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Business and Industry | Ethnic Consumer Patterns

Introduction

How strongly does ethnicity influence consumption? We ask this question in the context of car purchase decisions. In particular, we examine the concept of "ethnocentrism" here, which postulates that consumers normally consider goods from their own country/region superior to others. Given data availability, we focus on Asians and their car purchasing decisions in Southern California. The analysis below will not only allow us to answer this question, but it also demonstrates how GIS analysis can be used for car companies or dealers to reconsider locations. In the light of most recent reorganizations in the car industry and expected changes in the future, this type of analysis may prove especially helpful as a spatial reorganization of dealerships may occur.

To investigate our question of interest, we categorize brands by region of origin (e.g. Toyota and Honda as Asian, BMW as European, Ford and GM as American) and class (roughly corresponding to luxury, middle-class and economy). We then perform a simple spatial cluster analysis to identify dealership clusters, where a dealership cluster can be thought of as a set of dealers that are located close together and far from others. We construct trade areas around those dealership clusters, and calculate, for example, the share of Asian population in the trade area. We compare this share of Asian population with the share of Asian brand car sales in the cluster. We find that in most cases higher shares of Asian population imply higher shares of Asian car sales. However, only low income Asians really have a relatively strong affinity to Asian brands, while middle income Asians are undistinguishable from American buyers, and high income Asians seem to rather buy American brands.

The Method

How many clusters of car dealerships exist in Southern California? Unfortunately, this question turned out to be hard to answer precisely. The reason is that it depends under which conditions a certain dealership should be included in a cluster. For example, should a dealership be included if it is quite far from all the others in a cluster, but offers a different brand? Or should a dealership be excluded from a cluster if it is close by but another dealer already carries the same brand?

We decided to allow a statistical program to answer this question for us. All that we required was that not too many clusters would carry a brand more than once, that the maximum distance between dealers in the largest cluster would not be too large and that there would not be too many clusters that only had one or two dealers. We learned that all three criteria were very hard to fulfill simultaneously. We consequently chose a solution that provided us with reasonable values for most of the clusters. We ended up with 200 clusters, with 13% of clusters having more than one dealership carrying a particular brand, a 36 mile distance for the largest cluster (which is bearable since it is located in a thinly populated area) and about 5% of individual dealers being listed as their own cluster. Note that visual inspection of resulting clusters (see any of the maps provided) would have suggested to combine certain clusters. However, we deliberately did not change clusters based on visual analysis to investigate the quality of this automated procedure.

Share of Asian car sales & Asian population
Share of high end car sales & per capita income
Car dealers by car brand origin & sales volume, per capita income by dealership cluster trade areas
Car dealers by car brand origin & tier, & dealership cluster trade areas
Inland Empire Business Atlas, ©University of Redlands, 2009. Funded in part through a cooperative agreement with the U.S. Small Business Administration. All opinions, conclusions, or recommendations expressed are those of the author(s) and do not necessarily reflect the views of the SBA or the University of Redlands. Site created and maintained by the Redlands Institute.