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Building Antifragile Supply Chains: Leveraging Digital Technologies to Transform Disruptions into Opportunities

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Building Antifragile Supply Chains: Leveraging Digital Technologies to Transform Disruptions into Opportunities

Building Antifragile Supply Chains: Leveraging Digital Technologies to Transform Disruptions into Opportunities

Nottingham Trent University Nottingham Business School

Dr Saeed Taheri Prof Antuela Takou

Wednesday, July 01, 2026 Self-Funded PhD Students Only

About the Project

Global supply chains are increasingly exposed to complex disruptions, including pandemics, geopolitical tensions, climate-related events, and technological change. Traditional research has focused on supply chain resilience, which emphasises the ability of systems to withstand disruptions and recover to their previous state. However, in highly uncertain environments, merely recovering may not be sufficient.

The concept of antifragility, introduced by Nassim Taleb, offers a more transformative perspective. Antifragile systems do not simply survive disruptions; they benefit from volatility and uncertainty, becoming stronger and more effective as a result of shocks. While this concept has gained growing attention in management and operations research, supply chain antifragility remains underdeveloped both conceptually and empirically. There is limited understanding of how supply chains can systematically learn from disruptions, adapt their structures and governance mechanisms, and leverage digital technologies to improve performance over time.

This PhD project aims to address this gap by developing new theoretical and analytical insights into antifragile supply chains. The research will explore the following key questions:

  • How can antifragility be conceptualised and operationalised in supply chains, and how does it differ from resilience and robustness?
  • What mechanisms and feedback processes enable supply chains to improve their performance when exposed to disruptions?
  • Which supply chain structures, governance arrangements, and strategic practices support the development of antifragile capabilities?
  • How can emerging technologies, such as artificial intelligence (AI), machine learning (ML), and simulation modelling, be used to identify vulnerabilities, predict disruptions, and support antifragile decision-making?
  • How do behavioural factors, including managerial risk perception and decision-making, influence the adoption of antifragility strategies?

The project will employ a hybrid methodological approach, combining AI and ML techniques with simulation modelling to analyse disruption patterns, explore system dynamics, and identify pathways through which supply chains can evolve and improve under uncertainty.

Expected Contributions

This research will contribute to the emerging field of antifragile supply chains by developing a conceptual framework and analytical tools for understanding how supply chains can learn from disruptions and improve over time. The project will generate insights relevant to both academia and industry, supporting organisations in designing supply chains that not only withstand shocks but also adapt and thrive in volatile environments.

The successful candidate will gain experience in advanced analytical methods, including AI/ML, simulation modelling, and complex systems analysis, while contributing to cutting-edge research on the future of resilient and adaptive supply chains.

References

  • Größler, A., 2020. A managerial operationalization of antifragility and its consequences in supply chains. Systems research and behavioral science, 37(6), pp.896-905.
  • Ivanov, D., 2023. Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability. International Journal of Production Economics, 263, p.108938.
  • Nikookar, E., Stevenson, M. and Varsei, M., 2024. Building an antifragile supply chain: a capability blueprint for resilience and post‐disruption growth. Journal of Supply Chain Management, 60(1), pp.13-31.
  • Axenie, C., López-Corona, O., Makridis, M.A., Akbarzadeh, M., Saveriano, M., Stancu, A. and West, J., 2024. Antifragility in complex dynamical systems. npj Complexity, 1(1), p.12.
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