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<p>As labor- and resource-intensive sectors, the co-location of manufacturing and producer services (industrial co-agglomeration, ICA) alters regional resource distribution. High-speed rail (HSR) generates time-space compression effects that improve factor mobility and affect local carbon outputs. Existing research rarely investigates HSR’s influence on carbon emission efficiency (CEE) through this lens. Our analysis employs 2006–2020 panel data from 27 Yangtze River Delta (YRD) cities, measuring ICA through location entropy, assessing CEE via the SBM-DEA model, and quantifying factor misallocation using the LSDV approach. Spatial Durbin modeling and mediation analysis reveal ICA’s spatial impacts on CEE and HSR-induced resource misallocation pathways, clarifying their underlying connections. The results show that: (1) ICA’s direct effect on CEE is inverted U-shaped (inflection point at 2.213), while its spillover effect is U-shaped (inflection point at 2.601). HSR modifies these thresholds, converting negative effects to positive in three cities for the direct effect and twelve cities for the spillover effect. (2) ICA has a U-shaped impact on labor misallocation (inflection point at 2.820) and capital misallocation (inflection point at 2.269). HSR accelerates efficiency changes, reversing misallocacompetitiveness of china’s electroniction effects in three cities for labor and eight cities for capital. (3) Resource misallocation mediates the effect of ICA on CEE under HSR, with labor misallocation accounting for 26.5% and capital misallocation for 9.99%. The findings provide a policy basis for improving CEE and developing a low-carbon economy in the YRD urban agglomeration through optimized ICA and resource allocation.</p>

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Industrial collaborative agglomeration, resource misallocation and carbon emission efficiency

  • 期刊论文

  • 发表日期：

    2025年10月23日

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  • Yuzhi Qi

摘要

As labor- and resource-intensive sectors, the co-location of manufacturing and producer services (industrial co-agglomeration, ICA) alters regional resource distribution. High-speed rail (HSR) generates time-space compression effects that improve factor mobility and affect local carbon outputs. Existing research rarely investigates HSR’s influence on carbon emission efficiency (CEE) through this lens. Our analysis employs 2006–2020 panel data from 27 Yangtze River Delta (YRD) cities, measuring ICA through location entropy, assessing CEE via the SBM-DEA model, and quantifying factor misallocation using the LSDV approach. Spatial Durbin modeling and mediation analysis reveal ICA’s spatial impacts on CEE and HSR-induced resource misallocation pathways, clarifying their underlying connections. The results show that: (1) ICA’s direct effect on CEE is inverted U-shaped (inflection point at 2.213), while its spillover effect is U-shaped (inflection point at 2.601). HSR modifies these thresholds, converting negative effects to positive in three cities for the direct effect and twelve cities for the spillover effect. (2) ICA has a U-shaped impact on labor misallocation (inflection point at 2.820) and capital misallocation (inflection point at 2.269). HSR accelerates efficiency changes, reversing misallocacompetitiveness of china’s electroniction effects in three cities for labor and eight cities for capital. (3) Resource misallocation mediates the effect of ICA on CEE under HSR, with labor misallocation accounting for 26.5% and capital misallocation for 9.99%. The findings provide a policy basis for improving CEE and developing a low-carbon economy in the YRD urban agglomeration through optimized ICA and resource allocation.