Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics

Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulne...

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Main Authors: Ruguo Fan, Yang Qi, Yitong Wang, Rongkai Chen
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Systems
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Online Access:https://www.mdpi.com/2079-8954/13/7/599
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author Ruguo Fan
Yang Qi
Yitong Wang
Rongkai Chen
author_facet Ruguo Fan
Yang Qi
Yitong Wang
Rongkai Chen
author_sort Ruguo Fan
collection DOAJ
description Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model based on Chinese low-carbon patent data, comprising a low-carbon collaboration network of innovation entities and a low-carbon knowledge network of technological components. Applying dynamic shock propagation modeling, we analyze how risks spread within and between network layers under various shocks. Our findings reveal significant differences in vulnerability distribution: the knowledge network consistently demonstrates greater susceptibility to cascading failures than the collaboration network, reaching complete system failure, while the latter maintains partial resilience, with resilience levels stabilizing at approximately 0.64. Critical node analysis identifies State Grid Corporation as a vulnerability point in the collaboration network, while multiple critical knowledge elements can independently trigger system-wide failures. Cross-network propagation follows distinct patterns, with knowledge-network failures consistently preceding collaboration network disruptions. In addition, propagation from the collaboration network to the knowledge network showed sharp transitions at specific threshold values, while propagation in the reverse direction displayed more gradual responses. These insights suggest tailored resilience strategies, including policy decentralization approaches, ensuring technological redundancy across critical knowledge domains and strengthening cross-network coordination mechanisms to enhance low-carbon innovation system stability.
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spelling doaj-art-01840a21e0724d6e9bcfdf2e8170af052025-08-20T03:08:06ZengMDPI AGSystems2079-89542025-07-0113759910.3390/systems13070599Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation DynamicsRuguo Fan0Yang Qi1Yitong Wang2Rongkai Chen3School of Economics and Management, Wuhan University, Wuhan 430072, ChinaSchool of Economics and Management, Wuhan University, Wuhan 430072, ChinaSchool of Economics and Management, Wuhan University, Wuhan 430072, ChinaSchool of Applied Economics, Renmin University of China, Beijing 100872, ChinaGlobal low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model based on Chinese low-carbon patent data, comprising a low-carbon collaboration network of innovation entities and a low-carbon knowledge network of technological components. Applying dynamic shock propagation modeling, we analyze how risks spread within and between network layers under various shocks. Our findings reveal significant differences in vulnerability distribution: the knowledge network consistently demonstrates greater susceptibility to cascading failures than the collaboration network, reaching complete system failure, while the latter maintains partial resilience, with resilience levels stabilizing at approximately 0.64. Critical node analysis identifies State Grid Corporation as a vulnerability point in the collaboration network, while multiple critical knowledge elements can independently trigger system-wide failures. Cross-network propagation follows distinct patterns, with knowledge-network failures consistently preceding collaboration network disruptions. In addition, propagation from the collaboration network to the knowledge network showed sharp transitions at specific threshold values, while propagation in the reverse direction displayed more gradual responses. These insights suggest tailored resilience strategies, including policy decentralization approaches, ensuring technological redundancy across critical knowledge domains and strengthening cross-network coordination mechanisms to enhance low-carbon innovation system stability.https://www.mdpi.com/2079-8954/13/7/599low-carbon innovationinnovation networkpropagation modelinterdependent networkrisk propagation
spellingShingle Ruguo Fan
Yang Qi
Yitong Wang
Rongkai Chen
Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics
Systems
low-carbon innovation
innovation network
propagation model
interdependent network
risk propagation
title Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics
title_full Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics
title_fullStr Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics
title_full_unstemmed Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics
title_short Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics
title_sort identifying critical risks in low carbon innovation network ecosystem interdependent structure and propagation dynamics
topic low-carbon innovation
innovation network
propagation model
interdependent network
risk propagation
url https://www.mdpi.com/2079-8954/13/7/599
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AT yangqi identifyingcriticalrisksinlowcarboninnovationnetworkecosysteminterdependentstructureandpropagationdynamics
AT yitongwang identifyingcriticalrisksinlowcarboninnovationnetworkecosysteminterdependentstructureandpropagationdynamics
AT rongkaichen identifyingcriticalrisksinlowcarboninnovationnetworkecosysteminterdependentstructureandpropagationdynamics