Optimizing Renewable Energy Adoption in the GCC: A Structural Equation Modeling Approach to Assessing Policy Impact and Consumer Behaviour

Abstract

Purpose:This study, with its focus on the Gulf Cooperation Council (GCC) countries, aims to analyse the effectiveness of sustainable energy policies. By examining the causal relationships between policy frameworks, consumer behaviour, and the adoption rate of renewable energy technologies, it provides practical insights that can guide policymakers and professionals in the field of sustainable energy and policy development. Design/Methodology/Approach:This research will employ a rigorous approach, utilising Structural Equation Modelling (SEM) to construct a comprehensive model. This model will assess the direct and indirect effects of various policy instruments on the uptake of renewable energy in both residential and commercial sectors. Data will be collected through surveys, focusing on consumer attitudes, awareness of energy policies, and behavioural Factors, and existing government records, which will be analysed for policy implementation data, adoption rates, and economic impact data, ensuring a robust analysis of quantitative and qualitative variables influencing energy choices. Expected Findings:The study is poised to uncover significant insights into how different policy measures influence the decision-making process of energy consumers. These findings are expected to highlight key policy levers that could significantly accelerate the transition towards sustainable energy sources within the GCC, thereby shaping future policy development in the region. Originality/Value:This research stands out in the limited but growing frame of literature on the effectiveness of energy policies in the Middle East. It particularly shines within the context of socio-economic variables and regional sustainability goals. The study will provide unique and valuable recommendations for policymakers to refine strategies that facilitate the broader adoption of sustainable energy technologies.