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A comprehensive model for individuals' acceptance of smart energy technology : a meta-analysis

Title data

Gimpel, Henner ; Graf, Vanessa ; Graf-Drasch, Valerie:
A comprehensive model for individuals' acceptance of smart energy technology : a meta-analysis.
In: Energy Policy. (2019) .
ISSN 0301-4215
DOI: https://doi.org/10.1016/j.enpol.2019.111196

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
Projektgruppe WI Energie und kritische InfrastrukturenNo information

Abstract in another language

Individuals' use of smart energy technology – i.e., technology that increases energy efficiency or increases the integration of renewable energy sources – holds great potential to solve the energy-related climate problem. However, individuals’ current uptake of smart energy technology is low. If policy makers are to successfully address this issue, it is vital that they understand the determinants of individuals’ smart energy technology adoption. Hence, this paper provides a comprehensive adoption model for smart energy technology, including data from over 4k individuals in Europe, Asia, and North America involved in various technological contexts and phases of diffusion. A meta-analysis identifies Attitude and Performance Expectancy as the primary determinants of individuals’ smart energy technology adoption. Further, results show that Environmental Concern influences all other determinants. Implications for research and policy makers are discussed.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Meta-analysis; Smart energy technology; Smart grid; Smart energy saving systems; Technology adoption; Smart city
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 15 Jan 2020 12:39
Last Modified: 29 Jul 2020 08:40
URI: https://eref.uni-bayreuth.de/id/eprint/53759