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Determinants of Solar Photovoltaic Adoption Intention among Households: A Meta-Analysis

Author

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  • Wenjie Li

    (Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University, Shenzhen 518060, China)

  • Jiaolan Zhu

    (School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

  • Yongchang Li

    (Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University, Shenzhen 518060, China)

  • Yaning Li

    (Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University, Shenzhen 518060, China)

  • Zhikun Ding

    (Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University, Shenzhen 518060, China
    Key Laboratory for Resilient Infrastructures of Coastal Cities (Shenzhen University), Ministry of Education, Shenzhen 518061, China
    Shenzhen Key Laboratory of Green, Efficient and Intelligent Construction of Underground Metro Station, Shenzhen University, Shenzhen 518060, China)

Abstract

In recent years, research on the intention to adopt solar photovoltaic technology has yielded rich results. However, controversy still exists regarding the key antecedents of households’ intention to adopt solar photovoltaic technologies. To clarify the critical factors influencing the intention to adopt solar photovoltaic technology and potential moderating variables, this study utilized meta-analysis to perform a quantitative literature analysis on 29 empirical articles. It identified eight key influencing factors and tested the moderating effects of two variables: sample size and research area. The results show that “Attitude” and “Government Incentive” are moderately correlated with the intention to adopt. “Social Influence”, “Product Knowledge”, “Effort Expectancy”, “Perceived Cost-benefit”, “Performance Expectancy”, and “Perceived Behavioral Control” are weakly correlated with the adoption intention. The study also found that using the sample size and research area as moderating variables can partly reveal differences between various studies. Overall, the findings of this study offer theoretical guidance for subsequent in-depth studies and support for the practical promotion of solar photovoltaic technology.

Suggested Citation

  • Wenjie Li & Jiaolan Zhu & Yongchang Li & Yaning Li & Zhikun Ding, 2024. "Determinants of Solar Photovoltaic Adoption Intention among Households: A Meta-Analysis," Sustainability, MDPI, vol. 16(18), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8204-:d:1481946
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    2. Xiaoxiao Li & Ming Li & Pick-Soon Ling & Chee-Hua Chin, 2025. "Modelling Gen Z’s Photovoltaic Purchase Intentions: A Mediator–Moderator Model," Sustainability, MDPI, vol. 17(18), pages 1-19, September.

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