Characterizing the Composition of Economic Activities in Central Locations

Abstract

This research draws on advances in spatial networks by representing a city as a weighted primal graph of a street network; this format takes into account the context of the location and its importance. The link-based multiple centrality indexes (L-MCIs) are introduced to represent location properties in terms of closeness, intermediacy, straightness, and accessibility to all other locations. The proposed methodology was built on concepts of the multiple centrality assessment model. Results from the L-MCIs clearly identified the major city centers in Santa Barbara County, California, on the basis of the geometric configuration of the network. Moreover, these centrality indexes also exhibited some unique properties that could be observed across other network structures. A clustering technique accounted for spatial dependence in centrality values across multiple spatial scales; this technique aided in classifying the region into locations of high centrality and low centrality. The novelty of this approach was further demonstrated in examining the relationship between the structural properties of the street network and spatial organization of economic activities in Santa Barbara County. Results from this study confirm that link-based network centrality indexes are important determinants of the spatial distribution of economic activities. Professional services and retail trade form a major proportion of economic activities in locations with very high centrality values, for example, downtown areas. Locations with high betweenness centrality values are especially attractive to retail trade activities, because they generate a greater potential for business opportunities. The results clearly revealed the presence of a core–periphery type of city model in Santa Barbara County.