Residential solar photovoltaic adoption behaviour: End-to-end review of theories, methods and approaches

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Embargoed until: 2023-02-02
Author(s)
Alipour, M
Salim, H
Stewart, Rodney A
Sahin, Oz
Year published
2021
Metadata
Show full item recordAbstract
The effectiveness of deployment policies to promote the uptake of residential rooftop solar photovoltaic systems ultimately hinges on the behaviour of households who decide to accept or reject the technology. Over the past years, research has strived to understand, designate significant predictors, model the behaviour of heterogeneous households, and predict the diffusion rate by putting a wide range of approaches in place. Inspired by compiling a comprehensive database of home solar adoption studies, the present study systematically reviews the adopted theories, methods and approaches used within 199 original quantitative, ...
View more >The effectiveness of deployment policies to promote the uptake of residential rooftop solar photovoltaic systems ultimately hinges on the behaviour of households who decide to accept or reject the technology. Over the past years, research has strived to understand, designate significant predictors, model the behaviour of heterogeneous households, and predict the diffusion rate by putting a wide range of approaches in place. Inspired by compiling a comprehensive database of home solar adoption studies, the present study systematically reviews the adopted theories, methods and approaches used within 199 original quantitative, qualitative, statistical, and non-statistical articles covering households’ attitudes, awareness, tendencies, knowledge, motives, willingness, intentions, and adoption decisions. The study provides a critical analysis of investigations on the adoption of solar photovoltaics, solar home systems, and solar photovoltaics coupled with battery energy storage systems. The outcome of the review revealed 108 future and 91 retroactive studies that exploit 10 key dependent variables by means of 52% primary (empirical data), 34% secondary (available sources), and 13% covering both modes of data collection. The sensitivity of these dependent variables was tested by 36 intervention variables that seek to capacitate effective managerial policies. The complexity of the individual decision was comprehended by 13 forms of behavioural theories, with the top-ranked two being the diffusion of innovation and the theory of planned behaviour. The literature showcased a total of 170 quantitative, 20 qualitative, and nine mixed-method studies, with statistical and non-statistical techniques being applied 139 and 86 times, respectively. Regression analysis was the most commonly used statistical analysis method, followed by spatial analysis for non-statistical models. At the heart of the predictive methods for analysing the diffusion rate of these solar technologies, nuances of 25 agent-based models and their social networks were examined in depth. The review further revealed 14 spectra of household categories as well as 12 typologies of household comparisons.
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View more >The effectiveness of deployment policies to promote the uptake of residential rooftop solar photovoltaic systems ultimately hinges on the behaviour of households who decide to accept or reject the technology. Over the past years, research has strived to understand, designate significant predictors, model the behaviour of heterogeneous households, and predict the diffusion rate by putting a wide range of approaches in place. Inspired by compiling a comprehensive database of home solar adoption studies, the present study systematically reviews the adopted theories, methods and approaches used within 199 original quantitative, qualitative, statistical, and non-statistical articles covering households’ attitudes, awareness, tendencies, knowledge, motives, willingness, intentions, and adoption decisions. The study provides a critical analysis of investigations on the adoption of solar photovoltaics, solar home systems, and solar photovoltaics coupled with battery energy storage systems. The outcome of the review revealed 108 future and 91 retroactive studies that exploit 10 key dependent variables by means of 52% primary (empirical data), 34% secondary (available sources), and 13% covering both modes of data collection. The sensitivity of these dependent variables was tested by 36 intervention variables that seek to capacitate effective managerial policies. The complexity of the individual decision was comprehended by 13 forms of behavioural theories, with the top-ranked two being the diffusion of innovation and the theory of planned behaviour. The literature showcased a total of 170 quantitative, 20 qualitative, and nine mixed-method studies, with statistical and non-statistical techniques being applied 139 and 86 times, respectively. Regression analysis was the most commonly used statistical analysis method, followed by spatial analysis for non-statistical models. At the heart of the predictive methods for analysing the diffusion rate of these solar technologies, nuances of 25 agent-based models and their social networks were examined in depth. The review further revealed 14 spectra of household categories as well as 12 typologies of household comparisons.
View less >
Journal Title
Renewable Energy
Copyright Statement
© 2021 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Note
This publication has been entered as an advanced online version in Griffith Research Online.
Subject
Electrical and Electronic Engineering
Mechanical Engineering
Interdisciplinary Engineering