Optimal distribution (re)planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics

Ivanov, Dmitry; Павлов, А. В.; Sokolov, Boris

doi:10.1016/j.ejor.2014.02.023

Cited by 142 publications

(71 citation statements)

References 43 publications

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“…For a recent review of literature on supply chain disruptions and recovery see Ivanov et al (2017). Research has investigated how to optimize supply chain coordination (Sawik 2014) with promising results, but a single disruption can propagate with devastating effects, and little is known about the propagation phenomenon from a systemic perspective (Ghadge et al 2011;Ivanov et al 2014a;2014b). Because supply chains are inherently complex, understanding risks of disruptions is truly a multi-criteria problem requiring multiple solution approaches (Ho et al 2010), and has been of increasing interest in the research community.…”

Section: Introductionmentioning

confidence: 99%

“…We define supply chain disruption propagation as the spread of the disruption effects beyond the initial disruption location. Other terminology for supply chain disruption propagation in the academic literature include risk diffusion (Basole and Bellamy 2014), cascading failures (Hearnshaw and Wilson 2013) and the Ripple Effect (Ivanov et al 2014a;2014b;Solokov et al 2016).…”

Section: Introductionmentioning

confidence: 99%

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Supply chain disruption propagation: a systemic risk and normal accident theory perspective

Scheibe

Blackhurst

2017

International Journal of Production Research

291

162

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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 increased level of granularity into disruption propagation: correlation of risk, compounding effects, cyclical linkages, counterparty risk, herding and misaligned incentives. Organisations should consider these themes and their interactions to effectively deal with supply chain disruptions. ABSTRACTWhen 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 increased level of granularity into disruption propagation: correlation of risk, compounding effects, cyclical linkages, counterparty risk, herding, and misaligned incentives. Organizations should consider these themes and their interactions to effectively deal with supply chain disruptions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Supply chain disruption propagation: a systemic risk and normal accident theory perspective

Scheibe

Blackhurst

2017

International Journal of Production Research

291

162

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“…At the same time, the integrated decision-making allows reaching various conflicting objectives, such as reduction in total cost and increase in service level. However, the research on the integrated decision-making in the presence of supply chain disruption risks is nearly unreported, e.g., Ivanov et al [2]. The purpose of this paper is to study the integrated decision-making to simultaneously select suppliers of parts and schedule production and delivery of finished products to customers in a supply chain under disruption risks.…”

Section: Introductionmentioning

confidence: 98%

Integrated supply, production and distribution scheduling under disruption risks

Sawik

2016

Omega

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“…The author established that, along with cost, percentage of supplier uptime, disruption length, capacity, and flexibility play an important role in determining a buyer's disruption management strategy. The recent developments in the field of supply chain disruption management from a multidisciplinary perspective were summarized by Ivanov et al [17][18][19] who studied the Ripple effect in supply chains. They emphasized that the Ripple effect can consolidate research in supply chain disruption management, similar to the bullwhip effect regarding demand and lead time fluctuations.…”

Section: Literature Reviewmentioning

confidence: 99%

Stochastic versus Deterministic Approach to Coordinated Supply Chain Scheduling

Sawik

2017

Mathematical Problems in Engineering

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The purpose of this paper is to consider coordinated selection of supply portfolio and scheduling of production and distribution in supply chains under regional and local disruption risks. Unlike many papers that assume the all-or-nothing supply disruption pattern, in this paper, only the regional disruptions belong to the all-or-nothing disruption category, while for the local disruptions all disruption levels can be considered. Two biobjective decision-making models, stochastic, based on the wait-and-see approach, and deterministic, based on the expected value approach, are proposed and compared to optimize the trade-off between expected cost and expected service. The main findings indicate that the stochastic programming wait-and-see approach with its ability to handle uncertainty by probabilistic scenarios of disruption events and the much simpler expected value problem, in which the random parameters are replaced by their expected values, lead to similar expected performance of a supply chain under multilevel disruptions. However, the stochastic approach, which accounts for all potential disruption scenarios, leads to a more diversified supply portfolio that will hedge against a variety of scenarios.

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Optimal distribution (re)planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics

Cited by 142 publications

References 43 publications

Supply chain disruption propagation: a systemic risk and normal accident theory perspective

Supply chain disruption propagation: a systemic risk and normal accident theory perspective

Integrated supply, production and distribution scheduling under disruption risks

Stochastic versus Deterministic Approach to Coordinated Supply Chain Scheduling

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