we can’t really think about the future and what might happen as we don’t know whether we are still going to be here in the future’ (female, 21-30, Uganda). Most agreed however, that they would take more buses rather than walking if they were cheaper. They might also make longer trips more frequently (to Cardiff generally) to visit friends and family if they could afford it.

Other Comments One female who volunteers helping refugees and asylum seekers commented that the buses are very difficult for them to use, largely because of the language barrier and people don’t have the confidence

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to try them so they usually have to walk around. Also, because if someone is in ‘section 4’ (awaiting a decision on asylum), they are not entitled to cash benefits, only vouchers which cannot be used for transport. This is particularly difficult when people need to go to the hospital and/or to the police station where they need to sign. Travelling anywhere is a big concern for most participants and the issues are around the language barrier, the difficulties in knowing how to use public transport and most of all, the cost. One female commented that being an asylum seeker, she sometimes had to travel to visit her lawyer. Whilst she was reimbursed the fee, she said she found it hard to pay the money up front as it sometimes took a while to claim back.

1.5 Indian UK residents’ discussion group

5 Males 5 Females 2 Unwaged, 3 Part time employed, 2 adult education, 3 full time employed 3 drivers, 1 provisional driver, 6 non drivers Q1. Would you say your general travel patterns have changed in the last two years?

The majority of the group thought they were traveling more than they did 2 years ago, not a lot more but work options and family are moving away from Highfields slowly but surely.

There was also a degree of shift in mode, walking for health was quoted by two members rather than using public transport.

I started walking more for health, it is much better for you and it is cheaper too (Male 50’s)

However the drivers suggested that they may drive less, expense being one reason and change in employment for the second.

One woman thought she would definitely be traveling more, having just gained employmentand sitting a driving test soon.

I have a young family; they are getting to the stage when I will need to take them to as many places as can for school, leisure and family.

The older members of the group suggested that just as life slows down so does the urge and need to travel. On discussion on the use of public transport concessions for the older generations, nobody thought they would travel free for the sake of travelling and would not necessarily use public transport more frequently.

Q2. Thinking about the long term future do you think you will be traveling more or less than you do now?

The majority suggested that they would be traveling more, the two key reasons for this being, employment and family. However the majority of this group are public transport users rather than car users.

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Employment around Highfields is scarce, with a high local unemployment rate. Everyone in the group felt they would have to travel in some cases considerable distances, either by car, public transport or transport provided by the recruitment agencies.

3 of the group are employed in work which involves shift work introduces further problems due to the lack of public transport to meet shift timings, which results in long walks (over one hour in one case)

I have to walk, the bus services don’t run early mornings or late at night. I can’t cycle through the city it is not safe, not so much the cars though they are a worry, it is also the pedestrians (drunks during the night time and early mornings sometimes) push people off their bikes or intimidate me. (45 year male walking through town to meet agency bus to Northampton and back)

The second key reason is family, as the family grows and disperses in order to seek employment and start their own family; the remaining family now have to travel to see them. This also results in the departing sons, daughters and siblings returning back to Highfields on a regular basis. The older members of the group suggested in reality they would be traveling less locally but on the other hand the family would be visiting those more, they hope. The result more and more journeys.

Q3. How do you MAINLY travel for these different purposes at the moment?

The majority of the group are public transport users and happy to walk, Highfields is well served in terms of public transport and with local shops and services providing just about all the community needs.

Q4a. What would you say are the advantages and disadvantages of travel by train?

In general the whole group did not use trains, certainly not with any frequency or more than once a year. Trains are considered too expensive, coach travel being the preferred mode of transport.

The only advantage of the train was the speed when compared to coach travel, comfort was considered comparable, with personal security being better on the coach.

Q4b. What would you say are the advantages and disadvantages of travel by car?

The main advantages of a car was seen by the majority as a means to employment and family. The main advantage to the younger male community was ’image or status’, means to employment and an active social life. The better the car the better employment chances and better social life, the group suggested that possibly the faster the car the better.

For the younger Asian, a car provides not only mobility but freedom, image/status and to a degree ‘flash’ (when it comes to the new 5 series BMW). Regarding sex it was suggested that females are least likely to immediately attempt to learn to drive and get a car compared to young males, different priorities, and differences in culture being the primary reasons behind the smaller number of young female Asian drivers than males coupled maybe with a more pragmatic value, that a car is a necessity when it is required.

A secondary advantage being personal security when traveling in a ca as opposed to walking, cycling and public transport.

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As previously identified local employment opportunities are scarce and still possibly reducing, resulting in the need for a car to enhance employment options, widening the field or range of choices. Though public transport is recognised as good in the area, Leicester is not necessarily seen as having enough jobs for the population, with many of the group knowing family and friends commuting over 30 – 50 miles by car.

Disadvantages of a car were mainly seen as cost. The expense of learning to drive, insurance, running and purchasing the car all deter people from driving. Parking was also raised as an issue in Highfields and the associated security of the car once parked.

Q6. Do you think driving less applies to others?

The group thought that young people, rural residents and migrants will be driving more. Young people and new migrants will drive more due to work and social commitments, rural people due to service closures in their villages and towns.

As soon as the new migrants get a car they are off, it’s a bit like Disney Land for them, as it was for us I assume

City centre and potentially suburban dwellers will drive less as public transport improves and as the big out of shopping malls lose their attraction due to online sales.

1.6 Luton on the move discussion group (Futures Community Centre)

10 adults (Asian) All households had a car 7 females 3 males 7 drivers, 5 with own car with 2 sharing the family car General travel patterns and recent changes With regard to general travel patterns the majority had not changed their usual modes and distances, with the exception of three. One person had recently moved to the area resulting in a longer commute to work by car (public transport was not an option). The second has two children just starting school (outside of walking distance) and the third had recently retired. The key message was that a family car was a necessity in this day and age unless living and working in a major city such as London or Birmingham.

The drivers found that the convenience of the car for work, household and family commitments outweighed the inconvenience of relying on public transport for all but long distance journeys. The non-drivers regularly used the local public transport for work and shopping alike when required, but all had access to a family driver when needs be (journeys requiring a car were made albeit constrained by driver availability).

Attitudes to public transport

Price was the major constraint on long distance public transport (primarily being dependant of number of people traveling, resulting in a higher cost to car use when three or more people are traveling), the second being journey purpose (social activities tended toward train use, however when traveling with children and or elderly parents generally resulted in the car being more practicable option, being door to door).

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Luton was considered to have very good rail access to London and beyond, with the majority being aware of ticketing options and good knowledge of the cost advantages of using coaches occasionally (significant family gatherings, festivals, weddings etc.) though these were organised by various external sources.

Cycling was not considered an option at all, safety being the most stated reason for why cycling is not viable, however discussion move on as to how impractical cycling was felt to be especially for women, levels of fitness required and the great British weather closed the argument.

General walking was considered in the same vein as cycling, however walking for health was seen in a positive light, but, local shopping trips and social visits were still made by car, “if you got it, you might as well use it”. There was also an underlying theme of ‘status’ that applied not only to the local shopping trip or visit but included the school run by car “if you got it, you might as well flaunt it” was implied with some jesting .

Views on hybrid solutions were negligible within the group as were views on technology, smart phones and computers were used occasionally to research journey options. The key reason for using the internet was for searching for children’s activities and associated package bargains such as theme parks or shows for the school holiday periods.

Future plans and attitudes

The driverless car was discussed briefly and the thought of automatous taxis but drooped quickly as the expense was ridiculed and considered toys for the rich.

On discussion of the first time driving, the majority saw no difficulty with the testing regime and learning process, though all thought that it is getting more thorough and expensive as was the cost of car ownership and insurance. It was noticed that the cost of testing and licencing has been recently reduced, which was seen as a welcome relief though also seen as marginal when looking at the total cost of getting in their first car for many.

The black box scenario and its role in moderating driving was seen as a bonus for those with older children now driving, not so much the cost as it was perceived as just as expensive in reality, but rather than the fact it recorded driver behaviour “If my son’s insurance goes up, I know it is because he has been speeding. It provides a degree of restraint and keeps him safer”.

In summation all the group thought that in cities with good public transport links, accessible shopping and work places will result in less car ownership for those who wish to live in a city. For those who can’t or don’t want to, the car will be here to stay. It might be smarter, cleaner and safer but for the next generation or so will be required regardless.

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BUSINESS

1.7 Business Drivers, Leicester

8 Males 2 Females Company director, banker, solicitor, trades men, recruitment manager and services staff All drivers Q1. Would you say your general travel patterns have changed in the last two years?

The majority were surprised that there has been a decline in mileage driven on UK roads, with only one person saying that their car mileage had reduced, due to more frequent use of trains.

I travel to London frequently, for early meetings I tend to use the train to avoid peak hour traffic heading to the city, yet drive part of the way to negate the costs (Drives from Leicester to Market Harborough – Cheaper rail travel and cheaper parking). Advance ticketing is not a real solution as meeting times can vary, which can result in an expensive return trip and or prolonged waiting periods which are unproductive. For meetings for which I can avoid peak traffic I still tend to be driven by car.(10 trips to London per month)

The balance of the group tended to drive just as frequently as per normal, though one engineer’s (Alarm maintenance) company has introduced a route optimisation scheme for regular maintenance runs’, though he was sceptical of any major reduction it produces at a personal level.

In relation to personal driving, all suggested that internet shopping may have reduced some trips for shopping, but this is offset by the current trend for shopping at more than one supermarket/superstore (low price such as Aldi) and more frequent local shopping to avoid waste.

One idea was raised as to why there may be a reduction in company cars usage, as in the case of one group member was the increase in personally leased cars (as opposed to the traditional company car) which are priced on annual mileage, leasing a car over two years with mileage caps (lower the mileage, lower the payment) resulted in this member hardly using their car for the last two months to avoid high penalties payable at the end of the lease.

On discussion as to why the group was surprised as to the fall in overall mileage across the UK, the majority thought that more people would be driving to work due to the disaggregation of the work place.

Though job tenure appears to be stable, more people are commuting further distances to find work with the biggest increase over the decade among commuters in the Midlands and south-west England


Apart from retirement thus affecting the work journey and old age that generally reduces activities albeit physically or financially, there was not much agreement amongst the group about the amount if any of reduced travel in the future.

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The majority of the group are very much car dependant for work requirements, with only one using a bus to access the work place, or gains a lift as a passenger.

One use trains occasionally for work purposes, however one member travels regularly by air for work using taxi and trains to reach the airports and commutes by train to London when not oversees.

Cycle use was limited to leisure where used by two of the group, bus and taxi by one and the rest dependant on the car, with the exception of a tendency to walk or taxi for social events where alcohol is involved..


The primary advantages of traveling by train was seen to be the direct city to city link arriving with a high degree of punctuality without the stress and effort required as if you would of driven.

The ability to work, socialise or relax safely and comfortably during the journey was also seen as important.

The disadvantages outnumbered the advantages

Cost was seen as the major disadvantage, more so when travelling with a colleague or friends due to the combined travel cost far exceeding the cost of a car journey.

It is cheaper for three people in a taxi making a return trip to London than going via the train, two people if travelling at peak time.

There is also the cost /journey factor, the quicker the train the higher the cost. London was seen as expensive and faster than a car journey. The cost to Birmingham was considered a fair price yet takes longer than a car journey and almost the same train journey time as going to London, resulting in a no win situation in either case.

Peak travel can also subject to overcrowding on trains to London, though it was considered not to be as bad as some routes into London or other major cities.

Off peak travel was not seen as an advantage for work travel, the time restrictions do not match work requirements in general, advance ticketing was considered feasible but as previously discussed the cost of not meeting the return trip can negate the previously gained cost advantage.

Off peak and advance travel was considered an advantage when traveling socially and meets expectation but again there are trade-offs, Sunday travel as across the network generally results in much longer train journeys with no fast trains. For example most trains out of Leicester taking an extra 50 minutes to London and about 30minutes longer returning than the week day service.

Finding the right ticket or ticket routing in order to maximise savings was seen by the majority as a nightmare by many.

Leicester to Liverpool or Manchester being a typical example, ticket agents route you through Birmingham. Yet if you are in the know changing at Nuneaton can save £20-£50 off the cheapest quoted via Birmingham.

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The primary advantages of traveling by car is the totally unrestrained ability to travel when and where you wanted to go to at a reasonable cost, in a means that the driver is generally accustomed to (weather, routing, degree of comfort, choice of music and so on) and take with you want you want in the way of luggage, tools etc. and securely.

Personal safety is also addressed by using the car.

The car also provides the means to find alternate routes, should the need arise due to a road closure or incident in order to minimise journey time and also provides the option of completely changing your destination or route should the need or desire arise. Something you cannot easily do once on the train or coach.

The disadvantages again outnumbered the advantages but do not justify giving up travelling by car as in the case of train travel.

The initial cost outlay, though minimal can vary to very expensive, however this can also be offset against loans or various lease arrangements.

Running costs can vary but tend to reflect the initial choice of car, the AA recommend between 35p to 55p per mile depending engine type for the majority of cars. (this is much cheaper than a taxi or bus in most typical journeys)

Parking can prove problematic for many car owners, especially in high density urban and employment areas and expensive in so many city destinations.

Journey times can be unpredictable due to congestion on the roads; however most congestion is predictable and thus considered in estimating journey times.

The last disadvantage mentioned by the group was the many people unable/not fit to drive on the road.

1.8 London Central – Business Group

All professional people in 30-50 years old, 5 men and 5 women living and working in central London – 3 of the 10 were self-employed.

All living in couples but no children Only one owned a car but all but one had a driving licence Lecturer, solicitor, investment manager, shop manager, designer, architect, dentist,

software designer, civil engineer, social services administrator, church warden. High use of public transport, walking and smart phone communication. Not necessarily high income especially those in creative or public sector occupations in part

due to proportion of income spent on housing. A lot of networking and active/leisure social lives

Introductions (first names only) – assure anonymity Where they live and how they mainly travel around

This group lived in inner London boroughs namely Greenwich, Lewisham, Brent, Camden, Ealing and Walthamstow. They were extensive users of public transport of all modes within London and also travelled outside London for both business and leisure - mainly by train

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but in a few instances by air (to Scotland). Only one person owned a car (rarely used) and another drove a company van.

Views about different modes of transport – car, train, bus taxis, cycling Why they don’t use other modes – perceptions as well as objective factors such as cost What drives choices? Knowledge of advanced rail fares, rail travel cards, concessionary bus fares

Cars were not considered to be desirable for London residents and no-one had an off street parking space. The one person who did own a car rarely used it and was considering getting rid of it. “I might drive a bit more often but then I’d lose my parking space – I mainly use it for visiting my parents who live in Northampton.” For the rest of the group car ownership had low priority although 8 out of 10 of the group had passed their driving test. “When I was younger living in Stoke it was the done thing to drive but now it seems like another life. What is the point of owning a car in London?”

However, it was accepted that sometimes a car was needed such as visiting locations outside city centres although even then train plus taxis were often preferred. A key influence on such a decision was confidence that there would be a taxi available and there was also a cost calculation with the consensus in the group that paying more than £12 for one way for an add on taxi fare was about the limit. “Above that I’d tend to drive.”

Two people within the group were members of car clubs which they used for both car and vans – mainly for leisure at weekends. Other group members were interested in the details of how car clubs worked out and several said they would consider joining. “I didn’t realise they had vans so that would be useful sometimes although generally I would use home delivery anyway.”

Bus/local train/tube – everyone in the group had good knowledge of London and all modes of public transport. This included experience of when the tube in particular was crowded and detailed strategies for avoiding peak time were discussed which included varying routes, times and multimodal choices including walking. “I managed to negotiate a different timetable which meant I could avoid peak times on the tube.” “It took me a while to realise that I could avoid the squash on the Central Line by going to Warren Street instead of Euston Square.” All members of the group used real time information to check bus times – mainly smart phones rather than electronic bus stop information and no one bothered with timetables. Apps showing the best route to less familiar places were also popular “I never get lost in London – even at night I know the night bus routes and I also use Next Bus and Hail.”

Intercity Trains As with the local public transport system, the group had a good knowledge of the intercity train system and fare structures. Booking

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Advanced fares was common and many instances of good bargains were given. “I’ve become an unofficial travel adviser to others in the firm – I often manage to pay less for First Class than standard and what with free gin and tonics and meals I reckon I’ve made a profit!” There was general agreement however that regular fares were expensive and sometimes unavoidable especially for business travel. “The problem is not knowing when meetings will end – I can’t tell you how often I’ve had to hang around Newcastle waiting for the Advanced fare time. Once I ended up paying twice just to get away and another time I had to pay again because the meeting went on longer.” For others in the group the cost of train travel was met by their company so they didn’t mind too much about fare levels although those in the public sector did complain about the ban on First Class. “Personally I think having two classes on trains is outmoded. The key need for business travellers is comfort to work on long journeys and that shouldn’t depend on price discrimination – it’s bad for society and for business too.” It was interesting that general distain for status based on car ownership seemed to translate into broader views about the democracy of train travel and the desire for different forms of traveller separation. “Yes the quiet carriage is useful but what you really need is a business section with printers, wifi and so on. There could also be sections for families or people with a lot of luggage or music playing.”

One complaint about train travel was lack of reliable satellite signal capacity. “Surely they could solve that by now – it’s a major problem not to be able to speak to people without getting cut off especially during business calls.”

There was also a discussion about the circumstances in which people would fly rather than travel by train. The main feature was time and the preference to get there and back in a day (e.g. Scotland) but this was seen in the context of total travel time rather than on board times.

“I do fly to Glasgow but only from City Airport where you get on and off quickly – otherwise I’d go by train for anywhere in UK except perhaps Aberdeen. I used to fly to Newquay too which was expensive but set against paying for a hotel not so bad.” Agreement and suggestion that train companies should compare end to end journey times with air to allow more realistic comparisons.

Coaches had not been used by anyone in the past year and there was poor knowledge of routes, fares, discounts, facilities and so on. One person had used the coach from the airport and been surprised at the

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availability of refreshments and wifi.

Cycling and walking Indeed walking was a key mode of travel for this group both end to end or as part of a trip. Motivation was equally time, enjoyment of London and health. It was interesting that clothing and bags including rucksacks were discussed as part of the travel experience - to some extent establishing identity. “I always have two pairs of shoes – one for walking and the other for when I get there.” “I love winter clothes and fashion – it makes walking around London so interesting.” In comparison apart from one man, cycling had little appeal especially to the women who saw this as dangerous and inconvenient in terms of weather, luggage, the bother of locking and inability to use mobile phones. NB a lot more to be said about attitudes to cycling but time did not allow.

Car ownership as a sign of success Status symbol – aspirations to own cars – what sort of price range and models?

Interesting images of who cycles or not – is this replacing cars as identifiers? Very little interest in cars and some positively against. “Just imagine how wonderful London would be without cars.” “I can’t understand why Soho hasn’t been pedestrianized – surely pressure from business alone should have made it happen.”

Views on hybrid solutions Car clubs, shared cars, black box to drive insurance cost down. Role of technology in modal and travel choice

Technology – all had smart phones and made full use of them for travel information not just via apps (two people regretted the demise of Transport Direct) but for exchanging information about delays on public transport – twitter was the most popular. Two people also used real time satellite information to change destinations and routes during trips. “I get messages from Flash Mob about a new happening.” “I’m on a gay dating network which pings me when someone likely is nearby.”

Passing the driving test and driving skills Problems with theory test, problems of old age, couples issues (women in couple not driving and lose skill)

All had up to date driving licences but of the 10 only 3 drove on a regular basis. One had a work van and also used it for private trips. No problem passing the test and a general view that being able to drive was needed as a basic life skill. Some sense of this being part of their earlier life especially those who had moved to London since passing the test. “I had driving lessons in my early 20’s automatically but not so sure I would have bothered with hindsight.”

The future – will they/have they consider/ed transport issues when their situation changes marry/have children/divorce, partner dies, new job etc Will they use cars more/the same or less?

We did discuss what they would do if they had families but apart from not planning to have children anyway – the group agreed that they might then have to move away from central London and possibly buy a car but would still choose housing convenient for public transport.

However in the main they thought that individual car ownership would decline – hybrid forms of public/private transport such as autonomous taxis and travelators would be the norm with ever higher speed rail for longer trips.

Conclusion

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This group were interesting (although may be a minority) in their reference points based on attitudes to fashion, music and design with an element of distain for lesser mortals including those who valued car ownership. A lot rested on living singly or as couples without children but of course this demographic section is growing especially in big cities.

1.9 Leeds, Business Group Focus group 2: Business Travellers Participants: Lucy (small local business), Adam (small local business), Jonathan (big consultancy), Phil (music sector), Charlie (education sector), Gerhard (markets), Johanna (education sector), Emer (lawyer), Charles (Building and Consultancy) Current transport habits 7 of the 9 participants have a car. One person who doesn’t have not a driving licence, uses taxis, buses and trains. However, driving by car is not their preferred mode of transport. Particularly, they go to city centre and to their clients using a bike (3), using public transport or walking (2). This is perceived to be faster, more convenient (due to congestion, difficulty and cost of parking for cars) and more environmental friendly (environmental concern is big factor in determining travelling choice for 3 and they would like to get rid of their cars in the future). The car is used only when, for business purpose, they have to carry equipment (3), move fast between locations (“I use the car only when it is impossible to move otherwise”) or go in the suburbs/other cities (2). It is avoided in other situations. In some cases participants perceive cars as faster than trains for example two people drive to London for this reason. Car-ownership as status symbol Some of the participants (3) reject this interpretation. For some others (2) it is still “your business image”. In any case, more than the car in itself, it is important it to be clean and presentable, and be good-looking.” The car is still a convenient and comfortable mode of transport: it is warm, you can put your music inside, and there is an inherent pleasure in driving. Most participants agreed with this comment. Black-boxes in cars There was a sharp separation in opinions: some of the participants thought it was a good tool for diagnostic, others saw it is as an obstacle to their freedom. Trains Jonathan would use a train to London only if with other colleagues. Otherwise a car is more convenient: train takes same time and it is as unreliable as driving. Participants have used National Express and Megabus when they were students. Train are faster but too costly, especially to reach certain destinations for which also advance booking is costly. No one thought companies had specific policies in preferring one mode of travelling for staff and

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generally left it to the individual. Not many companies knew about Advanced Fares “I have to admit I get an Advanced Fair and then charge the company the full turn up and go fare. Once I even drove unbeknown to them.” Buses in Leeds Buses are too expensive and too slow in town. It would be good to have an Oyster card in Leeds, or better still a national travel card. “Imagine if you could get points for using public transport like at Tescos. I’m sure it would encourage me and a lot of others to start collecting.” Walking Two participants were very used to walking up to 50min to go to some business destinations – one mainly on health grounds and the other to save money on taxis when visiting out of the way industrial estates. . Most participant however, would only walk up to 15min or at the most 30 if no public transport. Cycling and walking was perceived as good for health from everyone. However, they are perceived as not good for health in a polluted environment, as enhancing the time spent exposed to pollutants so this was something best done in the suburbs rather than the city centre. Future of motoring The vision for the future of each participant is: - Adam: rationalize public transport. More cycle lane and pedestrian facilities. - Lucy: nationalization of rail (to reduce costs and make it less unbalanced). Create an integrated cycle system in all big cities. Spend in trains - Gerhard: given the fact that there is still not alternative to cars, is necessary to make them more environmental friendly: the car is not going to disappear but will became better. - Jonathan: improve rail and road transport because you can't go everywhere by rail. Franchising has worked well. Build HS2, as East Coast is full. Necessity of more routes. Improve both rails and roads. - Phil: more trains, take off people from the roads. Invest in East-West rail connections and not North-South - Johanna: against building new roads, but need to maintain existing. HS2 is not needed as only a narrow group of people can benefit from that. It is necessary to make more small schemes to free capacity and to create infrastructure not where there are already. She proposes a national smart-card for public transports, train, busses and coaches. -Charlie: all of the above. It is important to provide best cycle routes, a trains system in Leeds. Train is the best and need to be improved. Conclusion This group, mainly comprising small businesses were heavily influenced by cost and even though car owners made careful ‘cost benefit’ calculations about travel choices including taking account of congestion, cost and health issues.

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1.10 Birmingham 6 Males 2 Females

Sales manager, office administrator, tradesmen, restaurant manager and services staff

All drivers, with little regular public transport experience apart from Taxi’s

Q1. Would you say your general travel patterns have changed in the last two years?

The group were not surprised there had been a decline in the predicted number of journeys over the last 5 years, recession being a major contributor but also due to technology, “I hardly go to the cinema now, with a large screen TV and on-demand movies. It’s not sad but cheaper and more comfortable at home”. (Once a week film buff)

In terms of business the majority considered technology has played a major role in business logistics with regards to transport, facilitating rapid movement of both goods and services, when combined with customer expectation (next day delivery) this has resulted in a major shift in goods and service movement of which is accelerating over recent years. “Home deliveries have reduced trips dramatically, a delivery van full filling 50 trips may be at a time, 100 or so in a day if not more”.

However some in the group thought that the proliferation of ‘white van’ delivery services rather than the more traditional bulk delivery was seen as a major contributor to traffic volume and associated congestion as a direct output of local business.

In terms of the group, two members utilise the train more with all looking forward to the advent of HS2 in Birmingham. One member is now using the bus for her daily commute due to a new bus corridor in Birmingham which is proving to be more reliable than a personal car with regard to journey time.


The majority in the group admit that their travel may have reduced (trip numbers) due to online processes and associated convenience for business reasons, but not so for personal related journeys.

Many of the reasons for previous business trips have been replaced by technology, information exchange for example being a classic reason, cost restraints and efficiencies also contribute to the decline of the business trip, but there will always be a need for goods and services to be delivered and face to face commercial exchange, so although the business trip has declined, the group felt that the trip rates will not continue to fall any further.

There was agreement that public transport in Birmingham was improving, which may result in a small degree in modal shift; apps for taxi’s and other similar technology will also contribute in the future, enhancing the shift to public transport. UBER was discussed as a promising technology development with the group thinking it would do well in Birmingham.

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Work

The majority of the group are car dependant for business reasons, carrying goods and tools for some, with only one now using a bus. Cycling in the summer by one, but car on all but the best days and when time and work commitments allow.

Social

Being car dependant requires a total commitment to safe legal driving, hence taxi use and the designated driver was a priority when considering car use for social reasons. “that’s why all the country pubs have closed or turned to food”

Shopping

The majority of the group all used online shopping on a monthly basis and regularly shopped by car, only one used online shopping for fresh food reducing the number of shopping trips. “I am still a taxi service for the children though; I think I am driving more to be honest”


The advantages of traveling by train was seen to be the direct city to city link, punctuality without the stress and time in many instances as if you would of driven. All believed that true, but in reality the station to final destination and return also needs to reflect the convenience of the train or all the advantages are negated.

The disadvantages outnumbered the advantages

Cost was seen as the major disadvantage, more so when travelling with a colleague or friends due to the combined travel cost far exceeding the cost of a car journey.

The cost to Leicester or Liverpool was considered a fair price yet takes longer than a car journey and almost the same train journey time as going to London, resulting in a no win situation in either case.

Off peak travel cost advantages was not seen as a real benefit as mostly unrealistic in terms of business demands (time constraints), advance ticketing was considered feasible but only in exception circumstance (faith in forward planning versus cancelation cost).

Off peak and advance travel was considered an advantage when traveling socially and meets expectation but again there are trade-offs.


The key advantage suggested by the group was freedom of travel to where and when at a reasonable cost, in a safe, flexible and familiar environment.

The disadvantages are basically what are out of the groups’ control, congestion, bad drivers, accidents and frustration.

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Cost was not seen as a disadvantage, it was generally considered that a car is a basic requirement just as a home is, travel cost was considered to be cheaper and safer than any other form of public transport in the vast majority of instances.

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MIGRANTS 1.11 Migrants - Leeds 8 participants: Agata (Poland), Alejandro (Mexico), Sanna (Germany), Tatjana (Latvia), Magda (Mexico), Shiru (India), Cara (Italy), George (Chile). (Names have been changed but not countries or origin) Current transport habits Walking Majority of participants walk to go to work-places, also walking distances up to 30min. Cars Tatjana and Shiru live far from city centre, have a car and usually drive. Sanna and Agata have access to a shared car, with friends or partner. Magda would have liked to buy a car to use at leisure time, but is too costly. Participants discussed the different car-insurances types in their countries (car or person) and also the problem of getting a UK driving licence. Driving licensing varies in different countries: - Mexico: people learn driving with friends, there is no exam. Some courses are available - Poland: it is required a course with an official driving instructor but then the car is insured not the person - Germany: people learn driving only with driving instructors - Latvia: official driving courses Shiru decided to take her test in the UK to ensure that she was safer while driving. Agata, that has a car in Poland, is willing to go back there to renew her licence, as she perceives easier to pass the test in Poland. However, Tatjiana and Sanna think it is harder to pass the test in their countries (Latvia and Germany). Sanna notice that she had several problems in transferring her insurance premium in the UK while moving from Germany. Bikes Some of the participants have a bike or would like to, but they have concerns about cycling in town, which is perceived as unsafe (“buses are aggressive”). Trains Everyone agreed that train fares are extremely expensive and unaccessible. The advance fare system is rarely used due the inability of planning ahead a journey. Tatjana suggested using cookies to reduce price go down. Participants have all experienced using coaches, especially Megabus, that is however considered as a non pleasant transport mode for some (packed, unreliable, long journeys -”it is looking for traffic jams”), despite the free wi-fi on board and the price which make it a good deal. Willingness to buy a car in the future Apart from Magda, who would like to buy a car for leisure, the participants that don't have a car are not planning to buy one, because is not needed or even not liked as an idea (Sanna). Despite this fact, participants think that still car-ownership is a status symbol, but only in specific environments (working in banks, consultancy, etc). On the other hand participants recognise how in certain environments car use is also perceived as not environmental friendly choice and thus disapproved of (e.g. Sanna works in the Faculty of Environment, and two people worked in firms

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with no parking). Sanna experienced car renting shemes in the past and she thinks this is a good travel option possibly unreliable (in terms of availability of vehicles especially for leisure time) Black-box in cars Participants generally think it is a good idea for good drivers Driving in UK Participants generally don't see left-side driving as an obstacle to drive once gained some experience: it is easy to get used to it, it is not difficult in reality also thanks to good road-signals. However, it still represents, for members of their communities, a mental barrier to start driving in UK. City buses Participants generally complain with the quality of buses in Leeds: it is quicker to walk than taking a bus, especially in the city centre area. Moreover, they believe it cost is absolutely disproportionate with the service: in certain cases taxis are cheaper and preferred. Sanna speaks about Germany best-practice of free fare for students (cost included in University admin fee). However, Shiru, uses bus regularly to get from the periphery to his workplace before he had access to a car, and thinks it is convenient. In general home-country public transport system (Latvia, Germany) is perceived as more efficient, accessible and cheaper. Its being public is also perceived as a good point. Tatjana would like to use public transport but has to use a car because of inefficiency of buses and the cost of the system. In terms of personal safety, female participants would take a bus till 8pm, and then prefer to use a taxi. Taxis are generally getting competitive and offering good fares. Smart Phones Technology All participants have one but don’t find the local public transport information reliable. Future of motoring The vision for the future of each participant is:

Alejandro: make public transport cheaper, especially within cities Tatjana: make public transport more comfortable, more eco-friendly: people need to use it. Sanna: walkable and cyclable city centre (less noise, less traffic). Built a metro/tram

system. Agata: cheaper trains (being faster they help people make more money) Shiru: more road-signals, improve existing roads. Build cycle lanes in the countryside to

guarantee safety of drivers and cyclists Mgda: more cycling facilities, cheaper trains

Conclusion The views of the migrants are strongly influenced by their earlier experience in their own countries. Where public transport is seen as good back home, they generally compare the UK offer as inferior and vice versa. There is little sense of car as conferring status and higher levels of cycling and walking.

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1.12 Leicester recent migrants on the move discussion group

Polonia West Leicester Community Centre

10 adults (5 females, 5 males) 4 drivers, 3 with own car, 1 sharing the family car and 1 person with a provisional licence ( all in employment) Travel patterns The majority have changed their travel patterns over the last two years, primarily due to employment opportunities/demand, personal circumstances and the growing desire to travel. Older friends (such as school/university friends) and colleagues of many in the group have travelled to other parts of the UK as work opportunities avail themselves. In conjunction with the desire to see other parts of the UK this is resulting in a degree of social travel, trips to London, Brighton and up north have all been made by members of the group, exploring not only the country but the employment market at the same time as making social/leisure journeys.

A few of the group felt that though there are many work opportunities in Leicester, the initial employment opportunities are limited due to the lack of English, with many recent migrants working in situations where Polish is the only spoken language. Finding a way out of such a position is a priority for the majority, this in turn results in more travel to other employment areas.

Modal choice

The members of the group travelled by private car/van, agency provided transport, cycled, walked and used public transport all dependant on personal circumstance. Cost effective journeys being the priority in most cases, Green issues were not a consideration in reality. A car was a preference, but not necessarily a priority due to cost, public transport was seen as sufficient to meet the needs of most. Cycling to work was seen as the best option for many, utilising public transport when weather conditions make it unsafe or uncomfortable.

Cars

The car was seen as a more practical means of making a journey, wasting money on a new or flash car was not considered a necessity or a priority by any in the group at this stage of their life, a more reliable was more likely to be the priority in the future.

Trains

Trains were considered and used but their use was based on cost effectiveness, lift sharing was prevalent amongst friends (cost) with social media being used to find lifts for both local and long distance travel. Coach travel was considered the best option in many cases, again a cost based preference.

New technologies

New cars or hybrid cars were not even on the radar for the group, awareness of the technology was not an issue, and there was no perceived need. Internet, journey planning and the use of social media was widely embraced by the whole group.

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Driving licence

Driving licence, all the drivers had changed their Polish licence to an English licence over the years, it was thought to be cheaper and easier getting a licence in Poland, but fraught with difficulties remaining with one. No one had retained a Polish car, “It is OK if you live down south, re validating your EU licence every 6 months when combined with a cigarette and booze shopping run makes it feasible, covering the ferry costs, but a bit dodgy to tell the truth.”

The cost of learning to drive and car ownership were both considered expensive and will only be considered if work opportunities would benefit, cost of insurance was not so much of an issue with this group as all were over 25, when below this age even thinking about a car was pointless. “They would be better off going back to Poland”

The future

There is no lack of aspiration with the group in terms of car ownership, it is purely a priority and progressive based acquisition process.

Conclusion

This groups travel and choice of mode is fundamentally based on cost and need, cost effective travel is the preferred mode albeit socially or employment based. As the future develops and changes so too will the preferred mode of travel change. It is envisaged by this group that stability and rewarding employment will eventually result in more travel in line with more disposable income.

1.12 Recent Migrants – Woking General Introductions This group consisted of 8 participants (7 female and 1 male). 3 had

been in the UK for one year or less, one for 2 years and the remaining four had been in the UK for considerably longer (between 7 and 10 years). All but one came from European countries (Poland (2 participants), Romania, Spain, France, Germany, Czech Republic) and one from Venezuela. Two are students, one staying in England for at least three years (driver and has a car) and one on a gap-year (non-driver). Two work as au pairs and do not know how long they will stay in the UK (one non-driver and one has access to a car for work related activity). One female is a stay at home mum (driver), another works part-time (driver) and another works full-time from home (driver). The male participant works full-time in a neighbouring town (has licence but no car). Three are totally reliant on public transport and cycling as they do not own cars (one has a licence and hopes to buy a car soon) whilst all other participants relied heavily on their cars, with only occasional train use (mainly to London).

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Car Four participants used their cars for almost all journeys, citing comfort and convenience as reasons for doing so. Of those who have been in the UK for the longest time, three said they had initially moved to London where they had used public transport for all journeys and on moving to Woking, decided this was un-tenable and thus learned to drive and bought cars. These three females also had two children each and so thought that now, the car was especially ‘essential for carrying their things around’. Two participants who currently use mostly buses, plan to buy a car within the next year as they view the car as much more convenient than having to wait for buses which are infrequent and often late. One au pair has use of a car but only for activities related to her job so for all other journeys, she has to rely on the bus and her bike. Interestingly, she commented that when she was at home in France, she always used her car and would never think of using public transport but now, she has had to get used to it and concludes ‘it is not as bad as I imagined it would be’. One female commented that she always drives because although she could walk to the train station, there is a lack of footpaths along one stretch of the road and ‘the cars go past really fast and it’s scary’. For the 2 drivers who have been in the UK for a year or less, they still find they must concentrate on which side of the road to drive on. Even for one female who has been in the UK for 9 years, she commented ‘driving is Ok for me now, but still, when I am walking and crossing the road, I still look the wrong way’. Bus Four participants used the bus frequently and all noted that they were infrequent, particularly from some of the surrounding villages to get into the town centre. One noted ‘there is only one bus an hour and the last one is around 6pm so that is really poor. I have to get a taxi sometimes, just to get to the supermarket’. Another female commented that she would rather cycle to another nearby train station and then take the train to Woking because the train runs much more frequently than the bus. For the participant relying on the bus and train to get to work, he noted that ‘as long as you know which bus you have to get, you can just stick to that and it generally works. It takes a long time but it does work’. He is however, looking forward to buying a car in the near future for convenience and to save time. Another used to rely on the bus but said that ‘often the buses were late and I would just give up and walk to town’. Now, she drives everywhere. She also noted that when travelling with a pushchair, it could sometimes be difficult to get on the bus if another pushchair or

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a wheelchair was already in the allocated space. Another said that she was once waiting at a bus stop waving her hand to signal the bus to stop and it drove past her, leaving her with the impression ‘they just pretend they don’t see you’. The participant from Germany stated that although she has to rely on the bus, ‘for me, the buses shake too much, they are old and I don’t feel very safe’. For long journeys however, all agreed the bus was a good option but only if you have the time, as they often take much longer than the train but often tickets are a fraction of train prices. One commented for example, that she bought a bus ticket to travel to Leeds next month for £14 ‘which is so cheap compared to the train’. For the participants with children however, they would still prefer to drive as the convenience of being able to stop when they need to and carry more luggage outweighed any cost benefits. Interestingly, these same participants noted how the children saw the bus as ‘an adventure’ and how they ask, ‘mummy, when can we go on a bus or a train’. Despite this, one participant stated ‘I don’t think my children have ever been on a bus’ – a sentiment also echoed by another participant. Whilst no-one commented on the cost of running a car (one person noted how petrol prices had decreased in recent months), a few commented on the cost of car parks and often they tried to find other places to park in nearby residential streets and then walk into town or to the train station. One female (French) participant stated ‘it’s strange because I don’t have a problem paying for public transport but for parking my car, I don’t really want to give money so I try to find a free place near town’. Train All use the train for travelling to London which is the most frequent destination outside of Woking and surrounding areas that people travelled to. All agreed that they would never consider driving to London because of the cost and also because the train service is so frequent. Three participants have a young person’s railcard and enjoy the discounts they receive each time they travel. None were familiar with the other railcards available (friends & family and two together). Two (with children) were aware of the special offers in the Summer where ‘kids go free’ and they had taken advantage of them. One stated ‘if I was travelling to London more frequently, I would definitely get a railcard’ and other commented ‘I would definitely consider more trips to London on the train with the children at weekends and in the holidays if there were more special offers’. Cycling 3 participants used a bicycle on a regular basis for travelling around.

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Of these, two stated that they do not feel particularly safe cycling on the roads. For one Polish participant, she noted how drivers in the UK did not seem to consider cyclists at all and they don’t allow enough space when passing and they pass too fast. She comments that ‘now I have learned to cycle not so close to the pavement so drivers can see they have to slow down to pass me’. Another commented that despite these concerns (and comparisons with the excellent cycle lanes in Germany), she relies on her bike most days and she appreciated the exercise that it gives her. Another participant who did not cycle, commented that as a driver, she did not like cyclists as she felt that the road was too narrow to accommodate cars and cyclists and she felt that cyclists therefore, were sometimes unpredictable and ‘you never know what they are going to do and that scares me’. Another stated that she would like to cycle more and now that she is working locally, she is trying to find a safe route to take to work which does not involve cycling on main roads as she does not feel safe doing so. Taxi One female commented that when she moved to Woking from London, she was struck but how unaware of the area they appeared to be, although she notes that now ‘they all use sat-nav so it’s not a problem’. All who had used taxis commented on how expensive they were, with one stating that she thinks she was once overcharged by such a large amount that she vowed never to use a taxi again, although she noted that sometimes it was unavoidable. Another commented that she did not feel particularly safe taking a taxi alone, particularly at night and so always ensured that she travelled with someone else.

Car as status symbol

Largely, all agreed that their choice of car was mainly based on practical considerations such as value for money and size, with most preferring a smaller car for driving around town and ease of parking. Three commented that the ideal was to have two cars, one small car for driving short distances and a bigger, more comfortable one for longer distances, going on holiday and away for weekends for example. The participant from Germany on the other hand commented that ‘at home, it is a lifestyle choice, everyone has big, expensive, good cars’ so for her, car choice was bound up in status considerations.


None in the group were familiar with black-box technology, although a few said that they would consider it if it meant cheaper insurance. All drivers used sat-nav technology for getting around. None used

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any sort of transport related apps for train or bus times.

Passing the driving test and driving skills

One Polish participant who will take her driving test soon and hopes to buy a car later this year, stated that she thinks it will be easy to pass the test here in the UK. She stated that ‘in Poland, lots of people take the test 7 or 8 times before they pass. I think the rules are much stricter there. Here I have a few friends who have passed first or second time so I think it is much easier’.

The Future

Two participants were looking forward to buying cars in the near future for the convenience that affords. Interestingly, the participant from France stated that when she goes home, even for a short visit, she will now consider using public transport which is something she would never have thought of before getting used to it here; ‘I am more OK to take the bus now because I know now that it’s not as horrible as I imagined it would be’. Two thought they would like to cycle and walk a bit more as they felt they had become too reliant on their cars ‘I used to walk everywhere and since I got the car, I have become so lazy and I need to get some more exercise. I used to feel much better and have more energy’. One participant has been considering replacing her car with an electric car, for environmental reasons. Though she comments that ‘I don’t know enough about it yet, how easy it is to charge and where I could do that around here’.

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8 APPENDIX D Statistical Results

D1 Young People 1. Respondent demographics (n= 2233) Figure 23 Sex

Figure 24 Age group

Male, 44%

Female, 56%

Under 20, 15%

20 ‐ 30, 54%

31 or more, 31%

174

Figure 25 Car ownership

Figure 26 Licence holding

Yes, 48%No, 52%

No, 18%

Provisional, 21%

Full, 61%

175

Figure 27 Regional distribution

Figure 28 Main mode of travel for short local trips

9%

4%

9%

16%

15%

7%

8%

26%

2%

5%

0% 5% 10% 15% 20% 25% 30%

Scotland

Wales

North East

North West

Midlands

South East

South West

London

Northern Island

East

20%

6%

33%

36%

6%

0% 5% 10% 15% 20% 25% 30% 35% 40%

Bus

Train/tube

Car

Walk

Cycle

176

Figure 29 Main mode of travel for long trips

15%

39%

47%

0% 10% 20% 30% 40% 50%

Bus/coach

Train/tube

Car

177

Rankings Figure 30 First preference summary

Figure 31 Too expensive to learn to drive

0%

1%

2%

2%

6%

7%

16%

24%

42%

0% 10% 20% 30% 40% 50%

Environmental reasons

Social media use

Internet shopping

Not into cars – no interest

People prefer to walk/cycle -…

No need – public transport …

Too expensive to learn to drive

Too expensive to run a car

Insure too expensive

18%

20%

33%

9%

6%

5%

3%

4%

2%

0% 5% 10% 15% 20% 25% 30% 35%

1 most likely

2

3

4

5

6

7

8

9 least likely

178

Figure 32 Insure too expensive

Figure 33 Too expensive to run a car

Figure 34 No need – public transport good/adequate

33%

26%

20%

5%

5%

3%

3%

3%

2%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

32%

33%

16%

5%

4%

4%

3%

2%

2%

0% 5% 10% 15% 20% 25% 30% 35%

1 most likely

2

3

4

5

6

7

8

9 least likely

5%

4%

8%

25%

18%

13%

10%

8%

8%

0% 5% 10% 15% 20% 25% 30%

1 most likely

2

3

4

5

6

7

8

9 least likely

179

Figure 35 People prefer to walk/cycle - healthier

Figure 36Social media use so people don’t need to drive to meet

Figure 37 Not into cars – no interest

3%

5%

6%

17%

19%

18%

15%

11%

7%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

2%

3%

4%

10%

11%

13%

14%

22%

21%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

2%

3%

4%

10%

14%

12%

20%

17%

18%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

180

Figure 38 Environmental reasons

2%

3%

5%

9%

11%

18%

17%

16%

19%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

181

Ranking by sex Figure 39 First preference


0%

3%

4%

0%

9%

5%

8%

17%

54%

0%

0%

0%

1%

4%

9%

23%

31%

32%

0% 10% 20% 30% 40% 50% 60%


Social media use

Internet shopping


People prefer to walk/cycle -healthier

No need – public transport good/adequate




Female Male

13%

20%

31%

9%

9%

6%

4%

5%

3%

22%

21%

33%

8%

4%

4%

2%

4%

2%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

182

Figure 41 Too expensive to insure


34%

24%

17%

6%

4%

4%

4%

5%

3%

31%

29%

22%

5%

5%

2%

2%

2%

2%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

31%

31%

12%

4%

5%

5%

3%

4%

3%

33%

34%

18%

5%

2%

3%

2%

1%

1%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

183



5%

5%

10%

24%

16%

12%

11%

9%

8%

4%

4%

7%

26%

19%

14%

9%

8%

8%

0% 5% 10% 15% 20% 25% 30%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

5%

6%

8%

15%

19%

14%

15%

11%

7%

2%

4%

5%

17%

19%

20%

14%

11%

7%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

184

Figure 45 Social media use so people don’t need to drive to meet

Figure 46Internet shopping

3%

4%

5%

11%

12%

14%

11%

20%

20%

1%

2%

3%

9%

11%

13%

16%

23%

22%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

3%

4%

6%

10%

10%

15%

15%

17%

19%

3%

2%

3%

11%

13%

14%

17%

16%

20%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

185



3%

4%

5%

13%

13%

13%

18%

15%

16%

2%

2%

3%

9%

14%

11%

21%

19%

19%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

4%

3%

5%

8%

11%

16%

19%

15%

20%

1%

2%

4%

11%

12%

19%

16%

16%

19%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Female Male

186

Ranking by age group Figure 49 Ranking by age group summary

1%

3%

2%

2%

5%

2%

16%

29%

43%

2%

2%

3%

0%

3%

6%

18%

32%

32%

3%

1%

4%

1%

3%

4%

19%

34%

28%

0% 10% 20% 30% 40% 50%



Social media use

Internet shopping






Over 30 20 ‐ 30 Under 20

187


16%

23%

43%

6%

7%

2%

2%

1%

1%

18%

21%

30%

9%

6%

5%

3%

4%

3%

19%

17%

31%

9%

7%

5%

3%

6%

2%

0% 10% 20% 30% 40% 50%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

188


43%

24%

18%

5%

3%

2%

3%

1%

2%

32%

27%

20%

5%

5%

3%

2%

3%

2%

28%

26%

21%

6%

5%

3%

4%

4%

3%

0% 10% 20% 30% 40% 50%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

189


29%

40%

16%

4%

4%

4%

1%

1%

1%

32%

32%

17%

5%

3%

3%

2%

3%

2%

34%

30%

13%

5%

5%

4%

4%

2%

3%

0% 10% 20% 30% 40% 50%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

190


2%

4%

9%

36%

18%

17%

5%

7%

3%

6%

4%

9%

26%

19%

11%

10%

8%

8%

4%

5%

8%

18%

16%

16%

12%

10%

11%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

191


5%

3%

4%

17%

27%

14%

18%

7%

6%

3%

5%

7%

17%

19%

18%

13%

12%

7%

3%

5%

6%

15%

16%

19%

16%

12%

9%

0% 5% 10% 15% 20% 25% 30%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

192


1%

1%

2%

7%

9%

13%

16%

30%

21%

2%

2%

5%

10%

10%

13%

13%

22%

22%

2%

5%

5%

11%

15%

13%

14%

16%

20%

0% 5% 10% 15% 20% 25% 30% 35%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

193

Figure 56 Internet shopping

2%

1%

3%

8%

10%

15%

18%

15%

29%

3%

3%

4%

9%

12%

14%

17%

17%

20%

4%

4%

5%

14%

13%

14%

15%

17%

14%

0% 5% 10% 15% 20% 25% 30% 35%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

194


1%

2%

4%

9%

13%

12%

21%

20%

18%

2%

3%

3%

9%

14%

13%

21%

17%

18%

3%

4%

5%

13%

14%

11%

17%

16%

18%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

195


3%

4%

7%

10%

10%

14%

14%

17%

21%

2%

2%

4%

9%

13%

19%

19%

14%

18%

1%

3%

2%

8%

10%

21%

16%

19%

20%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Over 30 20 ‐ 30 Under 20

196

Ranking by licence holding Figure 59 Ranking by licence holding summary

3%

1%

5%

2%

3%

5%

23%

33%

25%

1%

2%

3%

2%

2%

6%

22%

32%

30%

2%

2%

3%

2%

4%

4%

15%

32%

35%

0% 5% 10% 15% 20% 25% 30% 35% 40%


Social media use

Internet shopping







Full Provisional None

197


23%

20%

25%

8%

8%

4%

5%

4%

2%

22%

23%

30%

9%

6%

3%

2%

4%

1%

15%

20%

36%

9%

6%

5%

3%

5%

2%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

198


25%

26%

26%

7%

4%

5%

2%

3%

2%

30%

27%

21%

5%

5%

2%

4%

2%

3%

35%

26%

18%

5%

5%

3%

3%

3%

2%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

199


33%

30%

15%

6%

2%

4%

2%

5%

3%

32%

33%

17%

5%

2%

4%

3%

1%

2%

32%

34%

15%

4%

4%

4%

3%

2%

2%

0% 5% 10% 15% 20% 25% 30% 35% 40%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

200


5%

5%

10%

21%

19%

13%

12%

8%

6%

6%

3%

10%

29%

18%

11%

7%

9%

8%

4%

5%

8%

24%

18%

14%

11%

8%

9%

0% 5% 10% 15% 20% 25% 30% 35%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

201


3%

7%

6%

17%

22%

14%

16%

7%

9%

2%

3%

9%

17%

20%

19%

14%

12%

5%

4%

4%

6%

16%

18%

18%

15%

12%

7%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

202


1%

2%

3%

13%

8%

10%

10%

25%

27%

2%

4%

4%

6%

10%

16%

15%

22%

23%

2%

3%

5%

10%

12%

13%

15%

20%

19%

0% 5% 10% 15% 20% 25% 30%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

203

Figure 66 Internet shopping

5%

3%

5%

8%

12%

12%

18%

15%

22%

3%

2%

3%

10%

11%

14%

16%

17%

24%

3%

3%

5%

11%

12%

15%

15%

17%

18%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

204


2%

3%

3%

11%

16%

16%

17%

18%

15%

2%

4%

4%

8%

15%

12%

22%

17%

16%

2%

2%

4%

11%

13%

11%

20%

17%

19%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

205


Figure 69 Do you hold a driving licence by age group

3%

5%

7%

8%

8%

23%

18%

14%

14%

1%

1%

3%

11%

14%

19%

17%

16%

17%

2%

3%

5%

9%

12%

16%

16%

16%

21%

0% 5% 10% 15% 20% 25%

1 most likely

2

3

4

5

6

7

8

9 least likely

Full Provisional No

25%

48%

26%

24%

60%

16%

9%

54%

37%

0% 10% 20% 30% 40% 50% 60% 70%

Under 20

20 - 30

31 or more

Over 30 20 ‐ 30 Under 20

206

Travel Modes and ranking Figure 70 Main mode of travel for short trips

Figure 71 Main mode of travel for long trips

20%

6%

33%

36%

6%

0% 5% 10% 15% 20% 25% 30% 35% 40%

Bus

Train/tube

Car

Walk

Cycle

15%

39%

47%

0% 10% 20% 30% 40% 50%

Bus/coach

Train/tube

Car

207

Figure 72 Main mode of travel for short trips by age group

Figure 73 Main mode of travel for short trips by sex

29%

6%

20%

38%

7%

20%

7%

31%

37%

5%

15%

4%

42%

34%

5%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Bus Train/tube Car Walk Cycle

Under 20 20 ‐ 30 31 or more

20%

8%

31%34%

7%

20%

4%

33%

38%

4%

0%

5%

10%

15%

20%

25%

30%

35%

40%


Male Female

208

Figure 74 Main mode of travel for long trips by age group

Figure 75 Main mode of travel for long trips by sex

16%

47%

37%

17%

43%40%

10%

27%

63%

0%

10%

20%

30%

40%

50%

60%

70%

Bus/Coach Train/tube Car

Under 20 20 ‐ 30 31 or more

20%

8%

31%34%

7%

20%

4%

33%

38%

4%

0%

5%

10%

15%

20%

25%

30%

35%

40%


Male Female

209

Figure 76 First priority by main mode of transport for short local trips

3%

3%

4%

4%

6%

7%

5%

34%

35%

8%

3%

8%

3%

8%

11%

11%

30%

19%

2%

2%

2%

2%

2%

2%

19%

30%

38%

1%

1%

4%

1%

1%

5%

19%

37%

31%

3%

1%

3%

3%

15%

4%

14%

26%

33%

0% 5% 10% 15% 20% 25% 30% 35% 40%


Social media use

Internet shopping


People prefer to walk/cycle ‐ healthier





Cycle Walk Car Train/tube Bus

210

Figure 77 First priority by main mode of transport for long trips

Car ownership and ranking

4%

3%

5%

3%

7%

5%

17%

32%

25%

2%

2%

4%

2%

3%

8%

18%

31%

30%

2%

2%

2%

2%

2%

2%

18%

33%

37%

0% 5% 10% 15% 20% 25% 30% 35% 40%


Social media use

Internet shopping







Car Train/tube Bus/coach

211

Figure 78 Car ownership (total sample)

Figure 79 Car ownership by licence holding (n=1730)

Figure 80 Car ownership by sex

Yes, 48%No, 52%

12%

76%

88%

24%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Provisional Full

Yes No

62%58%

38%42%

0%

10%

20%

30%

40%

50%

60%

70%

Male Female

Yes I own a car No I don't own a car

212

Figure 81 Main mode of transport for short local trips by car ownership

Figure 82 Main mode of transport for long trips by car ownership

Figure 83 Access to a car for ‘no car ownership’ by licence holding

9%4%

59%

24%

4%

30%

7% 7%

48%

8%

0%

10%

20%

30%

40%

50%

60%

70%



8%

19%

73%

20%

59%

21%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Bus/Coach Train/tube Car


28% 30%

47%36%

25%34%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Provisional Full

Yes No Sometimes

213

Figure 84 First priority by car ownership

Figure 85 Would you like to own a car at the moment

3%

3%

4%

2%

4%

4%

16%

31%

34%

1%

1%

2%

2%

2%

5%

17%

33%

36%

0% 5% 10% 15% 20% 25% 30% 35% 40%


Social media use

Internet shopping







No Yes

Yes, 24%

No, 16%

Already own a car, 60%

214

Figure 86 Would you like to have a car some day in the future

Figure 87 First priority by would you want to own a car at the moment

Yes ‐ very keen, 14%

Yes ‐ perhaps, 18%

No ‐ definitely not, 4%

Probably not, 4%

Already own a car, 60%

2%

1%

2%

1%

2%

4%

17%

31%

40%

1%

1%

2%

2%

2%

8%

18%

36%

31%

3%

3%

4%

2%

4%

4%

16%

31%

32%

0% 10% 20% 30% 40% 50%


Social media use

Internet shopping







All ready own a car No Yes

216

APPENDIX D Statistical Results

1. Older people Figure 1-1 SEG value

Figure 1-2 Residential area

10%

23%

26%

8%

11%

22%

9%

25%

32%

12%

12%

11%

0% 10% 20% 30% 40% 50%

A

B

C1

C2

D

E

Under 55 Over 55

27%

38%

35%

51%

35%

14%

0% 20% 40% 60% 80% 100%

Central/urban

Suburban

Market town/rural

Under 55 Over 55

217

Figure 1-3 Would you say your general travel patterns have changed in the last two years?


Figure 1-5 Thinking about the long term future do you think you will be traveling more or less than you do now in general?

56%

52%

44%

48%

0% 20% 40% 60% 80% 100%

Over 55

Under 55

Yes No

43%

62%

39%

20%

18%

18%

0% 20% 40% 60% 80% 100%

Over 55

Under 55

Travel more Travel less Travel by different mode

23%

37%

16%

10%

61%

53%

0% 20% 40% 60% 80% 100%

Over 55

Under 55


218

Figure 1-6 Thinking about the long term future do you think you will be traveling more or less than you do now for work?

Figure 1-7 Thinking about the long term future do you think you will be traveling more or less than you do now for education?

Figure 1-8 Thinking about the long term future do you think you will be traveling more or less than you do now for shopping

12%

34%

16%

12%

72%

54%

0% 20% 40% 60% 80% 100%

Over 55

Under 55


7%

20%

12%

13%

81%

68%

0% 20% 40% 60% 80% 100%

Over 55

Under 55


8%

18%

12%

13%

79%

68%

0% 20% 40% 60% 80% 100%

Over 55

Under 55


219

Figure 1-9 Thinking about the long term future do you think you will be traveling more or less than you do now for leisure?

Figure 1-10 Modal choice

26%

31%

8%

10%

66%

59%

0% 20% 40% 60% 80% 100%

Over 55

Under 55


36%

33%

50%

42%

11%

13%

11%

13%

36%

28%

40%

32%

15%

19%

18%

15%

0% 10% 20% 30% 40% 50%

Car – work

Car – education

Car - shopping

Car - leisure

Walk – work

Walk – education

Walk – shopping

Walk - leisure

Under 55 Over 55

220

Figure 1-11 Main mode of travel for work

36%

5%

7%

17%

11%

2%

3%

5%

14%

36%

2%

12%

22%

15%

6%

3%

1%

3%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train

Bus/metro/underground

Walk

Cycle

Van

Other

Varies

Under 55 Over 55

221

Figure 1-12 Main mode for education

33%

8%

7%

18%

13%

1%

3%

3%

15%

28%

7%

11%

18%

19%

5%

2%

2%

9%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies

Under 55 Over 55

222

Figure 1-13 Main mode for shopping

50%

13%

1%

18%

11%

0%

1%

1%

5%

40%

11%

5%

18%

18%

2%

1%

1%

4%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies

Under 55 Over 55

223

Figure 1-14 Main mode for leisure

Figure 1-15 Licence holding

42%

15%

8%

13%

13%

2%

1%

2%

4%

32%

11%

12%

15%

15%

6%

1%

1%

7%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies

Under 55 Over 55

18%

2%

69%

11%

17%

10%

64%

10%

0% 20% 40% 60%

Non driver

Provisional

Full licence

Licence but don't drive

Under 55 Over 55

224

Figure 1-16 Over 55’s licence holding by area

Figure 1-17 Household car ownership

28%

3%

54%

15%

17%

2%

71%

10%

12%

0%

78%

10%

0% 20% 40% 60% 80% 100%

Non driver

Provisional

Full licence


Rural Suburban Central/urban

23%

51%

22%

5%

26%

46%

22%

6%

0% 20% 40% 60%

None

One

Two

Three or more

Under 55 Over 55

225

Figure 1-18 Over 55’s Household car ownership by area

Figure 1-19 Do you expect to have a new car in the coming year or so?

41%

45%

11%

4%

21%

53%

21%

5%

13%

53%

30%

5%

0% 20% 40% 60% 80% 100%

None

One

Two

Three or more


27%

65%

8%

20%

59%

21%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe

Under 55 Over 55

226

Figure 1-20 Is a new car a priority?

6%

82%

12%

55%

27%

18%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe

Under 55 Over 55

227


2. Business travel Figure 2-1 GEG value

13%

31%

30%

12%

11%

4%

9%

34%

37%

8%

8%

3%

7%

14%

31%

17%

22%

9%

0% 5% 10% 15% 20% 25% 30% 35% 40%

A

B

C1

C2

D

E

Rare or never inter-work travel Occasional inter-work travel

Frequent travel during work

228

Figure 2-2 Work travel frequency by SEG value

Figure 2-3 Work travel frequency by residential location

43%

38%

30%

33%

28%

25%

37%

47%

42%

26%

23%

25%

21%

16%

28%

41%

49%

50%

0% 20% 40% 60% 80% 100%

A

B

C1

C2

D

E

Frequent travel during work Occasional inter-work travel

Rare or never inter-work travel

49%

36%

15%

44%

41%

16%

49%

32%

19%

0% 10% 20% 30% 40% 50% 60%

Central/urban

Suburban

Market town/Rural



229




44%

40%

38%

56%

60%

62%

0% 20% 40% 60% 80% 100%


Occasional inter-work travel

Rare or never inter-worktravel

Yes No

68%

49%

61%

18%

18%

23%

14%

33%

17%

0% 20% 40% 60% 80% 100%





36%

33%

30%

10%

10%

10%

55%

56%

60%

0% 20% 40% 60% 80% 100%





230



Figure 2-9 Thinking about the long term future do you think you will be traveling more or less than you do now for shopping?

33%

31%

22%

13%

13%

15%

54%

56%

63%

0% 20% 40% 60% 80% 100%





18%

15%

15%

15%

13%

10%

67%

72%

75%

0% 20% 40% 60% 80% 100%





21%

14%

14%

14%

13%

9%

65%

73%

77%

0% 20% 40% 60% 80% 100%





231



33%

30%

26%

11%

9%

7%

56%

61%

67%

0% 20% 40% 60% 80% 100%





48%

37%

48%

7%

11%

10%

12%

34%

31%

43%

33%

11%

20%

21%

14%

37%

26%

37%

32%

14%

18%

18%

14%

0% 10% 20% 30% 40% 50%

Car – work

Car – education

Car - shopping

Car - leisure

Walk – work

Walk – education

Walk – shopping

Walk - leisure

Rare or never inter‐work travel Occasional inter‐work travel


232


48%

5%

12%

18%

7%

1%

5%

1%

2%

34%

9%

15%

20%

11%

5%

1%

1%

3%

37%

5%

8%

24%

14%

5%

1%

3%

3%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



233

Figure 2-13 Main mode of travel for education

37%

9%

11%

16%

11%

5%

3%

0%

9%

31%

6%

11%

14%

20%

5%

3%

4%

6%

26%

4%

9%

18%

18%

3%

1%

3%

17%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



234

Figure 2-14 Main mode of travel for shopping

57%

10%

4%

11%

10%

2%

2%

1%

3%

43%

10%

3%

14%

21%

2%

1%

1%

4%

37%

10%

5%

22%

18%

1%

0%

1%

6%

0% 20% 40% 60%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



235

Figure 2-15 Leisure

48%

9%

9%

8%

12%

6%

2%

1%

6%

33%

12%

11%

14%

14%

7%

2%

2%

5%

32%

11%

11%

20%

14%

4%

0%

1%

7%

0% 20% 40% 60%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



236



7%

6%

4%

12%

7%

71%

10%

24%

9%

53%

14%

0% 20% 40% 60%

Non driver

Provisional

Full licence




12%

51%

31%

6%

23%

49%

22%

6%

33%

44%

19%

4%

0% 20% 40% 60% 80% 100%

None

One

Two

Three or more



237



23%

62%

15%

21%

58%

21%

13%

63%

24%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe



71%

11%

18%

69%

19%

12%

59%

24%

17%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe



238


3. Migrants Figure 3-1 Migrant SEG value


7%

21%

29%

12%

15%

16%

11%

26%

31%

10%

8%

13%

0% 5% 10% 15% 20% 25% 30% 35%

A

B

C1

C2

D

E

Born in UK or lived 10 years or more Migrants

50%

37%

13%

34%

40%

26%

0% 20% 40% 60% 80% 100%

Central/urban

Suburban

Market town/Rural


239




46%

40%

54%

60%

0% 20% 40% 60% 80% 100%

Migrants

Born in UK or lived 10 yearsor more

Yes No

41%

26%

11%

13%

48%

61%

0% 20% 40% 60% 80% 100%

Migrants

Born in UK or lived 10 years ormore


41%

25%

11%

12%

48%

62%

0% 20% 40% 60% 80% 100%

Migrants



240




25%

28%

14%

13%

61%

59%

0% 20% 40% 60% 80% 100%

Migrants



22%

12%

14%

11%

64%

77%

0% 20% 40% 60% 80% 100%

Migrants



18%

13%

15%

12%

67%

75%

0% 20% 40% 60% 80% 100%

Migrants



241



30%

29%

12%

8%

58%

63%

0% 20% 40% 60% 80% 100%

Migrants



28%

7%

13%

23%

16%

4%

3%

2%

4%

43%

6%

11%

19%

9%

4%

2%

1%

4%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies


242


21%

7%

13%

17%

22%

5%

2%

3%

11%

35%

7%

8%

18%

15%

4%

2%

1%

9%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies


243


32%

12%

6%

19%

20%

2%

1%

1%

5%

49%

11%

3%

17%

13%

1%

0%

1%

4%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies


244

Figure 3-13 Main mode of travel for leisure

24%

13%

13%

15%

17%

5%

1%

2%

9%

41%

13%

9%

14%

12%

5%

1%

1%

5%

0% 10% 20% 30% 40% 50%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies


245


Figure 3-15 Migrant licence holding by area

22%

9%

57%

12%

15%

6%

70%

10%

0% 20% 40% 60%

Non driver

Provisional

Full licence



31%

10%

43%

17%

27%

5%

44%

23%

5%

0%

73%

23%

0% 20% 40% 60% 80% 100%

Non driver

Provisional

Full licence



246


Figure 3-17 Migrant household car ownership by area

31%

48%

19%

3%

23%

50%

23%

4%

0% 20% 40% 60%

None

One

Two

Three or more


37%

47%

13%

3%

28%

46%

24%

3%

12%

55%

28%

5%

0% 20% 40% 60% 80% 100%

None

One

Two

Three or more


247



Figure 3-20 Migrant car ownership with children in the household

8%

80%

11%

23%

49%

28%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe


65%

19%

17%

68%

18%

14%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe


28%

49%

18%

4%

12%

58%

28%

1%

0% 20% 40% 60% 80% 100%

None

One

Two

Three or more

Children None

248


4. BME groups Figure 4-1 SEG values


11%

6%

5%

10%

6%

10%

13%

26%

23%

14%

23%

12%

31%

29%

30%

34%

20%

29%

30%

27%

29%

10%

13%

11%

12%

10%

8%

12%

8%

16%

19%

8%

15%

11%

8%

14%

8%

32%

17%

27%

13%

8%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

White UK

White European

Pakistani/Bangladeshi

African

Caribbean

Any other group

Indian

A B C1 C2 D E

27%

52%

54%

49%

59%

50%

47%

37%

31%

29%

44%

27%

42%

39%

36%

17%

17%

8%

14%

8%

14%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

White UK

White European


African

Caribbean

Any other group

Indian

Central/urban Suburban Market town/rural

249



34%

41%

44%

46%

42%

38%

50%

66%

59%

56%

54%

58%

62%

50%

0% 20% 40% 60% 80% 100%

White UK

White European


African

Caribbean

Any other group

Indian

Yes No

49%

56%

55%

59%

48%

58%

73%

33%

14%

38%

18%

33%

32%

18%

18%

30%

8%

22%

18%

11%

9%

0% 20% 40% 60% 80% 100%

White UK

White European


African

Caribbean

Any other group

Indian


250


24%

40%

40%

40%

36%

30%

29%

12%

9%

14%

13%

14%

10%

14%

64%

51%

46%

47%

50%

60%

57%

0% 20% 40% 60% 80% 100%

White UK

White European


African

Caribbean

Any other group

Indian


251


15%

34%

34%

37%

32%

28%

32%

14%

10%

16%

14%

15%

9%

15%

0% 20% 40% 60% 80% 100%

White UK

White European


African

Caribbean

Any other group

Indian


252


8%

18%

26%

25%

24%

13%

15%

10%

12%

14%

14%

14%

15%

15%

82%

70%

60%

61%

61%

73%

70%

0% 20% 40% 60% 80% 100%

White UK

White European


African

Caribbean

Any other group

Indian


253


8%

10%

26%

26%

19%

15%

21%

11%

13%

13%

15%

12%

12%

18%

80%

77%

61%

59%

69%

72%

61%

0% 20% 40% 60% 80% 100%

White UK

White European


African

Caribbean

Any other group

Indian


254


25%

26%

35%

39%

34%

30%

37%

8%

10%

7%

10%

6%

11%

12%

67%

63%

59%

51%

59%

59%

51%

0% 20% 40% 60% 80% 100%

White UK

White European


African

Caribbean

Any other group

Indian


255


44%

41%

55%

43%

9%

14%

11%

13%

29%

21%

35%

23%

13%

27%

20%

20%

38%

26%

33%

34%

20%

14%

15%

11%

36%

28%

39%

39%

10%

12%

14%

11%

35%

15%

33%

35%

12%

15%

19%

12%

27%

22%

35%

23%

15%

18%

22%

15%

45%

34%

51%

46%

9%

19%

18%

11%

0% 10% 20% 30% 40% 50% 60%

Car – work

Car – education

Car - shopping

Car - leisure

Walk – work

Walk – education

Walk – shopping

Walk - leisure

Indian Any other group Caribbean

African Pakistani/Bangladeshi White European

White UK

256


44%

7%

12%

15%

9%

4%

2%

1%

7%

29%

7%

11%

23%

13%

5%

5%

3%

4%

38%

4%

8%

21%

20%

3%

1%

3%

1%

36%

4%

13%

22%

10%

3%

2%

2%

8%

35%

3%

10%

31%

12%

5%

2%

0%

1%

27%

10%

17%

23%

15%

4%

1%

1%

2%

45%

5%

11%

22%

9%

2%

2%

1%

2%

0% 10% 20% 30% 40% 50% 60% 70%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



White UK

257


41%

8%

6%

14%

14%

3%

2%

2%

11%

21%

5%

10%

8%

27%

7%

1%

1%

18%

26%

7%

11%

27%

14%

2%

2%

2%

10%

28%

7%

13%

23%

12%

4%

2%

2%

9%

15%

2%

15%

40%

15%

3%

2%

2%

6%

22%

9%

12%

20%

18%

5%

3%

3%

7%

34%

8%

11%

18%

19%

4%

2%

2%

3%

0% 10% 20% 30% 40% 50% 60%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



White UK

258


55%

13%

2%

15%

11%

1%

0%

1%

2%

35%

11%

2%

20%

20%

3%

2%

1%

7%

33%

14%

4%

25%

15%

1%

0%

1%

7%

39%

6%

8%

25%

14%

1%

0%

1%

6%

33%

11%

5%

24%

19%

3%

2%

1%

3%

35%

12%

6%

17%

22%

2%

1%

1%

5%

51%

12%

4%

12%

18%

1%

0%

1%

2%

0% 10% 20% 30% 40% 50% 60%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



White UK

259

Figure 4-14

43%

15%

8%

12%

13%

4%

0%

1%

4%

23%

11%

11%

14%

20%

7%

1%

2%

11%

34%

11%

6%

27%

11%

1%

1%

2%

8%

39%

9%

10%

14%

11%

5%

1%

2%

8%

35%

11%

11%

20%

12%

6%

1%

0%

5%

23%

15%

20%

13%

15%

8%

2%

2%

3%

46%

11%

9%

11%

11%

4%

2%

1%

4%

0% 10% 20% 30% 40% 50% 60%

Car as a driver

Car as a passenger

Train


Walk

Cycle

Van

Other

Varies



White UK

260


14%

4%

74%

9%

19%

4%

64%

13%

17%

13%

51%

19%

20%

9%

58%

13%

31%

8%

51%

11%

20%

10%

61%

9%

12%

11%

72%

5%

0% 20% 40% 60% 80% 100%

Non driver

Provisional

Full licence




White UK

261


19%

50%

25%

6%

29%

50%

18%

3%

30%

44%

20%

7%

32%

44%

20%

4%

40%

43%

12%

4%

26%

51%

19%

4%

17%

43%

33%

7%

0% 20% 40% 60% 80% 100%

None

One

Two

Three or more



White UK

262


5%

88%

7%

22%

52%

26%

12%

62%

26%

27%

44%

29%

22%

63%

15%

10%

60%

29%

31%

50%

19%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe

Indian Any other group

Caribbean African

Pakistani/Bangladeshi White European

White UK

263


29%

71%

0%

41%

27%

32%

46%

38%

15%

29%

42%

29%

31%

44%

25%

60%

40%

0%

60%

10%

30%

0% 20% 40% 60% 80% 100%

Yes

No

Maybe

Indian Any other group

Caribbean African

Pakistani/Bangladeshi White European

White UK

264

Figure 4-19 Car ownership with children in the household

10%

57%

28%

5%

21%

50%

28%

1%

21%

42%

26%

11%

18%

54%

27%

2%

18%

58%

21%

3%

13%

56%

28%

3%

11%

49%

37%

2%

0% 10% 20% 30% 40% 50% 60% 70%

None

One

Two

Three or more

Indian Any other group Caribbean African

Pakistani/Bangladeshi White European White UK

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