Living Lab’s first economic model was for the Singapore Grand Prix in 2012. In 2025 we became a software platform: government-grade intelligence for the visitor economy
Tourism carrying capacity assessment. Living Lab starts where a forecast ends: it compares the demand vector against the capacity ceiling for each date and zone, whether that ceiling is hotel rooms, transport, event access, or resident tolerance for congestion, and flags where intervention would change the outcome rather than describe it. Reference data is published by UN Tourism.
Attributes what the last peak did: where rate compression appeared, where resale activity surfaced, where residents were priced out, and whether the intervention that was made changed the outcome. Signal137 tells the committee whether the last peak paid off commercially and what it cost in resident support.
Tests the next peak before it arrives: release held-back capacity now, a time-limited access or pricing intervention at the peak, hold for the unwind. Modelled price sensitivity and displacement under each option, with a stated range. Demand137 sets the mitigation triggers before the peak, so the response is planned rather than improvised.
| Product | Your question | You get | What it changes |
|---|---|---|---|
| Demand137 | Whether to release additional capacity, and when | The gap between forecast demand and available capacity, by date and zone, not an annual average | The release timed to the specific pressure window, not the planning calendar |
| Demand137 | Whether to intervene on price or access | Modelled price sensitivity and displacement under the forecast scenario, with a stated range | The dates and locations where intervention changes the outcome, chosen |
| Demand137 | Can current capacity absorb a peak without lasting local damage? | Demand tested against an explicit operational and social threshold, not a headline visitor total | Mitigation triggers set before the peak |
| Demand137 | Does this tell us the exact price to set? | A price and displacement range under each scenario, not a single tariff | The price remains the operator's, city's, or venue's decision, made on evidence |
| Demand137 | How far ahead does this need to run? | Long enough to act before the market reacts: weeks for a hotel or event, longer for a transport or access change | The horizon set to the decision, not a default |
| Demand137 | Can it factor in a specific event or seasonal calendar? | Event dates, school holidays, and known peaks as standard inputs beside the demand vector | The calendar is in the model, not beside it |
| Signal137 | What did the last peak do to rate, resale, and rents? | Rate compression, resale activity, and rent movement attributed to the peak | The next peak is planned on what the last one did |
| Signal137 | Did the intervention we made change the outcome? | The result set against the counterfactual of no intervention | The next intervention is sized on evidence |
| Both | Does this account for residents, not only commercial pressure? | The same calendar built against a social or congestion threshold, not only a commercial ceiling | The community's question answered on the same evidence as the operator's |
| Both | Who holds this, and where? | Model, data, and a trained team inside your jurisdiction | The capability survives the change of official or consultant |
International visitors to the United States fell 4.2% in 2025, the first annual decline since the pandemic, while worldwide travel grew. The spending did not disappear. It moved. Five economies are absorbing most of it, and the shift now looks structural.
Oman has announced plans for a high-altitude destination at Jabal al Akhdar, combining sports training, wellness, and tourism at 2,400 metres. It is the kind of project a Gulf government can commit to at once, and the kind that lives or dies on a demand case nobody has yet published.
International arrivals to the United States fell 4.2% in 2025 while worldwide travel grew about 4%. Living Lab’s displacement model puts the forgone spending at roughly US$50bn, and about US$10.6bn of it within reach of five economies. Each is limited by a different constraint.
Most destinations run near capacity for part of the year and well below it for the rest. A visitor added in the peak displaces one already there. A visitor added in the shoulder fills an empty room and is served by staff who would otherwise be idle. Almost no destination runs the calculation before fixing a date.
We turn messy event and tourism data into decisions that help communities grow. Bring curiosity and rigour. We will hand you questions nobody has answered yet.
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