Exploring supply chain structural dynamics: New disruptive technologies and disruption risks

Dolgui, Alexandre; Ivanov, Dmitry

doi:10.1016/j.ijpe.2020.107886

Cited by 96 publications

(46 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Shih ( 2020 ) supported this condition of current pandemic, where the unavailability of human labour is the most critical issue which potentially harms the operations of the supply chain. Subsequently, many researchers suggested that technologies of industry 4.0 such as AI, the IoT, and big data analytics, can help in building resilience in SCM (Dolgui and Ivanov 2020 ; Birkel and Hartmann 2020 ; Nayal et al 2021 ).…”

Section: Discussion and Proposed Research Modelmentioning

confidence: 99%

Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research

et al. 2021

View full text Add to dashboard Cite

The challenging situations and disruptions that occurred due to the outbreak of the COVID-19 pandemic have created a severe need for supply chain resiliency (SCR). There has been a growing interest among researchers to investigate the resiliency in supply chain operations to overcome risks and disruptions and to achieve successful project management. The supply chain of every business requires innovative projects to accomplish competitive advantage in the market. This study was conducted to identify the significance of artificial intelligence (AI) for creating a sustainable and resilient supply chain, and also to provide optimum solutions for supply chain risk mitigation. A systematic literature review has been conducted to examine the potential research contribution or directions in the field of AI and SCR. In total, 162 articles were shortlisted from the SCOPUS database in the chosen field of research. Structural Topic Modeling (STM), a big data-based approach, was employed to generate several thematic topics of AI in SCR based on the shortlisted articles, and all topics were discussed. Furthermore, the bibliometric analysis was conducted using R-package to investigate the research trends in the area of AI in SCR. Based on the conducted review of literature, a research framework was proposed for AI in SCR that will facilitate researchers and practitioners to improve technological development in supply chain firms. The purpose is to combat sudden risks and disruptions so that project management will perform well Post COVID-19. The study will be also helpful for future researchers and practitioners to identify research directions based on existing literature covered in this paper in the field of SCR. Future research directions are proposed for AI-enabled resilient supply chain management. This study will also provide several implications for supply chain managers to achieve the required resilience in their supply chains post COVID-19 by focusing on the elements of the proposed research framework.

show abstract

Section: Discussion and Proposed Research Modelmentioning

confidence: 99%

Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research

et al. 2021

View full text Add to dashboard Cite

show abstract

“…(Dolgui et al, 2018 ; Ivanov & Dolgui, 2020 ; Ivanov et al, 2017 ) highlighted the crucial role of reconfiguration to mitigate the ripple effect and to deal with supply chain disruptions. Besides, (Dolgui & Ivanov, 2020 ; Dolgui et al, 2020 ) showed that RSC has an important role in ensuring competitiveness in the markets.…”

Section: Introductionmentioning

confidence: 99%

New metrics for measuring supply chain reconfigurability

2021

View full text Add to dashboard Cite

The COVID 19 pandemic, fluctuating demand, market uncertainty and the emergence of new technologies explain the need for a more flexible and agile supply chain. In fact, several important factors should be taken into account in the process of building an adaptive and reconfigurable supply chain. Reconfigurability is used to measure quantitatively the capability of supply chain to change easily their structure and functions. The aim of this work is to evaluate the level of reconfigurability of a supply chain. Quantitative measures of six indicators that characterize reconfigurability are presented in this paper. Then, an index of reconfigurability in supply chain is developed based on The Multi-Attribute Utility Theory in order to choose the most reconfigurable configuration. An illustrative example is also given. From the discussion, it is deduced that the characteristics of the reconfigurable supply chain impacts positively on the degree of reconfigurability.

show abstract

“…The ripple effect occurs when a disruption, rather than remaining localised or being contained to one part of the SC, cascades downstream and impacts the performance of the entire SC (Dolgui, Ivanov, and Sokolov 2018). Ripple effect is followed by SC structural dynamics (Dolgui and Ivanov 2020;Ivanov 2018) market share and reputation, etc., with adverse effects on the profitability of SC Gupta, Ivanov, and Choi 2020;. Some examples of the ripple effect are as follows:…”

mentioning

confidence: 99%

Ripple effect and supply chain disruption management: new trends and research directions

Dolgui

Ivanov

2021

International Journal of Production Research

Self Cite

218

View full text Add to dashboard Cite

Ripple effect is a specific area of SC disruptions and a strong stressor to SC resilience. Research on the ripple effect analyses how one or more disruptive events propagate through the SC and impact its resilience and performance. The phenomenon of the ripple effect, immensely existing in practice, has received great research interest in recent years. Ripple effect management, modelling and assessment became visible research avenues with a growing number and scope of contributions. This Special Issue presents recent developments on the ripple effect in SCs. The Special Issue focuses on studies that address the ripple effect and provide a comprehensive picture of the state of the art and future perspectives. The methodologies comprise of mathematical optimisation, simulation, game theory, control theoretic, data-driven analytics, network complexity, reliability theory research, and empirical research. Even though a variety of valuable insights have been developed in this area in recent years, new research avenues and ripple effect taxonomies are identified for further exploring the ripple effect in the settings of the COVID-19 pandemic, SC viability, viable SC model, and reconfigurable SCs. KEYWORDS Ripple effect; supply chain resilience; supply chain risk management; supply chain dynamics; supply chain engineering Supply chain engineering is one of the main issues in production research (Dolgui and Proth (2010). Research on supply chain (SC) disruption management has focused on both empirical and analytical methodologies in understanding and appeasing risk (Ho

show abstract

Exploring supply chain structural dynamics: New disruptive technologies and disruption risks

Cited by 96 publications

References 61 publications

Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research

Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research

New metrics for measuring supply chain reconfigurability

Ripple effect and supply chain disruption management: new trends and research directions

Contact Info

Product

Resources

About