energy literacy; energy technologies; electric vehicles; photovoltaic panels; home energy monitoring
Abstract :
[en] As societies transition to renewable energy sources and combat climate change, understanding the factors that drive the adoption of new technologies becomes increasingly important. This paper focuses on how energy literacy—an individual’s understanding of energy concepts and technologies—affects the adoption of Electric Vehicles (EVs), Photovoltaic (PV) systems, and Home Energy Monitoring (HEM), using household-level survey data.
The logistic regression analysis reveals that an increase in energy literacy significantly boosts the probability of adopting these technologies. Specifically, a one-point rise in energy literacy increases the likelihood of adopting any of the three technologies by at least 20.2%. Notably, energy literacy has a heterogeneous impact on individual technologies, significantly enhancing EV adoption by 38.9%, while showing no statistically significant effect on PV adoption.
Our findings highlight the importance of targeted energy education in promoting specific technologies, suggesting that tailored informational campaigns could be more effective in driving the adoption of EVs and HEM.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > FINATRAX - Digital Financial Services and Cross-organizational Digital Transformations
Disciplines :
Computer science Management information systems Microeconomics
Author, co-author :
ANDOLFI, Laura ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
ORTEGA MORENO, Boris ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
External co-authors :
no
Language :
English
Title :
Smart Choices: The Influence of Energy Literacy on Energy Technology Adoption
This research was funded in part by the Luxembourg
National Research Fund (FNR) and PayPal, PEARL grant
reference 13342933/Gilbert Fridgen. Additionally it was
funded in part by the Luxembourg National Research
Fund (FNR), grant reference 14783405. The authors
gratefully acknowledge the financial support of Creos
Luxembourg under the research project FlexBeAn. For
the purpose of open access, and in fulfillment of the
obligations arising from the grant agreement, the author
has applied a Creative Commons Attribution 4.0 International
(CC BY 4.0) license to any Author Accepted
Manuscript version arising from this submission.
