QUANTUM BUSINESS MODEL IN QUANTUM THEORY-BASED BUSINESS STRATEGY FOR DECISION MAKING

Traditional business decision models rely on classical probability and deterministic logic, which often fail to capture uncertainty, paradoxical behaviors, and dynamic market conditions. Quantum theory offers an alternative framework, introducing quantum probability, superposition, and entanglement to improve strategic decision-making. This research adopts a qualitative approach, incorporating expert interviews and secondary data analysis to explore the feasibility of a Quantum Business Model (QBM) in real-world business applications. The study investigates quantum probability in decision-making, quantum computing for business optimization, and challenges in QBM implementation. The findings indicate that quantum probability provides a more flexible decision-making framework, allowing for context-dependent and non-classical choices. Additionally, quantum computing optimization techniques enhance logistics, finance, and supply chain management by solving complex problems faster than classical models. However, significant technological, organizational, and ethical barriers hinder widespread adoption. While QBM presents transformational potential, its practical implementation is still limited by technological readiness, workforce skill gaps, and regulatory concerns. Businesses must develop hybrid quantum-classical strategies before full-scale quantum adoption is viable. The study highlights the importance of interdisciplinary collaboration in overcoming adoption challenges and ensuring the responsible implementation of quantum-based decision-making models. Future research should focus on empirical validation, hybrid quantum-classical approaches, and regulatory frameworks to facilitate QBM integration in diverse industries.