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.
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.
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.
Since its emergence in the 1970s, behavioral economics has integrated psychological insights into economics—drawing on Kahneman and Tversky's prospect theory, Thaler's psychological accounting and boost theory, and Schiller's behavioral finance—thereby dismantling the myth of the "homo economicus" and revealing systematic cognitive biases inherent to human decision-making. However, classical behavioral economics has been constructed from a collection of fragmented "effects" and "biases," lacking a unified, axiomatic mathematical framework; moreover, the frequent practice among researchers to selectively apply individual effects has undermined the discipline's predictive power and theoretical coherence. This book is the first academic monograph in the world to systematically expound on quantum behavioral economics—a new paradigm devised specifically to overcome this fundamental dilemma. It introduces concepts such as Hilbert spaces, state vectors, superposition, entanglement, measurement collapse, quantum probability, interference effects, unitary evolution, decoherence, non-commutative observables, and quantum phase transitions into the foundational bedrock of behavioral economics: that preferences and beliefs coexist in a superposition prior to decision-making; that decision-making consists of constructing measurements to extract definite preferences via measurement collapse; and that the beliefs and behaviors of individuals are entangled, exhibiting non-local quantum correlations. Furthermore, it posits that the sequence in which information is presented and the framing effects are intrinsic properties of quantum decision-making—rather than mere "biases." This book comprises six parts and thirty chapters: Part I, "Paradigm Revolution," establishes the philosophical foundations, the quantum subject hypothesis, and the analytical framework; Part II develops quantum probabilistic judgments, quantum heuristics, quantum prospect theory, quantum decision-making under uncertainty, and quantum framing effects; Part III explores quantum preferences, quantum utility, quantum choice theory, quantum endowment effects and loss aversion, as well as the current state of quantum research and default effects; Part IV extends the scope to quantum social preferences, quantum altruism, quantum trust and cooperation, quantum game theory, and quantum public goods games; Part V examines quantum intertemporal choice, quantum hyperbolic discounting, quantum self-control, quantum procrastination and addiction, and quantum habit formation and behavioral change across temporal dimensions; Part VI demonstrates the application of framing in finance, markets, public policy, and health domains, while offering insights into the future of this discipline. This work pursues three overarching objectives: theoretical unification and depth, originality and authority, and seamless readability. It is intended for graduate students, faculty, and researchers in behavioral economics, decision science, psychology, and finance, as well as for public policy makers and practitioners in financial markets to provide new paradigm-based analytical tools.
This paper describes an approach to economics that is inspired by quantum computing, and is motivated by the need to develop a consistent quantum mathematical framework for economics. The traditional neoclassical approach assumes that rational utility-optimisers drive market prices to a stable equilibrium, subject to external perturbations or market failures. While this approach has been highly influential, it has come under increasing criticism following the financial crisis of 2007/8. The quantum approach, in contrast, is inherently probabilistic and dynamic. Decision-makers are described, not by a utility function, but by a propensity function which specifies the probability of transacting. We show how a number of cognitive phenomena such as preference reversal and the disjunction effect can be modelled by using a simple quantum circuit to generate an appropriate propensity function. Conversely, a general propensity function can be quantized,viaan entropic force, to incorporate effects such as interference and entanglement that characterise human decision-making. Applications to some common problems and topics in economics and finance, including the use of quantum artificial intelligence, are discussed.
Quantum interference effects play a fundamental role in social decision-making, offering a novel perspective beyond classical decision theories. This study explores the theoretical foundations of quantum decision-making, emphasizing the role of quantum probability in explaining cognitive biases, preference reversals, and decision anomalies. The research presents a quantum probability-based decision model and contrasts it with classical probability models. Through theoretical modeling and experimental design, we demonstrate how quantum interference alters decision probabilities and impacts group decision dynamics. The study further examines the applications of quantum decision theory in game theory, policy-making, financial markets, and artificial intelligence. Our findings suggest that quantum probability provides a more comprehensive and realistic framework for understanding human decision-making processes. Future research should focus on empirical validation, interdisciplinary integration, and the application of quantum computing to social decision modeling.
Quantum probability theory, originally developed in the context of quantum mechanics, has increasingly been applied to social sciences to explain decision-making, cognition, and collective behavior. Unlike classical probability models, which assume pre-existing and well-defined preferences, quantum models incorporate superposition, interference, and non-commutativity to capture the contextual dependence and measurement effects observed in human decisions. This paper systematically explores the theoretical foundations of quantum probability in social sciences, discusses model construction techniques, and reviews empirical findings supporting its application. By examining case studies in quantum cognition, quantum game theory, and quantum voting, we illustrate how quantum approaches provide alternative explanations for phenomena such as order effects, measurement-induced attitude shifts, and collective polarization. The paper also discusses the methodological challenges and limitations of quantum social science, emphasizing the need for rigorous experimental validation and interdisciplinary collaboration. Finally, we highlight the potential for integrating quantum probability models with emerging technologies such as quantum computing and artificial intelligence, opening new avenues for social science research and policy applications.
Abstract Foundations of Quantum Economics unfolds a coherent theoretical thread, replacing the rational-agent premise of mainstream economics with the quantum-person hypothesis: before observation, decision-makers sustain multiple conflicting options encoded in probability amplitudes, and a decision corresponds to collapse triggered by measurement. The book first lays cognitive and mathematical foundations, demonstrating that human judgement inherently exhibits quantum features including superposition, interference and order dependence. Classical probability theory fails for non-commutative economic events, making Hilbert spaces and probability amplitudes indispensable languages for economic inquiry. It then reconstructs causality, information, uncertainty and risk, arguing that economic causes are not uniquely fixed before the collapse of consensus; uncertainty is endogenous to the system, and risk represents the spread of superposed distributions rather than exogenous noise. Built upon this architecture, the work revisits core microeconomic notions such as value, utility, game interaction, supply and demand, property rights, institutions and innovation. All conventional theories are recovered as special limits under zero interference and single eigenstates, while superposition and entanglement furnish fresh explanatory power for economic anomalies. The analysis further expands into macroeconomics, interpreting growth, business cycles, money, fiscal policy, trade and welfare as coherent superposition, phase transition and collapse of collective cognition and consensus, and concludes with the renovation of econometrics and economic governance. The book’s central thesis holds that superposition, interference, observation and collapse are not metaphors borrowed from quantum physics, but intrinsic properties of human cognition and economic practice. Economic realities are not predetermined facts waiting to be discovered; instead, they are generated through human cognition, consensus and practice in the act of measurement. Quantum economics is far more than a cosmetic revision of existing models. It constitutes a shift of research programme, abandoning Laplacian determinism and reconceiving the economy as an open, generative process. The book articulates five interconnected layers: the quantum person as ontological starting point, quantum features of cognition, superposition of collective consensus, endogenous uncertainty, and quantuminformed governance. It reminds researchers and policymakers that economic observation and policy intervention are performative, capable of reshaping the very system they examine. Economics abandons the pursuit of a single, determinate optimum and embraces endogenous uncertainty; policymakers cease to be omniscient system engineers and become prudent stewards of consensus and designers of measurement bases. This volume establishes the unified bedrock for the whole quantum economics series and calls for a new, more honest and realistic economics embedded within the economic process itself.