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Wednesday, August 5, 2020 | History

2 edition of Deriving supply-side variables to extend geodemographic classification found in the catalog.

Deriving supply-side variables to extend geodemographic classification

James Debenham

Deriving supply-side variables to extend geodemographic classification

by James Debenham

  • 176 Want to read
  • 30 Currently reading

Published by University of Leeds, School of Geography in Leeds .
Written in English

    Subjects:
  • Population density -- Economic aspects.

  • Edition Notes

    Includes bibliographical references.

    StatementJames Debenham, Graham Clarke & John Stillwell.
    SeriesWorking paper (University of Leeds. School of Geography) -- 95/19
    ContributionsClarke, Graham, 1960-, Stillwell, John., University of Leeds. School of Geography.
    The Physical Object
    Paginationv, 61p. :
    Number of Pages61
    ID Numbers
    Open LibraryOL16390938M

    Published in Cybergeo: European Journal of Geography, Book Reviews Mechtild Rössler McEwan C., , Gender, geography and empire: Victorian women . Methodologically, rather than using traditional measures of demographic status to explore the contextual factors spurring broadband availability, this paper utilizes a geodemographic classification system to help clarify the social, demographic and economic differences at the local level; highlighting their potential impacts on broadband by:

    How geodemographic classifications are built. Richard Webber Introduction. geodemographic classifications to be optimised, initially at first, on a country by county basis. No two countries’ data infrastructure is the same. counts to create three separate variables for use in the classification . The classification of small areas into geodemographic or lifestyle types by means of multivariate statistical techniques was first undertaken on a national basis for local authorities and wards in Britain in the late s using Small Area Statistics from the Population Census (Webber, ; Webber and Craig, ). In the following Cited by: 9.

    A list of the reports produced by the NWRRL, (many with online abstracts), and information on ordering copies of the complete documents. Topics covered include the classification of residential districts, the issues of aggregation and the MAUP in the British Census, and the potential for fuzzy classification systems in geodemographic targeting. Geodemographic Information is based on a combination of demographics (age, gender, life-cycle stage, and occupation) with geographical area. View Glossary. About Us. As the leading voice, resource and network of the marketing research and data analytics community, the Insights Association helps its members create competitive advantage. All our.


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Deriving supply-side variables to extend geodemographic classification by James Debenham Download PDF EPUB FB2

2 Our contention is that the traditional systems pay no attention to the supply-side characteristics of the market that also vary spatially, and therefore we argue that existing systems might not be totally fulfilling the criteria of business need.

We suggest that no Deriving supply-side variables to extend geodemographic classification. DERIVING SUPPLY-SIDE VARIABLES TO EXTEND GEODEMOGRAPHIC CLASSIFICATION 1 INTRODUCTION Geodemographics involves the “classification of small areas. This paper argues that there may be considerable advantages to including supply-side indicators within geodemographic systems.

Whilst the term ‘supply’ in this context might imply the number of consumer services already in an area, equally important for understanding demand are variables such as the supply of jobs and houses.

DERIVING SUPPLY-SIDE VARIABLES TO EXTEND GEODEMOGRAPHIC CLASSIFICATION. Deriving supply-side variables to extend geodemographic classification By James Debenham, Graham Clarke and John Stillwell No static citation data No static citation data Cite.

The supply side variables proposed here a re designed to test for such d ependencies, while also building up a picture of the employment characteristics of an area. Tabl e 3 details the suite of.

Using the regional example of Yorkshire and Humberside in northern England, we indicate how a suite of supply-side variables relating to the labour market can be assembled and used alongside a suite of demand variables to generate a new area : J.

Debenham, G. Clarke and J. Stillwell. Debenham, J, Clarke, G, Stillwell, J,“Deriving supply-side variables to extend geodemographic classification”, working paper, School of Geography, University of Leeds Google Scholar Debenham, J, Clarke, G, Stillwell, J,“Extending geodemographic classification: A new regional prototype” Environment and Planning A 35 Cited by: Nevertheless it has been shown that geodemographics can be extended using supply-side and change variables to create a classification system that measures small areas on.

Deriving supply-side variables to extend geodemographic classification [Texte intégral] Article Paru dans Cybergeo: European Journal of Geography, Dossiers.

A geodemographic classification provides a set of categorical summaries of the built and socio-economic characteristics of small geographic areas. Thus, geodemographic segmentation leaves very little scope to cater to individual differences.

In fact, they are totally ignored. In fact, they are totally ignored. This, it is not necessary that the segregation is bound to yield good results for the company.

Introduction “Geodemographics is the analysis of people based on a statistical classification of the area in which they live” which “aims to capture the important socio-economic dimensions of and differences between, neighbourhoods”.Such classifications are created from data primarily collected from the census (e.g.) or by combining census, survey and commercially motivated Cited by: geodemographic classification systems remain purely demand based and static.

Nevertheless it has been shown that geodemographics can be extended using supply-side and change variables to create a classification system that measures small areas on theFile Size: KB.

*Market segmentation in which consumers are grouped according to demographic variables, such as income and age, and identified by a geographic variable, such as post code or zip code.

The base data is obtained from the census data. Two principles are involved: (1) people who live in the same neighbourhood, defined by a census enumeration district, are likely to share similar buying habits; (2.

¾Including - education, socio-economic class, car ownership & commuting and health & care. Employment attributes. ¾Including - level of economic activity and employment class type.

How many data inputs are involved.Output Areas, 41 Variables = 9, data points. Creating a Geodemographic Classification. Geodemographic Segmentation 1. Geodemographic Segmentation 2. Geodemographic Segmentation o identifies specific households in a market by focusing on local neighborhood geography o create classifications of actual, addressable, mappable neighborhoods where consumers live and shop 3.

Tryon, R.C.: Cluster analysis; correlation profile and orthometric (factor) analysis for the isolation of unities in mind and personality., Ann Arbor, Mich.: Edwards.

The variables are size, division, composition in terms of age and gender, literacy rate and other human factors. Geography is the study of the location and space vis-a-vis the variation in both physical and human phenomena. Geodemographic segmentation in marketing relies on the following assumptions of consumer behaviour: 1.

Based on these principles, geodemographic segmentation helps to infer the characteristics and likely behaviour patterns of the residents in each area, with the additional benefit that the geographical locations of neighbourhoods and segments are known and reachable. In there was just one neighbourhood classification in the UK.

Building a Geodemographic Classification • Step Check Correlation of the Variables Building a Geodemographic Classification • Step Select variables Building a Geodemographic Classification • Step Specify „number of clusters‟ and „spatial area‟ Number of Clusters Spatial Area Deriving new variables to extend geodemographic classification.

we indicate how a suite of supply-side variables relating to the labour market can be assembled and used alongside a suite of.In marketing, geodemographic segmentation is a multivariate statistical classification technique for discovering whether the individuals of a population fall into different groups by making quantitative comparisons of multiple characteristics with the assumption that the differences within any group should be less than the differences between groups.