Solar energy paper index
Factors influencing Somalia household’s willingness to pay renewable energy: employing structural equation modeling
One-line summary
A solar energy research paper on Factors influencing Somalia household’s willingness to pay renewable energy: employing structural equation modeling.
Engineering notes
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Chinese explanation / 中文解读
中文解读待补充:本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
This study used PLS path analysis and structural equation modelling (SEM) to examine the factors influencing Somali households' willingness to pay for renewable energy. Non-probability purposive sampling was used in a quantitative survey to select respondents from Mogadishu, the capital city of Somalia. 300 home power bill payers who were informed about energy costs and renewable energy requirements were given a standardized closed-ended questionnaire. Following data cleaning, SPSS version-25 and SmartPLS-4 were used to analyze 255 valid replies using descriptive and inferential statistics. With an R2 of 0.428, the structural model has moderate explanatory power, accounting for 42.8% of the variance in willingness to pay for renewable energy. The model's robustness is confirmed by an adjusted R2 of 0.402. The findings showed that consumer intention, environmental concern, perceived behavioral control, subjective norms, and Attitude have a positive significant impact on willingness to pay for renewable energy. Belief about the cost of renewable energy shows no significant relationship with willingness to pay for renewable energy. The results of the moderation analysis indicate that the relationships between environmental concern, subjective norms, and attitude with willingness to pay for renewable energy are considerably moderated by customer intention. However, the relationship between perceived behavioral control and belief about the cost of renewable energy with willingness to pay for renewable energy is not moderated by consumer intention. The findings offer policymakers and renewable energy stakeholders insights to increase adoption rates.
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