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Measuring structural characteristics and evolutionary patterns of an industrial carbon footprint network: A social network analysis approach

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  • Yuan Yuan
  • Xintong Sun
  • Ning Liu

Abstract

The formation of an industrial network is inevitable because an industrial structure evolves to a higher level. The continuous material exchange among sectors creates a path for the embodied carbon in products to flow freely among industries. With the gradual complication of industrial networks, however, the emission reduction behavior of sectors not only becomes rooted in individual conduct, but also originates from the interaction forces between individuals. Therefore, carbon management in industries in the real economy needs to be explored from the perspective of these complex networks. On the basis of these considerations, this study utilized a hybrid model, the Economic Input–Output Life Cycle Assessment model, to construct the carbon footprint network of China's industries in 2002, 2007, 2012, and 2017. We also applied social network analysis to quantify the structural characteristics and evolutionary patterns of the network. Results showed that the transmission efficiency of resources and the subgroup‐integrated degree of the actors within the carbon footprint network were excellent, which was conducive to coordinated carbon emission reduction of these sectors from a network perspective. Agriculture and services were the engines driving sector‐wide carbon emission reduction through links within the network. Furthermore, some sectors, such as transportation and the warehousing industry, basic chemicals and chemical products manufacturing, and metal smelting and rolling processing industry, act as bridges and brokers. These sectors are keys to ensuring network cohesion and reducing the risk of network fragmentation. Finally, the industrial block network presented a hierarchical structure of a core–edge network. The network followed a trend of structural changes in which the network core became increasingly clear, and the network distribution pattern gradually concentrated on a single block. This finding revealed a new pathway for collaborative carbon mitigation in the industry from the perspective of the industrial community. La formación de una red industrial es inevitable porque cualquier estructura industrial evoluciona hacia un nivel superior. El continuo intercambio de materiales entre sectores crea una vía para que el carbono incorporado en los productos fluya libremente entre las industrias. Sin embargo, con la complicación gradual de las redes industriales, el comportamiento de los sectores en materia de reducción de emisiones no sólo se arraiga en la conducta individual, sino que también se origina en las fuerzas de interacción entre los individuos. Por lo tanto, la gestión del carbono en las industrias de la economía real debe explorarse desde la perspectiva de estas complejas redes. Partiendo de estas consideraciones, este estudio utilizó un modelo híbrido, el modelo de Evaluación del Ciclo de Vida Económico de Input‐Output, para construir la red de la huella de carbono de las industrias de China en 2002, 2007, 2012 y 2017. También se aplicó el análisis de redes sociales para cuantificar las características estructurales y los patrones de evolución de la red. Los resultados mostraron que la eficiencia de transmisión de los recursos y el grado de integración de los actores en la red de la huella de carbono eran excelentes, lo que propició una reducción coordinada de las emisiones de carbono de estos sectores desde la perspectiva de la red. La agricultura y los servicios fueron los motores que impulsaron la reducción de las emisiones de carbono en todo el sector a través de los enlaces dentro de la red. Además, algunos sectores, como el transporte y la industria de almacenamiento, la fabricación de productos químicos básicos y la industria de fundición y laminación de metales, actúan como puentes e intermediarios. Estos sectores son clave para garantizar la cohesión de la red y reducir el riesgo de fragmentación de la misma. Por último, la red de bloques industriales presentó una estructura jerárquica de red núcleo–borde. La red siguió una tendencia de cambios estructurales en la que el núcleo de la red se hizo cada vez más aparente, y el patrón de distribución de la red se concentró gradualmente en un solo bloque. Este hallazgo reveló una nueva vía de colaboración para la mitigación del carbono en la industria desde la perspectiva de la comunidad industrial. 産業構造が高度化するため、産業ネットワークの形成は避けられない。各部門間における継続的な資材交換は、embodied carbon(内包二酸化炭素)が産業間で自由に流通する通路を形成する。しかし、産業ネットワークが徐々に複雑化するにつれ、各部門のCO2排出削減行動は、個人の行動に根ざしているだけでなく、個人間の相互作用にも起因している。したがって、この複雑なネットワークの観点から、実体経済の産業におけるCO2管理を探求する必要がある。これらの考察に基づき、本研究ではハイブリッドモデルであるEconomic Input–Output Life Cycle Assessment(EIO‐LCA)モデルを用いて、2002年、2007年、2012年、2017年の中国の産業におけるカーボンフットプリントのネットワークを構築した。また、ネットワークの構造特性と進化のパターンを定量化するために、ソーシャルネットワーク解析を適用した。結果から、資源の伝達効率とカーボンフットプリントのネットワーク内のアクターのサブグループの統合度が優れていることが示されたが、これはネットワークの観点から、この部門の協調的CO2排出削減を促進するものであった。農業とサービス部門は、ネットワーク内のリンクを介して部門全体のCO2排出削減を推進する原動力となった。さらに、運輸・倉庫業、基礎化学品・化学製品製造業、金属製錬・圧延加工業などの一部の部門が橋渡しや仲介役となっている。これらの部門は、ネットワークの凝集性を確保し、ネットワークの断片化のリスクを軽減するのに重要である。また、産業連携ネットワークは、コアエッジネットワークの階層構造を示した。このネットワークは、ネットワークコアが次第に明らかになり、ネットワーク分布パターンが次第に単一ブロックに集中する構造変化の傾向にあった。この知見から、産業コミュニティの観点から、産業界における協調的なCO2削減のための新しい経路が示された。

Suggested Citation

  • Yuan Yuan & Xintong Sun & Ning Liu, 2022. "Measuring structural characteristics and evolutionary patterns of an industrial carbon footprint network: A social network analysis approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 159-180, November.
  • Handle: RePEc:bla:rgscpp:v:14:y:2022:i:s2:p:159-180
    DOI: 10.1111/rsp3.12544
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    References listed on IDEAS

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    1. Watanabe, Nicholas M. & Kim, Jiyeon & Park, Joohyung, 2021. "Social network analysis and domestic and international retailers: An investigation of social media networks of cosmetic brands," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    2. Lopreite, Milena & Puliga, Michelangelo & Riccaboni, Massimo & De Rosis, Sabina, 2021. "A social network analysis of the organizations focusing on tuberculosis, malaria and pneumonia," Social Science & Medicine, Elsevier, vol. 278(C).
    3. Onat, Nuri Cihat & Kucukvar, Murat, 2020. "Carbon footprint of construction industry: A global review and supply chain analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    4. Hu, Ying & Yu, Yang & Mardani, Abbas, 2021. "Selection of carbon emissions control industries in China: An approach based on complex networks control perspective," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    5. Sun, Xiaoqi & An, Haizhong & Liu, Xiaojia, 2018. "Network analysis of Chinese provincial economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1168-1180.
    6. Can, Umit & Alatas, Bilal, 2019. "A new direction in social network analysis: Online social network analysis problems and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    7. Scott, John, 1988. "Social Network Analysis and Intercorporate Relations," Hitotsubashi Journal of commerce and management, Hitotsubashi University, vol. 23(1), pages 53-68, December.
    8. Marian R. Chertow, 2007. "“Uncovering” Industrial Symbiosis," Journal of Industrial Ecology, Yale University, vol. 11(1), pages 11-30, January.
    9. Chen, Cheng & Matzdorf, Bettina & Zhen, Lin & Schröter, Barbara, 2020. "Social-Network Analysis of local governance models for China's eco-compensation program," Ecosystem Services, Elsevier, vol. 45(C).
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