Coupled Supply and Demand Forecasting in Platform Accommodation Markets

TL;DR

This paper reviews and develops a framework for jointly forecasting supply and demand in platform accommodation markets, emphasizing the endogenous nature of supply and its impact on booking models.

Contribution

It introduces a coupling framework that integrates behavioral, informational, and intervention factors to improve supply-demand forecasting in elastic markets.

Findings

Supply is endogenous and co-evolves with demand through pricing and interventions.

Ignoring supply constraints leads to fragile booking models under shocks.

A toy simulation demonstrates identification failure in traditional models.

Abstract

Tourism demand forecasting is methodologically mature, but it typically treats accommodation supply as fixed or exogenous. In platform-mediated short-term rentals, supply is elastic, decision-driven, and co-evolves with demand through pricing, information design, and interventions. I reframe the core issue as endogenous stock-out censoring: realized booked nights satisfy B_{k,t} <= min(D_{k,t}, S_{k,t}), so booking models that ignore supply learn a regime-specific ceiling and become fragile under policy changes and supply shocks. This narrated review synthesizes work from tourism forecasting, revenue management, two-sided market economics, and Bayesian time-series methods; develops a three-part coupling framework (behavioral, informational, intervention); and illustrates the identification failure with a toy simulation. I conclude with a focused research agenda for jointly forecasting supply, demand, and their compositions.