In recent years, quantum economics has emerged as a revolutionary discipline that applies the fundamental principles of quantum physics to offer a new perspective on the uncertainty and complexity inherent in modern economic systems. Quantum cognition plays a fundamental role in this framework, explaining how individuals process information and make decisions in contexts of ambiguity and uncertainty. Using quantum mechanisms such as the superposition of mental states, interference, and entanglement, quantum cognition models complex behavioral phenomena that are inexplicable by classical decision theory, such as the effects of presentation order and cognitive paradoxes. This article examines the intersection between quantum economics, quantum cognition, decision-making, and sustainability in financial environments through a systematic review following the PRISMA methodology and a bibliometric analysis. Recent advances in artificial intelligence and quantum computing are driving the practical application of these approaches, improving the management of uncertainty in sectors such as renewable energy and sustainable resource management. The results show that quantum economics is a promising framework for the design of policies and strategies aimed at achieving the Sustainable Development Goals (SDGs).
In recent years, quantum economics has emerged as a revolutionary discipline that applies the fundamental principles of quantum physics to offer a new perspective on the uncertainty and complexity inherent in modern economic systems. Quantum cognition plays a fundamental role in this framework, explaining how individuals process information and make decisions in contexts of ambiguity and uncertainty. Using quantum mechanisms such as the superposition of mental states, interference, and entanglement, quantum cognition models complex behavioral phenomena that are inexplicable by classical decision theory, such as the effects of presentation order and cognitive paradoxes. This article examines the intersection between quantum economics, quantum cognition, decision-making, and sustainability in financial environments through a systematic review following the PRISMA methodology and a bibliometric analysis. Recent advances in artificial intelligence and quantum computing are driving the practical application of these approaches, improving the management of uncertainty in sectors such as renewable energy and sustainable resource management. The results show that quantum economics is a promising framework for the design of policies and strategies aimed at achieving the Sustainable Development Goals (SDGs).
Classical models of decision-making under uncertainty, grounded in expected utility theory and Bayesian probability, often fail to account for systematic cognitive anomalies such as preference reversals, order effects, ambiguity aversion, and context-dependent choices. Quantum cognition models offer a novel theoretical framework that applies the mathematical principles of quantum probability—such as superposition, interference, and non-commutativity—to cognitive processes without assuming physical quantum mechanisms in the brain. By representing cognitive states as probabilistic superpositions that collapse through decision “measurements,” these models provide parsimonious explanations for violations of classical rationality. This paper examines how quantum cognition frameworks capture contextual influence, belief updating, and interference effects in uncertain decision environments. Drawing on findings from cognitive psychology and behavioral economics, the study highlights the relevance of quantum cognition for applications in economic choice modeling, legal decision analysis, and artificial intelligence. The analysis suggests that quantum probability offers a robust alternative to classical approaches when modeling human decision-making in complex, ambiguous, and context-sensitive situations.
Quantum economics is an interdisciplinary field that combines the principles of quantum mechanics and economic theories. The research examines the main theoretical and practical aspects of quantum economics, starting with its theoretical foundations based on the principles of quantum mechanics, such as superposition, uncertainty and entanglement, and ending with practical applications and perspectives for further research. Special attention was paid to the potential impact of quantum technologies on finance, marketing, supply chain management, as well as on macroeconomic planning and policy. It discusses how quantum algorithms can transform traditional approaches in economic research and practice, providing new methods for analyzing complex data, improving forecasting of economic trends, and optimizing decisions under uncertainty. Quantum economics opens up new perspectives for understanding dynamic and interconnected processes in the global economy, which can fundamentally change our perception of economic laws and strategies. It is emphasized that the quantum economy is at the initial stage of its development, and scientists and practitioners face many challenges and questions that need to be solved. In the future, we can expect the development of new tools for economic analysis and decisionmaking based on quantum computing, which will allow us to cope with current and future economic challenges more effectively. The quantum economy can also offer new approaches to risk management and financial security, especially in light of growing cyber threats and the need to protect economic information. Quantum economics is an exciting and promising direction that can significantly enrich both theoretical and applied aspects of economic science.
Abstract In the current context, where the productivity paradox coexists with growing concerns about inequality, quantum economics and quantum game theory are emerging as novel frameworks to address inherent uncertainty and complex strategic interactions. Quantum game theory applies the principles of quantum mechanics to model strategic interactions, providing new insights into decision-making, optimization and conflict resolution. In this article, we conduct a systematic review following the PRISMA methodology and a bibliometric analysis of the literature on quantum game theory to assess its development, methodologies and applications. We examine the growing interest in quantum technologies such as quantum computing, quantum communication and quantum simulation, which have had a significant impact on both theoretical models and practical economic and social systems. By mapping trends in the quantum game theory research landscape, this article aims to identify key advances, highlight important milestones and propose future directions for research in this emerging field. This comprehensive mapping not only elucidates the dynamic evolution and interdisciplinary convergence of quantum and evolutionary game theory, but also establishes a foundation for future research, fostering innovative approaches to complex decision-making in increasingly uncertain and interconnected environments.
This article explores the interdisciplinary interface between quantum computing and economic theory, with a particular emphasis on how foundational concepts from quantum mechanics reshape core methodological and epistemological assumptions in economics. Drawing on a comprehensive bibliographic methodology, the study synthesizes contributions from quantum physics, computational theory, and economic modeling to trace the impact of quantum logic -especially principles such as superposition, entanglement, and measurement irreversibility- on both theoretical constructs and applied frameworks. Particular attention is given to emblematic algorithms (e.g., Shor’s and Grover’s) as case studies for illustrating computational discontinuities in fields such as cryptographic trust, portfolio optimization, and decision-making under uncertainty. The article also surveys recent developments in quantum machine learning and quantum-inspired models relevant to economic forecasting and adaptive policy design. Ethical and distributional concerns are critically addressed, especially in relation to the asymmetric global access to quantum resources. By mapping this emerging field through a structured review of cross-disciplinary literature, the paper offers a conceptual framework for understanding how quantum technologies may influence future research in financial economics, risk theory, and the modeling of complex systems operating under deep informational constraints.
The emergence of quantum computing has prompted researchers to examine potential parallels between quantum mechanical principles and human cognitive processes. This article explores the theoretical framework of quantum cognition, examining how concepts from quantum mechanics, including superposition, entanglement, and measurement, might inform our understanding of human decision-making, memory, and consciousness. While quantum computing operates on fundamentally different physical principles than biological neural networks, the mathematical formalisms of quantum mechanics offer novel perspectives on cognitive phenomena that classical probability theory struggles to explain. This review critically examines the current state of quantum cognition research, its applications in computational modeling, and the ongoing debates regarding the validity of quantum mechanical analogies in psychological theory. The analysis reveals both promising theoretical insights and significant limitations in applying quantum principles to human cognition, highlighting the need for empirical validation and careful distinction between mathematical analogy and physical reality.
Classical economic decision-making models rely on assumptions of stable preferences, logical consistency, and additive probabilities. Yet decades of behavioral research consistently reveal systematic violations of these principles, including preference reversals, framing effects, and context-sensitive judgment patterns that challenge rational-choice theory. This study examines how quantum propensity modeling—grounded in mathematical structures derived from quantum theory—offers a compelling alternative for understanding these anomalies. Unlike classical models, quantum cognition treats decisions as evolving cognitive states represented in superposition, allowing individuals to hold simultaneous, uncertain predispositions before committing to a choice. Contextual interference, probability amplitude effects, and state-dependent transitions enable these models to accurately describe how information order, framing, and emotional cues distort decision trajectories. Through qualitative analysis of case studies from behavioral economics, cognitive psychology, and decision theory, this research highlights how quantum models capture the non-commutativity of choices, the instability of preferences under uncertainty, and the mechanisms behind cognitive interference patterns. The findings suggest that quantum propensity modeling not only explains well-documented behavioral anomalies more coherently than classical frameworks but also provides a theoretical foundation for applications in market forecasting, algorithmic pricing, consumer behavior analysis, and policy design. Ultimately, the study argues that quantum-inspired decision models represent a transformative step toward more realistic, context-aware interpretations of economic behavior.