A Proposal for a Global Hospitality Capital and Resource Efficiency Index (GH-CREI)

By Dr. Tong Yin, Founder & CEO, InsightBridge Global LLC

Abstract

RevPAR, ADR, occupancy and revenue growth are indispensable measures of hotel demand and pricing, but they do not show how effectively an enterprise converts capital, physical capacity and labor into sustainable profit. That distinction has become more consequential in the post-recovery phase. European hotel margins have stabilized while payroll and distribution costs have risen, US profitability remains below earlier benchmarks, and the cost and intensity of hotel capital have increased. This paper proposes the Global Hospitality Capital & Resource Efficiency Index (GH-CREI), a transparent composite measure calculated at hotel-asset level and aggregated bottom-up. It retains common indicator families across three operating tiers while changing pillar weights to reflect differences in capital intensity, service complexity and labor requirements. The method combines capital efficiency, profit conversion, capacity and space–time utilization, and labor efficiency; normalizes observations within tier, region and year cohorts; and uses a weighted geometric mean with uncertainty tests. A Nordic pilot, supplemented by company and second-market comparators, illustrates why revenue growth, margin improvement and capital efficiency can point in different directions. No entity score is published because the normalization cohort does not yet exist. The proposal is intended as an open, testable starting point for owners, operators, investors, lenders, statisticians and researchers.

1. Introduction: the measurement gap

Hotel performance is usually communicated through RevPAR, average daily rate (ADR), occupancy and total revenue growth. These measures have strong practical advantages. They are standardized, widely understood, available monthly and readily comparable across properties and markets. The STR/CoStar glossary also places hotels into established chain-scale segments, enabling a common vocabulary for benchmarking. Headline metrics are therefore selected because they are standardized and comparable, not because they necessarily answer every capital-allocation question.

The limitation is one of scope. RevPAR shows rooms revenue per available room, not the capital required to create that room, the labor needed to service it, the distribution cost incurred to sell it, or the profit retained after operating expenses. ADR can rise while occupancy or ancillary-space utilization falls. Total revenue can grow while the incremental profit conversion rate weakens. A hotel with a high room rate may still employ its balance sheet, physical infrastructure, built space and working hours less efficiently than a more modestly priced competitor.

Recent evidence makes this distinction material. In Europe, the FY2025 gross operating profit (GOP) margin was approximately 36.5%, broadly flat after a 2024 peak, while flow-through was 35%. Northern Europe recorded TRevPAR growth of 1.4% but GOPPAR growth of only 0.2%, and total payroll per available room rose nearly 5%, according to the HotStats review of the post-recovery phase. The picture is not uniformly weak: early 2026 European RevPAR grew 5.6% and profit rose 12% year on year, according to HotStats’ Q1 assessment. The relevant point is not that revenue management has ceased to work. It is that revenue no longer provides a sufficient summary of profit conversion.

The same issue appears in the United States. A CBRE Trends sample of 2,216 hotels reported 2025 operating revenue growth of 2.6%, equal to CPI, while GOP margin declined to 34.8% from 35.1% and EBITDA margin fell to 22.8% from 23.3% (Lodging Magazine). HotStats data cited in September 2026 placed US GOPPAR in 2025 still 10% below 2019, with wages 15.3% above 2019 against operating revenue 12.8% above 2019 (Hospitality Net). These figures describe a conversion problem, not simply a demand problem.

Labor and distribution reinforce the case. Eurostat reported Q2 2026 hourly labor-cost growth of 3.1% in the euro area and 3.2% in the EU; EU accommodation and food service activities also rose 3.1% (Eurostat). US hotels paid nearly $128bn in wages and benefits in 2025, projected to approach $131bn in 2026 (AHLA). Globally, RevPAR had risen 19% since 2019 while booking costs per available room had risen 25% (ITB Berlin and Duetto, citing HotStats). Booking Holdings itself processed 1,235m room nights and $186.1bn in gross bookings in 2025, with $26,917m revenue and $8,186m marketing expense (Booking Holdings). The author’s computation from that source gives revenue equal to 14.5% of gross bookings and marketing expense equal to 4.4%. These are platform-level ratios, not a hotel commission rate, but they indicate the scale of intermediation funded by the travel system.

Capital has also become more demanding. The ECB raised its deposit facility rate to 2.50%, its main refinancing rate to 2.65% and its marginal lending rate to 2.90%, effective 16 September 2026 (ECB). HVS reports senior euro-denominated hotel facilities commonly at 55–65% loan-to-value, margins of E+165–350bps and tenors of 5–7 years for stabilized assets (HVS). Meanwhile, the global construction pipeline reached a record 15,976 projects and 2,433,948 rooms, including 1,385 luxury projects and 257,947 luxury rooms (Lodging Econometrics). HVS estimates 2025 development budgets at more than $1.6m per luxury key, compared with $170–197k for limited-service and midscale extended-stay hotels, a roughly 8–9 times difference by the author’s computation from HVS development-cost data.

Metrics should also reflect the enterprise life cycle. During start-up and expansion, growth, market share and distribution reach are appropriate measures of market formation. In a mature market or stabilized asset, profitability, capital productivity and resource utilization become decisive. This is not an argument to replace RevPAR. It is an argument to place revenue management inside a wider economic account.

This paper therefore proposes GH-CREI. Its contribution is a reproducible bridge between detailed accounting, operational benchmarking and decision-ready communication. It specifies the unit of analysis, tiering, indicators, normalization, weighting, aggregation, robustness tests and disclosure protocol; then illustrates the interpretation with public Nordic and corporate data. The proposal separates verified facts, author’s computations and methodological propositions throughout.

2. What existing measures capture and miss

Revenue measures describe market realization. Occupancy measures the share of room capacity sold; ADR measures the average realized room rate; RevPAR combines the two. TRevPAR extends the numerator to total revenue. Under the Uniform System of Accounts for the Lodging Industry (USALI), GOP and GOPPAR move the analysis closer to operating profit. They still do not, by themselves, connect profit to invested capital or reveal whether rooms, restaurants, meeting areas and labor hours are jointly productive.

USALI’s 12th Revised Edition materially improves the feasibility of a broader index. Effective 1 January 2026, it makes departmental full-time-equivalent reporting mandatory through Schedule 15, adds mandatory annual brand and operator cost reporting through Schedule 16, renames the utilities schedule Energy, Water and Waste, and includes an optional booking-channel revenue schedule. The same HFTP expert overview states that labor is typically about 30% of hotel revenue and 40% of expenses. Standardized FTE and operator-cost data can therefore support labor and distribution measures that were previously assembled inconsistently.

Hospitality scholarship already recognizes that a room-night is not the only perishable unit. Kimes defines RevPASH as revenue for a period divided by available seats multiplied by the length of that period (Kimes, 1999). Function-space revenue management similarly treats area and time as constrained inventory (Kimes and McGuire, 2001). GH-CREI extends that reasoning: rooms, seats, function space, capital and paid labor time are complementary productive resources.

Capital metrics provide another missing lens. Return on capital employed (ROCE) relates operating profit to the balance-sheet resources supporting it, while asset turnover relates revenue to capital employed. Reporting is feasible. Whitbread publishes a fully reconciled group ROCE of 11.1% for FY26 and explains its pre-IFRS 16 definition (Whitbread FY26 results). Yet corporate ROCE can mean very different things for an owner-operator, a lessee and an asset-light franchisor. The index must fix the accounting basis and locate the capital at the asset that employs it.

Frontier methods such as data envelopment analysis (DEA) and stochastic frontier analysis (SFA) offer rigorous ways to estimate relative efficiency. Assaf and Josiassen provide a state-of-the-art review and meta-analysis of frontier analysis (Journal of Travel Research). Nurmatov, Fernandez Lopez and Coto Millan reviewed 350 tourism DEA articles across about 200 journals and found concentration in hotels, Europe and Asia (International Journal of Hospitality Management). These methods are analytically valuable but rarely appear in routine investor communication and can be inaccessible to property practitioners. GH-CREI is proposed as a transparent complement, not a substitute.

Composite-index construction has its own discipline. The OECD/JRC Handbook sets out a ten-step framework spanning theory, data, imputation, multivariate analysis, normalization, weighting, aggregation, uncertainty analysis, links to other indicators and visualization. Greco and colleagues emphasize weighting, aggregation and robustness choices (Social Indicators Research), while Saisana, Saltelli and Tarantola show why uncertainty and sensitivity analysis are part of index quality rather than optional additions (JRSS Series A). These principles govern the specification below.

Finally, lease accounting matters. IFRS 16 has required lessees, for annual periods beginning on or after 1 January 2019, to recognize a right-of-use asset and lease liability (IFRS Foundation). An IFRS 16 basis does not remove every owner-lessee difference, but it makes lessee capital substantially more visible and provides a more comparable starting point.

3. Design principles of GH-CREI

P1. Hotel asset as the unit of analysis. GH-CREI measures whole-asset economics: owner and operator economics are combined regardless of whether the legal form is ownership, lease, management or franchise. Portfolios and groups are aggregated bottom-up. Group financials are used only with an explicit operating-model adjustment.

P2. Common families, tier-specific weights. Every tier retains the same capital, profit, utilization and labor families. Weight matrices differ because a luxury full-service hotel and a budget limited-service hotel are economically different production systems.

P3. Efficiency rather than size. Inputs are expressed as ratios per unit of capital, room, square metre, hour or FTE. Absolute revenue, portfolio size and market capitalization do not directly increase the score.

P4. Concentration as risk. Seasonal concentration and distribution dependence are inverse indicators. A property that produces the same annual volume from a narrower season or more costly channel mix uses capacity less resiliently.

P5. Transparency and reproducibility. Each input should trace to audited statements, USALI schedules, official statistics or a disclosed benchmark panel. Raw indicators must be published beside composite scores so that users can distinguish data from aggregation.

P6. Relative cohort scoring. Scores are relative within tier × region × year cohorts. Absolute performance thresholds should not be invented before a sufficiently large multi-year panel exists.

4. Specification

4.1 Tiering

The STR/CoStar chain-scale classification supplies the starting taxonomy:

GH-CREI tier	Chain-scale mapping	Practical interpretation
Tier 1	Luxury + Upper Upscale	Full-service; five-star and ultra-luxury treated as an independent sub-market where sample size permits
Tier 2	Upscale + Upper Midscale + Midscale	Three- and four-star mainstream lodging
Tier 3	Economy/budget limited-service	Two-star and below; predominantly pure lodging

Tiering is economic, not ceremonial. HVS development costs exceed $1.6m per luxury room but are $170–197k for limited-service and midscale extended-stay rooms (HVS). Labor intensity also differs. A Chinese industry compilation reports 2019 employees per available room of 1.13 in five-star, 0.82 in four-star and 0.46 in three-star hotels (Shinegrade); another industry report places economy hotels around 0.2, with a roughly 0.16–0.25 range (JD Capital). The public-company pilot below yields 0.18 FTE per room for Scandic and about 0.36 employees per room for Whitbread, while HSH’s group-wide figure is about 2.5 but includes non-hotel operations. Revenue mix and occupancy patterns also differ. Tier-specific weights acknowledge these production differences without abandoning a common conceptual framework.

4.2 Pillars and core indicators

Pillar / code	Indicator and formula	Primary input source	Direction
C1	ROCE = EBIT ÷ (total assets − current liabilities). Asset alternative: NOI after FF&E reserve ÷ gross asset value at cost or appraisal	Audited statements; asset accounts and valuation	Higher
C2	Asset turnover = total revenue ÷ capital employed	Audited statements	Higher
P1	GOP margin = GOP ÷ total revenue	USALI operating statement	Higher
P2	GOPPAR = GOP ÷ available room-nights	USALI and room inventory	Higher
P3	Flow-through = ΔGOP ÷ Δtotal revenue, trailing 24 months	Current and prior USALI statements	Higher
P4	Distribution cost ratio = (commissions + channel and transaction costs) ÷ rooms revenue	USALI Schedule 16 and channel records	Lower, inverse
U1	Annual room occupancy = occupied room-nights ÷ available room-nights	Property management system; STR/CoStar	Higher
U2	Seasonal concentration = Gini coefficient of monthly occupied room-nights	Monthly property data; national statistics	Lower, inverse
U3	Non-rooms space productivity = non-rooms revenue ÷ m² of revenue-generating non-rooms space; RevPASH and function-space RevPAST are sub-metrics where available	USALI departments, floor plans and booking systems	Higher
L1	Revenue per FTE = total revenue ÷ average FTE	USALI Schedule 15	Higher
L2 / L3	Labor cost ratio = total labor cost ÷ total revenue; FTE per available room = average FTE ÷ available rooms	USALI Schedule 15 and operating statement	Lower, inverse

The presentation combines L2 and L3 in one row, while they remain separately normalized measures in the labor pillar. Seasonal concentration follows the Gini-based approach used by Duro. All capital measures use an IFRS 16 or economically aligned ASC 842 basis. The asset-level alternative is necessary when the balance sheet does not combine owner and operator capital.

4.3 Normalization and missing data

Observations are first winsorized at the cohort’s 5th and 95th percentiles. Positive indicators are normalized within tier × region × year:

x̂ = (x − x_min) ÷ (x_max − x_min) ∈ [0,1]

For inverse indicators, the normalized value is flipped:

x̂_inverse = 1 − x̂

This makes 1 consistently represent stronger relative efficiency. A pillar is computed only when at least two-thirds of its indicators are available; otherwise the entity is not rated. No imputed value should silently replace a missing economically important input. Any permitted imputation must be disclosed and included in sensitivity tests.

4.4 Proposed weights

Tier	Capital C	Profit P	Utilization U	Labor L
Tier 1	35%	25%	25%	15%
Tier 2	30%	30%	20%	20%
Tier 3	20%	20%	25%	35%

Weights sum to 1, with equal indicator weights inside each pillar by default. Tier 1 places the greatest weight on capital because luxury construction costs and non-room space are substantial, while utilization remains material because multiple revenue areas are perishable. Tier 2 balances capital and profit conversion. Tier 3 gives labor the largest weight because limited-service economics depend on standardized, lean delivery, while utilization remains central to a lodging-led model.

These weights are propositions, not empirical findings. Tests must include principal components analysis, benefit-of-the-doubt DEA weights as developed by Cherchye and colleagues, and ±10-point perturbations of pillar weights with rebalancing. Rank shifts must be reported, following the sensitivity discipline of Saisana, Saltelli and Tarantola.

4.5 Aggregation

Within each pillar, GH-CREI takes the arithmetic mean of available normalized indicators. Across pillars, the default is a weighted geometric mean, which limits full compensation of a weak pillar by a strong one:

I_j = 100 × Π_k (S_kj)^(w_k)

Here S_kj is entity j’s normalized score for pillar k, floored at 0.01, and w_k is the tier weight. Flooring prevents a single zero from mechanically reducing the entire index to zero while retaining a substantial penalty. The arithmetic sensitivity version is:

I_j^A = 100 × Σ_k w_k S_kj

Both versions must be published. An entity is flagged when its rank changes by more than one quintile between them. The geometric choice follows the OECD/JRC concern with compensability and the robustness issues reviewed by Greco and colleagues.

4.6 Reporting

The reporting panel comprises the 0–100 score, cohort percentile, quintile band, four pillar sub-scores and all raw indicator values. It also reports the arithmetic sensitivity score, relevant rank flags, missingness and accounting basis. A rolling three-year average dampens cycle effects, while annual raw values remain visible. The score is never presented without its cohort definition.

4.7 Data protocol and disclosure

Audited statements commonly provide revenue, EBIT, total assets, current liabilities, employee costs, employee numbers and lease liabilities. GOP, GOPPAR, flow-through, channel costs, departmental FTE and revenue-generating area are often voluntary or non-GAAP. USALI’s revised schedules narrow this gap, but the index should distinguish reported inputs from derived proxies.

Where direct data are absent, the three financial statements can support transparent approximations. The income statement supplies revenue, operating profit and labor expense; the balance sheet supplies capital employed and leases; the cash-flow statement helps reconcile capital expenditure, disposals and non-cash items. A proxy is acceptable only when its construction and limitations are visible. For private groups, statutory filings, statistical offices, property registries and benchmarking panels such as HotStats, CBRE Trends and Benchmarking Alliance can be cross-verified. Cross-verification does not convert unlike definitions into identical measures; definitional adjustments remain necessary.

A recommended minimum disclosure set for listed hotel companies is: property-level or regional GOP and GOPPAR; average FTE under a stated definition; total labor cost; owned, leased, managed and franchised room counts; right-of-use assets and lease liabilities; commissions and channel costs; revenue-generating non-room area; and a reconciled capital-return measure. Publication of these data would improve both investment analysis and operating accountability without requiring a proprietary scoring system.

5. Illustrative application: the Nordics and comparators

This pilot shows how raw pillar indicators can read differently from headline revenue. It does not publish GH-CREI scores or rankings because a sufficiently defined tier × region × year cohort for normalization does not yet exist.

5.1 Market layer

The Nordic data combine demand strength with meaningful utilization variation. In Norway, July 2026 hotel guest nights reached 4,005,330, up 4.1% year on year, with a 39.5% foreign share and an average room price of NOK 1,600, up 5.8% (Statistics Norway). Yet, in the Benchmarking Alliance sample of about 70,000 rooms, Norway’s 2025 annual occupancy was 62.5%, ADR NOK 1,444 and RevPAR NOK 903; December occupancy was around 44%, and maximum registered capacity was 93,227 rooms (NHO Reiseliv annual report). Q1 2026 occupancy was 55.5%, average rate NOK 1,392 and RevPAR NOK 773 (NHO Reiseliv Q1 report). NHO Reiseliv’s managing director separately summarized official data by saying that 45% of Norway’s hotel rooms are vacant annually (Finansavisen/NTB). A record month can coexist with a first-order seasonality issue.

Across the region, Stockholm RevPAR rose 12.0% to SEK 1,234 with ADR up 7.4%, while Copenhagen RevPAR rose 6.6% at 88.2% occupancy. Rovaniemi was Finland’s only growing city market, with RevPAR up 14.0% on volume, while Helsinki, Turku and Tampere softened (CBRE September 2026 Nordic figures). An index should therefore preserve asset and segment variation rather than infer common efficiency from a regional average.

Scandic’s Q2 2026 illustrates this directly. Group net sales rose 3.5% to SEK 5,998m, but organic growth was 1.2%; occupancy was 65.6%, RevPAR SEK 882, and adjusted EBITDA margin improved to 13.3% from 12.5% (Scandic half-year report). The group margin therefore expanded. Finland, however, reported sales of SEK 1,051m versus SEK 1,156m and adjusted EBITDA of SEK 58m versus SEK 142m, reducing the margin to 5.5% from 12.3%. Scandic shares fell 7.95% on the day (Investing.com). The careful interpretation is that headline group growth and margin improvement concealed a segment-level profit-conversion problem to which the market reacted. Asset-level GH-CREI inputs would make that divergence visible without treating the share movement as proof of causality.

5.2 Enterprise layer

All calculated figures below are explicitly the author’s computations from the linked company filings; amounts inside the formulas are in millions of each company’s reporting currency (SEK for Scandic, GBP for Whitbread, HK$ for HSH, USD for Marriott and Hilton). The uniform pilot basis is ROCE = EBIT ÷ (total assets − current liabilities) under IFRS 16 or US GAAP.

Entity	Model and tier	Public-data reading	Interpretation and caveat
Scandic 2025	Predominantly leased; Tier 2	Author’s computations from Scandic 2025: 2,661 ÷ (52,590 − 6,560) = 5.8% ROCE; 7,025 ÷ 22,289 = 31.5% labor cost ratio; 6,588 ÷ 22,289 = 29.6% rent ratio; 22,289m ÷ 10,178 = SEK 2.19m revenue per FTE. For 2024, 10,097 ÷ 55,319 = 0.18 FTE per room.	An alternative excluding IFRS 16, 1,467 ÷ (2,968 + 35) = 48.9%, omits landlord capital. The 2024 room base avoids the Dalata inclusion in year-end 2025 rooms.
Whitbread FY26	Owner-operator, 49% freehold; Tier 3	Whitbread reported 11.1% ROCE under its pre-IFRS 16 definition and 12.7% for Premier Inn UK. Author’s computations: 648.9 ÷ (9,568.6 − 889.4) = 7.5% uniform ROCE; 801.6 ÷ 2,920.2 = 27.5% employee-cost ratio. Using reported average employees, (2,920.2 − 260.9)m ÷ 30,723 = c.£86.6k revenue per employee and 30,723 ÷ 86,582 = c.0.36 employees per room.	The 11.1% and 7.5% results are definitional sensitivity, not different operating performance. Employee counts are headcount, not FTE.
HSH 2025	Owner-operator; Tier 1	Author’s computations from HSH results: 961 ÷ (55,051 − 7,574) = 2.0% ROCE; 7,978m ÷ 7,768 = HK$1.03m revenue per employee; 7,768 ÷ 3,106 = c.2.5 employees per room. Reported hotel EBITDA margin rose to 20% from 14%, while operations revenue rose 11% and operating EBITDA rose 43%.	Margin recovery coexists with low capital return in an asset-intensive group with assets under development. The staffing ratio includes commercial properties, Peak Tram and clubs, so it overstates hotel staffing.
Marriott 2025	Asset-light franchisor; comparator	Author’s computations from Marriott’s 10-K: 4,141 ÷ (27,540 − 8,398) = 21.6% ROCE; goodwill, brands and contract costs of 19,243 ÷ 27,540 = 69.9% of assets; owned/leased rooms 0.8% of system; equity −$3,771m.	Corporate return mainly measures brand and contract capital, not hotel-asset capital.
Hilton 2025	Asset-light franchisor; comparator	Author’s computations from Hilton’s 10-K: 2,693 ÷ (16,774 − 4,508) = 22.0% ROCE; intangibles 11,781 ÷ 16,774 = 70.2% of assets; owned/leased rooms 1.1% of system; equity −$5,359m.	As with Marriott, this is a brand-capital return and must be separated from owner balance sheets.

Scandic shows why lease capitalization matters. Its 48.9% non-IFRS 16 calculation and 5.8% uniform calculation describe the same operating year but radically different capital boundaries. Whitbread shows the same issue from another direction: its carefully reconciled 11.1% reported measure becomes 7.5% under the pilot denominator. GH-CREI must use one basis and publish the reconciliation.

HSH shows why margin cannot stand in for capital efficiency. Hotel EBITDA margin improved from 14% to 20%, and operating EBITDA increased 43%, but uniform ROCE was about 2.0%. This is consistent with intensive capital and assets under development, not evidence that the margin recovery was unimportant. Its regional occupancies of 57–68% and the HVS luxury cost benchmark clarify why luxury performance needs simultaneous margin, utilization and capital measures.

Marriott and Hilton show a unit-of-analysis problem rather than a performance defect. Both corporate ROCE results are about 22%, both have negative equity, approximately 70% of reported assets are intangibles under the calculations above, and only about 1% of system rooms are owned or leased. Their returns appropriately describe valuable brand and contract systems. They do not reveal whether the underlying hotel owners employ building capital efficiently. This distinction is consistent with the author’s earlier discussion of margin and invested capital in Hotel News Resource.

5.3 Second-market cross-checks

Budapest demonstrates that demand and utilization can move differently. Guest nights reached a record 9.83m in 2025 versus 9.47m in 2019, while room supply expanded by roughly 12–13%. Occupancy was 71.4% versus 76% in 2019, yet RevPAR rose from €57.56 to €78.42, a 36.3% increase (Horwath HTL). In H1 2026, RevPAR rose 15% to just under €90, but average GOP rose 4.9%, several full-service branded hotels declined, and Budapest trailed Prague by more than €10 in GOP per available room. Expected 2026 openings represented 5.0% supply growth (Hospitality Net). RevPAR leadership does not automatically imply profit leadership.

In Bulgaria, nearly two-thirds of surveyed hotels reported average occupancy below 50%, and 58% reported importing labor (HTIF and BAHE survey). Official March 2026 bed occupancy was 25.5%, down 1.1 points, although overnight-stay revenue rose 11% (BTA citing NSI). The combination makes capacity and labor utilization essential to interpretation.

Saudi Arabia shows why pipeline capital and achieved utilization belong in one frame. Existing inventory was 176,260 rooms, with 105,225 under construction or in advanced planning and more than half of the pipeline in luxury or upper-upscale. Riyadh’s January–April 2026 occupancy was 49.3% and RevPAR fell 18.3% year on year (Knight Frank). These facts do not determine future returns, but they make capital intensity and utilization central evaluation variables.

5.4 What the pilot suggests

Four provisional inferences follow. First, revenue growth and efficiency can diverge at asset and segment level, as Scandic Finland illustrates. Second, operating model determines what corporate ROCE measures, so hotel-asset computation is essential. Third, seasonality is a first-order Nordic utilization variable even when peak demand sets records. Fourth, labor and distribution costs can weaken profit conversion, while a higher rate environment raises the hurdle for capital efficiency. These are hypotheses consistent with the evidence, not completed causal tests.

6. Limitations and open questions

GH-CREI cannot eliminate accounting heterogeneity. IFRS and US GAAP differ, and IFRS 16 and ASC 842 produce different expense patterns. Historical cost, appraisal and fair-value measurement can generate unlike asset denominators. Assets under development expand capital employed before stabilized earnings appear, as relevant to HSH. Currency translation can alter group comparisons without changing local productivity.

Mixed-use hotels create allocation questions across residences, retail, clubs and transport operations. Group data can conceal property dispersion, while asset accounts can omit central services. Owner, operator and franchisor records may not align. Benchmark panels face survivorship and self-selection, and private-company filings can arrive with long lags. Cohorts must be large enough to support winsorization, percentiles and regional segmentation without revealing confidential contributors.

Measurement can also change behavior. Under Goodhart’s law, an indicator used as a target may be optimized at the expense of its purpose. Cutting labor below service standards could improve a narrow cost ratio while damaging guest experience, maintenance and future cash flow. GH-CREI therefore needs service-quality and asset-condition safeguards in interpretation, even if they are not mixed mechanically into the efficiency score.

The proposed weights remain contestable. Equal within-pillar weights may mask correlation; geometric aggregation may penalize data noise; relative scoring can allow a weak cohort to produce a top performer. Annual data are timely enough for capital analysis but slow for operations. Private data access and assurance costs may constrain coverage. Open questions include the minimum cohort size, treatment of newly opened and renovated hotels, allocation of shared brand expenses, currency conversion, and whether separate owner and operator diagnostic panels should accompany the whole-asset score.

A credible index will therefore need an independent governance body, an open methodology, version control, a data dictionary, restatement rules and published sensitivity results. GH-CREI should remain revisable as evidence accumulates.

7. Practitioner self-assessment worksheet

The worksheet is diagnostic, not a scoring shortcut. A property should assemble a consistent year of inputs, reconcile lease and owner capital, and compare raw ratios only with its tier × region × year cohort. It should not apply invented absolute score bounds.

Code	Required inputs	Formula	Recommended external benchmark
C1	EBIT; total assets; current liabilities; or asset NOI after FF&E reserve and gross asset value	EBIT ÷ (total assets − current liabilities)	Audited peers; CBRE Trends; statutory filings
C2	Total revenue; capital employed	total revenue ÷ capital employed	Audited peers; CBRE Trends
P1	GOP; total revenue	GOP ÷ total revenue	HotStats; CBRE Trends
P2	GOP; available rooms; days open	GOP ÷ available room-nights	HotStats
P3	Current and prior GOP and total revenue for trailing 24 months	ΔGOP ÷ Δtotal revenue	HotStats; internal budget history
P4	Commissions; channel and transaction costs; rooms revenue	(commissions + channel and transaction costs) ÷ rooms revenue	USALI Schedule 16; channel reports
U1	Occupied and available room-nights	occupied ÷ available room-nights	STR/CoStar; national statistics
U2	Monthly occupied room-nights	Gini(monthly occupied room-nights)	National statistics; Benchmarking Alliance
U3	Non-rooms revenue; revenue-generating m²; seat-hours or function-space-hours where available	non-rooms revenue ÷ m²; RevPASH/RevPAST sub-metrics	HotStats; CBRE; comparable venues
L1	Total revenue; average FTE	total revenue ÷ average FTE	USALI Schedule 15; CBRE Trends
L2 / L3	Total labor cost; total revenue; average FTE; available rooms	labor cost ÷ revenue; FTE ÷ available rooms	USALI Schedule 15; national labor statistics

The practitioner should record source, reporting perimeter, accounting standard and any proxy beside each input. Only after data validation should normalized cohort values and pillar scores be calculated.

8. Conclusion and invitation

RevPAR remains a useful measure of demand realization, but it cannot answer whether a hotel enterprise uses capital, physical capacity and labor effectively and efficiently. The evidence reviewed here shows why the distinction matters: profit conversion can lag revenue, seasonality can coexist with record peaks, margin recovery can coexist with low capital return, and corporate return can describe brand capital rather than hotel assets.

GH-CREI offers a testable architecture rather than a finished rating. It fixes the hotel asset as the economic unit, retains common indicator families across three tiers, normalizes within comparable cohorts, limits compensability through geometric aggregation, and makes raw data and robustness tests part of the result. Its immediate value is not a league table, but a more complete question set for owners, operators, investors, lenders and public authorities.

I offer this as an opening proposal, not a finished standard, as a first stone intended to draw out better ones. I welcome peers and experts across hospitality, finance, accounting, statistics and academia, as well as colleagues from other industries, to critique, refine and improve the index. The purpose is to build a measure that genuinely evaluates whether enterprises use capital, physical resources and labor effectively and efficiently, and how they truly perform. Comments and collaboration are welcome at tongyin@insightbridge.global.

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About the author

Tong Yin, Ph.D., holds a doctorate in hospitality management from Auburn University and is the founder of InsightBridge Global LLC. His research and consulting work focus on ultra-luxury hotel asset management, organizational behavior, and the evolving business model of international hotel groups.

tongyin@insightbridge.global · insightbridge.global