The Dynamic Impact of Industrial Robot Penetration on Chain Resilience: City Evidence from China

Nowadays, the security and stability of the global industrial chain are facing unprecedented challenges. In this context, understanding how industrial robots affect chain resilience is key to promoting high-quality economic development. This study focuses on 104 cities in the Yangtze River Delta, using data from 2006 to 2021. It applies a threshold regression model and a spatial Durbin model to examine how industrial robot penetration drives chain resilience and how its effects spread across regions. The results reveal three main findings: First, the integration of advanced manufacturing and modern services, together with strong urban innovation capacity, plays a significant role in enhancing industrial chain resilience. Second, this study evaluates policy experiments, such as Low-Carbon City and Broadband China initiatives, using a multi-period difference-in-differences model. The findings show that pilot cities involved in these programs demonstrate higher levels of chain resilience. Third, the relationship between robot penetration and chain resilience shows clear spatial and temporal patterns. Cities with higher robot usage tend to drive development in surrounding areas. This, in turn, encourages more intensive production and fosters stronger coordination across industries. Overall, this study contributes to the growing body of research on chain resilience. More importantly, it offers practical policy insights. Governments and regional firms can work together to build a new development model that enhances resilience and supports long-term economic stability.

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Publication Details

Journal
Systems
Published
2025-05-07
DOI
https://doi.org/10.3390/systems13050362
Citations
4
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
8.91
Controls
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article

The Dynamic Impact of Industrial Robot Penetration on Chain Resilience: City Evidence from China

Rendao Ye, Yilan Zhang
4 citations
Systems
Supply Chain Resilience and Risk Management
8.91
article

The Dynamic Impact of Industrial Robot Penetration on Chain Resilience: City Evidence from China

Rendao Ye, Yilan Zhang
article en
4 citations

Abstract

Nowadays, the security and stability of the global industrial chain are facing unprecedented challenges. In this context, understanding how industrial robots affect chain resilience is key to promoting high-quality economic development. This study focuses on 104 cities in the Yangtze River Delta, using data from 2006 to 2021. It applies a threshold regression model and a spatial Durbin model to examine how industrial robot penetration drives chain resilience and how its effects spread across regions. The results reveal three main findings: First, the integration of advanced manufacturing and modern services, together with strong urban innovation capacity, plays a significant role in enhancing industrial chain resilience. Second, this study evaluates policy experiments, such as Low-Carbon City and Broadband China initiatives, using a multi-period difference-in-differences model. The findings show that pilot cities involved in these programs demonstrate higher levels of chain resilience. Third, the relationship between robot penetration and chain resilience shows clear spatial and temporal patterns. Cities with higher robot usage tend to drive development in surrounding areas. This, in turn, encourages more intensive production and fosters stronger coordination across industries. Overall, this study contributes to the growing body of research on chain resilience. More importantly, it offers practical policy insights. Governments and regional firms can work together to build a new development model that enhances resilience and supports long-term economic stability.

SystemsVol. 13(5)
Hangzhou Dianzi University (CN)
Openalex Percentile: Top 3%
Supply Chain Resilience and Risk Management
8.91
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