Discriminant effects of consumer electronics use-phase attributes on household energy prediction

Ardeshir Raihanian Mashhadi and Sara Behdad

Energy Policy, 2018, vol. 118, issue C, 346-355

Abstract: The aim of this study is to provide a better understanding of the heterogeneities in user-product relationships and their consequences regarding the household energy predictions. Several supervised and unsupervised machine learning algorithms have been applied to a comprehensive data set of residential energy consumptions collected by the US Energy Information Association. The results of the analyses reveal that, while the heterogeneities in the use-phase of consumer electronics could skew their environmental assessment results, they do not possess the same discriminant influences on the household electricity consumption compared to certain socio-demographics or usage of home appliances. Various cross-comparisons among product features and use-phase behaviors have been made and the most important predictors of the residential electricity consumption based on the data have been introduced. Product-level and user-level discussions on the findings have also been provided.

Keywords: Residential electricity consumption; Consumer behavior; User-product interactions; Machine learning (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:enepol:v:118:y:2018:i:c:p:346-355

DOI: 10.1016/j.enpol.2018.03.059

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