研究目的
To identify and prioritize the effectiveness of various drivers that could increase construction professional’s uptake of solar PV projects and the anticipated outcomes of these drivers.
研究成果
The study found that lowering the costs of solar technology is the most effective driver for promoting the uptake of solar PV projects among construction professionals. Improved solar panel efficiency and energy storage were identified as the most anticipated outcomes. The findings suggest that once costs can be lowered to an affordable level, uptake of solar PV is likely to increase across the construction industry. Future research should focus on ways to achieve lowered costs of solar PV technology and increase technology efficiency levels.
研究不足
The study's sample was limited to construction professionals in the greater Melbourne region, which may not represent the views of professionals in other Australian states or territories. The comparison of mean scores should be read with due caveats on the limitations of the working sample and the constraint on the scope of research.
1:Experimental Design and Method Selection:
An online questionnaire survey was designed to collect data from construction industry professionals regarding their views on drivers and outcomes of solar PV projects. The survey included demographic questions, agreement levels on drivers, and anticipated outcomes of solar PV projects.
2:Sample Selection and Data Sources:
Targeted respondents were construction practitioners within the greater Melbourne region, including developers, consultants, contractors, and sub-contractors. Data was collected through professional databases and LinkedIn.
3:List of Experimental Equipment and Materials:
Online Qualtrics questionnaire platform was used for survey distribution and data collection.
4:Experimental Procedures and Operational Workflow:
Invitations were sent to 200 targeted respondents to complete the questionnaire. Responses were analyzed using an entropy ranking approach to prioritize drivers and outcomes.
5:Data Analysis Methods:
Mean scores and standard deviations were calculated for each driver and outcome. Entropy ranking analysis was conducted to measure the obtained results simultaneously, facilitating prioritisation and ranking of both the drivers and outcomes.
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