Conference paper Open Access

Intelligent energy feedback: Tailoring advice based on consumer values

Bent, Caitlin; Kmetty, Zoltán


Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Bent, Caitlin</dc:creator>
  <dc:creator>Kmetty, Zoltán</dc:creator>
  <dc:date>2017-06-28</dc:date>
  <dc:description>With the roll-out of smart meters across the EU comes the opportunity for more tailored, informative feedback to be offered to domestic consumers regarding their energy consumption. To maximise the energy saving potential of this feedback, it must be accompanied by relevant, interesting advice. In this paper, we explore a mechanism for more effectively tailoring such advice, which is being developed by the Natconsumers project. There are two strands to developing tailored advice: determining what advice to give someone, and determining how to give it. In this paper, we focus on the latter: based upon their interests and motivations, how should advice be framed for different types of people? In what terms should the message be communicated, and in what tone? To investigate this, we have conducted a survey of 4,000 people across four European countries, examining their attitudes, values and demographics. Using these results, we present an attitudinal segmentation model, which allows us to identify what types of messages will be most resonant to different segments of energy consumers. In the wider Natconsumers project, this will be linked with additional segmentation models of load profiles and household characteristics/demographics in order to create a mechanism for the generation of tailored energy efficiency advice across Europe.</dc:description>
  <dc:identifier>https://zenodo.org/record/820511</dc:identifier>
  <dc:identifier>10.5281/zenodo.820511</dc:identifier>
  <dc:identifier>oai:zenodo.org:820511</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/657672/</dc:relation>
  <dc:relation>isbn:978-91-983878-1-0</dc:relation>
  <dc:relation>doi:10.5281/zenodo.820510</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>attitudes</dc:subject>
  <dc:subject>behavioural change</dc:subject>
  <dc:subject>consumer behaviour</dc:subject>
  <dc:subject>customer feedback</dc:subject>
  <dc:subject>drivers</dc:subject>
  <dc:subject>EU project</dc:subject>
  <dc:subject>in-home feedback</dc:subject>
  <dc:subject>smart metering</dc:subject>
  <dc:subject>advice</dc:subject>
  <dc:title>Intelligent energy feedback: Tailoring advice based on consumer values</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
</oai_dc:dc>
54
37
views
downloads
All versions This version
Views 5454
Downloads 3737
Data volume 29.1 MB29.1 MB
Unique views 5151
Unique downloads 3535

Share

Cite as