Popularization of Science

Popularization of Science

Interpretive structural modelling of challenges affecting the improvement of computing power in Iran

Authors
Mohammad Ali Keramati 1
Hossein Shirzai 2
Kaveh Alba 3
1 Associate Professor, Islamic Azad University, Central Tehran Branch. Tehran, Iran.
2 Assistant Professor of Islamic Azad University, Qom branch, Qom. Iran.
3 Technology Management Group. Islamic Azad University, Central Tehran branch. Tehran. Iran.
10.22034/popsci.2025.491536.1380
Abstract
Introduction: In recent decades, computational power has been recognized as a key driver of technological innovation and economic growth. According to the 2024 Global Network Readiness Index, Iran ranks 79th out of 133 countries, indicating existing technological capacity but weaknesses in effective utilization. Enhancing technological infrastructure and computational power is essential for the development of emerging technologies, including artificial intelligence and data analytics.
Objective: The purpose of this research is to identify and model computational power challenges in Iran using interpretive structural equations(ISM) and provide an analytical framework for policy and decision-making in this field.
Method: This applied and descriptive research was conducted with a mixed approach (qualitative and quantitative). In the qualitative part, the opinions and experiences of experts who had at least five years of specialized experience in information technology and computing power were collected to identify key factors and their relationships. In the quantitative part, interrelationship matrixes and access matrixes were created based on qualitative data and using mathematical calculations, ranking and analysis of the factors' impact were performed.
Findings: Six main challenges were identified: infrastructure, financial issues, sanctions, human resources, cybersecurity threats, and high energy consumption. Results revealed that sanctions and the shortage of specialized human resources, with the highest influence score (5) and dependency score (2), act as independent factors and drive other challenges.
Conclusion: The study presents an innovative conceptual model of computational power challenges in Iran. This model can guide policymakers and planners in prioritizing investments, developing infrastructure, and strengthening specialized human resources, thereby enhancing the country’s capacity in emerging technologies.
Keywords
Computing power
Interpretive Structural Modeling
Structural Self-Interaction Matrix
Emerging technologies
MicMac
Subjects
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