The study aims to address the limitations of conventional tourism carrying capacity (TCC), reframing it as a proactive rather than reactive strategic asset. By examining whether TCC can strengthen destinations’ adaptive capacity and long-term competitiveness through a smarter use of existing resources, the research investigates how a data-driven, subsystem-level optimization of TCC can identify where the constraints bind the destination and how tourism demand management can relieve them.
A data-driven, subsystem-based optimization model identifies critical bottlenecks that condition the destination’s competitiveness. Canestrelli and Costa’s framework is modeled as a linear programming problem that maximizes tourism benefits through efficient resource use across interdependent destination subsystems. Behavioral usage rates and expenditure estimates, elicited through stakeholder surveys and validated against institutional sources, calibrate the model across three Mediterranean destinations together with subsystem capacities drawn from secondary data.
Simulations aimed at optimizing resource use and mitigating subsystem stress showed that flexible, targeted adjustments improve flow distribution and yield without exceeding stress thresholds. By identifying and rebalancing pressure points among subsystems, findings highlight that competitiveness and long-term destination performance are strengthened through smarter resource utilization and low-cost, behavioral interventions.
Extending Canestrelli and Costa’s framework into a comparative, data-driven application on the composition and behavior of demand, the study repositions carrying capacity (CC) as an internal lever of competitiveness management rather than an external constraint. The approach operates TCC as an ex ante decision-support tool for optimizing flows and yield, offering practical and methodological implications that align systemic management with long-term destination competitiveness.
