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

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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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    References listed on IDEAS

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    1. Thipnapa Huansuriya & Kris Ariyabuddhiphongs, 2023. "Predicting Residential Photovoltaic Adoption Intention of Potential Prosumers in Thailand: A Theory of Planned Behavior Model," Energies, MDPI, vol. 16(17), pages 1-20, August.
    2. Amin Barnawi & Mohamed A. Zohdy & Tarik Hawsawi, 2023. "Determining the Factors Affecting Solar Energy Utilization in Saudi Housing: A Case Study in Makkah," Energies, MDPI, vol. 16(20), pages 1-15, October.
    3. Ye, Liang-Cheng & Rodrigues, João F.D. & Lin, Hai Xiang, 2017. "Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016," Applied Energy, Elsevier, vol. 203(C), pages 496-505.
    4. Ding, Zhikun & Chen, Weilin & Hu, Ting & Xu, Xiaoxiao, 2021. "Evolutionary double attention-based long short-term memory model for building energy prediction: Case study of a green building," Applied Energy, Elsevier, vol. 288(C).
    5. Pi-Chuan Sun & Hsueh-Mei Wang & Hsien-Long Huang & Chien-Wei Ho, 2020. "Consumer attitude and purchase intention toward rooftop photovoltaic installation: The roles of personal trait, psychological benefit, and government incentives," Energy & Environment, , vol. 31(1), pages 21-39, February.
    6. Wang, Chaofan & Wang, Yilan & Zhao, Yujia & Shuai, Jing & Shuai, Chuanmin & Cheng, Xin, 2023. "Cognition process and influencing factors of rural residents' adoption willingness for solar PV poverty alleviation projects: Evidence from a mixed methodology in rural China," Energy, Elsevier, vol. 271(C).
    7. Gimpel, Henner & Graf, Vanessa & Graf-Drasch, Valerie, 2020. "A comprehensive model for individuals’ acceptance of smart energy technology – A meta-analysis," Energy Policy, Elsevier, vol. 138(C).
    8. Marek Angowski & Tomasz Kijek & Marcin Lipowski & Ilona Bondos, 2021. "Factors Affecting the Adoption of Photovoltaic Systems in Rural Areas of Poland," Energies, MDPI, vol. 14(17), pages 1-14, August.
    9. Tarun M. Khanna & Giovanni Baiocchi & Max Callaghan & Felix Creutzig & Horia Guias & Neal R. Haddaway & Lion Hirth & Aneeque Javaid & Nicolas Koch & Sonja Laukemper & Andreas Löschel & Maria del Mar Z, 2021. "A multi-country meta-analysis on the role of behavioural change in reducing energy consumption and CO2 emissions in residential buildings," Nature Energy, Nature, vol. 6(9), pages 925-932, September.
    10. Saqib Ali & Petra Poulova & Ahsan Akbar & Hafiz Muhammad Usama Javed & Muhammad Danish, 2020. "Determining the Influencing Factors in the Adoption of Solar Photovoltaic Technology in Pakistan: A Decomposed Technology Acceptance Model Approach," Economies, MDPI, vol. 8(4), pages 1-20, December.
    11. Zhi, Qiang & Sun, Honghang & Li, Yanxi & Xu, Yurui & Su, Jun, 2014. "China’s solar photovoltaic policy: An analysis based on policy instruments," Applied Energy, Elsevier, vol. 129(C), pages 308-319.
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