Predictors, taxonomy of predictors, and correlations of predictors with the decision behaviour of residential solar photovoltaics adoption: A review

The successful diffusion of rooftop solar photovoltaics (SPV) in residential sector depends on the decisions of bounded rational households to accept this technology. Such heterogeneous decision is formed by socio-demographic, economic and technical predictors interwoven with a variety of behavioural traits. Over the past years, these exogenous and endogenous predictors have served as the starting point of a large body of studies seeking to understand the heterogeneity of the behaviour and to predict the diffusion rate. The present systematic review primarily identifies the predictors of 173 original quantitative and qualitative studies on the residential adoption behaviour of SPV, solar home system (SHS) and SPV coupled with battery energy storage system (SPV-BESS) technologies. For the designated predictors, the study proposes a customised taxonomy aimed at in-depth understanding of knowledge in an organised and coherent framework. Extracted from 133 of the 173 initially reviewed papers, the last objective of the review further expands on current understanding of the predictors by exploring their correlations with the behaviour. The upshot of the review unfolds a total of 333 predictors that sought to investigate households' attitude, knowledge, tendency, awareness, willingness, intention and adoption decisions towards the uptake of SPV, SHS, and SPV-BESS. The identified predictors are classified into individual, social and information dimensions, with 20 categories and 20 subcategories. An exhaustive comparison on the frequency use of predictors denotes more popularity of social predictors led by ‘age’ and ‘income’, and ‘financial knowledge’ at the category dimension. However, the synthesised results of the vote-counting method applied to a total of 239 factors suggest a lower correlation of several traditional determinants (e.g., age, gender) whereas certain attitudinal traits categorised as individual demonstrate significant correlation with the behaviour. •Review of 173 studies on the adoption behaviour of residential solar PV systems.•Identification of 333 predictors that describe and predict individual behaviour.•Taxonomy of predictors classified as individual, social and information dimensions.•Frequency use of the identified predictors, and comparisons of their use.•Investigation of correlations of the predictors with the decision behaviour.