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<p>Blockchain technology (BCT) is dramatically altering industries by providing a decentralized, secure, and transparent system to trade without any intermediaries—promoting trust and automation in public and private networks. Managers and decision-makers need to apply multi-attribute group decision-making (MAGDM) processes under uncertainty in order to identify the factors that influence BCT adoption and its possible uses. This study presents a systematic approach to the identification and addressing of barriers preventing the implementation of BCT. First, we introduce a number of intricate aggregation processors based on complex q-rung orthopair fuzzy settings (Cq-ROFSs) for synthesizing the views of specialists. Moreover, we propose a set of interesting complex q-rung orthopair fuzzy Einstein geometric operators such as Cq-ROFEWG, Cq-ROFEOWG, and Cq-ROFEHG operators to enhance aggregation under uncertainty. Then, we describe an advanced EDAS-based decision-making process that meets MAGDM requirements, complete with an explanatory flowchart step-by-step. The proposed technique is used to review the BCT implementation over fourteen critical aspects, thus validating its practical application. Finally, both conventional models and the proposed framework performance comparison reveal the proposed framework can offer enhanced reliability and realistic insights for decision-makers.</p>

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Decision support model for blockchain adoption using EDAS technique in the complex q-rung orthopair fuzzy structure

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月1日

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  • Umar Ali,
  • Junxiang Li,
  • Usman Zulfiqar,
  • Kamran B. A. Salam,
  • Rifaqat Ali,
  • Imran Siddique,
  • Ihsanullah Saqib,
  • Rana Muhammad Zulqarnain

摘要

Blockchain technology (BCT) is dramatically altering industries by providing a decentralized, secure, and transparent system to trade without any intermediaries—promoting trust and automation in public and private networks. Managers and decision-makers need to apply multi-attribute group decision-making (MAGDM) processes under uncertainty in order to identify the factors that influence BCT adoption and its possible uses. This study presents a systematic approach to the identification and addressing of barriers preventing the implementation of BCT. First, we introduce a number of intricate aggregation processors based on complex q-rung orthopair fuzzy settings (Cq-ROFSs) for synthesizing the views of specialists. Moreover, we propose a set of interesting complex q-rung orthopair fuzzy Einstein geometric operators such as Cq-ROFEWG, Cq-ROFEOWG, and Cq-ROFEHG operators to enhance aggregation under uncertainty. Then, we describe an advanced EDAS-based decision-making process that meets MAGDM requirements, complete with an explanatory flowchart step-by-step. The proposed technique is used to review the BCT implementation over fourteen critical aspects, thus validating its practical application. Finally, both conventional models and the proposed framework performance comparison reveal the proposed framework can offer enhanced reliability and realistic insights for decision-makers.