E-resources
Peer reviewed
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Chen, Chien-fei; Xu, Xiaojing; Arpan, Laura
Energy research & social science, March 2017, 2017-03-00, Volume: 25Journal Article
This study investigated a set of social-psychological predictors affecting smart meter support and adoption intention based on the Technology Acceptance and Sustainable Energy Technology Acceptance Models among 711 U.S. residents. Despite low levels of adoption in the U.S., this study suggested that the majority of our participants supported smart meter technology and were willing to adopt this technology. Two perceived technology attributes – usefulness and risk to privacy – had direct effects on support for smart meter installation and adoption intention, while the other technology attribute, perceived cost, had no impact. Individual differences in trust in one’s utility company and problem perception related to energy issues affected support and adoption intention through the mediators of perceived usefulness and privacy risk. Problem perception also had direct effects on support and adoption intention. Democrats reported higher levels of trust in utility companies and problem perception than non-Democrats. This study provides useful insights for utility managers, researchers and policy makers.
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