Rethinking How Hotel Performance Is Evaluated
Why this matters
This study’s findings underscore a growing institutional unease with conventional metrics used to assess hotel performance, particularly in gateway and secondary markets within the Greater Bay Area. By highlighting the limitations of standard data envelopment analysis (DEA) models—specifically their failure to account for product diversification—the research calls into question the reliability of widely accepted efficiency benchmarks. For allocators and lenders, this signals a need to recalibrate underwriting and portfolio monitoring frameworks that have traditionally leaned on these metrics to gauge operational health and competitive positioning. More broadly, the study reflects a shift in how hospitality assets are evaluated amid evolving consumer preferences and increasingly complex service offerings. As institutional capital continues to flow into hotels, especially in markets where product differentiation is a key driver of revenue resilience, reliance on oversimplified performance models risks mispricing risk and return profiles. This could have downstream effects on capital allocation, loan underwriting, and asset management strategies, potentially prompting a reassessment of underwriting assumptions and due diligence processes. The research invites a more nuanced approach to performance analytics that better captures the multifaceted nature of hotel operations in today’s market environment.
Editorial analysis · AI-assisted
On the RET wire
- Disclosed hospitality deal value tracked in June 2026: $3.8B across 20 reported transactions. All Hospitality coverage →
Computed from Real Estate Trail’s own tracked coverage
A PolyU study of 53 GBA hotels finds none achieved efficiency between 2015-2019, and argues standard DEA models overstate performance by ignoring product diversification.
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