Abstract
Understanding the complexity of store location in sprawling polycentric cities requires exploitation of new spatial analysis methods that can decipher patterns in georeferenced point data. This article shows how the intrametropolitan location of retailing is best understood as a series of interconnected spatial distributions with varying order-based characteristics. A scattered pattern, which initially appears random or chaotic, is a web of differentiated spatial regimes containing wide-ranging order. A variety of clustering and colocation methods are used to uncover spatial patterns of retailing in Phoenix, Arizona. The analysis simultaneously identifies establishment associations and disassociations within and across sectors. Results show that clothing and motor vehicles are the most likely to cluster next to establishments in the same sector. These sectors also have strong intersectoral relationships across retailing. We find limited evidence that the size of establishments significantly increases with distance from sectoral mean centers. Geospatial technologies are increasingly used by individual retailers to locate and manage their facilities. It is important that scholarly analysis of retailing spatial patterns keeps pace, especially as cities grow and land use and land value patterns become more complex.
Original language | English (US) |
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Pages (from-to) | 396-420 |
Number of pages | 25 |
Journal | Professional Geographer |
Volume | 65 |
Issue number | 3 |
DOIs | |
State | Published - Aug 2013 |
Keywords
- clustering
- colocation
- location
- retail
- spatial
ASJC Scopus subject areas
- Geography, Planning and Development
- Earth-Surface Processes