Network evolution model for supply chain with manufactures as the core
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DOI: 10.1371/journal.pone.0191180
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Cited by:
- Aymeric Vié & Alfredo J. Morales, 2021. "How Connected is Too Connected? Impact of Network Topology on Systemic Risk and Collapse of Complex Economic Systems," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1327-1351, April.
- Shen, Ai-Zhong & Guo, Jin-Li & Wu, Guo-Lin & Jia, Shu-Wei, 2018. "The agglomeration phenomenon influence on the scaling law of the scientific collaboration system," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 461-467.
- Yoon, Gyugeun & Chow, Joseph Y.J., 2024. "A sequential transit network design algorithm with optimal learning under correlated beliefs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 191(C).
- Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
- Xuda Lin & Xing Li & Sameer Kulkarni & Fu Zhao, 2021. "The Application of Blockchain-Based Life Cycle Assessment on an Industrial Supply Chain," Sustainability, MDPI, vol. 13(23), pages 1-15, December.
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