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 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

Hotel Brand Conversions: What Works and What Doesn’t

As many as one-third of U.S. hotels have been converted from one brand to another in recent years, a process that frequently improves the hotel’s financial performance—although that is not always the case. Using data collected between 1994 and 2012 from PKF Hospitality Research, an analysis of brand conversions by 260 hotels shows that hotels moving downscale generally improved their occupancy, and thus their top-line revenue and profit ratios, compared to a control group of 2,750 hotels that did not change brands. However, hotels that moved upscale did not see notable changes in revenue or profit, nor did hotels that moved across their tier, especially when they stayed within their brand family. Two factors seem to drive the financial results for converted hotels—the relative strength of the brand and the fit between the brand and the property.

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 Comparison of the Performance of Brand-Affiliated and Unaffiliated Hotel Properties

Research has shown that performance differences exist between brand-affiliated hotels and unaffiliated properties. However, the extant empirical results are mixed. Some research has shown that brands outperform unaffiliated hotels on various metrics, whereas other research has shown the opposite. This article analyzes this issue using a matched-pair approach where we compare the performance differences of brand-affiliated and unaffiliated properties between 1998 and 2010. The matched-pair approach ensures that local competitive conditions as well as hotel characteristics are the same across the comparison pair. In addition, all potential omitted-variable bias and model misspecifications are avoided. Thus, to address our research question, we compare branded hotels with unaffiliated properties that are identical in age, market segment, location, and duration of operation, as well as having a similar number of rooms. Our analysis shows that performance differentials are present, albeit not systematic. We found no consistent advantages in all segments for either the affiliated hotels or the comparable unaffiliated properties, taking into account our comparison factors. That said, the methodology of our approach yields results that are more informative to the affiliation choice of owners and to the growth strategies of hotel brand–owner companies than those of previous empirical studies.

Utilizing “Big Data” to Improve the Hotel Sector’s Energy Efficiency: Lessons from Recent Economics Research

Hotel chains have access to a treasure trove of “big data” on individual hotels’ monthly electricity and water consumption. Benchmarked comparisons of hotels within a specific chain create the opportunity to cost-effectively improve the environmental performance of specific hotels. This paper describes a simple approach for using such data to achieve the joint goals of reducing operating expenditure and achieving broad sustainability goals. In recent years, energy economists have used such “big data” to generate insights about the energy consumption of the residential, commercial, and industrial sectors. Lessons from these studies are directly applicable for the hotel sector. A hotel’s administrative data provide a “laboratory” for conducting random control trials to establish what works in enhancing hotel energy efficiency.

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.

Key Organizational Resources and the Sustainable Competitive Advantage of Cornell University’s School of Hotel Administration: Suggestions for Tourism & Educational Programs in China

Tourism and hospitality scholars and educational institutions in developing countries can benefit from systematic analysis of their counterparts in developed countries. Using the framework of sustainable competitive advantage, this paper explores the key organizational resources of the School of Hotel Administration at Cornell University that have assured its position as the leading hospitality program worldwide. The paper analyses key resources Cornell Hotel School uses to leverage and sustain its competitive advantage. Suggestions for positioning and enhancing future Chinese tourism and hospitality programs are provided. [Abstract in Chinese] 中国旅游发展起步较晚,在旅游教育的多数领域落后于西方发达国家。选择西方优秀旅游院系进行系统研究并总结其成功经验,对于提高我国旅游教育水平有着重要的意义。本文以持续竞争优势理论为框架,以全球旅游接待业教育的典范——康乃尔酒店管理学院为对象,详细分析了这所著名酒店学院的核心资源和确保其长期保持领袖地位的持续竞争优势,并提出可供中国旅游教育界参考借鉴的措施建议

Shining Examples of Service When the Lights Went Out: Hotel Employees and Service Recovery during the Blackout of 2003

The electrical outage in the summer of 2003 that interrupted power to thousands of hotels wrought a variety of facilities failures and service-process problems. Fortunately, strong service-recovery efforts from hotel employees mitigated the worst of the blackout’s effects. Using survey data from hotel managers who experienced the blackout, this study highlights those employee actions that most contributed to immediate service recovery; however, the study also reveals limited organizational learning or efforts to failsafe hospitality service from the eventuality of future power failures.