This project attempts to bolster scholarly discourse on the use of social capital to solve collective action problems related to energy behavior. Despite the growing prominence of energy analysis in U.S. policy since the 1970’s, human social behavior has received comparatively little attention as a major factor in explaining variation in energy consumption.  Environmental behavioral and policy research has also yet to explore seriously the impact of various forms of social capital on behavioral and attitudinal trends in unsustainable energy consumption. The suggested analysis aims specifically to determine the influence of technology-driven social norms and connectedness on energy conservation priorities. It employs data collected through a residential energy customer segmentation study that links energy consumption and behavioral data to a uniquely rich set of attitudinal survey measures.

             Negative binomial regression techniques are used to estimate the conservation implications of increased social capital as reflected by heavy use of online networking tools such as Facebook, Twitter, and MySpace.   Models will test whether heavy users of these tools place high levels of importance on environmental priorities such as the need to confront climate change.  Additional analysis examines whether survey participants are “practicing what they preach” by comparing these attitudinal measures to their actual levels of energy consumption.   The data allow for count measures of different priorities based on a 10-point sticker allocation system in which survey respondents placed 20 stickers across an array of 8 competing priorities such as cost savings, comfort, and environmental protection.

             Results confirm theoretical connections between web-based social capital and conservation priorities.  High levels of web-use are strongly associated with pro-environmental attitudes relative to competing cost and comfort-based priorities.   Further, each additional point allocated to environmental protection is associated with a 2.4 % decrease in annual electricity expenditure. This information is directly relevant to policymakers, utility managers, and industry representatives seeking to design energy strategies that capitalize on differences in human behavior with regard to their attitudes and use of technology.  Such enhanced understanding of residential energy behavior the will allow managers to target receptive demographics and effective technological solutions in designing energy policy. It will also inform new efforts to create technologies, educational campaigns and adaptations to existing utility systems that lead to lower levels of primary residential energy consumption in the U.S.