This dashboard models the trajectory of tourism distribution, control, and authenticity in destinations that have faced structural pressures comparable to Levi's. It draws on observed patterns from Iceland, Barcelona, Bali, and Amsterdam — geographically and culturally diverse cases that share three characteristics with Levi: rapid international growth, fragmented local supply, and a small number of platforms mediating most discovery.
The numbers shown here are not Levi-measured data. Levi-specific public data on OTA share, margin retention, ownership concentration, and block-booked inventory is not currently published. The absence of that data is itself a finding — one this project intends to address through primary research with local providers.
What this dashboard offers is a structural projection: if Levi follows the trajectory other comparable destinations have followed, this is roughly what the next fifteen years look like. The model also shows an alternative path — what changes if local control over distribution is deliberately defended.
The two paths are not predictions. They are illustrations of what is possible.
What you are looking at
- Pattern source. Global OTA penetration trends (Phocuswright, Skift industry reports), commission norms (Booking Holdings and Expedia Group public filings, GetYourGuide and Viator published commission ranges), and observed dynamics in destinations facing comparable structural pressures: Iceland, Barcelona, Bali, Amsterdam.
- Historical points (2010–2025). Reflect industry directionality across the comparison set, not direct Levi measurements. Where Levi-specific data exists and is verifiable, it is used. Where it does not, comparable-destination data is used as proxy.
- Future points (2030–2040). Project current rates of change for the default path, and a plausible recovery trajectory for the local-first intervention path.
- The Authenticity Index. A composite 0–100 score combining four signals: owner-led delivery (30%), direct booking share (25%), group size (25%), and experience duration (20%). Each signal is normalised to 0–100 before weighting. The weights are author-determined and open to challenge.
What this dashboard cannot do
It cannot tell you what is happening in Levi today with the precision Visit Levi or the Kittilä municipality could provide if they chose to publish the relevant data. It is a structural model, not a measurement.
What it can do
It can make visible the trajectory that destinations on this curve have followed elsewhere, and the choices available to destinations that recognise the curve early enough to act. That is the value of the model. Treat it accordingly.