System Dynamics Modeling of Backup Purchasing Strategies under Supply Disruption Risks

Wang, Yanxin; Huang, Minfang; Chen, Jianbin

doi:10.14257/ijunesst.2014.7.6.25

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…This study suggests setting multi-echelon inventory levels before production disruption and a backup plan after disruption to match sales at the needed sales ratio. Similarly, Wang et al (2014) studied backup suppliers and shed light on the backup purchasing strategy's value.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation-based assessment of supply chain resilience with consideration of recovery strategies in the COVID-19 pandemic context

Moosavi

Hosseini

2021

Computers & Industrial Engineering

106

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In the wake of the COVID-19 pandemic, many firms lacked a strategy to cope with disruptions and maintain resiliency. In this study, we develop a measurement method to evaluate the impact of resilience strategies in a multi-stage supply chain (SC) in the presence of a pandemic. For the first time, we propose a method to deduce quantitative resilience assessment from simulation. We implement two resilience strategies, i.e., prepositioning extra-inventory and a backup supplier, and then we simulate its impact on SC resilience and financial performance. The simulation results indicate that the extra inventory leads to a higher resilience than a backup supplier but costs more for the given contextual setting. Finally, we examine the demand fulfillment and observe that the extra-inventory strategy allows for a higher service level, confirming our resilience simulations. We discuss the managerial implications of these findings on the descriptive and predictive analysis levels. Decision-makers can utilize our model and findings to develop a response plan in the occurrence of a pandemic or any long-duration high magnitude disruption. Also, scholars and managers can use our proposed method to measure SC resiliency from simulation in any disruption.

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Section: Literature Reviewmentioning

confidence: 99%

Simulation-based assessment of supply chain resilience with consideration of recovery strategies in the COVID-19 pandemic context

Moosavi

Hosseini

2021

Computers & Industrial Engineering

106

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“…SD is extensively used to analyze the complexity of supply chains [30][31][32][33]. As an example, Wang et al [1] compared different backup purchasing strategies for managing supply disruption risks. Additionally, Mota et al [34] analyzed the water supply disruption phenomenon and its impact on the bioethanol production process.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Random disruptions in key supply chain processes (i.e., procurement, production, and distribution) are neither controllable nor predictable [1][2][3]. This motivates decision makers to implement specific strategies to both ensure continuous production and timely fulfill orders.…”

Section: Introductionmentioning

confidence: 99%

A System Dynamics Model to Evaluate the Impact of Production Process Disruption on Order Shipping

et al. 2019

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Multiple studies have analyzed the importance of preventive maintenance. Similarly, they have developed and/or evaluated various spare part inventory management policies that help companies reduce the duration of production disruptions resulting from sudden mechanical failures. All of these studies assess the impact of mechanical failures on local aspects, such as idle times or management policies. However, they do not holistically evaluate how machine failures affect key performance indicators. To address this gap, we proposed a System Dynamics (SD) model to systemically analyze the impact of machine part failures on order shipping, a key performance indicator. Similarly, we assessed the impact of machine part failures on the levels of the company’s finished goods inventory. The research was conducted in a glass bottle manufacturing company. To increase order shipping as a performance indicator, we identified the key variables of the production process and conducted a sensitivity analysis of the variables. Our results indicate that it is possible to reach the company’s 98–100% complete delivery policy.

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Effectiveness of responsive pricing in the face of supply chain disruptions

Bugert

Lasch

2018

Computers & Industrial Engineering

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System Dynamics Modeling of Backup Purchasing Strategies under Supply Disruption Risks

Abstract: We model a supply chain using system dynamics involving one retailer

Cited by 3 publications

References 16 publications

Simulation-based assessment of supply chain resilience with consideration of recovery strategies in the COVID-19 pandemic context

Simulation-based assessment of supply chain resilience with consideration of recovery strategies in the COVID-19 pandemic context

A System Dynamics Model to Evaluate the Impact of Production Process Disruption on Order Shipping

Effectiveness of responsive pricing in the face of supply chain disruptions

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