Creating path breakthroughs with skill endowment and complementarity: evidence from the regional industrial evolution of China, 2000–2015

This study explores how skill endowments and complementarity influence industrial development trajectories, particularly those leading to path-breaking economic activities. By drawing on the multidimensional cross-relatedness approach of evolutionary economic geography (EEG), industry-occupation cross-relatedness networks were constructed for 264 Chinese prefecture-level cities on the basis of Chinese industry and occupation data, and subsequently these were analysed to examine their interactions. Empirical evidence suggests that regions are inclined to develop new industries closely associated with skill structure. More importantly, regions with high-skilled labour agglomeration and high-low skilled labour co-agglomeration have a stronger ability to develop new industries less related to their existing industrial structures and achieve path breakthroughs. The effects of skill endowment and complementarity vary across different regions and industries. Specifically, the impact of high-low skilled labour agglomeration on industrial path breakthroughs is more pronounced in eastern China. Moreover, in regions with greater economic complexity, industrial path breakthroughs are more closely associated with skill complementarity. Labour-intensive industrial diversification exhibits the strongest relationship with skill structure, whereas the regional path dependence effect is more pronounced in areas with higher industrial complexity.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2025-08-28
DOI
https://doi.org/10.1057/s41599-025-05771-2
Citations
2
Primary Topic
Economic and Technological Innovation
Type
article
Field-Weighted Citation Impact
6.26

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article

Creating path breakthroughs with skill endowment and complementarity: evidence from the regional industrial evolution of China, 2000–2015

Dieter F. Kogler, Rongjun Ao, Xiaoqi Zhou, Jing Chen et al.
2 citations
Humanities and Social Sciences Communications
Economic and Technological Innovation
6.26
article

Creating path breakthroughs with skill endowment and complementarity: evidence from the regional industrial evolution of China, 2000–2015

Dieter F. Kogler, Rongjun Ao, Xiaoqi Zhou, Jing Chen, Junsong Wang
article en
2 citations

Abstract

This study explores how skill endowments and complementarity influence industrial development trajectories, particularly those leading to path-breaking economic activities. By drawing on the multidimensional cross-relatedness approach of evolutionary economic geography (EEG), industry-occupation cross-relatedness networks were constructed for 264 Chinese prefecture-level cities on the basis of Chinese industry and occupation data, and subsequently these were analysed to examine their interactions. Empirical evidence suggests that regions are inclined to develop new industries closely associated with skill structure. More importantly, regions with high-skilled labour agglomeration and high-low skilled labour co-agglomeration have a stronger ability to develop new industries less related to their existing industrial structures and achieve path breakthroughs. The effects of skill endowment and complementarity vary across different regions and industries. Specifically, the impact of high-low skilled labour agglomeration on industrial path breakthroughs is more pronounced in eastern China. Moreover, in regions with greater economic complexity, industrial path breakthroughs are more closely associated with skill complementarity. Labour-intensive industrial diversification exhibits the strongest relationship with skill structure, whereas the regional path dependence effect is more pronounced in areas with higher industrial complexity.

Humanities and Social Sciences CommunicationsVol. 12(1)
University College Dublin (IE), Central China Normal University (CN), East China Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 4%
Economic and Technological Innovation
6.26
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