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Book

Handbook of Ripple Effects in the Supply Chain

01 Jan 2019-
TL;DR: This book offers an introduction to the ripple effect in the supply chain for larger audience and describes the impact of a disruption propagation on SC performance and disruption-based scope of changes in SC structural design and planning parameters.
Abstract: This book offers an introduction to the ripple effect in the supply chain for larger audience. Ripple effect describes the impact of a disruption propagation on SC performance and disruption-based scope of changes in SC structural design and planning parameters. As the result of the ripple effect SC structures change. It is different from the bullwhip-effect that affect the SC at the operational level by mismatching demand and supply without structural changes in the SC design, i.e., without SC structural dynamics
Citations
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Journal ArticleDOI
TL;DR: The results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs are presented and an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights are offered.
Abstract: Epidemic outbreaks are a special case of supply chain (SC) risks which is distinctively characterized by a long-term disruption existence, disruption propagations (i.e., the ripple effect), and high uncertainty. We present the results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs. First, we articulate the specific features that frame epidemic outbreaks as a unique type of SC disruption risks. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of epidemic outbreaks on the SC performance using the example of coronavirus COVID-19 and anyLogistix simulation and optimization software. We offer an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights. A set of sensitivity experiments for different scenarios allows illustrating the model's behavior and its value for decision-makers. The major observation from the simulation experiments is that the timing of the closing and opening of the facilities at different echelons might become a major factor that determines the epidemic outbreak impact on the SC performance rather than an upstream disruption duration or the speed of epidemic propagation. Other important factors are lead-time, speed of epidemic propagation, and the upstream and downstream disruption durations in the SC. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of epidemic outbreaks on the SCs and develop pandemic SC plans. Our approach can also help to identify the successful and wrong elements of risk mitigation/preparedness and recovery policies in case of epidemic outbreaks. The paper is concluded by summarizing the most important insights and outlining future research agenda.

1,282 citations


Cites methods from "Handbook of Ripple Effects in the S..."

  • ...We build our simulation model according to the above analysis and following the previously developed and validated simulation models for SC risk analysis (Ivanov, 2017a, 2017b, 2018a, 2019, 2020)....

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  • ...Among software tools to simulate the SC behaviors under risks, anyLogistix has been proven to be a very successful tool utilized in SC risk and resilience analysis (Ivanov, 2017a, 2017b, 2018b, 2019, 2020, Aldrighetti et al., 2019)....

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  • ...…simulation approach (Schmitt and Singh, 2012, Ivanov, 2017a, 2017b, Schmitt et al., 2017, Ivanov and Rozhkov, 2017, Macdonald et al., 2018, Ivanov, 2019, Tan et al., 2020) while some studies use agent-based (Li and Chan, 2013, Hou et al., 2018, Zhao et al., 2019) and system dynamics…...

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Journal ArticleDOI
TL;DR: The analysis reveals that adaptation capabilities play the most crucial role in managing the SCs under pandemic disruptions, and how the existing OR methods can help coping with the ripple effect at five pandemic stages following the WHO classification.

274 citations


Cites background from "Handbook of Ripple Effects in the S..."

  • ...For example, Ivanov and Dolgui (2019) proposed an LCN (low-certainty-need) SC framework which conceptually defines the notion of resileanness (i.e., resilient and lean)....

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  • ...An analysis of these aggregated categories lead us to a proposition of classifying the existing studies into three levels, i.e., network level, process level, and control level in line with (Ivanov and Dolgui 2019) and echoed by Golan et al. (2020)....

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Journal ArticleDOI
TL;DR: It is hypothesized that reconfigurability can be considered such an integral perspective that consolidates the research in SC adaptation to ever changing environments and goes beyond the existing knowledge to predict proactively the future directions in the reconfigurable SCs.
Abstract: Research on supply chain (SC) digitalization, resilience, sustainability and leagility has remarkably progressed, most of it focused on the individual contributions of these four major frameworks. ...

226 citations


Cites background from "Handbook of Ripple Effects in the S..."

  • ...…control (Ivanov, Sokolov, and Dolgui 2014a; Garvey, Carnovale, and Yeniyurt 2015; Ivanov et al. 2017a; Dolgui, Ivanov, and Sokolov 2018; Levner and Ptuskin 2018; Scheibe and Blackhurst 2018; Hosseini and Ivanov 2019; Ivanov et al. 2019a; Kinra et al. 2019; Li et al. 2019; Mishra et al. 2019)....

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  • ...…LCN – lowcertainty-need SC, see Ivanov and Dolgui 2019), or digital technologies to build supplier collaboration portals and use them for early warning signals, advanced selling notices and supply monitoring to increase resilience, inventory costs and responsiveness (Ivanov et al. 2019c, 2019d)....

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  • ...Moreover, Ivanov et al. (2019a) point out that . . . new disruptive SC business models will arise where SCs will be understood not as rigid physical systems with a fixed and static allocation of some processes to some firms....

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  • ...Recent studies by Baryannis et al. (2019), Dubey et al. (2019b), Ivanov et al. (2019a, 2019c), Schlüter, Hetterscheid, and Henke (2017) revealed several inherent features of the digital SC which can be utilized inmanaging SC risks and resilience....

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  • ...…Choi, Wallace, and Wang (2018), Dolgui et al. (2020a), Fragapane et al. (2019), Frank, Dalenogare, and Ayala (2019), Gunasekaran et al. (2016), Ivanov et al. (2016, 2019b), Moghaddam and Nof (2018), Tang and Veelenturf (2019), Wamba et al. (2017), Zennaro et al. (2019) introduced a number of…...

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Journal ArticleDOI
TL;DR: The results reveal, for the first time, that the ripple effect can be a bullwhip-effect driver, while the latter can be launched by a severe disruption even in the downstream direction.
Abstract: The ripple effect refers to structural dynamics and describes a downstream propagation of the downscaling in demand fulfilment in the supply chain (SC) as a result of a severe disruption. The bullw...

208 citations

Journal ArticleDOI
TL;DR: A new model based on integration of Discrete-Time Markov Chain (DTMC) and a Dynamic Bayesian Network (DBN) is constructed and a metric that quantifies the ripple effect of supplier disruption on manufacturers in terms of total expected utility and service level is proposed.
Abstract: The ripple effect can occur when a supplier base disruption cannot be localised and consequently propagates downstream the supply chain (SC), adversely affecting performance. While stress-testing o...

116 citations


Cites background or methods from "Handbook of Ripple Effects in the S..."

  • ...Ivanov (2019b) studied production-ordering systems in with the disruption risks in recovery and the influence of disruptions on production and distribution networks through discrete event simulation, performed with anyLogistix software....

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  • ...Hosseini and Ivanov (2019) proposed metrics that measure the resilience of supply networks with ripple effect consideration using BN....

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  • ...Neglected, however, remain the operational production-ordering decisions, which in some cases could have a significant impact on the ripple effect (Dolgui, Ivanov, and Rozhkov 2019; Ivanov 2019b)....

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  • ...Managing supply disruption risks and building SCR using contingency and mitigation strategies are well studied in Ivanov (2019a), Ivanov and Sokolov (2019), Pavlov et al. (2019), Ivanov and Dolgui (2019), He et al. (2018), Dolgui, Ivanov, and Sokolov (2018), Chen, Das, and Ivanov (2019), Ivanov…...

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  • ...…contingency and mitigation strategies are well studied in Ivanov (2019a), Ivanov and Sokolov (2019), Pavlov et al. (2019), Ivanov and Dolgui (2019), He et al. (2018), Dolgui, Ivanov, and Sokolov (2018), Chen, Das, and Ivanov (2019), Ivanov (2018a) and Ivanov, Tsipoulanidis, and Schönberger (2019)....

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References
More filters
Journal ArticleDOI
TL;DR: The results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs are presented and an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights are offered.
Abstract: Epidemic outbreaks are a special case of supply chain (SC) risks which is distinctively characterized by a long-term disruption existence, disruption propagations (i.e., the ripple effect), and high uncertainty. We present the results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs. First, we articulate the specific features that frame epidemic outbreaks as a unique type of SC disruption risks. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of epidemic outbreaks on the SC performance using the example of coronavirus COVID-19 and anyLogistix simulation and optimization software. We offer an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights. A set of sensitivity experiments for different scenarios allows illustrating the model's behavior and its value for decision-makers. The major observation from the simulation experiments is that the timing of the closing and opening of the facilities at different echelons might become a major factor that determines the epidemic outbreak impact on the SC performance rather than an upstream disruption duration or the speed of epidemic propagation. Other important factors are lead-time, speed of epidemic propagation, and the upstream and downstream disruption durations in the SC. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of epidemic outbreaks on the SCs and develop pandemic SC plans. Our approach can also help to identify the successful and wrong elements of risk mitigation/preparedness and recovery policies in case of epidemic outbreaks. The paper is concluded by summarizing the most important insights and outlining future research agenda.

1,282 citations

Journal ArticleDOI
TL;DR: The reasons and mitigation strategies for the ripple effect in the supply chain are observed and a ripple effect control framework that includes redundancy, flexibility and resilience analysis is presented.
Abstract: In this study, the ripple effect in the supply chain is analysed. Ripple effect describes the impact of a disruption propagation on supply chain performance and disruption-based scope of changes in...

469 citations

Journal ArticleDOI
TL;DR: In this article, the authors present the Ripple effect in supply chains and summarise recent developments in the field of supply chain (SC) disruption management from a multi-disciplinary perspective, identifying gaps in current research and delineating future research avenues.
Abstract: This study aims at presenting the Ripple effect in supply chains It develops different dimensions of the Ripple effect and summarises recent developments in the field of supply chain (SC) disruption management from a multi-disciplinary perspective It structures and classifies existing research streams and applications areas of different quantitative methods to the Ripple effect analysis as well as identifying gaps in current research and delineating future research avenues The analysis shows that different frameworks already exist implicitly for tackling the Ripple effect in the SC dynamics, control and disruption management domain However, quantitative analysis tools are still rarely applied in praxis We conclude that the Ripple effect can be the phenomenon that is able to consolidate research in SC disruption management and recovery similar to the bullwhip effect regarding demand and lead time fluctuations This may build the agenda for future research on SC dynamics, control, continuity and disrup

417 citations

Journal ArticleDOI
TL;DR: The analysis reveals that adaptation capabilities play the most crucial role in managing the SCs under pandemic disruptions, and how the existing OR methods can help coping with the ripple effect at five pandemic stages following the WHO classification.

274 citations

Journal ArticleDOI
TL;DR: A qualitative, grounded theory case study approach is employed to help understand what drives supply chain disruption propagation and to provide theoretical insights into this emerging area.
Abstract: When a disruption occurs in a firm, its effects are often felt throughout the supply chain. As supply chains expand globally and companies pursue velocity and efficiency, the probability of disruptions propagating throughout a chain grows. In this paper, we employ a qualitative, grounded theory case study approach to help understand what drives supply chain disruption propagation and to provide theoretical insights into this emerging area. For a more complete perspective, we study three interconnected tiers in seven unique supply chains. Each supply chain triad consists of (1) a focal firm (a manufacturer), (2) a supplier to the focal firm and (3) a customer of the focal firm allowing us to gain perspective from three levels in multiple supply chains. Three aggregate dimensions are defined which help explain the propagation of supply chain disruptions: the nature of the disruption, structure and dependence, and managerial decision-making. Within these dimensions, six themes are identified giving an increa...

255 citations