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Infrastructure, Energy & Services
Journal articleOpen access

Industrial Upgrading and Urban Energy Transition: Unpacking Co-Evolutionary Mismatches in China’s Legacy Industrial Cities

Published 19 Aug 2026 · Added to radar 5 Nov 2026

Source abstract

Industrial legacy cities are trapped in carbon lock-in—a self-reinforcing condition where fossil-fuel infrastructure, industrial structures, and institutional inertia collectively resist urban energy transition. Yet whether and how industrial upgrading policies (IUP) can effectively disrupt this lock-in remains unclear. Using panel data from 148 Chinese legacy cities over 2012–2022, we employ a staggered difference-in-differences model combined with policy-text quantification to evaluate the effects of IUP. Results show that IUP significantly raises urban energy transition by 2.52 percentage points, with technology-enabling instruments delivering the strongest leverage among the three policy tool categories. Mechanism analysis uncovers a co-evolutionary mismatch: green technology innovation mediates 42.21% of the total effect, while the mediating pathway through energy consumption structure remains statistically insignificant—evidence that production-side innovation and energy-side infrastructure exhibit systematically divergent adjustment elasticities in response to industrial upgrading policy. Policy effects also differ across city types, with stronger responses in old industrial base, regenerative, and single-type cities. These findings advance carbon lock-in theory by identifying co-evolutionary mismatch as a distinct source of structural friction in urban industrial transitions and provide actionable pathways for aligning urban industrial restructuring with decarbonization goals.

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Structured record

Source-reported findings
  • Results show that IUP significantly raises urban energy transition by 2.52 percentage points, with technology-enabling instruments delivering the strongest leverage among the three policy tool categories.
Methods
difference-in-differences, panel-data analysis

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