Analysing performance barriers to the large-scale adoption of green hydrogen in the Indian landscape

Purpose Rising greenhouse gas emissions significantly drive global climate change, highlighting the need for sustainable energy solutions. This study explores performance barriers affecting the large-scale adoption of green hydrogen as a clean energy source in India. It presents a managerial framework that assesses these barriers' severity, aiding strategic planning by revealing their interconnections. Design/methodology/approach An extensive literature review identifies 22 barriers to green hydrogen adoption. Using best–worst method (BWM), these are categorised into six groups. The decision-making trial and evaluation laboratory (DEMATEL) then analyses the 16 most critical performance barriers through a cause-and-effect approach to identify influential factors. The sensitivity analysis is performed to ensure the robustness of the results. Findings Findings show that infrastructure challenges, lack of materials availability and clean water and financial barriers, like high production and maintenance costs, significantly hinder green hydrogen initiatives in India. The analysis reveals that raw material availability and electrolyser capacity are the most impactful barriers affecting the performance of the green hydrogen value chain. Practical implications With global demand for sustainable energy surging amid rising emissions and ecological concerns, green hydrogen is becoming a viable source for sustainable energy production, especially in developing nations like India. This framework helps organisations and policymakers systematically evaluate and prioritise barriers to green hydrogen adoption, providing actionable insights for strategic interventions. Originality/value This study presents a structured framework employing BWM and DEMATEL to categorise and analyse green hydrogen adoption barriers. It equips practitioners and policymakers with a practical tool to assess and prioritise performance barriers, offering insights into their hierarchical and causal relationships.