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A Targeted Review on Revisiting and Augmenting the Framework for Technology Acceptance in the Renewable Energy Context

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  • Tanvi Bhatia

    (School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Gnana Bharathy

    (School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Mukesh Prasad

    (School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia)

Abstract

Given that the implementation of renewable technologies has some key bottlenecks in adoption, this topic has been explored. Particularly, we are reviewing existing theories and models to understand their fit for changing social structures and evolving world contexts. This review begins with an introduction followed by a background study on renewable energy technology (RET). We have employed a mixed-approach methodology to synthesize the relevant literature. The review comprises a summary and comparison of some existing theories and models such as TAM, TRA, and UTAUT, elucidating factors influencing technology adoption processes. Additionally, the review discusses the scope for future research, emphasizing the need for more nuanced frameworks that account for contextual intricacies and emerging trends in renewable energy adoption. Ultimately, the review concludes with insights into the ongoing discourse surrounding energy technology acceptance and recommendations on the inclusion of current world views in the scope for future study.

Suggested Citation

  • Tanvi Bhatia & Gnana Bharathy & Mukesh Prasad, 2024. "A Targeted Review on Revisiting and Augmenting the Framework for Technology Acceptance in the Renewable Energy Context," Energies, MDPI, vol. 17(8), pages 1-27, April.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1982-:d:1380566
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    References listed on IDEAS

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    1. David Autor & David Dorn & Gordon Hanson & Kaveh Majlesi, 2020. "Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure," American Economic Review, American Economic Association, vol. 110(10), pages 3139-3183, October.
    2. Rezaei, Rohollah & Ghofranfarid, Marjan, 2018. "Rural households' renewable energy usage intention in Iran: Extending the unified theory of acceptance and use of technology," Renewable Energy, Elsevier, vol. 122(C), pages 382-391.
    3. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    4. Anda, Martin & Temmen, Justin, 2014. "Smart metering for residential energy efficiency: The use of community based social marketing for behavioural change and smart grid introduction," Renewable Energy, Elsevier, vol. 67(C), pages 119-127.
    5. Lopes, Marta A.R. & Henggeler Antunes, Carlos & Janda, Kathryn B. & Peixoto, Paulo & Martins, Nelson, 2016. "The potential of energy behaviours in a smart(er) grid: Policy implications from a Portuguese exploratory study," Energy Policy, Elsevier, vol. 90(C), pages 233-245.
    6. Shaheen, Susan A & Martin, Elliot & Lipman, Timothy E, 2008. "Dynamics in Behavioral Response to Fuel-Cell Vehicle Fleet and Hydrogen Fueling Infrastructure," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0pk0008g, Institute of Transportation Studies, UC Berkeley.
    7. Shuangying Chen & Qiyue Li & Bo Lei & Na Wang, 2021. "Configurational Analysis of the Driving Paths of Chinese Digital Economy Based on the Technology–Organization–Environment Framework," SAGE Open, , vol. 11(4), pages 21582440211, October.
    8. Olawale Fatoki, 2022. "Determinants of Intention to Purchase Photovoltaic Panel System: An Integration of Technology Acceptance Model and Theory of Planned Behaviour," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 432-440, May.
    9. Park, Chan-Kook & Kim, Hyun-Jae & Kim, Yang-Soo, 2014. "A study of factors enhancing smart grid consumer engagement," Energy Policy, Elsevier, vol. 72(C), pages 211-218.
    10. Ponce, Pedro & Polasko, Kenneth & Molina, Arturo, 2016. "End user perceptions toward smart grid technology: Acceptance, adoption, risks, and trust," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 587-598.
    11. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    12. Ameli, Nadia & Brandt, Nicola, 2015. "What Impedes Household Investment in Energy Efficiency and Renewable Energy?," International Review of Environmental and Resource Economics, now publishers, vol. 8(1), pages 101-138, May.
    13. Yingxia Cao & Haya Ajjan & Paul Hong & Thuong Le, 2018. "Using social media for competitive business outcomes," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 15(2), pages 211-235, May.
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