At a time when India experiences rapidly rising living standards, while facing increasing sustainability challenges, decoupling economic growth from the increase in energy consumption is a critical challenge. Energy efficiency solutions in the residential sector have an important role, as these can significantly curb energy consumption. To steer future adoption towards energy-efficient appliances, it is imperative to understand the drivers and barriers behind consumer choices. The objective of this study is to understand the drivers and barriers behind the adoption of energy-efficient appliances in Indian households. These insights can be used to accelerate the adoption of these appliances and help India transition to a greener and more sustainable future. This study leverages an explanatory mixed methods approach in which a quantitative logistic regression model is followed by a qualitative analysis consisting of semi-structured expert interviews. This methodology is suitable for this research as it performs a robust empirical analysis of data through a regression. At the same time, the methodology allows deepening the understanding of observed patterns and contextualizes findings through expert insights. This synergy combines quantitative rigour with qualitative depth, providing a holistic understanding of factors influencing energy-efficient appliance adoption. The initial phase consisted of a critical literature review, showing a limited academic focus on understanding the drivers behind energy-efficient appliance adoption in the Indian household sector. Variables relevant to adoption patterns were developed in this section, based on an overview of the academic research. In addition, the policy environment was conceptualized to create an overview of the policy domain and understand the effect of various Indian policies on energy-efficient consumer choices. This overview aided the understanding of the breadth and impact of policy measures. The quantitative element of the mixed methods approach is a logistic regression model in R, leveraging the IRES survey and the AEEE energy-efficiency index datasets. To corroborate and contextualize the quantitative findings, a qualitative phase was developed, consisting of 10 semi-structured expert interviews in India with policymakers, researchers, industry leaders, and lobby organizations. Insights from the qualitative phase were systematically extracted using a thematic analysis. Lastly, an integration step was taken to combine the findings from both research phases and offer a comprehensive and nuanced understanding of drivers and barriers behind the adoption of energy-efficient lighting and fans. This quantitative analysis revealed key drivers behind the adoption of LED lighting and energy-efficient ceiling fans such as a clear relationship between household income and the adoption of energy-efficient appliances, with higher income levels correlating strongly with increased adoption likelihood. Awareness, particularly regarding star labeling and environmental benefits, along with higher education levels and living conditions, such as grid connections and climate zones also positively influences energy-efficient appliance adoption. Urbanization significantly impacts the adoption of energy-efficient ceiling fans, while its effect on LED lighting adoption, though present, is not statistically significant. State-level policy impacts appear more nuanced, highlighting the need for further qualitative exploration to understand underlying regional influences. In the thematic analysis following from the expert-interviews, patterns around evolving themes were developed, revealing the dynamics behind the observed relationships between variables...