Data · dataset · 2026
The Two Sides of a Coin: Perceived and Objective Energy Literacy for Technology Adoption
Listed in D2ET Open Science Portal
Residential electrification through energy technologies such as electric vehicles, photovoltaic systems, and energy storage and smart charging solutions is a key element of the energy transition.
Description
While prior research has analyzed the role of objective energy literacy and perceived knowledge in shaping individual’s decisions in other contexts, little is known about their effects on household energy technology uptake. Using a representative household survey of 1,011 respondents in Luxembourg, this paper examines how objective and perceived energy literacy jointly influence the adoption of residential energy technologies.
We first show that both objective and perceived energy literacy are positively associated with the probability of adopting at least one energy technology. However, the two dimensions are substantially misaligned: nearly 70% of respondents overestimate their objective energy knowledge. Exploiting this miscalibration, we distinguish between over-estimators, under-estimators, and well-calibrated individuals.
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We find that adoption behavior among mis-calibrated individuals is less systematic, whereas calibrated energy literacy exhibits a clear and robust positive relationship with technology uptake. Our findings show that energy literacy is not a unidimensional construct and that confidence in one’s knowledge is as important as knowledge itself. From a policy perspective, the results suggest that interventions aimed solely at increasing factual knowledge may be insufficient.
Effective policy design should also target the calibration of beliefs, for instance through feedback mechanisms, self-assessment tools, and decision-support instruments that help households better align perceived and actual energy knowledge.
Links
Where it is published
- Dataverse dataset page d2et-openscience.list.lu/dataset.xhtml?persistentId=perma%3AD2ET.2IUD3K ↗
landing page · from d2et openscience list lu
- Persistent identifier d2et-openscience.list.lu/citation?persistentId=perma%3AD2ET.2IUD3K ↗
DOI / persistent id · from d2et openscience list lu
Catalogue records · 1
- Dataverse API d2et-openscience.list.lu/api/datasets/:persistentId/?persistentId=perma%3AD2ET.2IUD3K ↗
metadata API · from d2et openscience list lu
Topics
- Stated by source
- Computer and Information Science
- From keywords
- Energy
- Inferred from text
- Electrical engineering 71%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| D2ET Open Science Portal | perma:D2ET.2IUD3K | 5 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4008 | enrichment · d2et openscience list lu | taxonomy-embedding@1.0.0 | title+keywords+description (71%) |
| concepts[field].dataverse_subject:computer-and-information-science | source · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 | /subjects |
| concepts[field].local:field:energy | mapping · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 | /subjects |
| created_date | source · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 | |
| description | source · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 | /description |
| publication_date | source · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 | |
| title | source · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 | /name |
| updated_date | source · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 | |
| version_label | source · d2et openscience list lu | connector:d2et_openscience_list_lu@1.0.0 |