1983
DOI: 10.1016/0167-4870(83)90057-0
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A behavioral model of residential energy use

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Cited by 276 publications
(189 citation statements)
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“…number of children and adults, sex of household members). For example, while the presence of children is expected to increase energy use at home (Van Raaij & Verhallen, 1983), the number of adults has a much larger influence on total energy use than the number of children (Hirst, Goeltz, & Carney, 1982).…”
Section: The Effects Of Household Characteristics On Energy Consumptionmentioning
confidence: 99%
See 1 more Smart Citation
“…number of children and adults, sex of household members). For example, while the presence of children is expected to increase energy use at home (Van Raaij & Verhallen, 1983), the number of adults has a much larger influence on total energy use than the number of children (Hirst, Goeltz, & Carney, 1982).…”
Section: The Effects Of Household Characteristics On Energy Consumptionmentioning
confidence: 99%
“…Generally, energy consumption indices are positively associated with income (Hirst, Goeltz, & Carney, 1982;Brandon & Lewis, 1999;Kahn, 2000;Van Raaij & Verhallen, 1983;Santin, 2011;Brounen, Kok, & Quigley, 2012;O'Neill & Chen, 2002). Yet, there are complexities in the energy consumption of lower-income groups.…”
Section: The Effects Of Household Characteristics On Energy Consumptionmentioning
confidence: 99%
“…As is illustrated in figure 1, in the case of heating, lower annual consumption costs will most probably be compensated by a demand for more heating related benefits. Van Raaij et al [7] mention such rebound as one of the factors linking attitude to the five behavioral patterns discerned, with the term attitude used as umbrella for concerns and benefits -price, environment, energy, health and comfort-and behavior standing for the way attitudes are translated in every day's life. Heating related benefits are health and comfort.…”
Section: User's Behavior and Reboundmentioning
confidence: 99%
“…There are several factors that drive household electricity consumption behavior, such as energy-related attitudes, socio-demographic factors, building characteristics, energy prices, etc. van Raaij and Verhallen [7] recognize this problem and suggest that habits can become alternative predictors of electricity consumption, because routines or habits may resist the cognitive and financial drive and still prevail over rational alternatives. In this sense, Joana M. Abreu et al [8] propose a methodology which demonstrates that it is possible to use pattern recognition methodologies to identify habitual electricity consumption behavior given the intrinsic characteristics of the residents.…”
Section: Existent Work About Intelligent Energy Management Systemsmentioning
confidence: 99%