D4.1 – Report on qualified clustering input attributes

Sobhan Naderian
2022 Zenodo  
This report captures the results of an extensive literature review of studies that cluster citizens in terms of their energy/environmental behaviors. The report maps the factors that might be used in the literature to create clusters for decarbonization under the work of WP4. Outputs of the review are presented at two levels, according to whom the data clusters refer to, namely individual and collective. At an individual level, major variables for clustering energy behaviors were categorized as
more » ... socio-economic and demographic, psychological, energy consumption/environmental patterns across different areas of life (housing, transport, etc.), and other contextual variables. At a collective level, major variables were categorized as socio-economic and demo- graphic, energy infrastructure variables, energy consumption profiles, environmental performance, and other contextual factors. Establishing clusters of citizens based on their individual attributes leads to their distinct grouping, which can provide insights regarding their energy behavior and lifestyle and can assist the development of policies targeting specific groups of citizens. However, when con- sidering spatially targeted policies, "aggregated level" data (e.g., at neighborhood or even at building level) might be more appropriate than household level data (Reyna et al., 2016). In the context of this study, clustering data for a single person or household fall under the individual level (although the house could be occupied by one or more persons), while clustering data collected at any scale bigger than household is considered collective. Finally, a potentially insightful way to cluster citizens and groups of citizens may be based on their needs/priorities (affordability, access to energy, sustainability, efficiency).
doi:10.5281/zenodo.7142966 fatcat:eexqln3cofbejiljsvf7kjspeq