Document Type : Original Article
Authors
1
Ph.D. student, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
2
Iran University of Science & Technology
10.48308/jimp.2026.245017.1733
Abstract
Introduction: Following the Fifth Industrial Revolution, blockchain technology has emerged as one of the most significant technologies for secure information exchange and the permanent recording of events. The fundamental characteristics of this technology — including decentralization, transparency, and immutability — along with its adoption across various sectors and industries, have redefined trust, data integrity, confidentiality, and transaction traceability. As a result, blockchain adoption has increased organizational productivity and reduced fraud in organizational operations. Private blockchains, because they can define access control levels, establish clear governance structures, and comply with legal and organizational requirements, are more suitable and practical than public blockchains for enterprise environments. Nevertheless, the wide variety of private blockchain types and their architectural configurations make selecting an appropriate network a complex decision-making challenge for organizational managers. One fundamental challenge in this selection process is identifying the appropriate characteristics of a blockchain network in line with the organization's objectives and operational nature. These characteristics span multiple dimensions—including security, performance, economic, and governance aspects—which, given their interdependencies, make evaluating and comparing networks a complex undertaking. Therefore, applying multi-criteria decision-making (MCDM) methods as decision-support tools can provide a systematic framework for evaluating such networks.
Methods: This study aims to develop a comprehensive hybrid multi-criteria decision-making framework for evaluating different types of private blockchain networks tailored to each organization’s objectives. Initially, 58 criteria were identified through a review of the relevant literature and expert interviews in this domain. From these, twenty influential and measurable criteria were selected and classified into five general categories: (1) performance and responsiveness, (2) reliability and resilience, (3) decentralization, governance, and membership management, (4) security and control integrity, and (5) economic and operational efficiency. Subsequently, single-valued neutrosophic sets were applied to estimate the importance weights of expert opinions, which were then integrated with the DEMATEL method to calculate criterion importance weights. Finally, by determining a specific number of criteria and applying the TOPSIS method, the optimal private blockchain network is selected.
Findings: The results of implementing the proposed framework for selecting an appropriate blockchain network for a company in the insurance industry show that three criteria—network user count, network security level, and network throughput—are most important for this selection. A comparison of the selected networks across three different scenarios — seven criteria, five criteria, and twelve criteria — shows that the top three selected networks remain consistent across all three evaluation scenarios. Furthermore, in the twelve-criteria scenario, only the ordering of the alternative’s changes, which demonstrates the reliability of the proposed framework.
Conclusion: The purpose of this research is to present an evaluation framework to inform senior organizational managers in selecting the most suitable private blockchain network based on the organization’s objectives and activities. In other words, the proposed framework serves as a decision-support tool for senior managers' and experts' judgment within organizations. Furthermore, the proposed model is a scientific tool that helps improve the quality of activities carried out by companies providing blockchain-related services, particularly private blockchain. In addition, this research addresses the identification of influential criteria and their classification, and the results obtained from its implementation demonstrate their reliability.
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