Modeling the influence of critical factors on the adoption of green energy technologies
Shihong Zeng,
Arifa Tanveer,
Xiaolan Fu,
Yuxiao Gu and
Muhammad Irfan ()
Renewable and Sustainable Energy Reviews, 2022, vol. 168, issue C
Abstract:
Green energy technologies (GETs) are environmentally friendly in nature, making a promising contribution to attaining net-zero carbon goals. Although the Pakistani government has begun using GETs to minimize the adverse effects of carbon emissions, consumers' adoption rate is quite low. There are few studies examining consumers' desire to adopt GETs in the country. This study attempts to fill this research gap and also contributes by adding three novel factors to the theory of planned behavior (i.e., green energy technology awareness, openness to experience, and green energy technology discomfort) to comprehensively analyze the impact of various factors influencing consumers' desire to adopt GETs. For this purpose, the study establishes a systematic research framework. Data were collected from (n = 330) households in the five major cities (Peshawar, Abbottabad, Mardan, Mingora, and Swabi) of Khyber Pakhtunkhwa Province via an inclusive questionnaire survey. The formulated hypotheses are evaluated and scrutinized using structural equation modeling. The results reveal that environmental concern (β = 0.245), green energy technology awareness (β = 0.362), openness to experience (β = 0.256), and green energy technology benefits (β = 0.225) positively affect consumers' desire to adopt GETs. On the other hand, green energy technology costs (β = 0.325) and green energy technology discomfort (β = 0.395) have a negative effect on consumers' adoption of GETs. The research findings emphasize the importance of increasing recognition of GETs, reforming policy frameworks, and providing budget-friendly and user-friendly technologies. Research limitations and future research perspectives are also addressed.
Keywords: Green energy technologies; Consumer desire; Theory of planned behavior; Structural equation modeling (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (17)
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DOI: 10.1016/j.rser.2022.112817
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