Benchmarking as Recursive Learning: A Realist and Systems-Based Analysis of Organisational Learning in Destination Governance

Sustainability benchmarking has become central to destination governance, yet its influence on organisational learning remains poorly understood. This project examines how engagement with the Global Destination Sustainability Index (GDS-Index) shapes learning processes within Destination Management Organisations (DMOs), and under what contextual conditions benchmarking leads to symbolic compliance, fragile progress, or embedded sustainability governance. To address both substantive and methodological gaps, the study integrates realist evaluation with systems mapping through a structured analytic protocol. Seven years of benchmarking data from 93 destinations are analysed alongside 23 realist interviews with governance actors. Context–Mechanism–Outcome (CMO) configurations are treated as analytically stabilised explanations and are subsequently examined relationally using systems-oriented reasoning to test feedback loops, path dependence, and non-linear trajectories. The study identifies three recursive learning trajectories—symbolic, transitional, and realised—and reconceptualises benchmarking as a recursive learning scaffold. Methodologically, it advances a processual model of absorptive capacity and demonstrates how realist explanation can be strengthened through structured relational testing.