Abstract
The continuous development of energy management systems, coupled with a growing population, and increasing energy consumption, highlights the necessity to develop a deep understanding of household energy consumption behavior and interventions that facilitate behavioral change. Using a data mining segmentation technique, 2,505 Northern Ireland households were segmented into four distinctive profiles, based on their energy consumption patterns, socio-demographic, and dwelling characteristics. The change in attitude towards energy consumption behavior was analyzed to evaluate the impact of smart meter feedback as well. The key finding was 81% of trial participants perceived smart meters to be helpful in reducing their energy consumption. In addition, we found that the potential to reduce energy bills and environmental concerns were the strongest motivations for behavior change.
| Original language | English |
|---|---|
| Pages (from-to) | 21-37 |
| Number of pages | 17 |
| Journal | Journal of Global Information Management |
| Volume | 28 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Oct 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Behavior Change
- Data Mining
- Household
- Segmentation
- Smart Meter
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