Coupled supply and demand forecasting in platform accommodation markets
Year: 2026
Type: article
Abstract: Tourism demand forecasting is methodologically mature, but it usually treats accommodation supply as fixed, exogenous, or slow-moving. This Progress in Tourism Management article develops a narrated, conceptually focused review of forecasting in platform-mediated short-term rental markets, where supply is elastic, decision-driven, and jointly shaped with demand through pricing, information design, host participation, and policy intervention. The article reframes realized booked nights as a constrained outcome generated by latent demand, effective supply, and matching frictions. It synthesizes tourism forecasting, revenue management, two-sided market economics, causal inference, and compositional time-series methods; articulates a three-layer coupling framework spanning intervention, behavioral, and informational channels; and uses a stylized model experiment to illustrate one supply-shock failure mode. The contribution is a theoretical and methodological map: where platform accommodation forecasting has developed, what remains under-specified, and how future work can validate coupled supply–demand forecasting. It does not attempt a completed comparative empirical evaluation.
Source: Tourism Management
Author: Harrison E. Katz
Institution: Airbnb (United States)
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,690
OpenAlex ID: W7133336668