Dataset Information

Fragility of a multilayer network of intranational supply chains.

ABSTRACT: Supply chains enable the flow of goods and services within economic systems. When mapped for the entire economy and geographic locations of a country, supply chains form a spatial web of interactions among suppliers and buyers. One way to characterize supply chains is through multiregional input-output linkages. Using a multiregional input-output dataset, we build the multilayer network of supply chains in the United States. Together with a network cascade model, the multilayer network is used to explore the propagation of economic shocks along intranational supply chains. We find that the effect of economic shocks, measured using the avalanche size or total number of collapsed nodes, varies widely depending on the geographic location and economic sector of origin of a shock. The response of the supply chains to shocks reveals a threshold-like behavior. Below a certain failure or fragility level, the avalanche size increases relatively quickly for any node in the network. Based on this result, we find that the most fragile regions tend to be located in the central United States, which are regions that tend to specialize in food production and manufacturing. The most fragile layers are chemical and pharmaceutical products, services and food-related products, which are all sectors that have been disrupted by the Coronavirus Disease 2019 (COVID-19) pandemic in the United States. The fragility risk, measured by the intersection of the fragility level of a node and its exposure to shocks, varies across regions and sectors. This suggests that interventions aiming to make the supply-chain network more robust to shocks are likely needed at multiple levels of network aggregation.

SUBMITTER: Gomez M

PROVIDER: S-EPMC7509503 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Fragility of a multilayer network of intranational supply chains.

Gomez Michael M Garcia Susana S Rajtmajer Sarah S Grady Caitlin C Mejia Alfonso A

Applied network science 20200923 1

Supply chains enable the flow of goods and services within economic systems. When mapped for the entire economy and geographic locations of a country, supply chains form a spatial web of interactions among suppliers and buyers. One way to characterize supply chains is through multiregional input-output linkages. Using a multiregional input-output dataset, we build the multilayer network of supply chains in the United States. Together with a network cascade model, the multilayer network is used t ...[more]

PMID: 32984501

Similar Datasets

Project description:The United States has experienced prolonged severe shortages of vital medications over the past two decades. The causes underlying the severity and prolongation of these shortages are complex, in part due to the complexity of the underlying supply chain networks, which involve supplier-buyer interactions across multiple entities with competitive and cooperative goals. This leads to interesting challenges in maintaining consistent interactions and trust among the entities. Furthermore, disruptions in supply chains influence trust by inducing over-reactive behaviors across the network, thereby impacting the ability to consistently meet the resulting fluctuating demand. To explore these issues, we model a pharmaceutical supply chain with boundedly rational artificial decision makers capable of reasoning about the motivations and behaviors of others. We use multiagent simulations where each agent represents a key decision maker in a pharmaceutical supply chain. The agents possess a Theory-of-Mind capability to reason about the beliefs, and past and future behaviors of other agents, which allows them to assess other agents' trustworthiness. Further, each agent has beliefs about others' perceptions of its own trustworthiness that, in turn, impact its behavior. Our experiments reveal several counter-intuitive results showing how small, local disruptions can have cascading global consequences that persist over time. For example, a buyer, to protect itself from disruptions, may dynamically shift to ordering from suppliers with a higher perceived trustworthiness, while the supplier may prefer buyers with more stable ordering behavior. This asymmetry can put the trust-sensitive buyer at a disadvantage during shortages. Further, we demonstrate how the timing and scale of disruptions interact with a buyer's sensitivity to trustworthiness. This interaction can engender different behaviors and impact the overall supply chain performance, either prolonging and exacerbating even small local disruptions, or mitigating a disruption's effects. Additionally, we discuss the implications of these results for supply chain operations.

Dataset Information

Fragility of a multilayer network of intranational supply chains.

Publications

Fragility of a multilayer network of intranational supply chains.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets