Towards understanding network topology and robustness of logistics systems

Ezaki, Takahiro; Imura, Naoto; Nishinari, Katsuhiro

doi:10.1016/j.commtr.2022.100064

Cited by 34 publications

(16 citation statements)

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“…By allocating additional capacity resources proportional to SC, the robustness of the system can be effectively increased. As a proof of concept, we demonstrate that capacity allocation based on the SC effectively increases the robustness of the system using the previous model (Ezaki et al 2022). This metric does not require solving an optimization problem or simulating a model.…”

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confidence: 88%

“…They might not be practically useful in the future logistics networks because they ignore the dynamical features of the delivery route (re) planning. For example, adaptive routing that takes into account current congestion and disruption patterns in the network can be effective in reducing travel time (Ezaki et al 2022). To take this mechanism into consideration, the metric should be based on the shortest paths when some links are not available.…”

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confidence: 99%

“…In section 1, we describe the computation algorithm for the proposed metric and other baseline metrics. Additionally, we explain the simulation model (Ezaki et al 2022) that is used to demonstrate that our approach is useful for decreasing the travel time in the logistics network under disruptions. In section 2 we show how the proposed metric is computed on an example network and present the results of our experiments.…”

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confidence: 99%

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Reinforcing critical links for robust network logistics: A centrality measure for substitutability

Ezaki

Imura²,

Nishinari³

2023

J. Phys. Commun.

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Logistics networks are becoming more complex and interconnected. Guaranteeing the performance of the entire system when a part of the network is disrupted (e.g., due to excessive demands and extreme weather conditions) is one of the important issues. However, how much transportation resources should be allocated to which part of the network while maintaining eﬃciency is an open question. In this paper, we propose a novel metric, the substitutability centrality, which quantiﬁes how much each transport link in the network contributes to the robustness of the system against disruptions. This metric is compelling in the following aspects: (1) it is intuitively interpretable; (2) it does not require simulation or optimization calculations; and (3) it takes into account changes in transportation routes of delivery due to disruptions. Furthermore, as a proof of concept, we demonstrate a simple case study, in which capacity allocation based on the proposed metric can maintain high performance of the system against various types of disruptions. We also found that this approach might not be effective for further increasing the robustness of networks that have many bypass routes.

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confidence: 88%

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confidence: 99%

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confidence: 99%

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Reinforcing critical links for robust network logistics: A centrality measure for substitutability

Ezaki

Imura²,

Nishinari³

2023

J. Phys. Commun.

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“…Diversity is also considered a key determinant of resilience [18]. In this regard, supply diversification increases supply flow and profitability, while customer diversification increases demand flow [11,19,20]. Similarly, firms with a diversified customer base can help protect against downstream demand disruption events, and by developing a diversified customer base, they can help improve their ability to recover from disruptions and improve their financial performance.…”

Section: Literature Review 21 Supply Chain Diversification and Supply...mentioning

confidence: 99%

Supply Chain Diversification, Digital Transformation, and Supply Chain Resilience: Configuration Analysis Based on fsQCA

Yin

Ran²

2022

Sustainability

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To determine the influence of COVID-19 on supply chains, previous research has examined the impact of supply chain diversification and digital transformation on supply chain resilience, but few studies have integrated these two aspects to understand their impact on supply chain resilience. Given this, our study implements the fuzzy set qualitative comparative analysis (fsQCA) method to investigate the influence of supply chain diversification (supply base diversification and customer base diversification) and digital transformation (digital transformation depth and breadth) on supply chain resilience. Using data from 191 listed manufacturing firms, it is shown that the dimensions of supply chain diversification and digital transformation do not have the necessary conditions to achieve high supply chain resilience, while the analysis of sufficient conditions shows that three paths can achieve high supply chain resilience—namely, those driven by digital transformation, supply chain diversification, and supplier centralization and customer base diversification. This study demonstrates the numerous and complex linkages between antecedent and outcome, and firms can choose the path that is best for them to improve supply chain resilience based on their size, degree of digital transformation, and supply chain diversification.

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“…A few studies have aimed to formally solve the network revision problem by making epidemiologically driven decision making, e.g., see Ding et al (2021) for air transportation, Guillot et al (2022) for bus networks, and Qu et al (2022) for an overview discussing the need of informed modeling and data acquisition. In this context it is important to understand that our transportation systems are built around efficiency and resilience, where redundancy is an important aspect for well-functioning ( Ezaki et al, 2022 ). In order to create pandemic-resilient systems, one needs different approaches.…”

Section: Introductionmentioning

confidence: 99%

Why are COVID-19 travel bubbles a tightrope walk? An investigation based on the Trans-Tasmanian case

Sun

Wandelt

Zhang

2023

Communications in Transportation Research

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Towards understanding network topology and robustness of logistics systems

Cited by 34 publications

References 50 publications

Reinforcing critical links for robust network logistics: A centrality measure for substitutability

Reinforcing critical links for robust network logistics: A centrality measure for substitutability

Supply Chain Diversification, Digital Transformation, and Supply Chain Resilience: Configuration Analysis Based on fsQCA

Why are COVID-19 travel bubbles a tightrope walk? An investigation based on the Trans-Tasmanian case

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