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<p>This paper aims to identify and evaluate the CSFs in the acceptance of blockchain technology (BCT) in Iranian Rubber Industry and rank the influential parts (IPs) of BCT in the Industry by the opinions of 120 experts and simultaneously applying fuzzy Delphi and SWARA (Step-wise Weight Assessment Ratio Analysis) and ARAS (A new additive ratio assessment). A developed model of the CSFs and IP of the BCT in the industry was proposed. The results indicate that 10 CSF from the 31 CSF have a very strong impact on the 9 parts. In the following, the weight of the CSFs was extracted. The analysis showed that the sixth CSFs, (F6: Cyber-Security, Trustable Collaborations and Reliability) was placed in first priority. Also, the 8th CSFs (F8: Experience and Knowledge), was ranked in last. At the end of the research, 9 IPs of the BCT in the Industry were evaluated. The final analysis proves that that the first part (A1: Customer Segments) is ranked first, and the eights part (A8; Key Partners) is ranked last. The proposed integrated conceptual model of this research can be very useful in identifying and evaluating the CSFs of BCT and the valuable IPs of this technology in the rubber industry and other related industries.</p>

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A Combined Decision System for Critical Success Factors and Influential Parts of Blockchain Technology

  • 期刊论文

  • 发表日期：

    2025年8月6日

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  • Mehdi Ajalli

摘要

This paper aims to identify and evaluate the CSFs in the acceptance of blockchain technology (BCT) in Iranian Rubber Industry and rank the influential parts (IPs) of BCT in the Industry by the opinions of 120 experts and simultaneously applying fuzzy Delphi and SWARA (Step-wise Weight Assessment Ratio Analysis) and ARAS (A new additive ratio assessment). A developed model of the CSFs and IP of the BCT in the industry was proposed. The results indicate that 10 CSF from the 31 CSF have a very strong impact on the 9 parts. In the following, the weight of the CSFs was extracted. The analysis showed that the sixth CSFs, (F6: Cyber-Security, Trustable Collaborations and Reliability) was placed in first priority. Also, the 8th CSFs (F8: Experience and Knowledge), was ranked in last. At the end of the research, 9 IPs of the BCT in the Industry were evaluated. The final analysis proves that that the first part (A1: Customer Segments) is ranked first, and the eights part (A8; Key Partners) is ranked last. The proposed integrated conceptual model of this research can be very useful in identifying and evaluating the CSFs of BCT and the valuable IPs of this technology in the rubber industry and other related industries.