Short-term Trading in Long-term Funds: Implications for Financial Managers

Most hospitality firms do not consider managing stock portfolios to be a main part of their operations. They are in the service business, using their real assets and the services provided by employees to create valuable experiences for guests. However, the need to focus on stock investments arises through those employees. Employees consistently rank benefits, including retirement benefits, among the top five contributors to job satisfaction and as a key consideration in accepting a job.1 It is not surprising, then, that more than 90 percent of companies with 500 or more employees offer retirement plans. The five largest hotel companies in the U.S. have over $10 billion in assets under management in their retirement plans, making these plans a key component in retirement investment decisions.

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.

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.

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.

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.

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).

Error Recovery Performance: The Impact of Leader Behavioral Integrity and Job Satisfaction

This article introduces the concept of error recovery performance, followed by the development and validation of an instrument to measure it. The first objective of this article is to broaden the current concept of service recovery to be relevant to the back-of-house operations. The second objective is to examine the influence of leader behavioral integrity (BI) on error recovery performance. Moreover, the study examines the mediating effect of job satisfaction between BI and error recovery performance. Finally, the study links error management performance with work-unit effectiveness. Data for Study 1 were collected from 369 hotel employees in Turkey. The same relationships were tested again in Study 2 to validate the findings of Study 1 with a different sample. Data for Study 2 were collected from 33 departmental managers from the same hotels. Linear regression analysis was used to test the direct effects. The mediating effects were tested using the mediation test suggested by Preacher and Hayes. In addition, in Study 2, general managers of the hotels were asked to rate the effectiveness of each manager and their respective department. Results from Study 1 indicate that BI drives error recovery performance, and this impact is mediated by employee job satisfaction. Results of Study 2 confirm this model and finds further that managers’ self-rated error recovery performance was associated with their general managers’ assessment of their deliverables and of their department’s overall performance.

Accounting for the Multi-Period Impact of Service When Determining Employee Requirements for Labor Scheduling

Providing good customer service, inexpensively, is a problem commonly faced by managers of service operations. To tackle this problem, managers must do four tasks: forecast customer demand for the service; translate these forecasts into employee requirements; develop a labor schedule that provides appropriate numbers of employees at appropriate times; and control the delivery of the service in real-time. This paper focuses upon the translation of forecasts of customer demand into employee requirements. Specifically, it presents and evaluates two methods for determining desired staffing levels. One of these methods is a traditional approach to the task, while the other, by using modified customer arrival rates, offers a better means of accounting for the multi-period impact of customer service. To calculate the modified arrival rates, the latter method reduces (increases) the actual customer arrival rate for a period to account for customers who arrived in the period (in earlier periods) but have some of their service performed in subsequent periods (in the period). In an experiment simulating 13824 service delivery environments, the new method demonstrated its superiority by serving 2.74% more customers within the specified waiting time limit while using 7.57% fewer labor hours.