Computational Occupancy Leakage
COLPotentially Sellable Room Nights Not Captured Because Inventory Is Excluded, Misunderstood, Distrusted, Stale, or Non-Actionable in AI-Mediated Discovery
Computational Occupancy Leakage measures unsold room nights from AI exclusion.
Definition
Computational Occupancy Leakage measures potentially sellable room nights that are not captured because inventory is excluded, misunderstood, distrusted, stale, or non-actionable in AI-mediated discovery. This is a proposed construct; the denominator requires estimation. Applicable sector: Hospitality.
Computational Occupancy Leakage quantifies potentially sellable room nights missed due to poor AI-mediated discovery. This is a proposed construct requiring estimation methodology.
Conceptual Formula
Computational Occupancy Leakage = (Estimated Sellable Room Nights − Captured Room Nights) / Estimated Sellable Room Nights. Denominator requires estimation.Methodology
Type
index construction
Data Sources
Confidence Level
low
Description
Computational Occupancy Leakage = (Estimated Sellable Room Nights − Captured Room Nights) / Estimated Sellable Room Nights. Denominator requires estimation.
Limitations
- Denominator is latent and requires estimation
- Requires attribution model
Key Takeaways
Key Points
- Proposed construct
- Denominator requires estimation
- Hospitality-specific leakage
Target Audience
Relevance Tags
Source Paper
Citation
For Computational Occupancy Leakage, see HomeSelf Research (2026), The Balance-Sheet Economics of AI-Mediated Demand.