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.

Highlights from the 2016 Sustainable and Social Entrepreneurship Enterprises Roundtable

The April 2016 Sustainable and Social Entrepreneurship Enterprises roundtable brought together over 20 faculty, students, and leaders and entrepreneurs from a wide variety of mission-driven enterprises that focus on sustainability or social welfare. Jeanne Varney, lecturer at the School of Hotel Administration, opened the day by inviting attendees to speak to and even test some of their innovative ideas on fellow participants during the day. Varney noted: “One of our goals for the roundtable was to have a really diverse set of attendees and to hear a lot of different perspectives.”

My Attitudes and Beliefs about Different Types of Research

[Excerpt] In this issue’s “From the Editor,” I describe a new review policy and process for both authors and reviewers. Authors should find that this new policy and process provides them with faster editorial decisions, higher quality feedback, and greater clarity about required revisions, as well as greater freedom to disagree with reviewers and to write the papers they (the authors) want. Reviewers should find that this new policy and process saves them from having to review obviously flawed papers and from having to review different versions of the same paper over and over again.

Does Tipping Help to Attract and Retain Better Service Workers?

A survey of several hundred restaurant servers in the United States found that servers’ attitudes toward working for tips and average tip sizes were weakly related (at best) to their service-orientation, intended job-tenure, and occupational-tenure. These findings suggest that tipping does not substantially help to attract and retain more service-oriented workers. Restaurateurs can eliminate tipping at their restaurants without fear that doing so will reduce the quality of their wait-staff.

An Empirical Investigation of the Relationships among Climate, Capabilities, and Unit Performance

For the current study, the authors examined the relationships among two dimensions of organizational climate and several indices of individual- and unit-level effectiveness. Specifically, the article proposes that an organization ’s service and training climate would be related to employee capabilities—operationalized in terms of frontline service capabilities and managerial support capabilities—and that such capabilities would be related to unit- level measures of employee turnover and sales growth. Using survey and operational data from 201 management and frontline staff members in 22 units of a national restaurant chain, the results from correlation and regression analyses generally supported the proposed relationships. This study replicates and extends previous research and provides a foundation for future conceptual development and empirical work in this research area.

On the Use of Regression and Verbal Protocol Analysis in Modeling Analysts’ Behavior in an Unstructured Task Environment: A Methodological Note

This paper discusses areas for future research opportunities by addressing accounting issues faced by management accountants practicing in hospitality organizations. Specifically, the article focuses on the use of the uniform system of accounts by operating properties, the usefulness of allocating support costs to operated departments, extending our understanding of operating costs and performance measurement systems and the certification of practicing accountants.

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.

Service Loyalty: An Integrative Model and Examination across Service Contexts

Marketing academics and practitioners generally agree that customer loyalty is vital to business success. There is less agreement on the factors that determine customer loyalty, particularly in service contexts. Research on the determinants of service loyalty has taken three distinct paths: 1) quality/value/satisfaction; 2) relationship quality; and, 3) relational benefits. In this research, the authors coalesce these paths to derive a model that links dimensions of customer loyalty (cognitive, affective, intention, and behavioral) with a system of determinants. The model is tested with data from varied services (airlines, banks, beauty salons, hospitals, hotels, and mobile telephone) and 3,500 customers in China. Results are consistent across contexts and support a multidimensional view of customer loyalty. Key loyalty determinants are customer satisfaction, commitment, service fairness, service quality, trust, and a construct new to service loyalty models—commercial friendship. The research contributes to the literature by providing a more complete, integrated view of customer loyalty and its determinants in services contexts.

Award for the Best Cornell Quarterly Article in 2002

[Excerpt] I am pleased to announce that the following article has been named Cornell Quarterly article of the year for 2002 (it appeared in the August 2002 issue): "Assessing the Profitability of Premium Players," by Anthony Lucas, Jim Kilby, and Jocelina Santos

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.

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.

From the Editor

[Excerpt] Cornell Hospitality Quarterly editor, Michael LaTour, lost his battle with cancer and passed away peacefully at his home on November 8, 2015. Mike LaTour’s in memoriam, which was written by his wife, Kathryn LaTour, reminds us of his legacy as an editor, scholar, and person. I want to use this “From the Editor” to highlight and discuss another of his editorial legacies. Before he passed away, Mike decided to introduce a “research note” section to the CQ—the first accepted one appears in this issue. I strongly supported Mike’s decision to have the CQ publish research notes and I intend to continue publishing them during my editorship.

Branding Hotels

[Excerpt] The hotel business has become a business of brands. Price Waterhouse Coopers estimates that there are over 300 hotel brands today with no one brand dominating the market. Every major brand management issue (brand extensions, global brand expansion, re-branding, un-branding, co-branding, brand portfolio development, brand acquisitions, new brand development, etc.) is being explored. An understanding of the competitive context and intra-and inter-brand dynamics will help owners, operators, asset managers, suppliers and litigators, as well as new entrants into the business make better and more informed brand management decisions.