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Industrial Agglomeration, Agglomeration Externalities and Enterprise Energy Intensity—An Analysis Based on Upstream and Downstream Industry Linkages

Xiaojie Liu & Hounan Chen

Managerial and Decision Economics2026https://doi.org/10.1002/mde.70094article
AJG 2ABDC B
Weight
0.50

What the paper says

ABSTRACT Continuous promotion of energy intensity (EI) reduction in the manufacturing industry is vital for achieving energy consumption and carbon emission reduction goals. This study expands the traditional specialized industrial agglomeration (IA) research perspective and establishes upstream‐IA and downstream‐IA types via industry linkages. Using microscale data for Chinese manufacturing enterprises from 2007 to 2015, through the agglomeration externality channel, we empirically assess the effects and paths of three IA types on enterprise EI and find the following: First, the specialized‐IA, upstream‐IA and downstream‐IA types significantly reduce enterprise EI, and the upstream‐IA type yields the greatest efficiency enhancement effect. Second, the analysis of the mechanism underlying agglomeration externalities reveals that the paths through which the specialized‐IA type affects EI are labour pooling, intermediate input sharing and knowledge spillover; the paths through which the upstream‐IA type operates are intermediate input sharing and knowledge spillover; and the path through which the downstream‐IA type operates is labour pooling. Third, the effect of IA is particularly significant in the sample of nonexporting enterprises and energy‐intensive enterprises. Fourth, the specialized‐IA, upstream‐IA and downstream‐IA types reduce EI without reducing production, thus achieving synergy between efficiency enhancement and consumption reduction.

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https://doi.org/https://doi.org/10.1002/mde.70094

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@article{xiaojie2026,
  title        = {{Industrial Agglomeration, Agglomeration Externalities and Enterprise Energy Intensity—An Analysis Based on Upstream and Downstream Industry Linkages}},
  author       = {Xiaojie Liu & Hounan Chen},
  journal      = {Managerial and Decision Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/mde.70094},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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