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Spatial analysis consists of quantitative, statistical techniques of analysis applied to data with a spatial dimension. An example of its application might be an investigation into how consumption patterns are similar in different neighborhoods associated with similar socioeconomic profiles. Spatial analysis may be used to explore how spatial factors interact with other phenomena, or to control for spatial factors to investigate other, nonspatial, factors. With the development of information technology and increasing capacity of computers, spatial analysis has become increasingly associated with geographic information systems (GIS). In addition, the development of sensors and scanners, such as video cameras and GPS devices, to capture spatial data and record the location of objects and phenomena has made spatial data more available.

A brief introduction describes the growing importance of space to social scientists. Following this, the concepts and methods used in spatial analysis are explored, highlighting the criticisms and potential problems of spatial analysis. The next section examines how spatial analysis has been developed and applied to the investigation of consumer culture. The final section discusses future directions in the spatial analysis of consumer culture.

Until recently, social science was primarily interested in how social phenomena evolved over time, and little attention was given to space or geography. Space tended to be seen as a passive receptacle containing social phenomena largely shaped by time or history. Therefore, spatial matters tended to be viewed as playing only a minor role. However, with the work of authors such as David Harvey, Doreen Massey, John Urry, and Ash Amin over the past twenty or thirty years, space has emerged at the forefront of discussion in the social sciences. While space has great relevance to the study of the consumer, spatial analysis's association with a quantitative approach to research has meant its appeal has been limited to particular sections of the academic community and to public sector planners and private commerce. With the recent influence of critical theory in the social sciences, often referred to as the “cultural turn,” academics interested in consumer culture have often opted for a more qualitative approach. That is not to deny the great progress that has been made, and the flourish of interest, in spatial analysis over the last two decades.

Concepts, Methods, and Criticisms

Spatial analysis includes a wide range of different techniques and methods that build on and augment the quantitative statistical methods more generally applied across the social sciences. Spatial data can require specific methods of analysis. Specialist spatial techniques include spatial sampling, the use of grids and references, analysis of networks, spatial patterning, and spatial interpolation. The development of GIS software such as ArcGIS has greatly improved the speed and ease with which the techniques can be carried out. GIS software requires boundary information on the area under study. A number of different such data sets at different spatial scales for the United Kingdom can be downloaded online at Edina UKborders. National censuses, national health services, police records, and consumer surveys all provide useful data sources.

Some key concepts form the foundations of spatial analysis. One such concept is that “everything is related to everything else, but near things are more related than distant things” (Tobler 1970, 236). Referred to as the “first law of geography,” this is central to many methods for the analysis of spatial data, according to Christopher D. Lloyd. In empirical terms, this is termed spatial autocorrelation: data are not independent of one another, but values in nearby places tend to be more similar than values in locations that are far apart. Neighboring values tend to be similar.

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