TY - JOUR
T1 - How does the trust affect the topology of supply chain network and its resilience? An agent-based approach
AU - Hou, Yunzhang
AU - Wang, Xiaoling
AU - Wu, Yenchun Jim
AU - He, Peixu
N1 - Funding Information:
This research is supported in part by (i) National Natural Science Foundation of China (Nos. 71471041 and 71001028 ), (ii) National Social Science Foundation of China (No. 14CGL017 ), (iii) Fujian Social Sciences Planning Project ( FJ2017C022 ), and (iv) Research Start-up Funding for High-level Talents Project Sponsored by Huaqiao University ( Z17Y0035 ).
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/8
Y1 - 2018/8
N2 - This paper builds a dynamic supply chain network, where firms can select suppliers according to the trust, the selling price or just randomly. Simulation results show that the trust-based rule can significantly increase the aggregated working capital and decrease firm's likelihoods of bankruptcy. Moreover, firms’ sizes under trust-based and price-based rules follow power-law distributions. The degree distribution of supply chain network under price-based rule follows a power-law distribution, while those under trust-based and randomly-choosing rules are similar to that of random network. Furthermore, results also indicate that trust-based rule is the most robust one against random and targeted disruptions.
AB - This paper builds a dynamic supply chain network, where firms can select suppliers according to the trust, the selling price or just randomly. Simulation results show that the trust-based rule can significantly increase the aggregated working capital and decrease firm's likelihoods of bankruptcy. Moreover, firms’ sizes under trust-based and price-based rules follow power-law distributions. The degree distribution of supply chain network under price-based rule follows a power-law distribution, while those under trust-based and randomly-choosing rules are similar to that of random network. Furthermore, results also indicate that trust-based rule is the most robust one against random and targeted disruptions.
KW - Complex adaptive system
KW - Multi-agent simulation
KW - Supply chain network
KW - Supply chain resilience
KW - Supply disruption
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U2 - 10.1016/j.tre.2018.07.001
DO - 10.1016/j.tre.2018.07.001
M3 - Article
AN - SCOPUS:85049624040
SN - 1366-5545
VL - 116
SP - 229
EP - 241
JO - Transportation Research Part E: Logistics and Transportation Review
JF - Transportation Research Part E: Logistics and Transportation Review
ER -