Guest editors:

• Dr Siamak Kheybari (Leading Guest Editor)
  Lecturer in Business Analytics and Supply Chain Management
  Sheffield University Management School, University of Sheffield, UK
• Dr Amin Vafadarnikjoo
  Lecturer in Operations Management and Decision Sciences,Sheffield University Management School, University of Sheffield, UK
• Dr Abbi M. Kedir
  Director of Research the African Economic Research Consortium (AERC)

Special issue information:

There are a variety of factors impacting global supply chains, which are currently causing significant transformations (Zahoor et al., 2023). Contemporary global supply chains and international business are facing rising protectionism (Miroudot and Nordström, 2020), geopolitical tensions (Bednarski et al., 2025), trade protectionism, for instance through increased tariffs, which call for greater national resilience (Thakur-Weigold and Miroudot, 2024). These changes are marking a shift toward the de-globalisation of supply chains, also referred by some scholars as slowbalization (Kandil et al., 2020). International supply chains and multinational activities are becoming increasingly regionalised or even re-nationalized (Charpin, 2022). This trend is fueled by several forces, including rising labor costs in traditional manufacturing hubs, escalating geopolitical conflicts (Asadollah et al., 2024), trade wars (Handfield et al., 2020), risks associated with global sourcing (Baldwin and Freeman, 2022), and tightening of export controls (Bown, 2023). Recent evidence has highlighted the significance of this shift. For instance, a survey of 750 firms in the UK showed that 45% of companies plan to reshore their production due to import challenges and escalating shipping costs (Bailey and Rajic, 2022; Gupta et al., 2023; Rowsell, 2022).

Policies involving tariffs and strategic trade measures have evolved into powerful levers for reshaping global supply chains. By adjusting these policies, governments can encourage reshoring to avoid high import duties, promote nearshoring through preferential trade with neighboring countries, and drive friendshoring by favoring politically aligned nations to reduce risks (Adebanji et al., 2022; Tien et al. 2019). Decisions must balance objectives such as economic competitiveness, strategic autonomy, social equity, environmental sustainability, and broader welfare considerations. Designing such policies in a rapidly changing geopolitical and economic landscape presents policymakers and businesses with complex trade-offs, as they balance these goals against the risks of escalating trade tensions and market distortions.

Trade wars between two or more strong economies can pave the way to improve competitiveness of neighboring countries. For instance Vietnam capitalised on the U.S.-China trade war triggered in 2018 by expanding its labor-intensive exports, gaining market share in sectors where China’s competitiveness declined. By leveraging lower production costs and favorable trade conditions, Vietnam improved its position in global supply chains serving the U.S. market (Dhar et al. 2023).

Furthermore, tariff design for global supply chains constitutes a strategic-level decision-making problem marked by complexity, interdependence, and the dynamics of volatile, uncertain, complex, and ambiguous (VUCA) environments (Muntwiler, 2023). Traditional economic models often fall short of addressing the multi-dimensionality and deep uncertainty involved in tariff settings under de-globalization forces. In such environments, strategic decisions are vulnerable to cognitive biases stemming from bounded rationality (Mallard, 2015; Muntwiler, 2023), which can distort judgment and compromise decision quality (Lovallo & Kahneman, 2003). Individual differences, such as past experiences, cognitive abilities, and social networks, further amplify the subjective nature of strategic judgements (Yu, 2021). Therefore, managing behavioral biases is critical for improving tariff-policy outcomes. Multi-Criteria Decision Analysis (MCDA) has emerged as a powerful methodological tool in this regard. By offering structured frameworks to systematically evaluate competing tariff alternatives, integrate diverse stakeholder preferences, and balance tensions between globalization and de-globalization, MCDA provides a methodologically rigorous approach to enhancing decision quality. Its adoption can help decision-makers recognize and mitigate biases, ultimately leading to more equitable, transparent, and resilient supply chain strategies.

Objective

This special issue aims to address how MCDA can be innovatively applied to tariff design for global supply chains amidst de-globalization trends. We are particularly interested in methodological advancements and empirical applications that illuminate how policymakers, firms, and other stakeholders can better navigate this complex new landscape.

The potential suggested topics include, but are not limited to:

• MCDA methods and applications for balancing supply chain resilience and trade efficiency in tariff design
• Tariff strategies for critical supply chains under geopolitical uncertainty
• Sectoral case studies: energy, healthcare, technology supply chains
• Trade-offs between national self-sufficiency and global cooperation evaluated through MCDA
• Deglobalization metrics integrated into MCDA for supply chain tariffs
• Policy modeling: reshoring, and nearshoring evaluated through multi-criteria lenses
• Environmental and social impacts of protective tariffs, reshoring and nearshoring strategies
• Comparative analysis of tariff policies in emerging vs developed economies using MCDA
• Participatory MCDA approaches to integrate stakeholders (governments, firms, consumers)
• Mitigating cognitive biases in tariff settings for global supply chains through behavioral MCDA approaches.

Manuscript submission information:

Submission Open Date: 30 June 2026

Submission Due Date: 30 September 2026

After the submission open date, authors are advised to select the article type ‘VSI: MCDA for Tariffs and Supply Chains‘ in the editorial system of the journal.

References:

Adebanji, A., Insua, D. R., & Ruggeri, F. (2022). Dynamic linear models for policy monitoring. The case of maternal and neonatal mortality in Ghana. Socio-Economic Planning Sciences, 83, 101348.Asadollah, O., Carmy, L. S., Hoque, M. R., & Yilmazkuday, H. (2024). Geopolitical risk, supply chains, and global inflation. The World Economy, 47(8), 3450-3486.
Bailey, D. and I. Rajic (2022). ‘ Manufacturing after Brexit’. Available at https://ukandeu.ac.uk/wp-content/uploads/2022/01/UKICE-Manufacturing-After-Brexit-Report_FINAL-2.pdf.
Baldwin, R., & Freeman, R. (2022). Risks and global supply chains: What we know and what we need to know. Annual Review of Economics, 14(1), 153-180.
Bednarski, L., Roscoe, S., Blome, C., & Schleper, M. C. (2025). Geopolitical disruptions in global supply chains: a state-of-the-art literature review. Production planning & control, 36(4), 536-562.
Bown, C. P. (2023). The challenge of export controls. Finance & Development, 60(2), 18-21.
Charpin, R. (2022). The resurgence of nationalism and its implications for supply chain risk management. International Journal of Physical Distribution & Logistics Management, 52(1), 4-28.
Dang, B. T. T., Yawei, W., & Abdullah, A. J. (2024). The impact of the US-China trade war on Vietnamese exports to the US: a quantitative study using DiD approach. Journal of Trade Science, 12(4), 304-318.
Dhar, B. K., Tiep Le, T., Coffelt, T. A., & Shaturaev, J. (2023). US‐China trade war and competitive advantage of Vietnam. Thunderbird International Business Review, 65(2), 255-263.
Gupta, S., Wang, Y., & Czinkota, M. (2023). Reshoring: a road to industry 4.0 transformation. British Journal of Management, 34(3), 1081-1099.
Handfield, R. B., Graham, G., & Burns, L. (2020). Corona virus, tariffs, trade wars and supply chain evolutionary design. International Journal of Operations & Production Management, 40(10), 1649-1660.
Kandil, N., Battaïa, O., & Hammami, R. (2020). Globalisation vs. Slowbalisation: a literature review of analytical models for sourcing decisions in supply chain management. Annual Reviews in Control, 49, 277-287.
Lovallo, D., & Kahneman, D. (2003). Delusions of success. Harvard Business Review, 81(7), 56–63.
Mallard, G. (2015). Bounded Rationality and Behavioural Economics. Routledge.
Miroudot, S., & Nordström, H. (2020). Made in the world? Global value chains in the midst of rising protectionism. Review of Industrial Organization, 57(2), 195-222.
Muntwiler, C. (2023). Cognitive biases and debiasing in strategic decision making (Doctoral dissertation). University of St. Gallen.
Rowsell, J. (2022). ‘ Why the UK is facing a “tidal wave” of reshoring’. Available at https://www.cips.org/supply-management/news/2022/september/why-the-uk-is-facing-a-tidal-wave-of-nearshoring/.Thakur-Weigold, B., & Miroudot, S. (2024). Supply chain myths in the resilience and deglobalization narrative: Consequences for policy. Journal of International Business Policy, 7(1), 99-111.
Tien, Dr. N.H., Vu, N.T., Dung, H.T. and Duc, L.D.M. (2019), “China-US trade war and risks for Vietnam’s economy”, International Journal of Research in Finance and Management, Vol. 2 No. 2, pp. 86-91,
Yu, X. (2021). Strategic decision biases and decision-making principles. In The Fundamental Elements of Strategy: Concepts, Theories and Cases (pp. 101–119), Springer.
Zahoor, N., Wu, J., Khan, H., & Khan, Z. (2023). De-globalization, international trade protectionism, and the reconfigurations of global value chains. Management International Review, 63(5), 823-859.

Keywords:

De-globalisation; Strategic Trade Policy; Tariff Decision-Making; Supply Chain Transformation; Policy Evaluation; Trade Resilience; Cognitive and Behavioural Biases; Multi-Criteria Decision Analysis (MCDA)

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