Analysis of Quantum Computing’s Applicability in Data Analysis: Utilizing a Hybrid MCDM Approach With Quantum Spherical Fuzzy Sets

Quantum computing offers transformative processing capabilities, particularly in data analysis. However, its adoption in developing countries like Vietnam faces significant barriers, such as financial constraints, infrastructural limitations, and skill shortages. This study aims to determine and analyze these barriers’ impact weights and evaluate and rank potential solutions for overcoming the most critical barriers. This study proposes a multi-faceted approach integrating Multi-Criteria Decision Making (MCDM) methods, including the Delphi Method (DELPHI), Decision Making Trial And Evaluation Laboratory (DEMATEL), Combined Compromise Solution (COCOSO), Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), and the Multiplicative form of Multi-objective Optimization based on Ratio Analysis method (MULTIMOORA), alongside the Quantum Spherical Fuzzy (QSF) set analysis. This combination, especially integrating QSF DELPHI and QSF COCOSO models, represents a significant methodological contribution. Results indicate that Vietnam’s primary barriers to quantum computing are limited infrastructure, high costs, and a lack of skilled workforce. Correspondingly, the most highly rated solution strategies are cost reduction initiatives, investment in infrastructure, and training and education programs, which should be prioritized and considered to remove potential barriers. These findings highlight the need to prioritize addressing issues in facilities, human resources, and financial resources. This research bridges theoretical insights with actionable recommendations, providing a comprehensive roadmap for mitigating barriers and promoting the integration of quantum computing into Vietnam’s data analysis landscape.