The Appian Way, one of the worldβs oldest roads, is also a UNESCO World Heritage site. But how many visitors can it actually host without damage? Researchers have built a model to estimate the tourism carrying capacity (TCC) of linked cultural sites, using the Appian Way as a case study. The model relies on three capacity concepts: physical (available space), real (existing infrastructure), and effective (environmental impact). By analysing 614 municipalities and 13 gravity areas, they simulated three tourism growth scenarios for 2024β2034. 2019 results show the Appian Way overall sits at a βlow impactβ level, yet conditions differ widely across regions. Some towns already face high tourist loads, while others may see a sharp rise in the next decade. More infrastructure doesnβt always mean higher capacity: fragile environments can still be stressed by visitors. Conversely, ecologically healthy areas with few services risk overload. This research expands TCC assessment from single sites to whole territories, providing a valuable tool for sustainable tourism planning.
The proposed model builds on Cifuentes' three-tier carrying capacity: physical (C_f), real (C_r), and effective (C_e). Physical capacity is calculated using a surface density index for visitors, considering archaeological areas, pedestrian routes, and green spaces. Real capacity incorporates the infrastructure networkβparking, restrooms, public transportβthrough a provision index (I_d). Effective capacity finally integrates environmental impact via an ecological fragility index (I_f), assessing soil, flora, and fauna vulnerability. The final formula is C_e = C_f × I_d × (1 β I_f). For the Appian Way, data were gathered from institutional sources (ISTAT, Ministry of Cultural Heritage) and tourist flow sensors. Simulations for 2024β2034 include linear, exponential, and βgreen tourismβ scenarios, the latter with carbonβfootprint reduction policies. Results show that under linear growth, effective capacity stays within 30% of the maximum value over ten years; exponential growth pushes it beyond 60% in some areas, indicating overload risk. The analysis suggests targeted actions: strengthening infrastructure in zones with high I_d but low I_f, and restricting access in areas with high I_f. This integrated approach can be replicated for other serial sites, providing a quantitative basis for sustainable cultural tourism management.
