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Study of intention to use renewable energy technology in Malaysia using TAM and TPB

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  • Wong, Gai-Zhe
  • Wong, Kok-Hoe
  • Lau, Teck-Chai
  • Lee, Jun-Han
  • Kok, Yin-Hui

Abstract

Despite the increase in the usage of renewable energy in Malaysia, the proportion of renewable energy (RE) within the energy mix lags far behind satisfactory levels, at a mere 23% in 2020 compared to the 31% target by 2025 as per Malaysia's Energy Transition Roadmap. The public acceptance towards RE is one of the many obstacles that hinders the proliferation of RE in Malaysia. It is therefore imperative to determine the key factors which shape an individual's intention to utilize RE. In this study, three models are compared and assessed in terms of their efficacy in predicting such behavioural intention, namely the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB) and an extended model that combines the characteristics of the two prior theories. Partial-least-squares structural equation modelling, finite mixture partial least squares (FIMIX-PLS), and important-performance map analysis (IPMA) were performed on the collected survey dataset with 524 responses. Analyses revealed that attitude and perceived behavioural control are important factors of intention to adopt renewable energy technology, with perceived ease of use and perceived usefulness in turn being significant antecedents of attitude, whereas subjective norm did not influence intention. Among the three models, the extended model triumphs in terms of path significance and explanatory power, followed by TPB and then TAM. Results show that costs, ease of use and accessibility of RE remain limiting factors towards RE adoption in Malaysia, hence the need of appropriate policies/programmes, such as targeted incentive campaigns, to alleviate this issue.

Suggested Citation

  • Wong, Gai-Zhe & Wong, Kok-Hoe & Lau, Teck-Chai & Lee, Jun-Han & Kok, Yin-Hui, 2024. "Study of intention to use renewable energy technology in Malaysia using TAM and TPB," Renewable Energy, Elsevier, vol. 221(C).
    • Handle: RePEc:eee:renene:v:221:y:2024:i:c:s0960148123017020
    DOI: 10.1016/j.renene.2023.119787
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