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Research On Risk Cascading Propagation And Recovery Strategy Of Automobile Supply Chain Network

Posted on:2022-05-10Degree:MasterType:Thesis
Country:ChinaCandidate:Z T WangFull Text:PDF
GTID:2492306740450604Subject:Logistics Engineering
Abstract/Summary:PDF Full Text Request
With the deepening of globalization,the relationship between the enterprises in the automobile supply chain can not be represented by a chain structure,so it is particularly important to study it from the perspective of network.Because most of the automobile enterprises adopt the global strategy,lean production mode,and the international situation is complex and changeable,the automobile supply chain network is subject to risk disturbance all the time.When the risk disturbance is large,leading to the failure of individual enterprises in the network,it is very easy to form risk cascade propagation in the network,and it is likely that a large number of enterprises will stop production and business,and the network will be forced to interrupt.Focusing on what kind of recovery strategy can reduce the scope of network risk propagation,reduce the impact degree,and improve the network efficiency,this paper constructs a disturbance based risk cascade propagation model,and explores its recovery strategy,so as to provide some suggestions for automobile enterprises to deal with risk cascade propagation,It provides a reference for the automotive supply chain network to take emergency recovery strategy.Considering the characteristics of numerous layers and highly dynamic topology of automobile supply chain network,a multi-level automobile supply chain network construction method based on node degree preference and competitive advantage preference is proposed.In order to be closer to the reality,not only the supply and demand cooperation between upstream and downstream,but also the competitive cooperation between peer nodes at the same level are considered in the network construction.Through simulation,the degree distribution,average path length and clustering coefficient are analyzed to prove the scale-free and small world characteristics of the network.Based on the analysis of risk propagation characteristics and main risk sources in automobile supply chain network,this paper proposes a risk cascade propagation model under disturbance based on the collection of risk events in automobile supply chain network in recent years,and takes risk propagation range,risk impact strength and global network efficiency as evaluation indexes.Through the simulation of the five level automobile supply chain network,it is found that increasing the tolerance coefficient can delay the risk cascade propagation,reduce the risk impact intensity,and slow down the reduction of network efficiency.Considering the influence of the three load allocation strategies on the three indicators,it is concluded that the residual capacity allocation strategy can reduce the risk propagation to the greatest extent and protect the network.The results show that the limited time recovery strategy has a periodic impact on the risk cascade.In terms of reducing the scope of risk transmission,the optimal recovery is better than the probability recovery.Therefore,when the recovery resources of the automobile supply chain network are limited,we should choose the node enterprises with the highest degree value and risk tolerance value to recover according to the recovery importance calculation method proposed in this paper,so as to quickly curb the risk cascade transmission.However,the three recovery strategies can not significantly improve the network efficiency,indicating that even if the recovery strategy is adopted,it still can not offset the damage caused by risk cascading propagation to the network.This paper emphasizes the necessity of preventing risk cascading propagation,and finally puts forward some suggestions for preventing risk cascading propagation in automobile supply chain network.
Keywords/Search Tags:Automobile supply chain network, cascading failure, risk propagation, recovery strategy
PDF Full Text Request
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