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Proposing a new LSGDM framework based on BWM with hesitant fuzzy information for prioritizing blockchain adoption barriers in supply chain

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  • Heidary-Dahooie, Jalil
  • Rafiee, Mostafa
  • Mohammadi, Mehdi
  • Meidute-Kavaliauskienė, Ieva

Abstract

Due to the vast advantages of Blockchain technology, especially transparency of information and the ability to track transactions, this technology has been considered in several areas, including supply chain management (SCM). However, due to the emergence of this technology, numerous barriers and limitations have hindered its use. Due to the special conditions of developing countries (such as Iran), there is still a need for independent research to localize these barriers in these countries. On the other hand, most of the research has focused more on identifying barriers and less on prioritizing them. Examining the specific features of the Blockchain technology field shows that there is a need to provide a decision-making framework based on large-scale group decision-making methods (LSGDM), which, in addition to simultaneously paying attention to the advantages of previous approaches (including the participation of different groups of stakeholders; the consensus reaching process (CRP) as well as the uncertainty and doubt of the stakeholders in the evaluations), can increase the applicability of the method by reducing the number of pairwise comparisons. Therefore, while identifying and localizing the list of barriers in Iran, the LSGDM method along with the proposed consensus framework can be used to aggregate the opinions between the experts in a network and create a relative consensus between them. The use of hesitant fuzzy (HF) sets has made it possible to model the uncertainty and hesitancy in the opinions of experts. Also, using the Best-Worst method (BWM) instead of the pairwise comparison approach between all criteria, has reduced the number of pairwise comparisons and provided other advantages such as reduced inconsistency and higher reliability. The results of applying this framework in Iran showed that lack of awareness and customer orientation, scalability and lack of management participation and support are the main barriers to the implementation of the blockchain for SCM in this developing country. The results can help decision makers and policy makers in this area to plan more accurately.

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  • Heidary-Dahooie, Jalil & Rafiee, Mostafa & Mohammadi, Mehdi & Meidute-Kavaliauskienė, Ieva, 2022. "Proposing a new LSGDM framework based on BWM with hesitant fuzzy information for prioritizing blockchain adoption barriers in supply chain," Technology in Society, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:teinso:v:71:y:2022:i:c:s0160791x22002871
    DOI: 10.1016/j.techsoc.2022.102146
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    1. Nir Kshetri, 2017. "Will blockchain emerge as a tool to break the poverty chain in the Global South?," Third World Quarterly, Taylor & Francis Journals, vol. 38(8), pages 1710-1732, August.
    2. Sara Saberi & Mahtab Kouhizadeh & Joseph Sarkis & Lejia Shen, 2019. "Blockchain technology and its relationships to sustainable supply chain management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2117-2135, April.
    3. Pei Wang & Xuanhua Xu & Shuai Huang, 2019. "An Improved Consensus-Based Model for Large Group Decision Making Problems Considering Experts with Linguistic Weighted Information," Group Decision and Negotiation, Springer, vol. 28(3), pages 619-640, June.
    4. Wu, Zhibin & Xu, Jiuping, 2016. "Managing consistency and consensus in group decision making with hesitant fuzzy linguistic preference relations," Omega, Elsevier, vol. 65(C), pages 28-40.
    5. ., 2021. "Introduction to Sustainable Consumption, Production and Supply Chain Management," Chapters, in: Sustainable Consumption, Production and Supply Chain Management, chapter 1, pages 1-6, Edward Elgar Publishing.
    6. Xuanhua Xu & Yanxia Huang & Ke Chen, 2019. "Method for large group emergency decision making with complex preferences based on emergency similarity and interval consistency," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(1), pages 45-64, May.
    7. Kshetri, Nir, 2021. "Blockchain and sustainable supply chain management in developing countries," International Journal of Information Management, Elsevier, vol. 60(C).
    8. Simonov Kusi-Sarpong & Himanshu Gupta & Joseph Sarkis, 2019. "A supply chain sustainability innovation framework and evaluation methodology," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 1990-2008, April.
    9. Herrera-Viedma, E. & Herrera, F. & Chiclana, F. & Luque, M., 2004. "Some issues on consistency of fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 154(1), pages 98-109, April.
    10. David Yermack, 2017. "Corporate Governance and Blockchains," Review of Finance, European Finance Association, vol. 21(1), pages 7-31.
    11. Kshetri, Nir, 2018. "1 Blockchain’s roles in meeting key supply chain management objectives," International Journal of Information Management, Elsevier, vol. 39(C), pages 80-89.
    12. Rezaei, Jafar & van Roekel, Wilco S. & Tavasszy, Lori, 2018. "Measuring the relative importance of the logistics performance index indicators using Best Worst Method," Transport Policy, Elsevier, vol. 68(C), pages 158-169.
    13. Tang, Ming & Liao, Huchang, 2021. "Multi-attribute large-scale group decision making with data mining and subgroup leaders: An application to the development of the circular economy," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    14. Queiroz, Maciel M. & Fosso Wamba, Samuel, 2019. "Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA," International Journal of Information Management, Elsevier, vol. 46(C), pages 70-82.
    15. Cui, Yongfeng & Liu, Wei & Rani, Pratibha & Alrasheedi, Melfi, 2021. "Internet of Things (IoT) adoption barriers for the circular economy using Pythagorean fuzzy SWARA-CoCoSo decision-making approach in the manufacturing sector," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    16. Xiang, Liu, 2017. "Energy network dispatch optimization under emergency of local energy shortage with web tool for automatic large group decision-making," Energy, Elsevier, vol. 120(C), pages 740-750.
    17. Badri Ahmadi, Hadi & Kusi-Sarpong, Simonov & Rezaei, Jafar, 2017. "Assessing the social sustainability of supply chains using Best Worst Method," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 99-106.
    18. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    19. Gunasekaran, A. & Patel, C. & McGaughey, Ronald E., 2004. "A framework for supply chain performance measurement," International Journal of Production Economics, Elsevier, vol. 87(3), pages 333-347, February.
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    1. Kumar, Sourabh & Barua, Mukesh Kumar, 2023. "Exploring the hyperledger blockchain technology disruption and barriers of blockchain adoption in petroleum supply chain," Resources Policy, Elsevier, vol. 81(C).

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