Predicting intention in applying solar energy technologies in agriculture industry: A moderated and mediated model

Excessive fossil fuel consumption has increased the greenhouse gases (GHG)s effect, and provoked climate change in recent decades. The agricultural industry, one of the major consumers of this energy type, highly contributes to the existing challenges. Applying solar energy technologies (SETs) in this industry can lead to the development of green energies and reduce existing problems. Structural equation modeling (SEM) is adopted to assess the factors influencing farmers' intention to utilize SETs. A researcher-devised questionnaire is distributed among 594 farmers in Tehran Province, Iran, and the obtained data is analyzed through AMOS (version 26) software package. The results revealed the positive and significant effects of attitude, awareness, self-efficacy, trust in technology, performance expectancy, and facilitating conditions on usage intention; thus, 57.4% predicted usage intention of SETs. The distance from the power grids (DPG)s moderates the correlation between 1) trust in technology and usage intention,2) the correlation between attitude and usage intention, and 3) facilitating conditions and trust in technology. Attitude partially mediated the correlation between variables (except self-efficacy) and usage intention. In addition to the theoretical implications, this study can assist the policymakers in defining policies for developing renewable energies (RE)s, especially solar, in developing countries.