Skip to main content
Log in

The Varying Impact of Geographic Distance as a Predictor of Dissatisfaction Over Facility Access

  • Published:
Applied Spatial Analysis and Policy Aims and scope Submit manuscript

Abstract

This research uses a Geographically Weighted Regression (GWR) analysis to compare perceptions of public service accessibility as captured by an attitudes survey against measures of geographical distance to those services. The 2008 Place Survey in Leicestershire, UK, captured data on respondent dissatisfaction about their access to different services and facilities. In this analysis, survey responses about access to Post Offices and libraries were summarised over census Output Areas. Road distances to the nearest facility were calculated for each Output Area. GWR was used to model the spatial variations in the relationship between facility distance and access dissatisfaction and how these relationships vary within and between different socio-economic groups (in this case OAC groups). The results show that for Post Offices, the effect of geographic distance as a predictor of access dissatisfaction is stronger than for libraries, that its effect varies spatially and that there is considerable variation within and between different socio-economic groups. For Libraries, geographic distance is a weaker predictor of dissatisfaction over access, there is little local variation in the effect of geographic distance as a predictor of library access dissatisfaction and that there is little variation within and between different socio-economic groups. These results indicate that as well as geography, other dimensions related to facility access need to be considered and that these will vary from facility to facility and from group to group.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. http://www.lsr-online.org/leicestershire-place-survey-2008.html

  2. http://www.lsr-online.org/placesurvey.html

  3. http://www.statistics.gov.uk/about/methodology_by_theme/area_classification/oa/default.asp

  4. For a variable to be ‘far below average’ it must have a difference of more than 0.15 below the UK mean

  5. For a variable to be ‘far above average’ it must have a difference of more than 0.15 above the UK mean

References

  • Aday, L. A., & Andersen, R. (1974). A framework for the study of access to medical care. Health Services Research, 9, 208–20.

    Google Scholar 

  • Atkin, C. (2003). Rural communities: human and symbolic capital development, fields apart. Compare, 33(4), 507–518.

    Google Scholar 

  • Bell, P., & Cloke, P. (Eds.). (1990). Deregulation and transport: Market forces in the modern world. London: David Fulton.

    Google Scholar 

  • Bell, P., & Cloke, P. (1991). Deregulation and rural bus services: a study in rural Wales. Environment and planning A, 23, 107–126.

    Article  Google Scholar 

  • Boardman, B. (1998). Rural transport and equity. London: Rural Development Commission.

    Google Scholar 

  • Bowden, C., & Moseley, M. J. (2006). The quality and accessibility of services in rural England: A survey of the perspectives of disadvantaged residents. Wolverhampton: Adas UK and University of Gloucestershire.

    Google Scholar 

  • Bracey, H. E. (1953). Towns as rural service centres: an index of centrality with special reference to somerset. Transactions, Institute of British Geographers, 19, 95–105.

    Google Scholar 

  • Brunsdon, C. F., Fotheringham, A. S., & Charlton, M. (1996). Geographically weighted regression—a method for exploring spatial non-stationarity. Geographical Analysis, 28, 281–298.

    Article  Google Scholar 

  • Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1998). Spatial nonstationarity and autoregressive models. Environment and Planning A, 30, 957–97.

    Article  Google Scholar 

  • Campaign for Better Transport. (2011a). Save our buses: Defending the country s get up and go ! (London: Campaign for Better Transport) http://bettertransport.org.uk/campaigns/save-our-buses [accessed 7/2/11].

  • Campaign for Better Transport. (2011b). Buses Matter: a report by Campaign for Better Transport for the RMT. (London: Campaign for Better Transport) http://bettertransport.org.uk/system/files/Buses+Matter.pdf [accessed 7/2/11].

  • Comber, A. J., Brunsdon, C., Hardy, J., & Radburn, R. (2009). Using a GIS-based network analysis and optimisation routines to evaluate service provision: a case study of the UK Post Office Applied Spatial Analysis and Policy, 2(1), 47–64.

    Google Scholar 

  • Comber, A. J., Sasaki, S., Suzuki, H., & Brunsdon, C. (2011). A modified grouping genetic algorithm to select ambulance site locations. International Journal of Geographical Information Science, 25(5), 807–823.

    Article  Google Scholar 

  • Commission for Rural Communities. (2010). The state of the countryside 2010. Wetherby: Countryside Agency Publications.

    Google Scholar 

  • Department of Communities and Local Government (DCLG). (2009). Place survey 2008–09: Manual. Wetherby: Communities and Local Government Publications.

    Google Scholar 

  • Department for Communities and Local Government. (2010). Draft Structural Reform Plan, Department for Communities and Local Government, London www.communities.gov.uk/publications/corporate/structuralreformplan.

  • Farrington, J., & Farrington, C. (2005). Rural accessibility, social inclusion and social justice: towards conceptualisation. Journal of Transport Geography, 13, 1–12.

    Article  Google Scholar 

  • Farrington, J., Gray, D., Martin, S., & Roberts, D. (1998). Car dependence in rural Scotland: challenges and policies. Edinburgh: The Scottish Office.

    Google Scholar 

  • Findlay, A. M., Stockdale, A., Findlay, A., & Short, D. (2001). Mobility as a driver of change in rural Britain: an analysis of the links between migration, commuting and travel to shop patterns. International Journal of Population Geography, 7, 1–15.

    Article  Google Scholar 

  • Forsyth, A., Lytle, L., & Van Riper, D. (2010). Finding food: Issues and challenges in using Geographic Information Systems to measure food access. Journal of Transport and Land Use, 3(1), 43–65.

    Google Scholar 

  • Fotheringham, A. S., Charlton, M., & Brunsdon, C. (1997). Measuring spatial variations in relationships with geographically weighted regression. In M. M. Fischer & A. Getis (Eds.), Recent developments in spatial analysis, spatial statistics, behavioral modeling and neurocomputing. London: Springer.

    Google Scholar 

  • Fotheringham, A. S., Charlton, M. E., & Brunsdon, C. (2001). Spatial variations in school performance: a local analysis using geographically weighted regression. Geographical and Environmental Modelling, 5, 43–66.

    Article  Google Scholar 

  • Fotheringham, A. S., Brunsdon, C., & Charlton, M. E. (2002). Geographically weighted regression: The analysis of spatially varying relationships. Chichester: Wiley.

    Google Scholar 

  • Gray, D., Shaw, J., & Farrington, J. (2006). Community transport, social capital and social exclusion in rural areas. Area, 38(1), 89–98.

    Article  Google Scholar 

  • Griffith, D. A. (2008). Spatial-filtering-based contributions to a critique of geographically weighted regression (GWR). Environment and Planning A, 40, 2751–2769.

    Article  Google Scholar 

  • Halliday, J. (1997). Children s services and care: a rural view. Geoforum, 28, 103–119.

    Article  Google Scholar 

  • Halliday, J., & Little, J. (2001). Amongst women: exploring the reality of rural childcare. Sociologia ruralis, 41(4), 423–437.

    Article  Google Scholar 

  • Higgs, G., & White, S. D. (1997). Changes in service provision in rural areas. Part 1: the use of GIS in analysing accessibility to services in rural deprivation research. Journal of Rural Studies, 13(4), 441–451.

    Article  Google Scholar 

  • Huang, Y. F., & Leung, Y. (2002). Analysing regional industrialization in Jiangsu province using Geographically Weighted Regression. Journal of Geographic system, 4(2), 233–249.

    Article  Google Scholar 

  • Langford, M., & Higgs, G. (2010). Accessibility and public service provision: evaluating the impacts of the Post Office Network Change Programme in the UK. Transactions of the Institute of British Geographers, 35(4), 585–601.

    Article  Google Scholar 

  • Li, T., Corcoran, J., Pullar, D., Robson, A., & Stimson, R. (2009). A geographically weighted regression method to spatially disaggregate regional employment forecasts for south east Queensland. Applied Spatial Analysis and Policy, 2, 147–175.

    Article  Google Scholar 

  • Little, J., Ross, K., & Collins, I. (1991). Women and employment in rural areas. London: Rural Development Commission.

    Google Scholar 

  • Lowe, P., Bradley, T., & Wright, S. (1986). Deprivation and welfare in rural areas. Norwich: GeoBooks.

    Google Scholar 

  • Mahar, C. (1991). On the moral economy of country life. Journal of Rural Studies, 7, 363–372.

    Article  Google Scholar 

  • Maroko, A. R., Maantay, J. A., Sohler, N. L., Grady, K. L., & Arno, P. S. (2009). The complexities of measuring access to parks and physical activity sites in New York City: a quantitative and qualitative approach. International Journal of Health Geographics, 8, 34.

    Article  Google Scholar 

  • McEntee, J., & Agyeman, J. (2010). Towards the development of a GIS method for identifying rural food deserts: geographic access in Vermont, USA. Applied Geography, 30, 165–176.

    Article  Google Scholar 

  • Moseley, M. (Ed.). (1978). Social issues in rural Norfolk. Norwich: University of East Anglia.

    Google Scholar 

  • Moseley, M. (1979). Accessibility: the rural challenge Methuen, London.

  • Nakaya, T., Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2005). Geographically weighted poisson regression for disease association mapping. Statistics in Medicine, 24, 2695–2717.

    Article  Google Scholar 

  • Office, C. (2010). The coalition: Our programme for government. London: Cabinet Office.

    Google Scholar 

  • Pavis, S., Platt, S., & Hubbard, G. (2000). Young people in rural Scotland: pathways to social inclusion and exclusion. York: Joseph Rowntree Foundation.

    Google Scholar 

  • Phillips, M. (2010). Rural community vitality and malaise: moving beyond the rhetoric . In ESRC and Scottish Government (Ed.), Rural community empowerment in the 21st century: building a can-do culture Economic and Social Research Council, Swindon.

  • Pinkerton, J., Hassinger, E., & O’Brien, D. J. (1995). Inshopping by residents of small communities. Rural Sociology, 60, 467–480.

    Article  Google Scholar 

  • Powe, N. A., & Hart, T. (2009). Competing for the custom of small town residents: exploring the challenges and potential. International Journal of Retail and Distribution Management, 37(9), 732–747.

    Article  Google Scholar 

  • Prentice, R. (1991). “Out-shopping” and the externalisation of the Isle of Man retailing economy. Scottish Geographical Magazine, 108, 17–21.

    Article  Google Scholar 

  • Rural Evidence Research Centre. (2009). Defra classification of Local Authorities in England: updated technical guide (London: Rural Evidence Research Centre) http://www.rerc.ac.uk/findings/documents_rural/LA_Class_Technical_Guide_April_2009.pdf [accessed 7/2/11].

  • Sasaki, S., Comber, A. J., Suzuki, H., & Brunsdon, C. (2010). Using genetic algorithms to optimise current and future health planning—the example of ambulance locations. International Journal of Health Geographics, 9, 4. doi:10.1186/1476-072X-9-4.

    Article  Google Scholar 

  • Sasaki, S., Igarashi, K., Fujino, Y., Comber, A. J., Brunsdon, C., Muleya, C. M., & Suzuki, H. (2011). The impact of community-based outreach immunization services on immunization coverage with GIS network accessibility analysis in peri-urban areas, Zambia. Journal of Epidemiology and Community Health. doi:10.1136/jech.2009.104190.

  • Storey, P., & Brannen, J. (2000). Young people and transport in rural areas. Leicester: Joseph Rowntree Foundation, Youth Work Press.

    Google Scholar 

  • Tyler, K. (2006). The racialised and classed constitution of English village life. Ethnos, 68(3), 391–412.

    Article  Google Scholar 

  • Urry, J. (2002). Mobility and proximity. Sociology, 36, 255–74.

    Article  Google Scholar 

  • Vickers, D. W., & Rees, P. H. (2007). Creating the national statistics 2001 output area classification. Journal of the Royal Statistical Society, Series A, 170(2), 379–404.

    Google Scholar 

  • Wheeler, D. (2007). Diagnostic tools and a remedial method for collinearity in geographically weighted regression’. Environment and Planning A, 39, 2464–2481.

    Article  Google Scholar 

  • White, S. D., Guy, C., & Higgs, G. (1997). Changes in service provision in rural areas. 2. Changes in post office provision in mid-Wales: a GIS-based evaluation. Journal of Rural Studies, 13(4), 451–465.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Rob Radburn and Tom Purnell of the Research and Insight Team at Leicestershire County Council, for use of the (anonymised) Place Survey data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexis Comber.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Comber, A., Brunsdon, C. & Phillips, M. The Varying Impact of Geographic Distance as a Predictor of Dissatisfaction Over Facility Access. Appl. Spatial Analysis 5, 333–352 (2012). https://doi.org/10.1007/s12061-011-9074-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12061-011-9074-8

Keywords

Navigation