Geodemographic classifications, the digital divide and understanding customer take-up of new technologies

  • Authors:
  • P. Longley;D. Ashby;R. Webber;C. Li

  • Affiliations:
  • -;-;-;-

  • Venue:
  • BT Technology Journal
  • Year:
  • 2006

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Abstract

The imperatives of social cohesion make it necessary to consider the highly variable characteristics of users alongside the design and implementation of IT networks and services. In this context much has been written on the so-called `digital divide' in society. Recent ESRC-funded research at UCL has illustrated how it is simplistic to think of the impacts of new information and communication technologies (ICTs) in terms of a single, or even small number of, `digital divides'. As developments in what has been termed the `e-society' reach wider and more generalised audiences, so it becomes appropriate to think of digital media as having wider-ranging but differentiated impacts upon consumer transactions, information gathering and citizen participation.This paper describes the development of a detailed, nationwide household classification based on levels of awareness of different ICTs, levels of use of ICTs, and their perceived impacts upon human capital formation and the quality of life. It illustrates how geodemographic classification makes it possible to provide context for detailed case studies, and hence identify how policy might best improve both the quality and degree of society's access to ICTs. We have provided a more detailed overview of the methodology elsewhere [1, 2] and here we also illustrate how the classification may be used to investigate a range of regional and sub-regional policy issues.A particularly innovative aspect of this classification is the Web resource hosted at www.spatial-literacy.org/esocietyprofiler. This site makes it possible to look at the classification system, aggregated to unit postcodes, across Great Britain. Users can look at national distributions for each of the groups and types in the classification, and offer feedback as to whether the classification appears to work for any locality.