RESTAURANT REGIONS: AN ECOLOGICAL COMMUNITY BASED MODEL OF RESTAURANT CHAIN DISTRIBUTION IN THE UNITED STATES
Location
Bobo Room, Hodgin Hall, Third Floor
Start Date
8-11-2017 2:15 PM
End Date
8-11-2017 3:15 PM
Abstract
This paper is an exercise in regional classification within the scope of food science. Hierarchical clustering was used to analyze the distribution of Restaurant and Institutions Top 400 restaurant chains within the contiguous United States. This study utilizes a clustering methodology traditionally used in analysis of ecological communities. Each restaurant chain was treated as an individual biological species, and the clustering software analyzed them as such. Ward’s (1963) algorithm was used to group the individual restaurant chain locations towards development of a regional model. Six regions were identified and then scrutinized through comparison to existing perceived regions in the United States. Additionally, the clustering methodology identified Indicator Species (IS) representative of each of the six restaurant regions. The top three statistically significant (IS) were isolated and used to evaluate each region. The characteristics of each (IS) were compared to the cultural, cuisine, and ethnic characteristics of their corresponding geographies. The six regions were found to be statistically significant, spatially familiar, and culturally representative of existing perceived geographical regions.
RESTAURANT REGIONS: AN ECOLOGICAL COMMUNITY BASED MODEL OF RESTAURANT CHAIN DISTRIBUTION IN THE UNITED STATES
Bobo Room, Hodgin Hall, Third Floor
This paper is an exercise in regional classification within the scope of food science. Hierarchical clustering was used to analyze the distribution of Restaurant and Institutions Top 400 restaurant chains within the contiguous United States. This study utilizes a clustering methodology traditionally used in analysis of ecological communities. Each restaurant chain was treated as an individual biological species, and the clustering software analyzed them as such. Ward’s (1963) algorithm was used to group the individual restaurant chain locations towards development of a regional model. Six regions were identified and then scrutinized through comparison to existing perceived regions in the United States. Additionally, the clustering methodology identified Indicator Species (IS) representative of each of the six restaurant regions. The top three statistically significant (IS) were isolated and used to evaluate each region. The characteristics of each (IS) were compared to the cultural, cuisine, and ethnic characteristics of their corresponding geographies. The six regions were found to be statistically significant, spatially familiar, and culturally representative of existing perceived geographical regions.
