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Modeling the enablers for blockchain technology adoption in renewable energy supply chain

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  • Sahebi, Iman Ghasemian
  • Mosayebi, Alireza
  • Masoomi, Behzad
  • Marandi, Fatemeh

Abstract

The literature illustrates Blockchain Technology (BT) to offer various advantages resulting in progress in the renewable energy supply chains (RESC). It is predicted that BT will bring a novel paradigm in the approach of transactions implemented in the RESC by decreasing the number of intermediaries, delayed payments, and high transaction lead times. As a developing economy, Iran provides the energy needs of an ever-growing population and confronts many issues affecting RESC. As a result, it is, therefore, crucial to accept BT in the RESC to leverage the different advantages. In the current study, we recognize and implement the relationships between the enablers of BT adoption in RESC. Twelve enablers were identified from the literature, and verified by the experts before using a Fuzzy Interpretive Structural Modelling (FISM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) methodology. The results propose that the comparison among the identified enablers shows the most superior of secure database for BT implementation in RESC tracked by immutability and decentralized database. The results will provide better situations for the practitioners to design the strategies for BT implemented in renewable energy within a real-time data-driven RESC.

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  • Sahebi, Iman Ghasemian & Mosayebi, Alireza & Masoomi, Behzad & Marandi, Fatemeh, 2022. "Modeling the enablers for blockchain technology adoption in renewable energy supply chain," Technology in Society, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:teinso:v:68:y:2022:i:c:s0160791x22000124
    DOI: 10.1016/j.techsoc.2022.101871
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    5. Ieva Meidute-Kavaliauskiene & Figen Yıldırım & Shahryar Ghorbani & Renata Činčikaitė, 2022. "The Design of a Multi-Period and Multi-Echelon Perishable Goods Supply Network under Uncertainty," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
    6. Ádám Sleisz & Dániel Divényi & Beáta Polgári & Péter Sőrés & Dávid Raisz, 2022. "A Novel Cost Allocation Mechanism for Local Flexibility in the Power System with Partial Disintermediation," Energies, MDPI, vol. 15(22), pages 1-18, November.
    7. Ieva Meidute-Kavaliauskiene & Nihal Sütütemiz & Figen Yıldırım & Shahryar Ghorbani & Renata Činčikaitė, 2022. "Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption," Energies, MDPI, vol. 15(4), pages 1-24, February.

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