Guest Editors
Dr. Reza Lotfi, Yazd University, Iran.
Prof. Gerhard-Wilhelm Weber, Poznan University of Technology, Poland.
Prof. Sadia Samar Ali, King Abdul-Aziz University, Saudi Arabia.
Summary
Antifragility is a property of systems that increase their capability to thrive due to stressors, shocks, volatility, noise, mistakes, faults, attacks, or failures. Therefore, antifragility is beyond resilience or robustness [1-2]. The resilient resists shocks and stays the same; the antifragility gets better. Antifragile Supply chains (SC) benefit from chaos and shocks in the presence of volatility, randomness, stressors, disorder, risk, and uncertainty, and finally, thrive and grow to survive. On the other hand, the ability to profitably produce and deliver a wide range of high-quality products and services within short processing times is denoted by antifragile SCs [2-4].
In addition, four strategies are suggested for building an antifragile SC in the literature review, moving from being resilient to becoming antifragile, moving to innovative SCs, forecasting market demand toward real-time, rapid response, and moving from outsourcing production to forming strategic partnerships [1-4].
We should pay more attention to sustainability in SC network design or production planning toward antifragility. We should consider the environmental (carbon emissions, carbon trading, waste management, and energy consumption) and social impact (welfare, employment). The success and competitive advantage of SC is applying sustainability with antifragility by novel technologies in the present and future [5-8].
Using novel technologies and sustainability for SC management, such as machine learning, blockchain, Internet-of-Things (IoT), and Artificial Intelligence (AI) as antifragility tools, can assist and enable the transition to antifragile SC. Using advanced digital technologies (like AI, Cloud, and automation) allows them to adapt, improve, and respond to the unpredictable, including random events, unexpected disruptions, and unplanned changes in business models. Digital technologies help lay the foundation for companies to build an antifragile system—to go beyond resiliency and be ready to respond to new opportunities and growth in every environment [8-9].
We think it is time to take the next step and learn how the SC could become antifragile. An antifragile SC is a dynamic SC that can gain from disruption. The antifragile SC is active and living, not static, and it evolves and gets better with unpredictable disruptions, which are the inherent characteristics of the post-COVID [8-9].
Finally, the pandemic forces many to rethink their strategies and bolster their supply chains to avoid significant business disruptions. Digitizing manual processes, making weaknesses resilient, executing with speed and agility, and leveraging a no-code platform are four steps to creating a more agile and anti-fragile SC [7-9].
This Special Issue (SI) investigates recent advances on antifragility and viability in supply chain network with considering digital and green technology. We are thus seeking contributions from authors presenting novel mathematical models toward ensuring antifragility in SCs.
Topics of interest include but are not limited to:
· Mathematical modeling by optimization approach with sustainability requirements
· Multi-Attribute Decision-Making (MCDM) with sustainability requirements
· Application of big data analytics, AI networks, machine learning tools, Blockchain, IoT, cloud systems, and 3D printing with sustainability requirements
· Novel uncertainty method for design and planning of SC
· Novel solution method for design and planning of SC
[1] Taleb, N. N. (2012). Antifragile: Things that gain from disorder (Vol. 3). Random House.
[2] Taleb, N. N., & Douady, R. (2013). Mathematical definition, mapping, and detection of (anti) fragility. Quantitative Finance, 13(11), 1677-1689.
[3] Nikookar, E., Varsei, M., & Wieland, A. (2021). Gaining from disorder: Making the case for antifragility in purchasing and supply chain management. Journal of Purchasing and Supply Management, 27(3), 100699.
[4] Größler, A. (2020). A managerial operationalization of antifragility and its consequences in supply chains. Systems Research and Behavioral Science, 37(6), 896-905.
[5] Munoz, A., Billsberry, J., & Ambrosini, V. (2022). Resilience, robustness, and antifragility: Towards an appreciation of distinct organizational responses to adversity. International Journal of Management Reviews, 24(2), 181-187.
[6] Lotfi, R., Nazarpour, H., Gharehbaghi, A., Sarkhosh, S. M. H., & Khanbaba, A. (2022). Viable closed-loop supply chain network by considering robustness and risk as a circular economy. Environmental Science and Pollution Research, 1-20.
[7] Lotfi, R., Safavi, S., Gharehbaghi, A., Ghaboulian Zare, S., Hazrati, R., & Weber, G. W. (2021). Viable supply chain network design by considering blockchain technology and cryptocurrency. Mathematical problems in engineering, 2021.
[8] Lotfi, R., Kargar, B., Hoseini, S. H., Nazari, S., Safavi, S., & Weber, G. W. (2021). Resilience and sustainable supply chain network design by considering renewable energy. International journal of energy research, 45(12), 17749-17766.
[9] Lotfi, R., Sheikhi, Z., Amra, M., AliBakhshi, M., & Weber, G. W. (2021). Robust optimization of risk-aware, resilient and sustainable closed-loop supply chain network design with Lagrange relaxation and fix-and-optimize. International Journal of Logistics Research and Applications, 1-41.
Keywords
Antifragility; sustainability; resiliency; agility; blockchain; artificial intelligence
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