Airports face persistent capacity constraints and increasing delays. This study introduces a behavioural framework for demand management that integrates airport and airline preferences with principles from Prospect Theory. By incorporating concepts from behavioural economics—such as loss aversion, reference dependence, and non-linear probability weighting—into choice architectures, we explore how adaptive decision environments can influence airline scheduling and demand distribution. A practical example illustrates the applicability of the proposed methodology. Results suggest that behavioural interventions can sustain economically viable schedules while maximising total prospect value. This approach provides policymakers and operators with innovative tools to address complex capacity challenges in air transport systems.
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