IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i8p1982-d1380566.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/8/1982/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/8/1982/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ellabban, Omar & Abu-Rub, Haitham, 2016. "Smart grid customers' acceptance and engagement: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1285-1298.
    2. Yu Wang & Shanyong Wang & Jing Wang & Jiuchang Wei & Chenglin Wang, 2020. "An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model," Transportation, Springer, vol. 47(1), pages 397-415, February.
    3. Riffat Ara Zannat Tama & Md Mahmudul Hoque & Ying Liu & Mohammad Jahangir Alam & Mark Yu, 2023. "An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh," Agriculture, MDPI, vol. 13(2), pages 1-22, February.
    4. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2023. "The Research Agenda on Smart Grids: Foresights for Social Acceptance," Energies, MDPI, vol. 16(18), pages 1-31, September.
    5. 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.
    6. Petra Mesarić & Damira Đukec & Slavko Krajcar, 2017. "Exploring the Potential of Energy Consumers in Smart Grid Using Focus Group Methodology," Sustainability, MDPI, vol. 9(8), pages 1-17, August.
    7. Christine Milchram & Geerten Van de Kaa & Neelke Doorn & Rolf Künneke, 2018. "Moral Values as Factors for Social Acceptance of Smart Grid Technologies," Sustainability, MDPI, vol. 10(8), pages 1-23, August.
    8. Yunis Ali Ahmed & Ammar Rashid & Muhammad Mahboob Khurshid, 2022. "Investigating the Determinants of the Adoption of Solar Photovoltaic Systems—Citizen’s Perspectives of Two Developing Countries," Sustainability, MDPI, vol. 14(18), pages 1-25, September.
    9. Marlena Piekut, 2021. "The Consumption of Renewable Energy Sources (RES) by the European Union Households between 2004 and 2019," Energies, MDPI, vol. 14(17), pages 1-31, September.
    10. Adu-Gyamfi, Gibbson & Song, Huaming & Obuobi, Bright & Nketiah, Emmanuel & Wang, Hong & Cudjoe, Dan, 2022. "Who will adopt? Investigating the adoption intention for battery swap technology for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    11. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    12. Ramasesh, Ranga & Tirupati, Devanath & Vaitsos, Constantin A., 2010. "Modeling process-switching decisions under product life cycle uncertainty," International Journal of Production Economics, Elsevier, vol. 126(2), pages 236-246, August.
    13. Cheng, Peng & OuYang, Zhe & Liu, Yang, 2019. "Understanding bike sharing use over time by employing extended technology continuance theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 433-443.
    14. Nazir Ullah & Waleed S. Alnumay & Waleed Mugahed Al-Rahmi & Ahmed Ibrahim Alzahrani & Hosam Al-Samarraie, 2020. "Modeling Cost Saving and Innovativeness for Blockchain Technology Adoption by Energy Management," Energies, MDPI, vol. 13(18), pages 1-22, September.
    15. Taheri, Fatemeh & D'Haese, Marijke & Fiems, Dieter & Azadi, Hossein, 2022. "The intentions of agricultural professionals towards diffusing wireless sensor networks: Application of technology acceptance model in Southwest Iran," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    16. Gonçalves, Luisa & Patrício, Lia, 2022. "From smart technologies to value cocreation and customer engagement with smart energy services," Energy Policy, Elsevier, vol. 170(C).
    17. Agozie, Divine Q. & Afful-Dadzie, Anthony & Gyamfi, Bright Akwasi & Bekun, Festus Victor, 2023. "Does psychological empowerment improve renewable energy technology acceptance and recommendation? Evidence from 17 rural communities," Renewable Energy, Elsevier, vol. 219(P1).
    18. Saeideh Sharifi fard & Ezhar Tamam & Md Salleh Hj Hassan & Moniza Waheed & Zeinab Zaremohzzabieh, 2016. "Factors affecting Malaysian university students’ purchase intention in social networking sites," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1182612-118, December.
    19. Dani Rodrik, 2018. "Populism and the economics of globalization," Journal of International Business Policy, Palgrave Macmillan, vol. 1(1), pages 12-33, June.
    20. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1982-:d:1380566. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.