Start Date

14-12-2012 12:00 AM

Description

Given rising electricity consumption, coupled with finite resources, ICT-enabled electrical networks such as smart grids are increasingly being deployed by energy companies. One part of smart grids is smart meter technology (SMT), which are digital electrical meters, having the potential to increase energy efficiency in both residential and industrial sectors. However, a challenge to SMT-implementation in residential settings is its adoption (and continued usage) by consumers. Despite these challenges, little academic research has been conducted on this topic. This study attempts to fill that void and is, to the knowledge of the authors, the first study to empirically investigate this topic from an user perspective. Specifically, we developed a model surrounding consumers’ intention to continue using SMT, by drawing on theories of adoption and motivational psychology, and testing it using a sample (n = 933) of SMT-users of a large super-regional energy supplier. Results provide support for our hypotheses.

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Dec 14th, 12:00 AM

Examination of the Determinants of Smart Meter Adoption: An User Perspective

Given rising electricity consumption, coupled with finite resources, ICT-enabled electrical networks such as smart grids are increasingly being deployed by energy companies. One part of smart grids is smart meter technology (SMT), which are digital electrical meters, having the potential to increase energy efficiency in both residential and industrial sectors. However, a challenge to SMT-implementation in residential settings is its adoption (and continued usage) by consumers. Despite these challenges, little academic research has been conducted on this topic. This study attempts to fill that void and is, to the knowledge of the authors, the first study to empirically investigate this topic from an user perspective. Specifically, we developed a model surrounding consumers’ intention to continue using SMT, by drawing on theories of adoption and motivational psychology, and testing it using a sample (n = 933) of SMT-users of a large super-regional energy supplier. Results provide support for our hypotheses.