IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i6p1405-d1357113.html
   My bibliography  Save this article

Modelling Public Intentions to Use Innovative EV Chargers Employing Hybrid Energy Storage Systems: A UK Case Study Based upon the Technology Acceptance Model

Author

Listed:
  • Christopher R. Jones

    (Department of Psychology, University of Portsmouth, Portsmouth PO1 2DY, UK)

  • Herman Elgueta

    (Department of Psychology, Universidad de Magallanes, Punta Arenas 6210427, Chile)

  • Nikita Chudasama

    (Department of Psychology, University of Portsmouth, Portsmouth PO1 2DY, UK)

  • Daphne Kaklamanou

    (Department of Psychology, University of Portsmouth, Portsmouth PO1 2DY, UK)

  • Duncan East

    (Marwell Wildlife, Winchester SO21 1JH, UK)

  • Andrew J. Cruden

    (Department of Mechanical Engineering, University of Southampton, Southampton SO17 1BJ, UK)

Abstract

The current study investigates public intentions to use an innovative, off-grid renewably powered EV charging technology called FEVER (Future Electric Vehicle Energy networks supporting Renewables). We report the findings of a questionnaire-based survey (QBS) conducted at a zoo in the south of England, exploring the prospect of demonstrating FEVER. The QBS was designed around a context-specific technology acceptance model (TAM) and administered both face-to-face ( n = 63) and online ( n = 158) from April to May 2023. The results indicate that most participants were willing to pay to use FEVER, particularly where revenue would benefit the zoo. The participants agreed they intended to use the chargers, and that they would be useful and easy to use. The participants agreed that there would be normative pressure to use the chargers, but that their use would be enjoyable. Of greatest concern was that the chargers would be blocked by others. The participants were ambivalent about concerns over charging duration and charge sufficiency. Structural equation modelling confirmed that the context-specific TAM explained 58% of people’s use intentions. The core relationships of the TAM were confirmed, with ‘perceived usefulness’ additionally predicted by subjective norms and ‘perceived ease of use’ additionally predicted by anticipated enjoyment. Of the other variables, only concern that the chargers would be blocked was retained as a marginal predictor of ‘perceived ease of use’. The implications of these findings for the co-design and demonstration of FEVER are discussed.

Suggested Citation

  • Christopher R. Jones & Herman Elgueta & Nikita Chudasama & Daphne Kaklamanou & Duncan East & Andrew J. Cruden, 2024. "Modelling Public Intentions to Use Innovative EV Chargers Employing Hybrid Energy Storage Systems: A UK Case Study Based upon the Technology Acceptance Model," Energies, MDPI, vol. 17(6), pages 1-25, March.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1405-:d:1357113
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/6/1405/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/6/1405/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    2. Sanchari Deb & Kari Tammi & Karuna Kalita & Pinakeswar Mahanta, 2018. "Review of recent trends in charging infrastructure planning for electric vehicles," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 7(6), November.
    3. Gebauer, Fabian & Vilimek, Roman & Keinath, Andreas & Carbon, Claus-Christian, 2016. "Changing attitudes towards e-mobility by actively elaborating fast-charging technology," Technological Forecasting and Social Change, Elsevier, vol. 106(C), pages 31-36.
    4. Devine-Wright, Patrick & Batel, Susana & Aas, Oystein & Sovacool, Benjamin & Labelle, Michael Carnegie & Ruud, Audun, 2017. "A conceptual framework for understanding the social acceptance of energy infrastructure: Insights from energy storage," Energy Policy, Elsevier, vol. 107(C), pages 27-31.
    5. Caperello, Nicolette & Kurani, Kenneth S. & TyreeHageman, Jennifer, 2013. "Do You Mind if I Plug-in My Car? How etiquette shapes PEV drivers’ vehicle charging behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 155-163.
    6. Whittle, Colin & Jones, Christopher R. & While, Aidan, 2020. "Empowering householders: Identifying predictors of intentions to use a home energy management system in the United Kingdom," Energy Policy, Elsevier, vol. 139(C).
    7. Li, Wenbo & Long, Ruyin & Chen, Hong & Geng, Jichao, 2017. "A review of factors influencing consumer intentions to adopt battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 318-328.
    8. 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.
    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. Philippe Cohard, 2020. "Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions," Post-Print hal-02987225, HAL.
    2. Melih Engin & Fatih Gürses, 2019. "Adoption of Hospital Information Systems in Public Hospitals in Turkey: An Analysis with the Unified Theory of Acceptance and Use of Technology Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1-19, October.
    3. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    4. Tsung Teng Chen, 2012. "The development and empirical study of a literature review aiding system," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 105-116, July.
    5. Abdesamad Zouine & Pierre Fenies, 2014. "The Critical Success Factors Of The ERP System Project: A Meta-Analysis Methodology," Post-Print hal-01419785, HAL.
    6. Debora Bettiga & Lucio Lamberti & Emanuele Lettieri, 2020. "Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach," Health Care Management Science, Springer, vol. 23(2), pages 203-214, June.
    7. Chen-Yuan Chen & Bih-Yaw Shih & Shih-Hsien Yu, 2012. "Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(3), pages 1217-1231, July.
    8. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    9. Mäntymäki, Matti & Salo, Jari, 2013. "Purchasing behavior in social virtual worlds: An examination of Habbo Hotel," International Journal of Information Management, Elsevier, vol. 33(2), pages 282-290.
    10. Cristopher Siegfried Kopplin, 2021. "Two heads are better than one: matchmaking tools in coworking spaces," Review of Managerial Science, Springer, vol. 15(4), pages 1045-1069, May.
    11. Ofir Turel & Catherine E. Connelly, 2012. "Team Spirit: The Influence of Psychological Collectivism on the Usage of E-Collaboration Tools," Group Decision and Negotiation, Springer, vol. 21(5), pages 703-725, September.
    12. Joan Torrent-Sellens & Cristian Salazar-Concha & Pilar Ficapal-Cusí & Francesc Saigí-Rubió, 2021. "Using Digital Platforms to Promote Blood Donation: Motivational and Preliminary Evidence from Latin America and Spain," IJERPH, MDPI, vol. 18(8), pages 1-17, April.
    13. Cliff R. Kikawa & Charity Kiconco & Moses Agaba & Dimas Ntirampeba & Amos Ssematimba & Billy M. Kalema, 2022. "Social Media Marketing for Small and Medium Enterprise Performance in Uganda: A Structural Equation Model," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    14. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    15. Wu, Wei-Wen & Lan, Lawrence W. & Lee, Yu-Ting, 2011. "Exploring decisive factors affecting an organization's SaaS adoption: A case study," International Journal of Information Management, Elsevier, vol. 31(6), pages 556-563.
    16. Lim, Joon Soo & Zhang, Jun, 2022. "Adoption of AI-driven personalization in digital news platforms: An integrative model of technology acceptance and perceived contingency," Technology in Society, Elsevier, vol. 69(C).
    17. Galeone, Graziana & Ranaldo, Simona & Fusco, Antonio, 2024. "ESG and FinTech: Are they connected?," Research in International Business and Finance, Elsevier, vol. 69(C).
    18. Sohn, Stefanie, 2017. "A contextual perspective on consumers' perceived usefulness: The case of mobile online shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 22-33.
    19. Vishal K. Gupta & Suman Niranjan & Banu A. Goktan & John Eriskon, 2016. "Individual entrepreneurial orientation role in shaping reactions to new technologies," International Entrepreneurship and Management Journal, Springer, vol. 12(4), pages 935-961, December.
    20. 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.

    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:6:p:1405-:d:1357113. 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.