Expanding the Big e-Society

Transcript

1. Expanding  the  Big  e-­‐Society:  A   contemporary  model  of  Internet   exclusion,  access  and  investment       Dean  Riddlesden     Department  of  Geography  and  Planning     University  of  Liverpool  
2. Introduc<on  to  the  Research  Project     •  Access  to  high  speed  broadband  has  become  increasingly  important  in  recent   years   •  Universal  Service  Commitment  (introduced  2010)  aimed  to  deliver  a  minimum   connec<on  speed  of  2  Mbps  to  every  household  in  the  UK  by  2012     •  Government  are  keen  to  get  everybody  online  –  jus<fied  by  key  economic   advantages  and  increased  compe<<veness.  Investment  in  broadband   infrastructure  accounted  for  9.5%  of  the  UK’s  GDP  growth  in  the  period   2002-­‐2007.           •  Outside  of  government  and  Ofcom  reports  there  have  been  few  academic  projects   that  aUempt  to  analyse  the  socio-­‐spa<al  structure  of  broadband  access  and   percep<ons  of  the  Internet     •  There  have  been  none  that  use  crowd-­‐sourced  speed  test  data  as  a  proxy  for   access  and  performance  
3. Key  Research  Ques<ons   •  What  is  the  current  geography  of  access  to  fixed  line  and   mobile  broadband  services  in  England?     •  How  is  the  geography  of  access  related  to  indicators  of   rurality  and  depriva<on?     •  What  is  the  current  geography  of  demand  for  broadband   services?  Are  there  dispari<es  between  demand  and   supply?     •  How  can  the  e-­‐society  be  classified?     •  How  can  Interven<on  Scenarios  be  simulated?  
4. Infrastructure   Two  Chapters:   •  Exploring  the  geography  of  access  to  fixed  line  broadband  services  in  England   using  crowd-­‐sourced  speed  check  data     •  Exploring  the  geography  of  access  to  mobile  broadband  in  England       Data:  Fixed  Line:   •  c.7m  crowd-­‐sourced     Internet  speed  test  results  (geocoded)   •  UK  exchange  loca<ons   •  ONS  Postcode  Directory     Data:  Mobile:   •  WiFi  hotspot  loca<on  database   •  Mobile  phone  base  sta<on  database   Output:   Broadband  Speed  Equity,  a  New  Digital  Divide?  –  Applied  Geography  (In  Press)  
5. 0 1 2 3 4 1a: Rural Retirement 1b: Farming Communities 1c: Country Life 2a: Aspirational Migrants 2b: Student Communities 2c: Settled City Living 3a: Urban Deprivation 3b: Connected Achievers 3c: Aspirational Multicultural Families 3d: Challenged Ethnic Mix 4a: Blue Collar Estates 4b: Blue Collar Transitions 4c: Blue Collar Terraces 5a: Socially Mobile Minorities 5b: Ethnic Communities 6a: Inner Suburbs 6b: Established Suburbs 6c: Suburban Aspiration 7a: Industrial Legacy 7b: Hard−Pressed Multi−Ethnic Neighbourhoods 7c: Elderly in Flats 8a: Traditional Trades 8b: Service Sector Urbanities 8c: Late Retirement Preliminary 2011 Output Area Classification Test Results Per Current Postcode
6. 2000 4000 6000 8000 10000 16 21 17 11 1 9 22 8 15 10 12 13 6 0 20 18 23 7 2 19 14 4 3 5 Hour Mean Download Speed (Kbps) URBAN_RURAL_INDEX Hamlet and Isolated Dwelling Less Sparse Hamlet and Isolated Dwelling Sparse Town and Fringe Less Sparse Town and Fringe Sparse Urban >= 10K Less Sparse Urban >= 10K Sparse Village Less Sparse Village Sparse
7. under 5176 5176 to 6705 6705 to 8206 8206 to 9853 9853 to 11516 over 11516 0km 50km100km Geography  of   Aggregate  Speed  
9. Behaviors     One  Chapter:   •  Inves<ga<ng  the  geography  of  demand  for   broadband  services   Data:   •  Oxford  Internet  Survey  (OXIS)   •  ESRC  Understanding  Society  Longitudinal   Survey  (small  area/  geocoded)   – Survey  Ques<on  Bank      
10. OXIS   •  Survey  of  the  general  public  commissioned  by  the  Oxford  Internet   Ins<tute  (OXII)  every  two  years  since  2003     •  Aims  to  gather  informa<on  about  Internet  access,  use  and  aftudes   and  the  difference  this  makes  for  everyday  life  in  Britain     Issues:   •  Representa<ve  sample,  but  small  in  size  -­‐    2660  respondents  across   260  Output  Areas  (OAs)   •  Need  to  es<mate  data  for  all  OAs  in  England   Response:   •  Small  Area  Es<ma<on/  Imputa<on  techniques   •  QUEST  decision  tree  models     •  Predicted  rates  for  41  OXIS  ques<ons  based  on  Age,  NS-­‐SeC,  and   measures  of  rurality.  (Gender,  GOR  poor  predictors)    
14. −60 −50 −40 −30 −20 −10 0 10 20 30 40 50 60 1a: Rural Retirement 1b: Farming Communities 1c: Country Life 2a: Aspirational Migrants 2b: Student Communities 2c: Settled City Living 3a: Urban Deprivation 3b: Connected Achievers 3c: Aspirational Multicultural Families 3d: Challenged Ethnic Mix 4a: Blue Collar Estates 4b: Blue Collar Transitions 4c: Blue Collar Terraces 5a: Socially Mobile Minorities 5b: Ethnic Communities 6a: Inner Suburbs 6b: Established Suburbs 6c: Suburban Aspiration 7a: Industrial Legacy 7b: Hard−Pressed Multi−Ethnic Neighbourhoods 7c: Elderly in Flats 8a: Traditional Trades 8b: Service Sector Urbanities 8c: Late Retirement Output Area Classification 2011 % Difference From National Average OXIS  QH13_Non  by  OAC  
15. Integra<on   Two  Chapters:     •  Crea<ng  a  bespoke  digital  geodemographic   (Infrastructure,  behaviours  &  census  data)   •  Valida<on  (bespoke  geodemographic)       Outcomes:     •  Iden<fy  longitudinal  changes  between  bespoke   geodemographic  and  previous  e-­‐society  classifica<ons     •  Online  Census  data  for  valida<on  
16. Policy  Interac<ons   One  Chapter:     •  Simula<ng  Interven<on  Scenarios   Objec<ves:   •  Use  geodemographic  to  iden<fy  areas  for   infrastructure  investment/  policy  interven<on   •  Review  findings  against  current  government  policy,   schemes,  targets  and  delivery  (e.g.  BDUK)   •  Use  geodemographic  to  profile  common  digital   exclusion  issues   •  Iden<fy  areas  of  high  access/  low  engagement  and  vice   versa      
17. Ques<ons?