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Forecasting of advertising effectiveness for renewable energy technologies: A neural network analysis

机译:可再生能源技术的广告效果预测:神经网络分析

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The adoption of renewable energy technologies (RETs) as a sustainable practice in the residential construction sector depends on promotional efforts. With a modeling-based contribution, this research aims to analyze advertising effectiveness in the context of RETs adoption regarding solar water heaters. The study is based on a survey of 398 Iranian citizens. A neural network analysis was employed to identify advertising effectiveness in terms of the AIDA framework. The results indicated that the neural network is able to predict the relationships among advertising effectiveness indices; namely attention, interest, desire in the RETs setting, and action. According to the neural network analysis, attention was found to be the most significant predictor of action, followed by interest and desire.
机译:在住宅建筑领域中采用可再生能源技术(RETs)作为一种可持续做法取决于推广工作。借助基于模型的贡献,本研究旨在分析采用太阳能热水器的RET的广告效果。该研究基于对398名伊朗公民的调查。根据AIDA框架,采用了神经网络分析来确定广告效果。结果表明,神经网络能够预测广告效果指标之间的关系。即注意力,兴趣,对可再生能源技术的渴望和行动。根据神经网络分析,发现注意力是行动的最重要预测因子,其次是兴趣和欲望。

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