Tourism, as one of the most dynamic sectors of the global economy, is in a constant state of change and renewal. Despite the global expansion of theoretical debates in this area, research on tourism destinations in Iran remains constrained by theoretical weaknesses, conceptual fragmentation, and a lack of analytical coherence. Classical frameworks, particularly Butler’s Tourism Area Life Cycle (TALC), have provided important foundations for destination studies but struggle to account for the complexity, heterogeneity, and nonlinear dynamics that characterize real tourism systems. This shortcoming highlights the need for new theoretical perspectives. This study introduces Evolutionary Economic Geography (EEG) as a promising paradigm for advancing the study of tourism destination evolution. EEG builds upon three interrelated concepts-path dependency, generalized Darwinism, and complexity theory-to examine how destinations develop, adapt, and transform over time. By adopting a narrative review approach, the research systematically analyzed scientific literature published between 1995 and mid-2025. Within this framework, destinations are conceptualized as adaptive complex systems shaped by multi-level interactions between human agency, institutional structures, and environmental conditions, and thus prone to both gradual adjustments and sudden, path-breaking changes. Concepts such as path creation, lock-in, and co-evolution enrich this perspective by explaining how tourism evolves in relation to broader social and economic systems. Applying EEG not only provides greater analytical coherence but also establishes a robust foundation for case studies in Iran’s tourism destinations. Overall, this approach, as a novel theoretical perspective, has the capacity to fill the conceptual gaps in Iranian tourism research and to open new horizons for future studies.