Data · dataset · 2026
The Value of (Energy) Data Privacy and its Effects on Privacy-Seeking Behavior
Listed in D2ET Open Science Portal
The digitalization of electricity systems creates a trade-off between system-wide efficiency gains and individual’s privacy risks.
Description
High-frequency smart-meter data enable utilities to improve forecasting, maintenance, and tariff design, but also allow increasingly accurate inferences about households’ routines, occupancy, and appliance usage. The key question is therefore not whether such data are valuable, but how households value these benefits relative to the privacy risks they entail.
This paper examines how belief-dependent perceptions of inference accuracy shape individuals’ valuation of energy data privacy and their privacy-seeking behavior. We implement a survey experiment with an embedded information treatment. First, we elicit privacy valuation through a discrete choice experiment in which respondents choose between electricity contracts differing in price, data granularity, and electricity reliability gains.
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Second, we exogenously shift beliefs by providing factual information on the inferential power of smart-meter data to a randomly selected treatment group. Third, we link post-treatment valuation to intended privacy-seeking behavior. Causal effects are identified using an instrumental variable strategy that exploits the interaction between baseline belief errors and the information treatment.
Evidence from a pilot study in Germany (N = 194) suggests that respondents underestimate inference accuracy. Correcting this misperception increases perceived accuracy and raises willingness to pay for privacy by about €1.4 per month. Results further indicate that higher privacy valuation increases intended privacy-protective actions.
Overall, privacy demand appears belief-dependent, with implications for policy design in digitalized energy systems.
Links
Where it is published
- Dataverse dataset page d2et-openscience.list.lu/dataset.xhtml?persistentId=perma%3AD2ET.TALNCC ↗
landing page · from d2et openscience list lu
- Persistent identifier d2et-openscience.list.lu/citation?persistentId=perma%3AD2ET.TALNCC ↗
DOI / persistent id · from d2et openscience list lu
Catalogue records · 1
- Dataverse API d2et-openscience.list.lu/api/datasets/:persistentId/?persistentId=perma%3AD2ET.TALNCC ↗
metadata API · from d2et openscience list lu
Topics
- Stated by source
- Computer and Information Science
- From keywords
- Psychology & Behavioral Science
- Inferred from text
- Data and information privacy 78%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| D2ET Open Science Portal | perma:D2ET.TALNCC | 4 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:460402 | enrichment · d2et openscience list lu | taxonomy-embedding@1.0.0 | title+keywords+description (78%) |
| 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:psychology-behavioral | 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 |