Degree Type

Dissertation

Date of Award

2019

Degree Name

Doctor of Philosophy

Department

Apparel, Events and Hospitality Management

Major

Hospitality Management

First Advisor

Robert Bosselman

Second Advisor

Tianshu Zheng

Abstract

This research study examined branding and non-branding, occupancy, ADR, RevPAR, Gross Operating Profit per Room (GOPAR), Net Operating Income per Room, chain scale classification (luxury and upper upscale), time of sale, and geographic location of hotel as predictors of hotel sales prices. Research has been conducted on various brands and chain scales and the impact of branding on hotel market value; however, there has not been a study on the impact branded versus non-branded hotels have on hotel sales prices. Further no known research exists on testing occupancy, ADR, RevPAR, GOPAR, NOI per Room and chain scale as predictors of hotel sales prices. Due to the increase in both branded and non-branded hotels, investors continue to investigate the importance of brands and the factors that influence sales prices and value. Variables like RevPAR and profitability continue to play important roles in the analysis of hotel value and sales prices by both analysts and investors. Implications on hotel sales price and market value are limited as previous research has not considered sales of independent hotels, which limits the usefulness to investors seeking to capitalize on branded hotels only. In addition, previous historical research has been conducted through an earlier period of time ending in 2006, yet there have been technological innovations in the industry since 2006 which have impacted hotel performance and sales price.

Quantitative statistical methods were employed utilizing Univariate Regression Analysis, Analysis of Variance (ANOVA) and the Analysis of Co-Variance (ANCOVA) aimed at testing the impact of occupancy, ADR, RevPAR, GOPAR, NOI per Room, chain scale classification (luxury and upper upscale), time of sale, and geographic location of hotel on hotel sales prices. Luxury and upper upscale hotel sales from eight (Boston, New York City, Washington DC, Chicago, Los Angeles, Dallas, Houston and Miami) of the top ten metropolitan statistical areas (MSAs) during the period of 2007 through 2017 were researched and used. RevPAR was statistically significant as a predictor of hotel sales prices. Further, for chain scale luxury sector hotels, GOPAR and RevPAR were both significant as predictors of hotel sales prices. Occupancy, ADR, NOI per Room, date of sale, and geographic location were not significant predictors of hotel sales prices.

The analyses did not appear to show a statistically significant relationship between occupancy, ADR, and NOI per Room as predictors in sales prices of branded and non-branded hotels. The lack of emphasis of these variables on sales prices indicates that buyers and sellers of real estate are first establishing their own assumptions of revenue performance through a RevPAR analysis. Investors are likely developing their own measures of GOPAR and NOI per room measures. The implication of this research is that RevPAR performance is considered important in hotel sales prices and much more so than any other variables.

Key Words: Brand, Non-Branded, Sales Price, RevPAR, GOPAR, NOI.

Copyright Owner

Timothy J Dick

Language

en

File Format

application/pdf

File Size

107 pages

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