Jessica Whitehead
A Geodemographic Segmentation of Residential Energy Consumers ©2016
The Canadian residential energy-sector is seen as a relatively untapped opportunity to reduce the urban environmental footprint. Research has shown that an effective way to drive household energy saving is by providing relevant information and feedback. This paper presents a methodology for building an application-specific geodemographic segmentation system for the purpose of developing tailored energy-awareness strategies and campaigns in the Toronto Census Metropolitan Area. This multivariate cluster analytic approach offers the prospect of blending energy-related variables with traditional census data to identify and describe neighborhoods in terms of their level of energy consumption, sociodemographic characteristics, and propensity for behavioral change. Considering that the widely used k-means clustering algorithm is inherently aspatial, Getis-Ord Gi* statistics were integrated into the segmentation system as an exploratory technique aimed at increasing the spatial homogeneity of the final clusters. A review of literature is provided to gain a better understanding of the complex relationship between energy-consumption, sociodemographic characteristics and energy-saving behaviors and attitudes. Based on existing studies, eight common themes were identified; energy expenditure, income, age and gender, dwelling and tenure, education, ethnicity and geography. The k-means cluster analysis revealed nine energy consumer segments: energy estates, comfort communities, spacious outskirts, new communities, big family fringe, economical living, green heritage, conservative condos and low-impact renters. Findings emphasize that distinct neighborhood energy-consumer types exist within the Toronto CMA that can be described in terms of their dwelling and occupant similarities, as well as energy-consumption and -saving potential. The paper concludes by suggesting possible segment-specific energy-saving strategies and how this research is situated within the emerging field of smart cities and broader urban sustainability discussion.