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A computational model for designing energy behaviour change interventions
The conflicting evidence in the literature on energy feedback as a driver for energy behaviour change has lead to the realization that it is a complex problem and that interventions must be proposed and evaluated in the context of a tangled web of individual and societal factors. We put forward an i...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647543/ https://www.ncbi.nlm.nih.gov/pubmed/31404194 http://dx.doi.org/10.1007/s11257-017-9199-9 |
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author | Mogles, Nataliya Padget, Julian Gabe-Thomas, Elizabeth Walker, Ian Lee, JeeHang |
author_facet | Mogles, Nataliya Padget, Julian Gabe-Thomas, Elizabeth Walker, Ian Lee, JeeHang |
author_sort | Mogles, Nataliya |
collection | PubMed |
description | The conflicting evidence in the literature on energy feedback as a driver for energy behaviour change has lead to the realization that it is a complex problem and that interventions must be proposed and evaluated in the context of a tangled web of individual and societal factors. We put forward an integrated agent-based computational model of energy consumption behaviour change interventions based on personal values and energy literacy, informed by research in persuasive technologies, environmental, educational and cognitive psychology, sociology, and energy education. Our objectives are: (i) to build a framework to accommodate a rich variety of models that might impact consumption decisions, (ii) to use the simulation as a means to evaluate persuasive technologies in-silico prior to deployment. The model novelty lies in its capacity to connect the determinants of energy related behaviour (values, energy literacy and social practices) and several generic design strategies proposed in the area of persuasive technologies within one framework. We validate the framework using survey data and personal value and energy consumption data extracted from a 2-year field study in Exeter, UK. The preliminary evaluation results demonstrate that the model can predict energy saving behaviour much better than a random model and can correctly estimate the effect of persuasive technologies. The model can be embedded into an adaptive decision-making system for energy behaviour change. |
format | Online Article Text |
id | pubmed-6647543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-66475432019-08-09 A computational model for designing energy behaviour change interventions Mogles, Nataliya Padget, Julian Gabe-Thomas, Elizabeth Walker, Ian Lee, JeeHang User Model User-adapt Interact Article The conflicting evidence in the literature on energy feedback as a driver for energy behaviour change has lead to the realization that it is a complex problem and that interventions must be proposed and evaluated in the context of a tangled web of individual and societal factors. We put forward an integrated agent-based computational model of energy consumption behaviour change interventions based on personal values and energy literacy, informed by research in persuasive technologies, environmental, educational and cognitive psychology, sociology, and energy education. Our objectives are: (i) to build a framework to accommodate a rich variety of models that might impact consumption decisions, (ii) to use the simulation as a means to evaluate persuasive technologies in-silico prior to deployment. The model novelty lies in its capacity to connect the determinants of energy related behaviour (values, energy literacy and social practices) and several generic design strategies proposed in the area of persuasive technologies within one framework. We validate the framework using survey data and personal value and energy consumption data extracted from a 2-year field study in Exeter, UK. The preliminary evaluation results demonstrate that the model can predict energy saving behaviour much better than a random model and can correctly estimate the effect of persuasive technologies. The model can be embedded into an adaptive decision-making system for energy behaviour change. Springer Netherlands 2017-12-18 2018 /pmc/articles/PMC6647543/ /pubmed/31404194 http://dx.doi.org/10.1007/s11257-017-9199-9 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Mogles, Nataliya Padget, Julian Gabe-Thomas, Elizabeth Walker, Ian Lee, JeeHang A computational model for designing energy behaviour change interventions |
title | A computational model for designing energy behaviour change interventions |
title_full | A computational model for designing energy behaviour change interventions |
title_fullStr | A computational model for designing energy behaviour change interventions |
title_full_unstemmed | A computational model for designing energy behaviour change interventions |
title_short | A computational model for designing energy behaviour change interventions |
title_sort | computational model for designing energy behaviour change interventions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647543/ https://www.ncbi.nlm.nih.gov/pubmed/31404194 http://dx.doi.org/10.1007/s11257-017-9199-9 |
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