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Empowering householders: Identifying predictors of intentions to use a home energy management system in the United Kingdom

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  • Whittle, Colin
  • Jones, Christopher R.
  • While, Aidan

Abstract

Trials of technologies designed to promote residential demand-side energy management (DSM) have found aggregate levels of load-shifting behaviour and curtailment in energy use. These aggregate data, however, mask considerable differences in people's engagement in DSM at an individual household level. We present the findings of a quantitative exploration of people's intentions to use a home energy management system (HEMS) for residential DSM in the United Kingdom. The technology acceptance model (TAM) was used in conjunction with constructs measuring psychological empowerment and environmental attitudes to explore participants' acceptance of a HEMS to facilitate load-shifting. Findings from a mediation analysis showed perceptions of the usefulness of the HEMS and its ease of use were important predictors of people's intentions to use one. They also highlight a potential conflict between an individual's home energy consumption goals and national DSM goals. The implications of these findings for understanding end-user acceptance of HEMS are discussed. We conclude that seeking opportunities to promote shared, internalised goals for residential DSM may be an avenue for increasing the uptake and use of technologies designed to enable load-shifting (and other energy conservation behaviours) among end-users.

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  • 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).
    • Handle: RePEc:eee:enepol:v:139:y:2020:i:c:s0301421520301002
    DOI: 10.1016/j.enpol.2020.111343
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    Cited by:

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    3. 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.
    4. Ariza-Montes, Antonio & Quan, Wei & Radic, Aleksandar & Koo, Bonhak & Kim, Jinkyung Jenny & Chua, Bee-Lia & Han, Heesup, 2023. "Understanding the behavioral intention to use urban air autonomous vehicles," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    5. Gonçalves, Luisa & Patrício, Lia, 2022. "From smart technologies to value cocreation and customer engagement with smart energy services," Energy Policy, Elsevier, vol. 170(C).
    6. Ion Popa & Marian Mihai Cioc & Stefan Catalin Pop & Daniel Botez & Marius-Ioan Pantea, 2023. "Aligning Public Policy with REPowerEU Program Objectives by Adopting EESS Solutions: A Technology Acceptance Model Approach," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(64), pages 660-660, August.
    7. Lucas Roth & Jens Lowitzsch & Özgür Yildiz, 2021. "An Empirical Study of How Household Energy Consumption Is Affected by Co-Owning Different Technological Means to Produce Renewable Energy and the Production Purpose," Energies, MDPI, vol. 14(13), pages 1-38, July.

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