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<p>Industrial carbon lock-in represents a structural barrier to low-carbon transformation, posing a significant challenge to realizing the Sustainable Development Goals (SDGs). However, the mechanisms through which industrial carbon unlocking can be effectively achieved remain underexplored. To address this gap, this study develops a novel quantitative evaluation system aligned with the SDGs by employing a Slacks-Based Measure model with undesirable output to assess industrial carbon unlocking efficiency (ICUE) across 30 provinces in China from 2000 to 2021. Moreover, by integrating a government–market–society institutional framework with dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA), the study determines multiple pathways driving high-level ICUE. The results reveal that: (1) ICUE exhibits a fluctuating yet overall upward trend with spatial heterogeneity (East &gt; Central &gt; West), although regional disparities have gradually narrowed; (2) no individual factor is necessary for high-level ICUE, which instead arises from multi-actor interactions, with market investment efficiency playing a universal role; (3) four unlocking pathways are identified: market–society dual-driven, government–market dual-driven, innovation–efficiency driven, and holistic synergy-driven, demonstrating functional equivalence; (4) a longitudinal comparison across four Five-Year Plan periods reveals increasing diversification in unlocking pathways and a transition from market-dominated models to more institutionally coordinated governance. Overall, this study represents one of the first attempts to integrate a multi-actor institutional perspective with dynamic fsQCA, enabling the exploration of how multiple drivers jointly configure to influence ICUE. The findings provide scenario-adaptive dynamic pathways for policymakers to promote carbon unlocking, thereby advancing progress toward the SDGs.</p>

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Unlocking the dilemma of industrial carbon lock-in: a configurational analysis integrating institutional logics theory

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月5日

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  • Kaijian Li,
  • Rui Li,
  • Liu Chen,
  • Lanxi Liu,
  • Luping Qin,
  • Beifei Yuan,
  • Yuxin Bai,
  • Guoxu Liu

摘要

Industrial carbon lock-in represents a structural barrier to low-carbon transformation, posing a significant challenge to realizing the Sustainable Development Goals (SDGs). However, the mechanisms through which industrial carbon unlocking can be effectively achieved remain underexplored. To address this gap, this study develops a novel quantitative evaluation system aligned with the SDGs by employing a Slacks-Based Measure model with undesirable output to assess industrial carbon unlocking efficiency (ICUE) across 30 provinces in China from 2000 to 2021. Moreover, by integrating a government–market–society institutional framework with dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA), the study determines multiple pathways driving high-level ICUE. The results reveal that: (1) ICUE exhibits a fluctuating yet overall upward trend with spatial heterogeneity (East > Central > West), although regional disparities have gradually narrowed; (2) no individual factor is necessary for high-level ICUE, which instead arises from multi-actor interactions, with market investment efficiency playing a universal role; (3) four unlocking pathways are identified: market–society dual-driven, government–market dual-driven, innovation–efficiency driven, and holistic synergy-driven, demonstrating functional equivalence; (4) a longitudinal comparison across four Five-Year Plan periods reveals increasing diversification in unlocking pathways and a transition from market-dominated models to more institutionally coordinated governance. Overall, this study represents one of the first attempts to integrate a multi-actor institutional perspective with dynamic fsQCA, enabling the exploration of how multiple drivers jointly configure to influence ICUE. The findings provide scenario-adaptive dynamic pathways for policymakers to promote carbon unlocking, thereby advancing progress toward the SDGs.