Review of quantitative methods for supply chain resilience analysis

By Seyedmohsen Hosseini, Dmitry A. Ivanov, Alexandre Dolgui. Transportation Research Part E: Logistics and Transportation Review, 2019

1,059 citations recorded by the source corpus.

Supply chain resilience (SCR) manifests when the network is capable to withstand, adapt, and recover from disruptions to meet customer demand and ensure performance. This paper conceptualizes and comprehensively presents a systematic review of the recent literature on quantitative modeling the SCR while distinctively pertaining it to the original concept of resilience capacity. Decision-makers and researchers can benefit from our survey since it introduces a structured analysis and recommendations as to which quantitative methods can be used at different levels of capacity resilience. Finally, the gaps and limitations of existing SCR literature are identified and future research opportunities are suggested.

Subfields: Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/20e9613822272e299bb7747cfd30b313faf27dbb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Information Systems

In Strategy and Management

Citations in the corpus

The Industry 5.0 framework: viability-based integration of the resilience, sustainability, and human-centricity perspectives (2022, background): “The literature contains a large body of knowledge on resilience (Aldrighetti et al. 2021, Altay et al. 2018, Blackhurst et al. 2011, Hosseini et al. 2019, Pettit et al. 2019, Ivanov 2021a, Qin et al. 2021), sustainability (Brandenburg and Rebs 2015, Dubey et al. 2015, Sarkis 2021), and…”
Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies (2021, methodology): “disruption propagations in the SCs) in global SCs, based on the research by Ivanov, Sokolov, and Dolgui (2014), Dolgui, Ivanov, and Sokolov (2018), and Li et al.”
A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0 (2020, positive): “…method applications to SC disruption risks and resilience, the number of model-based studies has been increasing exponentially over the last decade (Ho et al. 2015; Ivanov et al. 2017; Dolgui, Ivanov, and Sokolov 2018; Dolgui et al. 2020a; Ivanov and Dolgui 2019; Hosseini, Ivanov, and Dolgui 2019).”
Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain† (2019, background): “…and Li 2012; Torabi, Baghersad, and Mansouri 2015; Yildiz et al. 2016; Fattahi, Govindan, and Keyvanshokooh 2017; Rezapour, Farahani, and Pourakbar 2017; He et al. 2018; Ivanov et al. 2016; Lücker, Seifert, and Biçer 2019; Pavlov et al. 2019; Cavalcantea et al. 2019; Hosseini et al. 2019).”
Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic (2021, positive): “C) based simulation and optimization tools enable testing alternative network setups and possible redundancy elements, including supplier quantity, geographical locations, SC inventory levels, and production and transportation capacities (Hosseini et al., 2019; Ivanov, 2017; Ralston & Blackhurst, 20”
Impact of Internal Integration, Supply Chain Partnership, Supply Chain Agility, and Supply Chain Resilience on Sustainable Advantage (2021, background): “SC agility is a company’s tactic in carrying out operations to provide a fast response to the market at an efficient cost [27,41].”
Disruption risks in supply chain management: a literature review based on bibliometric analysis (2020, background): “With the increasing complexity and uncertainty of global supply chains, disruption events are frequently occurring in supply chain management (Hosseini, Ivanov, and Dolgui 2019; Kim, Chen, and Linderman 2015; Kamalahmadi and Parast 2016).”
Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic (2020, background): “…inventories, subcontracting capacities, backup supply and transportation infrastructures, omni-channel anddata-driven, real-timemonitoring andvisibility systems) (Craighead et al. 2007; Ho et al. 2015; Hosseini et al. 2019) helped the companies to survive and recover through the pandemic?”
A Review on Ergonomics in Agriculture. Part I: Manual Operations (2020, background): “Data visualization analysis produces interesting results concerning the identification of (a) the relevant research organizations worldwide, (b) relevant journals, and (c) categories and emerging trends being the most popular of the field [34].”
A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing (2019, background): “Achieving SC resilience involves adopting reactive and proactive approaches by creating certain protections and taking into account possible perturbations through contingency plans or backup supply planning [37, 38].”
Evaluating the factors that influence blockchain adoption in the freight logistics industry (2020, methodology): “The ANP has been successfully applied in various real world decision making scenarios (Choi, 2018; Hosseini et al, 2019; Hu et al, 2019; Supeekit et al, 2016).”