Barriers to Adapt Quantum Cryptography Technology in Digital Supply Chains: A Q Rung Orthopair Fuzzy Model
Abstract
The massive digitalization of supply chains has made information security and privacy of the utmost importance. Quantum cryptography (QC) technology has gained notable importance for data encryption to ensure these. This paper aims to fulfill two objectives: a) to unveil the barriers to the adaptation of QC in digital supply chains, and b) to develop innovative Comparisons between Ranked Criteria (COBRAC) framework using q-rung Orthopair fuzzy Einstein weighted averaging (q-ROFEWA) for multicriteria decision-making (MCDM). The present work designs a group decision-making study based on the opinions of 12 experts, expressed in linguistic terms. To derive the barriers, the current work uses the theoretical framework of Technology-OrganizationEnvironment (TOE). From the analysis, it is revealed that lack of awareness and knowledge (w = 0.1733), trust and privacy issues (w = 0.1624), and scale-up and infrastructural capability (w = 0.1348) are the top three barriers. It is seen that the model provides a robust result, maintaining a statistically significant high correlation with other MCDM methods. The sensitivity analysis demonstrates no considerable variation in the final result, given the changes in parameter values. The findings provide significant impetus for the decision-makers to create a reliable and secure ecosystem for DSCM.
References
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S. d’Souza, “Intelligent supply chain management using Quantum,” Doctoral dissertation, TCS, 2022. [Online]. Available: https://hal.science/hal-03740772/
D. Maheshwari, P. V. Florin, L. L. Dhirani, A. Waqas, B. S. Chowdhry, M. M. Ali, and G. Albeanu, “Role of Quantum Security in the Future of Smart Manufacturing,” in Integration of Heterogeneous Manufacturing Machinery in Cells and Systems, pp. 216–236, CRC Press, 2024.
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W. S. Du, “A further investigation on q-rung orthopair fuzzy Einstein aggregation operators,” Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6655–6673, 2021. doi: doi.org/10.3233/jifs-210548
D. Pamucar, V. Simic, Ö. F. Görçün, and H. Küçükönder, “Selection of the best Big Data platform using COBRAC-ARTASI methodology with adaptive standardized intervals,” Expert Systems with Applications, vol. 239, p. 122312, 2024.
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Published
2025-07-07
How to Cite
BISWAS, Sanjib; MITRA, Kaushik; BISWAS, Biplab.
Barriers to Adapt Quantum Cryptography Technology in Digital Supply Chains: A Q Rung Orthopair Fuzzy Model.
Yugoslav Journal of Operations Research, [S.l.], july 2025.
ISSN 2334-6043.
Available at: <https://yujor.fon.bg.ac.rs/index.php/yujor/article/view/1348>. Date accessed: 08 july 2025.
doi: https://doi.org/10.2298/YJOR240819019B.
Issue
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
