Reducing Household Energy Consumption: A Qualitative and Quantitative Field Study

Brandon, G; Lewis, Alan

doi:10.1006/jevp.1998.0105

Cited by 394 publications

(284 citation statements)

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“…In addition, attitudes and perceived behavioral control, personal norms, awareness of consequences and ascription of responsibility, have been found to -at least partially -explain the variation in observed energy savings (e.g. Wilhite et al, 1999, Axelrod and Lehman, 1993, Brandon and Lewis, 1999, Verplanken and Orbell, 2003, Abrahamse and Steg, 2009, Mills and Schleich, 2012. Abrahamse and Steg (2009) conclude that socio-demographic variables better explain the level of energy use, while psychological variables such as environmental concerns or attitudes towards energy conservation better explain changes in energy use which require cognitive effort.…”

Section: Resultsmentioning

confidence: 99%

Effects of feedback on residential electricity demand—Findings from a field trial in Austria

et al. 2013

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Marc BrunnerEffects of feedback on residential electricity demand -Findings from a field trial in Austria AbstractThis paper analyzes the effects of providing feedback on electricity consumption in a field trial involving more than 1,500 households in Linz, Austria. About half of these households received feedback together with information about electricitysaving measures (pilot group), while the remaining households served as a control group. Participation in the pilot group was random, but households were able to choose between two types of feedback: access to a web portal or written feedback by post. Results from cross section OLS regression suggest that feedback provided to the pilot group corresponds with electricity savings of around 4.5 % for the average household. Our results from quantile regressions imply that for households in the 30th to the 70th percentile, feedback on electricity consumption is statistically significant and effects are highest in absolute terms and as a share of electricity consumption. For percentiles below or above this range, feedback appears to have no effect. Finally, controlling for a potential endogeneity bias induced by non random participation in the feedback type groups, we find no difference in the effects of feedback provided via the web portal and by post. Highlights• We estimate the effects of feedback on household electricity use in a field trial in Linz, Austria.• Providing feedback on electricity use corresponds with average savings of around 4.5 %.• Effects of feedback are most pronounced in the 30th to the 70th percentile.• Feedback provided via a web portal and by post appears equally effective.

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Section: Resultsmentioning

confidence: 99%

Effects of feedback on residential electricity demand—Findings from a field trial in Austria

et al. 2013

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“…If low income households would be able to reduce their demand, they would do so at the expense of their comfort and wellbeing, as well as convenience [48]. This could be true because low-income households typically use less energy than the average consumer; as a result their ability to conserve energy is reduced [49]. Also, when confronted with an increase in energy costs, lower-income families tend to make "lifestyle cutbacks" [48].…”

Section: Equity Issuesmentioning

confidence: 99%

Residential peak electricity demand response—Highlights of some behavioural issues

Gyamfi

Krumdieck

Urmee

2013

Renewable and Sustainable Energy Reviews

218

111

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Electricity demand response refers to consumer actions that change the utility load profile in a way that reduces costs or improves grid security. The focus of demand response has mainly been on the commercial and big industrial sectors because of the large demand reduction that they can offer to the utility grid operators. Utilities are showing increasing interest in residential demand response (RDR). RDR can be treated as an energy resource which can be assessed and commercially developed, however, there are still some issues that remain to be addressed for RDR to be successful. These include price unresponsiveness of some residential consumers, equity issues and high cost of the metering infrastructure. The aim of this paper is to investigate and present some of the challenges in achieving effective voluntary demand reduction based on a review of residential demand response literature as well as the general residential energy use behaviour literature. The authors propose the use of a hybrid engineering approach using social psychology and economic 2 behaviour models to overcome these challenges and realize the benefits of supply security and cost management.

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“…Energy consumption behaviors of households vary systematically among socioeconomic groups and across geographic locations (Lutzenhiser, 1992;Brandon & Lewis, 1999). Household size and composition are important determinants of energy consumption for residential buildings (O'Neill & Chen, 2002;Kaza, 2010;Brounen, Kok, & Quigley, 2012).…”

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%

Different Regions, Differences in Energy Consumption: Do Regions Account for the Variability in Household Energy Consumption?

Estiri,

Gabriel,

Howard

et al. 2013

SSRN Journal

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This research aims to discover between-region variability in household energy consumption behaviors, using multilevel modeling with data from Residential Energy Consumption Survey in 2009. Where past research focuses on the physical characteristics of housing, our effort in this research centers on between-region variability and micro-level determinants of residential energy usage. We found significant between-region variability with household energy usage across the U.S. Results suggest that the association between heating degree days and energy consumption varies depending on the type of climate that a household lives in. Further, household energy usage is significantly associated with the race of the householder and income. In the discussion section, we connect this outcome to racial disparities between whites and non-whites in location choice, access to housing, and residential stratification. Moreover, the structure of our research reveals the necessity of multilevel modeling in gaining an accurate picture of residential energy consumption for more efficient energy conservation policy.

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Reducing Household Energy Consumption: A Qualitative and Quantitative Field Study

Cited by 394 publications

References 0 publications

Effects of feedback on residential electricity demand—Findings from a field trial in Austria

Effects of feedback on residential electricity demand—Findings from a field trial in Austria

Residential peak electricity demand response—Highlights of some behavioural issues

Different Regions, Differences in Energy Consumption: Do Regions Account for the Variability in Household Energy Consumption?

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