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.