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<p>Accelerating clean energy technology adoption requires a comprehensive understanding of the complex interplay between technological and social factors. In this Perspective, we discuss how the&#xa0;sociotechnical (ST) systems field of research, which is part of the broader field of science and technology studies (STS), aligns to the adoption readiness level (ARL) framework. Unlike the technology readiness levels, which focuses on the technical maturity of technologies, ARL aligns with STS and ST systems thinking through emphasis on the technical, economic, social, political and cultural factors that hinder technology adoption. We map four core risk areas of ARL — value proposition, market acceptance, resource maturity and licence to operate — to ST systems elements. This framework provides academics, policymakers and practitioners with theoretically grounded, context-tailored tools for improved assessment of clean technology adoption readiness.</p>

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Aligning sociotechnical systems perspectives and adoption readiness levels to accelerate clean energy adoption

  • 期刊论文

  • 发表日期：

    2026年2月3日

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  • Steve Griffiths,
  • Joao M. Uratani,
  • Dlzar Al Kez,
  • Aoife M. Foley,
  • Vanessa Chan

摘要

Accelerating clean energy technology adoption requires a comprehensive understanding of the complex interplay between technological and social factors. In this Perspective, we discuss how the sociotechnical (ST) systems field of research, which is part of the broader field of science and technology studies (STS), aligns to the adoption readiness level (ARL) framework. Unlike the technology readiness levels, which focuses on the technical maturity of technologies, ARL aligns with STS and ST systems thinking through emphasis on the technical, economic, social, political and cultural factors that hinder technology adoption. We map four core risk areas of ARL — value proposition, market acceptance, resource maturity and licence to operate — to ST systems elements. This framework provides academics, policymakers and practitioners with theoretically grounded, context-tailored tools for improved assessment of clean technology adoption readiness.