The environmental product variety and retail rents on central urban shopping areas: A multi-stage spatial data mining method

Abstract

This study examines the relationship between various measures of environmental product variety and retail rents in central urban shopping areas. Using a Geographic Information System (GIS)-based detailed survey database, this research identified 34 layers of environmental product variety in the most representative single-centred shopping areas of the six largest cities in Taiwan. This research extracted layers of product variety and other measures of product variety, such as the number of layers of product variety above each point of interest, the density, the Core/Periphery factor scores, the Shannon entropy index, the Simpson diversity index and the Herfindahl–Hirschman index of each street line buffer area. The proposed method was used to generate three-dimensional maps of the rent gradient and the extracted core and periphery layers of product variety. Thus, a tool was developed for examining the variety features from various angles. The results showed that, in general, the higher the product variety, the higher the rents. Nevertheless, the scores for the core and periphery of the environmental product variety were the dominant determinants; street line buffer areas can only have lower rents if they lacked the correct (i.e. the core layers) environmental product variety, even if they have higher measurements of other variety features.