The Impacts of Variety on the Costs and Profits of a Hotel Chain’s Properties

In the hotel industry, undistributed operating expenses represent a significant portion of the operating costs for a hotel. Exactly how most of these expenses arise is not well understood. Using data from more than 40 hotels operated by a major chain, the authors examine the links between the variety of a hotel’s products and customers and its undistributed operating expenses and revenues. Their findings show that undistributed operating expenses are related to the extent of the property’s business and product-services mix. The results suggest that although increasing a property's product-service mix results in higher undistributed operating expenses, the incremental costs are compensated for by higher revenues. However, increasing business mix while increasing undistributed operating expenses does not result in higher revenues.

Hotel Profit Implications from Rising Wages and Inflation in the U.S.

Macroeconomic models based on the Phillips Curve predict that as the unemployment rate declines toward the long-run, natural rate, the pace of wage and price growth accelerates and inflation rises.1 In this paper I analyze the profitability prospects for the U.S. hotel industry in today’s relatively volatile economic environment, keeping in mind the Phillips Curve’s general principle that inflation and employment have an inverse, but relatively stable short-term relationship. Although employment and economic growth in the U.S. have been uneven in recent months, the unemployment rate has declined to less than 5 percent, which many economists believe is close to the natural rate. Growth in wages and salaries, as measured by the Employment Cost Index, has concurrently been moving upward between 2.5 and 3.0 percent during the past 12 months. At the same time, general inflation remains below levels that might typically be expected this late in the cycle, although core inflation is bumping up against the Federal Reserve’s 2-percent target. If the inflation rate continues to move upward as predicted by Phillips Curve models (and encouraged by the Federal Reserve), rising labor costs and other expenses will exert downward pressure on U.S. business profits. Backward movement up the Phillips Curve (with greater inflation) coincides with an expanding economy. In that scenario, prices of goods and services also will rise in real terms if their supply cannot keep up with demand, and producers have the ability to raise prices (absent fixed-price contracts such as leases).

Hotel Sustainability Benchmarking Index 2016: Energy, Water, and Carbon

Several studies have been undertaken or attempted by industry and academe to address the need for lodging industry carbon benchmarking. However, these studies have focused on normalizing resource use with the goal of rating or comparing all properties based on multivariate regression according to an industry-wide set of variables, with the result that data sets for analysis were limited. This approach is backward, because practical hotel industry benchmarking must first be undertaken within a specific location and segment.1 Therefore, the CHSB study’s goal is to build a representative database providing raw benchmarks as a base for industry comparisons.2 These results are presented in the CHSB2016 Index, through which a user can obtain the range of benchmarks for energy consumption, water consumption, and greenhouse gas emissions for hotels within specific segments and geographic locations.

Serving More Segments and Offering More Products: What Are the Costs and Where Are the Profits?

Making more money involves more than targeting new customer segments and offering new services.

Hotel Valuation Software, Version 4.0

[Updated August 2016] The Hotel Valuation Software, freely available from Cornell’s Center for Hospitality Research, has been updated to reflect the many changes in the 11th Edition of the Uniform System of Accounts for the Lodging Industry (USALI). Version 4.0 of the Hotel Valuation Software provides numerous enhancements over the original tool from 2011. In addition to a significant increase in functionality and an update to reflect the 11th edition of the USALI, Version 4.0 takes advantage of the power of the latest release of Microsoft Excel®. Note that Version 4.0 works only on a PC running Microsoft Windows, it does not work on a Mac running OS X. Users desiring an OS X compatible version should click here (Labeled as Version 2.5). 酒店评估软件手册和三个程序（点击这里 ) Users desiring a Mandarin version of the Hotel Valuation Software should click here The Hotel Valuation Software remains the only non-proprietary computer software designed specifically to assist in the preparation of market studies, forecasts of income and expense, and valuations for lodging property. The software provides an accurate, consistent, and cost-effective way for hospitality professionals to forecast occupancy, revenues and expenses and to perform hotel valuations. Version 4.0 of the Hotel Valuation Software includes the following upgrades – a complete update to reflect the 11th edition of the USALI – the most significant change to the chart of accounts in a generation, an average daily rate forecasting tool, a much more sophisticated valuation module, and an optional valuation tool useful in periods of limited capital liquidity. Using established methodology, the Hotel Valuation Software is a sophisticated tool for lodging professionals. The tool consists of three separate software programs written as Microsoft Excel files and a software users' guide. The tool is provided through the generosity of HVS and the School of Hotel Administration. The three software modules are: Room Night Analysis and Average Daily Rate: Enables the analyst to evaluate the various competitive factors such as occupancy, average room rate, and market segmentation for competitive hotels in a local market. Calculates the area-wide occupancy and average room rate, as well as the competitive market mix. Produce a forecast of occupancy and average daily rate for existing and proposed hotels in a local market. The program incorporates such factors as competitive occupancies, market segmentation, unaccommodated demand, latent demand, growth of demand, and the relative competitiveness of each property in the local market. The program outputs include ten-year projections of occupancy and average daily rate. Fixed and Variable Revenue and Expense Analysis: The key to any market study and valuation is a supportable forecast of revenues and expenses. Hotel revenue and expenses are comprised of many different components that display certain fixed and variable relationships to each other. This program enables the analyst to input comparable financial operating data and forecast a complete 11-year income and expense statement by defining a small set of inputs: The expected future occupancy levels for the subject hotel Base year operating data for the subject hotel Fixed and variable relationships for revenues and expenses Expected inflation rates for revenues and expenses Hotel Capitalization Software: A discounted cash flow valuation model utilizing the mortgage-equity technique forms the basis for this program. Values are produced using three distinct underwriting criteria: A loan-to-value ratio, in which the size of the mortgage is based on property value. A debt coverage ratio (also known as a debt-service coverage ratio), in which the size of the mortgage is based on property level cash flow, mortgage interest rate, and mortgage amortization. A debt yield, in which the size of the mortgage is based on property level cash flow. By entering the terms of typical lodging financing, along with a forecast of revenue and expense, the program determines the value that provides the stated returns to the mortgage and equity components. The program allows for a variable holding period from four to ten years The program includes an optional model useful during periods of capital market illiquidity that assumes a property refinancing during the holding period

Environmental Implications of Hotel Growth in China: Integrating Sustainability with Hotel Development

China has embarked on the largest program of new hotel construction the world has ever seen. Even though the nation’s growth rate has eased somewhat in the past year, China’s hotel development continues at a pace that would see at least three new 150+ room hotels open every day for the next 25 years.1 Even if the industry does not continue to expand at this rate, China’s hotel growth carries substantial consequences in terms of increases in energy and water consumption, and an expanding carbon footprint. In this paper, we outline the dimensions of this issue, and we urge hotel developers to heed the national government’s push for greater sustainability.

A Flow-Through Analysis of the US Lodging Industry During the Great Recession

Purpose – The objective of this exploratory study is to investigate the “flow-through” or relationship between top-line measures of hotel operating performance (occupancy, average daily rate and revenue per available room) and bottom-line measures of profitability (gross operating profit and net operating income), before and during the recent great recession. Design/methodology/approach – This study uses data provided by PKF Hospitality Research for the period from 2007-2009. A total of 714 hotels were analyzed and various top-line and bottom-line profitability changes were computed using both absolute levels and percentages. Multiple regression analysis was used to examine the relationship between top and bottom line measures, and to derive flow-through ratios. Findings – The results show that average daily rate (ADR) and occupancy are significantly and positively related to gross operating profit per available room (GOPPAR) and net operating income per available room (NOIPAR). The evidence indicates that ADR, rather than occupancy, appears to be the stronger predictor and better measure of RevPAR growth and bottom-line profitability. The correlations and explained variances are also higher than those reported in prior research. Flow-through ratios range between 1.83 and 1.91 for NOIPAR, and between 1.55 and 1.65 for GOPPAR, across all chain-scales. Research limitations/implications – Limitations of this study include the limited number of years in the study period, limited number of hotels in a competitive set, and self-selection of hotels by the researchers. Practical implications – While ADR and occupancy work in combination to drive profitability, the authors' study shows that ADR is the stronger predictor of profitability. Hotel managers can use flow-through ratios to make financial forecasts, or use them as inputs in valuation models, to forecast future profitability. Originality/value – This paper extends prior research on the relationship between top-line measures and bottom-line profitability and serves to inform lodging owners, operators and asset managers about flow-through ratios, and how these ratios impact hotel profitability.