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2003
Analysis of hotel rates in four cities: New York City,Chicago, San Francisco, and AtlantaHui Ping Chang
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Recommended CitationChang, Hui Ping, "Analysis of hotel rates in four cities: New York City, Chicago, San Francisco, and Atlanta" (2003). Thesis. RochesterInstitute of Technology. Accessed from
Analysis of hotel rates in four cities:
New York City, Chicago, San Francisco, and Atlanta
by
Hui Ping Chang
A thesis submitted to the
Faculty of the school of Food, Hotel, and Travel Management
at
Rochester Institutes of Technology
in partial fulfillment of the requirements
for the degree
of
Master of Science
ROCHESTER INSTITUTE OF TECHNOLOGY Department of Hospitality and Service Management
Graduate Studies
M.S. Service Management Presentation of Thesis/Project Findings
Name: Hui Ping Chang SS# _____ Date:
Title of Research: Analysis of Hotel Rates in Four Cities: New York City,
Chicago, San Francisco, and Atlanta.
Specific Recommendations: (use other side if necessary)
12/9/03
Thesis Committee: (1) James W. Jacobs, Ph.D. (Chairperson)
(2)
OR (3)
Faculty Advisor:
Number of Credits Approved : __ --.:.4 ________ _
q -/0 - 0 3 Date Committee Chairperson's Signature
Date Committee Signature
Note: This form will not be signed by the Department Chairperson until all corrections, as suggested in the specific recommendations (above) are completed.
cc. Department Student Record File - Original
FORM I
ROCHESTER INSTITUTE OF TECHNOLOGY Department of Hospitality and Service Management
Graduate Studies
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The Author of a thesis or project should complete one of the following statements and include this statement as the page following the title page.
Title of Thesis/project: Analysis of Hotel Rates in Four Cities: New York City, Chicago, San Francisco and Atlanta
I, Hui Ping Chang , (grant, deny) permission to the
Wallace Memorial Library ofR.!.T., to reproduce the document titled above in whole or
part. Any reproduction will not be for commercial use or profit.
OR
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TABLE OF CONTENTS
ABSTRACT 3
CHAPTER 1 4
Overview 4
Problem Statement 4
Background 4
Purpose 5
significance 5
Methodology 6
literature review 7
Hypothesis 7
Definition of Terms 7
IdeologicalAssumptions 8
ProceduralAssumption 8
Scope and Limitations 8
LongRange Consequence 9
CHAPTER II 10
u.s. lodging industrymilestone 10
Hotel occupancy 13
international tourism 15
wanted: more tourists 16
how guests choosehotels? 17
marketing your community 18
CHAPTER III 20
methodology 20
hotel rates data collecting 20
Variables data 22
Correlation analysis 23
Significance testing 24
Stepwisemethod 24
multiple regression analysis 25
CHAPTER IV 26
RESULTS 26
NewYorkCityOutput 26
Chicago output 28
San Francisco output 30
Atlanta Output 33
CHAPTER IV 36
Discussion 36
Recommendations 37
BIBLIOGRAPHY 44
Table ofTables
Table 2. Foreign Travel: 1990 to 1999 (in thousands) 22
Table 3. Unemployment rate - Civilian labor force 22
Table 4. Lodging Industry summary: 1990 to 1998 23
Table 5. Number ofFortune 500 headquarter in the city 23
Table 7. New York City Hotel Rates vs. Potential Variables 26
Table 7.1. NYC CorrelationMatrix 26
Table 8. Chicago Hotel Rates vs. Potential Variables 28
Table 8.1 Chicago Correlation Matrix 28
Table 8.2 Chicago Summary output 29
Table 9. San Francisco Hotel Rates vs. Potential Variables 30
Table 9.1 San Francisco CorrelationMatrix 30
Table 9.2 SanFrancisco Summary Output 31
Table 9.3 SanFrancisco Summary Output 32
Table 10 Atlanta Hotel Rates vs. Potential Variables 33
Table 10.1 Atlanta Correlation Matrix 33
Table 10.2 Atlanta Summary Output 34
Table 10.3 Atlanta Summary Output 35
Tablel. Hotel Rates in 100Major Cities 1989-1999 39
Table 6. F. 05 distribution 42
Abstract
Hotel rate is essential to every traveler, every hotelier, every key person in travel
planning for their company, and even the tourism planner for the city. The graduate students
from RIT's hotel management program had conducted serial surveys on hotel rates in 100 major
cities in US from 1989-1999.
This study employed the data that RIT students collected as a foundation. First, four cities
were chosen in every region (East, Midwest, West and South). These four cities were New York
City, Chicago, San Francisco and Atlanta. Second, other possible factors were added in to
evaluation. They are national average hotel rates, foreigner visitors to US, unemployment rate,
average occupancy rate and number of Fortune 500 headquarter in the city. Third, statistical
analysis was applied to discover the relationship between hotel rates and those variables. This
study will conclude what factor is essential to the city's hotel rates. In addition, the equations for
future hotel rates perdition will be provided.
Data obtained from the hotel rate chart and five other factors were analyzed using excel.
Analyzing process include initial correlation analysis to eliminate the weakest factor. Following
by stepwise method, this assisted the researcher to determine the most efficient equation for each
city's hotel rates.
The study found thatcities'
hotel rates were highly correlated to national average, except
in Chicago. The hotel rate in Chicago had highest correlation with number of Fortune 500
headquarter in the city. Hotel occupancy rate is the weakest factor of the analysis for all four
cities.
Chapter I
Overview
Over the past decade, the United States had held the position as the number one travel
and tourism destination for total receipts generated worldwide and the second or third destination
for a number of visitors. The tourism industry played an important role in the U.S. economy.
Studying the hotel rates could provide information about hotel rates to expect in the future. In a
sense, customers could better plan their trips, hoteliers could better market themselves by having
a competitive price, and the corporations could better gauge their travel budget. Moreover, it
might also expose the potential to the city. For instance, if the city's hotel rate had weak
correlation with the foreigner visitors, the City Convention and Visitor's Bureaus might need to
work on attracting more foreigner visitors to raise its hotel performance.
This project would exanimate hotel rates of four major U.S. cities (New York City,
Chicago, San Francisco, and Atlanta) and compare with other possible factors that might
influence the hotel rate. In conclusion, this project might present significant factors to hotel rates,
as well as, the equations for predicting each of four cities future hotel rates.
Problem Statement
How could hoteliers determine what price to charge? Knowledge ofwhat influence the
hotel rates could help the company to determine their rates and stay competitive. And the
consumers would be benefit knowing what to expect concerning the future hotel rates.
Background
Each year, many investors tried to build hotelswithout identifying if the lodging market
was strong and reliable. It was difficult to make a good decision on where to locate a hotel. For
many enterprises in travel and tourism, pricing strategies had become the key element of their
marketing mix. Thecorporations'
travel managers had to gauge the travel expense line. Price
usually played an important role in decision making when leisure travelers chose their
destinations.
This project would provide specific data about hotel rates during 1990-1999. Hotel room
prices climbed as the hotel industry began to recover from overbuilding in the 1980's. What
were the factors that influence the pattern of supply and demand? To find out what the
equilibrium was in this market would help hoteliers continues making profit. Recognizing the
cost trends of the hotel industry would allow hotel owners to better predict pricing and to help
them succeed in the marketplace.
Purpose
The purpose of this study was to show the trend of the hotel room costs from 1989 to
1999 and to analyze the cost ofhotel rooms offour major cities (New York City, Chicago, San
Francisco, and Atlanta) in four different regions (East, Midwest, West, and South) in the
territorial United States, and to compare this data with the national average. In those four cities,
the study would consider economic status and other elements such as national hotel average rates
and Fortune 500 headquarter locations that may impact a city's hotel room rates. Finally, the
study would conclude with the determinant about what affected hotel room prices along with the
formula to utilize to determine future room rates.
Significance
Reliable information, and the competent analysis of information, was becoming
increasingly important for the effective planning, monitoring and management of the travel
industry. Having a picture ofwhole hotel industry as well as the local market would assist
hoteliers to better market themselves.
It was essential to research on the destination to keep costs in control. The travel
manager had to seek balance between meeting the dual corporate goals of the cost reduction and
effective execution ofbusiness activities. This study would provide valuable data for managers
that have to control theirbusiness'
travel expenses and for the hotel venture- entrepreneurs that
enter the business. The hotel industry could utilize this study as a marketing element. By
studying this project, corporations would have a better picture ofwhat might influence hotel
room rates and thereby created a better budgeting strategy.
This study would sample hotel rates in four major cities (New York City, Chicago, San
Francisco, and Atlanta) from 1990- 1999. It would identify the variables that influence the hotel
room rates of these major cities and provide the equations for hotel rate prediction. One could
use this as foundation for studying othercities'
hotel rates pattern.
Methodology
This study would use historical research to examine the pattern ofhotel room prices in
the U.S.A. It would establish the trend of the hotel room costs in past ten years by presenting the
data for hotel rates at 100 major cities in the U.S.A. Data collection was done by graduate
students from RT.T/s Food, Hotel and TravelManagement Department via telephone and mail
survey. The targets are mid-range hotels, with an average often to fifteen hotels per city.
This particular thesis emphasized four major cities (New York City, Chicago, San
Francisco, and Atlanta) in four different regions (North, Midwest, West, and South) and
compared them to national average hotel rates, foreigner visitors to US, unemployment rate,
average occupancy rate andnumber ofFortune 500 headquarter in the city. Ten observations
would record in each variable. Moreover, this study would offer the equation of future hotel rates
by utilizing statistical analysis such as correlation and regression.
Literature review
The literature foundation of this project would include tourism publishing and academic
research papers that explained what may affect the travel industry. This study would also assess
the information from tourism related websites, such as the Chamber ofCommerce, the Census
Bureau, and City Convention and Visitor's Bureaus. Understanding this information would be
the foundation for this study.
Hypothesis
This study would establish the trend ofhotel room rates by examining them with the
national average hotel rates, foreigner visitors to US, unemployment rate, average occupancy
rate and number ofFortune 500 headquarter in the city. Subsequently, this thesis would supply
regression model for each city and the equation for future hotel rates.
Definition ofTerms
Trend Underlying movement in a series of figures, usually and logically assumed to be
smooth. Generally extracted during decomposition of time series through the use
ofmoving annual average.
Marketing The performance ofbusiness activities directed at satisfying needs and wants
through the exchange process.
Data Measurements taken at the source ofbusiness process.
Business The social process that involves the assembly and use ofproductive resources to
create goods and services capable of satisfying society's needs and wants.
Budget A specific plan that shows how an organization or business unit will spend money
over time in order to meet its goal.
Customer Someone who has paid an admission price or is making a purchase.
Internet The Internet is the interconnection ofelectronic databases around the world with
access granted through service provides.
Strategic Planning Planning that usually takes place at the top management level and which
consists of setting goals, deciding upon polices and planning the future direction
of an organization. It is also referred to as long-range planning.
Chamber ofCommerce An association ofbusiness persons and merchants for the
promotion of commercial interests of a community within a specific region.
Ideological Assumptions
It was expected that the results of the study would provide valuable information for the
hotel industry and academic research.
Procedural Assumption
The data for this study was from the Corporate Travel Index. The information was
collected by graduate students in the Food, Hotel and Travel Department at R.I.T. The
procedural assumption is that the data was gathered accurately. The potential variables chosen
were nonbiased.
Scope and Limitations
Sampling four major cities in each region would offer the sufficient indicators to other
cities in U.S. The intention of the study was to present the trend ofhotel rates. The outcome of
the study would provide comparisons between hotel rates and other factors. National average
hotel rates, foreigner visitors to U.S, unemployment rate, average occupancy rate and number of
Fortune 500 headquarter in the city were chosen as possible factors that had an effect on hotel
rates.
There might be other factors that impacted the hotel rates but were not taken into
consideration for this project. Other limitation of the study was the number factor; only four
major cities, one for each region in the U.S.A, were examined.
Long Range Consequence
The study attempted to provide the pattern ofhotel rates at four major cities and to
identify factors that led hotel rates to fluctuate in New York City, Chicago, San Francisco and
Atlanta. Incorporation of the other factors such as inflation or observation of longer time period
would help other researchers to develop more accurate model for hotel rates prediction.
Chapter H
A hotel may have an influence on room costs for different reasons. This study will first
research what may affect hotel room costs. The next part of the study will be a concise review of
the applicable literature that is related to those four major cities (New York City, Chicago,
Atlanta, and San Francisco) in our study.
Initially, we will review the primary sources of applicable literature, including
magazines, text, newspapers and Internet. Secondly, reviews of the applicable materials that will
help to develop an understanding ofwhat the factors are that influence the hotel rates.
U.S. lodging industry milestone
Hotel industry had a terrible year in 1991. High interest rates and debt levels, combined
with an oversupply ofhotel room, outbreak of fighting in the Persian Gulf and a recession led to
record losses in 1991. Since 1992 over 4,200 properties with almost 400,000 rooms have been
opened in the small size categories. In 1993, it was a turning point for hotel industry as it started
to recover from the effects of the uncontrolled construction boom of the late 1980s and the
economic recession of the early 1990. During this period, supply exceeded demand which lead to
a decrease ofhotel rates.
Don't expect miracles, but victory in the gulf should boost the economy. It plunged after
the gulf crisis began and in January 1991 finally dragged consumer spending down with it. Say
goodbye to fear of $50-per-bbl. Oil. World oil supplies are greater than they were a year ago
despite the lack of the production from Iraq and Kuwait. With the war over, most experts
10
foresee a temporary plunge to as low as $15. This could only help consumers. With the cease
fire, tourists have at last begun making reservations. Confidence should rise higher as carriers
resume flights they suspended when the crisis escalated.
The different between the hotel industry in 1990, when it lost $5.7 billion, and 1993,
when it made $2.4 billion, was primarily due to the reduction in capital expenditures, like interest
expense, and an improvement in occupancy and average daily rate. The turnaround had little to
do with executives getting smarter and operations being more efficient. (Wolff, 1995). The
challenge is to capitalize on these increased revenues and become more efficient at running
properties.
Higher room rates are late but guaranteed arrival. Demand for rooms has been increasing
steadily over the past few years, rising 4.2% in 1994 alone; coupled with a flat supply ofnew
rooms that makes for an inevitable increase in rates.
From 1993 to 1998, there had been major shifts in hotel industry. The new trend included
consolidation of independently owned and operated properties to chain affiliated hotels, and
changing from full-service properties to limited-service hotels. Although, there had been a
significant annual growth in the number of rooms (supply) available in chain-affiliated hotel
during this period, the demand slightly more than kept pace and occupancy increased (Smith &
Lesure,1999).
The steady improvement in occupancy form its low in 1991 is highly noticeable in 1995.
In 1995, the hotel industry had the best occupancy levels since 1980. This phoneme happened
because the four consecutive years during which demand for lodging exceed the growth in
supply. While demand grew 1 1.3% form 1991 through 1995, lodging supply only expanded
2. 1% during this period. (Glenn, 1995)
11
The lodging industry in the U.S., which bled money for over seven years from 1987 to
1993, had a breakout performance in 1995. In 1996, the industry would earn more than $10
billion, a record, as occupancy and rates went up and costs went down.
Rising occupancy rates in the airline, hotel, and car rental industries in 1996 are driving
the cost increase. Corporate American would spend $5- $6 million more for travel and
entertainment this year. Average domestic corporate hotel rates would increase 5% -6% as
occupancy rates climb above 67% in 1996. Although demand us outpacing supply, occupancy
rates will rise at a slower rate than in 1994 as hotel increase building place. Electronic commerce
options will start to play a significant role in streamlining business travel services in coming
years. (Anonymous, 1996).
Many U.S. cities have occupancy rates exceeding 70%, reflecting the industry improved
vitality. With its growing emphasis on the themed destination hotels that are suitable for the
whole family, New York City, Chicago, San Francisco are especially strong market. In 1996,
several factors have contributed to the industry's reversal in fortunes. Favorable currency
exchange have encouraged foreigners to travel to the U.S. Corporations have loosed their purse
strings, resulting in greater business travel. And families are traveling again on their vacations. It
is this last trend that has spurred the hospitality industry to develop products geared toward
family travel (Cook, 1996)
Occupancy rates at all hotel categories with U.S. hotel will decline in 1998 compared to
1997. Although overall U.S. hotel occupancy will drop from 64.5 percent in 1997 to 63.6
percent in1998, relatively steady demand for hotel rooms combined with growth in average daily
room rates (ADR) are greater than that needed to offset declines in occupancy and will bring the
lodging industry another year ofrecordprofits.
12
Although room occupancy declined in 1998, the year was still profitable for the lodging
industry, because of increased room rates and tight control ofoperating expenses (Randell &
Lesure, 1999). The following are some of the positive and negative factors that are likely to
influence the US lodging facilities: a. Hotel occupancy levels are at historically high level in
many area of the country, b. The recovery of the lodging industry has sparked renewed interest in
hotel development, c. As lenders vie for a greater participation in the hotel industry, money is
now becoming more available for the development ofmid-rate loading facilities (Rushmore &
Goldhoff, 1998).
From 1990 to 1998 the average hotel in PKF'S survey has increased profit by7.2 percent,
and is 24 percentage points ahead of the inflation rate for those eight years. The stock market
took a brief, but steep dip late in 1998. That drew attention to concerns about corporate profit
and caused a ripple in the formerly strong consumer confidence. To ensure that profit stayed
strong, corporations examined costs and many of them trimmed their travel budget. Solid
management and cost control might be the secret to profit in 1999 (Glenn, 1999).
Hotel occupancy
Hotel occupancy rates are one of the most frequently maintained and closely monitored
records kept by individual hotels (Marries, 1992). They enable the identification of trends and
fluctuations within the industry, and provide a sensitive barometer of the fluctuating fortunes of
individual hotels.
Although sales are closely related to profitability, occupancy rates are not a precise
indicator ofprofit levels (Meidan, 1984). High occupancy levels may be achieved at the expense
ofheavy price discounting. In the face of low occupancy levels, the high fixed costs involved in
13
hotel operations frequently prompt substantial short-run price cuts to gain at least some revenue
from potentially unsold and totally perishable capacity(Middleton, 1994)
By differentiating hotel type, a comprehensive, concise and detailed monitoring of
occupancy performance can be highlighted for individual hotels for different hotel types and for
regional grouping hotels. An important information base is provided for hotel managers
concerned with the identification and implementation of targeted marketing initiatives to
improve their hotel's occupancy performance. The results will also be of interest to those
concerned more generally with performance of the hotel and tourism industries at the regional
and national level.
Occupancy performance analysis should be regarded as an essential input into marketing
of all hotels. It needs to be included in the process ofmarket analysis to identify the strengths
and weakness in the past and current performance ofhotels, and threats and opportunities they
face in the market place for different types of customers. The positioning of a hotel in
occupancy performance space, and comparisons with national, regional and similar hotel
performance norms, should facilitate this process and provide a vital input into the development
ofmarketing plans. A more precise and effective basis formarketing, however, would be
provided if the observed occupancy performance of a hotel could be compared, not with
industry, regional ,or hotel type norms, but with its expected performance, given its own
particular situation, circumstances and characteristics (Douglas & Robin, 2000).
By comparing actual occupancy rate to natural rates (long -run stabilized occupancy
rates), a development gap can be estimated in both relative terms, as "occupancygap"
in
absolute terms as a number of rooms. Based on the Smith Travel research data from 1987
through 1998, the natural occupancy rate for the United States is 62.9%, and its long-run
14
occupancy gap is 0.8%. This means the long run occupancy rate over the period of 1987 to 1998
was 0.8% above the natural rates. Expressed differently, the U.S. has a long -run "roomgap"
of
approximately 51,000 rooms. By this analysis, it showed that 51,000 rooms could be added to
the supply to meet growing demand. (deRoos, 1999).
International Tourism
International tourism will expand at a rate of about 3.7% annually in the 1990s, and
between three and four percent for the first decade of the next century. Two years ago before the
GulfWar, theWTO predicted international tourism in the 1990s to grow over 4 % per year.
Tourism can resist recession but it weakens when it comes to political instability, social
problems and terrorism (Silverstein, 1992).
International tourism will triple to 1.6 billion tourists in 2020 from 595 million tourists in
1996, and the United Sates will be the second most popular destination. Tourism will not only be
the world's biggest industry, it will be the largest the world has ever seen, according to Tourism:
2020 Vision, a study issued recently by theWorld Tourism organization. (Seal, 1998)
"Over the last three decades, tourism has been growing at a very highrate,"
said Enzo
Paci, WTO statistics chief and the study's author. "There is nothing to indicate this is going to
slow down. There are more and more people around the world who have not only the means but
also the desire to travel. On the other hand, we have a very strong increase in technology- the
transport and information which allow people totravel"
(Seal, 1998, p.69)
In addiction to facilitating travel, theWTO report said technology enhances the
psychological desire to travel because it produces personal isolation, which in turn increases the
craving for human connections. Tourism, by its nature, is probablyone of the best answers to
people seeking the human touch.
15
U.S. tourism industry is doing the right things. For example, it has already begun
marketing to awakened markets in South American countries, who are experiencing tremendous
growth and already beginning to send an increased number of tourists to the United State. This
marketing strategy shows theUS, tourism industry has already grasped the need to diversify into
new market segments (Seal, 1998).
By 2020, outbound travel from East Asian and Pacific counties will quintuple from its
current level, reaching 462 million trips a year, according to the report. Long-haul travel from
those regions will grow 6.2 percent a year, with Europe and the Americas continuing as the main
destinations ofAsian tourist (Seal, 1998). That means American hoteliers will need to cope with
catering to and satisfying the divergent tourist tastes ofboth Asian andWestern tourist. Catering
to an Asian market is particularly worthwhile since Asian tourists are high-spending. They are so
much farther away than other tourists from most destinations, so they spend a lot ofmoney and
time on transportation and they tend to stay longer.
Even as the volume ofAsian tourists continues to grow, however, Germany will maintain
will its position as theNo.l producer of trips abroad. The buoyancy of the German economy, as
well as the generally high cultural level of its people, accountfor this preeminence (Seal, 1998).
Wanted: more tourists
United Sate prides itselfon maintaining a global competitive edge in many areas. But it
fails badly in attracting international visitors. The U.S. is allowing everymodern country in the
world to speed past the U.S. with their commitments to international tourism campaigns, enticing
visitors by the millions to travel to their countries.
U.S. share of international tourism has plummeted 1.6%, from 9.4 % share to just 7.8 %,
thereby forfeiting $57.3 billion and 230,000American jobs just in five years. How much does
16
the United Sates spend annually to promote international tourism, one of the world's fastest
growing industries? Zero. Other industrialized countries, France, for example, spends $73
million, with Spain and the United Kingdom each allotting $79 million. (Norman, 1998)
At 1995, White House Conference on Travel and Tourism, members of the travel
industry gathered to focus on a national travel and tourism strategy, Perhaps the most important
result was the creation ofprivate-sector-managed, government-sanctioned U.S. National Tourism
Organization to grow the national's 96 billion in bound international travel market (Norman,
1998).
International tourism is an often overlooked contributor to U.S. nation's economy. While
international visitors represent less than 5% of all travelers in the United States, they generate
almost 20% of all tourism revenues and produce over $10 billion in federal, state and local tax
revenues. Tourism has also become one of the country's largest employers, directly employing 7
million Americans and generating a total travel related payroll of $127.9 billion, spread through
out every region of the country (Norman, 1998)
How guests choose hotels?
A hotel's core offerings, along with price, amenities and loyalty programs, account for
80% of the hotel selections criteria for business travelers. These travelers tend to prefermid-
range hotels for 41% of their trips. For mid-range hotels, business guests consider location and
amenities first, then price. When choosing upscale hotels, price is the most important selection
criterion (Watkins, 2003).
Leisure travelers choose economy hotels for 47% of their trips. In that segment, amenities
are most critical to guests. Price becomes a more important issue as travelers moved up the
segment scale and is the most important value driver for both mid-range and upscale hotels.
17
Travelers are willing to pay more for improving security in hotels. On average, business travelers
say they are willing to pay $ 7.73 in ADR for a more secure property. Leisure travelers will pay
$10.75 (Watkins, 2003).
Firms need to understand their own distinctive competencies and their operational
strengths and limitations and choose the product/ service delivery strategy with their win
capabilities and overall direction.
Marketing your community
In early 90s, there was a growing trend in the United States "mini-vacations"
trips that
last no more than three days. Mini-vacations typically involveshort- distance trips during which
travelers often remain within their home state. Consequently, it was important for destination
marketing organizations (e.g. tourism and visitor boards) to gain a better understanding of the
needs and wants of the in-state tourist market.
Market segmentation is a fundamental prerequisite for effective marketing. Several
researchers have suggested the use ofdestination-image analysis as a way to segment the tourist
market. Such studies indicate that varying perceptions of the tourist destination held by tourists
form different marketplaces should be considered in tourism- marketing efforts. Tourists make
decisions on places to visit based on the images, beliefs, and perceptions they hold of the
destination. The objective reality of the destination is not necessarily the determining factor in
the tourists decisions (Chou, Weaver & Kim, 1991).
Importance -performance analysis (IPA) is a effective marketing tool for the destination
marketing organizations (DMOs). IPA considers both the perceived importance ofdestination
attributes and the destination's performance on those attributes, as perceived by visitors. The
following information should be collected: 1. the attributes that attract visitors to the city; 2.
18
visitor's perceptions ofhow well the city performs on these attributes; and 3. therespondents'
demographic characteristics. IPA process can be used by any community consideringtourism-
marketing programs for its mini-vacation market (Chou, Weaver & Kim, 1991).
DOMs should pay attention on: one of the city's largest employers has recently
announced cutbacks and potential lay offs. Overall, as the potential for a declining corporate base
occur, fewer business transactions will take place and commercial interest will decline. Business
travelers will likely seek lodging in either more attractive or alternate locations, which translates
into fewer visitors and overnight stays and less revenue. Other factors, such as events,
advertising, environmental change (nature disasters, war), and political policy will also effect
tourism industry.
After reviewing these materials, it displayed some important messages that the occupancy
rated might not necessary effect hotel rates, the history of the tourism in past ten years and the
important of tourism to U.S.
19
Chapterm
Methodology
This study focused on hotel room rates in New York City, Chicago, San Francisco and
Atlanta. By comparing four major cities hotel room rates (from 1990- 1999) to other factors:
national average hotel rate, foreigner visitors to U.S., unemployment rate, average occupancy
rate and number ofFortune 500 headquarter in the city, this study would provide the companies
and customers the important information on what would influence the hotel rates.
This charter would demonstrate how the analysis be done for the study. By using excel,
correlation analysis and multiple regression analysis would apply to examine the relationship
between the hotel rates and other variables.
Hotel rates Data collecting
It had been the responsibility of the Food, Hotel and TravelManagement program at
Rochester Institute ofTechnology to collect hotel room cost data and various other data in order
to assist the Corporate Travel Magazine in creating the annually published Corporate Travel
Index. Each year from 1989- 1999 the graduate students from food and hotel management
collected the data by telephone & mail survey. Questionnaires were used to collect information
ofhotels room costs at 100 cities. The targets were mid range hotels. All the hotels that were
chosen were originally listed on theSABRE system. Students collect the data and obtain the
average hotel room costs. Data from the 100 cities were then averaged again to derive the
national average ofhotel room costs. The data was published at Corporate Travel Index every
20
year through 1999. The following cities were listed in their appropriate region, and comprised
the top 100 business travel cities in the United Stated according to the US Census Bureau:
Albany, NY
Boston, MA
Hartford, CT
Philadelphia, PA
North
Allentown, PA
Buffalo, NY
New York, NY
Pittsburgh, PA
Baltimore, MD
Harrisburg, PA
Newark, NJ
Providence, RI
Rochester, NY
Stamford, CT
Syracuse, NY
Washington, DC
Adanta, GA
Biloxi, MS
Charleston, WV
Columbia, SC
El Paso, TX
Greensboro, NC
Jacksonville, FL
Little Rock, AR
Miami, FL
New Orleans, LA
Orlando, FL
South
Austin, TX
Birmingham, AL
Charlotte, NC
Corpus Christie, TX
Ft. Lauderdale, FL
Houston, TX
Knoxville, TN
Louisville, KY
Mobile, AL
Norfolk, VA
Raleigh/Durham, NC
Baton Rouge, LA
Charleston, NC
Chattanooga, TN
Dallas, TX
Greenville, SC
Jackson, MS
Lexington, KY
Memphis, TN
Nashville, TN
Oklahoma City, OK
Richmond, VA
Orlando, FL
Raleigh/Durham, NC
Richmond, VA
Roanoke, VA
San Antonio, TX
Sarasota, FL
Savannah, GA
Shreveport, LA
Tallahassee, FL
Tampa, FL
Tulsa, OK
Midwest
Akron, OH
Cleveland, OH
Detroit, MI
Dayton, OH
Madison, Wl
Omaha, NE
Chicago, IL
Columbus, OH
Ft. Wayne, IN
Indianapolis, IN
Milwaukee, Wl
Peoria, IL
Cincinnati, OH
DesMoines, IA
Grand Rapids, MI
Kansas City, MO
Minneapolis,MN
Rochester, MN
Springfield, MO
St. Louis, MO
Toledo, OH
Wichita, KS
Albuquerque, MN
Denver, CO
Las Vegas, NV
Sacramento, CA
Santa Barbara, CA
Spokane, WA
West
Anaheim, CA
Fresno, CA
Oakland, CA
Salt Lake City, UT
San Francisco, CA
Phoenix, AZ
Bakersfield, CA
Honolulu, HI
Portland OR
San Diego, CA
San Jose, CA
Los Angeles, CA
Seattle, WA
Tucson, AZ
21
This study, first, gathered the data from 1989-1999. Second, it reorganized the
data by alphabetic order (Table 1). The table will display hotel rates for each 100 cities form
1990- 1999 into four regions. Lastly, utilize excel to analyze the data. This will demonstrate the
relationship between the hotel rate and other factors.
Variables data
The variables for this study are gathering from the following sources. Using excel, these
variables will be evaluated with hotel rates.
Table 2. Foreign Travel: 1990 to 1999 (in thousands)
Year 1990 1991 1992 1993 1994
Foreign
travel to the
U.S.
36,365 39,363 42,674 47,262 44,753
Year 1995 1996 1997 1998 1999
Foreign
travel to the
US
43,318 46,489 47,754 46,395 48,492
Source: U.S. CensusBureau
Table 3. Unemployment rate- Civilian labor force
Year
Unemployment
Rate
1989
5.3
1990
5.6
1991
6.9
1992
7.5
1993
6.9
1994
6.1
1995
5.6
1996
5.4
1997
4.9
1998
4.5
1999
4.2
Source: U.S. Census Bureau
22
Table 4. Lodging Industry summary: 1990 to 1998
Year Average
Occupancyrate
1990 63.3
1991 60.9
1992 61.7
1993 63.6
1994 65.2
1995 65.5
1996 65.2
1997 64.5
1998 63.6
Source: U.S. CensusBureau
Table 5. Number ofFortune 500 headquarter in the city
Number ofFortune 500
New York San
City Chicago Franciscc) Atlan
1990 43 19 3 7
1991 39 19 4 6
1992 39 19 6 6
1993 35 21 6 6
1994 49 20 6 7
1995 49 17 10 12
1996 47 17 10 11
1997 46 15 8 10
1998 46 15 8 11
1999 46 14 9 11
Source: FortuneMagazines
Correlation analysis
Correlation coefficient is the coefficient that indicates the strength of the association
between any two metric variables. Thesign (+ or -) indicates the direction of the relationship.
23
The value of can range form -1 to +1, with +1 indicating a perfect positive relationship, 0
indicating not relationship, ,an d-1 indicating a perfect negative or reverse relationship.
This study will first present correlation matrix-table to illustrate the intercorrelations
among all variables. Eliminate the weakest relationship that is <0.2. If the correlation coefficient
is above 0.5 but blow 0.6, stepwise method will be applied.
Significance testing
This research will use R and F test in significance testing process. Significance testing of
regression coefficients provides the researchers with an empirical assessment of their true
impact. It determines whether the impacts represented by the coefficients are generalizable to
other samples form this population. In regression analysis, estimated coefficients are specific to
the sample used in estimation. Coefficients can vary form sample to sample. This points out the
need for concerted effort to validate any regression analysis on different samples. In doing so,
researcher must expect the coefficients to vary but the attempt is to demonstrate that relationship
generally holds in other sample so that the results can be assumed to be gerneralizable to any
sample drawn form the population(Hair, Anderson, Ththam & Black, 1998).
Stepwise method
Stepwise estimation is the method of selecting variables for inclusion in the regression
model that starts by selecting the best predictor of the dependent variable. Additional
independent variables are selected in terns of incremental explanatory power they can add to the
regression model. Independent variables are added as long as their partial correlation coefficients
are statistically significant.Independent variables may also be dropped if their predictive power
drops to insignificant level when another independent variable is added to the model (Hair,
1998).
24
After elimination of the weakest variable from correlation analysis, this study will
exercise stepwise method by examining theR2
This step is done by adding in each variable, and
observing the change ofR2
value. In this study, only tests the variable which has correlation
coefficient between 0.5 and 0.6. If the percentage R2change is insignificant, the variable will be
removed from the further analysis.
R is the measurement of the proportion of the dependent variables. The coefficient can
vary between 0 and 1. If the regression model is properly applied and estimated, the research can
assume that the higher R2, the greater the explanatory power of the regression equation, and
therefore the better the prediction ofthe dependent variable.
Multiple regression analysis
Multiple regression analysis is a general statistical technique used to analyze the
relationship between a single dependent variable and several independent variables. Its basic
formulation is: Y=Xi+ X2+. . ..+Xn
To test the hypothesis that the amount ofvariation explained by the regression model is
more than the variation explained by the average (i.e., thatR2
is greater than zero) F ratio is used.
F ratlO jJC regression/01 regression
SSE total /df residual
Where df regression number of estimated coefficient (including intercept)- 1
dfresiduai= simple size-number of estimated coefficients (including intercept)
In regression analysis, this study will first perform the F test. If the F ratio greater than
the Fa yield from table F Distribution (Table 6), it means this multiple regression model is
statically significant in a given significantlevel (a). In this study, a level is set to be 5 %.
In conclusion, this study will point out thesignificant variable to hotel rates. Moreover,
this study will offer regressionmodel for each city for prediction of its hotel rates.
25
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Chapter IV
Discussion
Finally, form tables above, one could perceive the results of the relationship between
hotel rates and variables for each city. Here are the variables: Y represents the hotel rates in that
city; Xi represents National hotel rates; X2 represents Foreigners visitors to U.S., X3 represents
Unemployment rates; X4 represents Hotel occupancy rate; and X5 represents number of Fortune
500 headquarter in the city.
New York City
This study concluded that the equation forNew York City was: Y=127. 13+1 6IX1-
O.OOO7X2-6.85X3. Hotel rates in New York City were highly related to national average rate
(table 7. 1). This indicated that generally the trend ofNew York City hotel rates followed other
cities in U.S. In comparison with other cities (table 7. 1, table 8.1, table 9. 1& table 10. 1), the
number ofFortune 500 headquarter had a weakest relation withNew York City's hotel rates.
Therefore, corporate travel could be one potential area for the city to improve their hotel
business. Having more business base in the city would encourage more business travel and raise
the hotels performance inNew York City.
Chicago
This study concluded that the equationfor Chicago was: Y=257.59+1.89X1-0.003X2-
8.456X3-5.446X5. Hotel rates in Chicago were highly related to Fortune 500 headquarter (table
8. 1). This might also explain why the city hotel rates have highest correlation with
unemployment rates compare to other city. Chicago hotel industry strongly depended on
business travel. The city tourism should continue having more business conferences and creating
36
more business opportunity in the city. The average occupancy rate had the weakest relationwith
Chicago than other three cities. This could be a sign of supply exceeded demand in this area.
San Francisco
This study concluded that the equation for San Francisco was:Y=-13.44+1.922Xi-
0.0002X2-2.55X3. Hotel rates in San Francisco were highly related to national average (table
9.2). The national average rate had strongest relationship with San Francisco than other three
cities. This could interpret as one can use San Francisco's hotel performance as a scope to gain a
big picture ofUS hotel industry. The foreigner visitors to U.S. had highest correlation with San
Francisco among these four cities. It confirmed that the city's tourism was highly depended on
international travel. Therefore, how to attract more international visitors was essential to the city
tourism.
Atlanta
This study concluded that the equation for Atlanta was: Y=56.55+ 1.55Xi+ 0.0003X2+
2.35X3. Hotel rates in Atlanta were highly related to national average (table 10.1). In addition,
the city correlation matrix was verysimilar to San Francisco. It would also be beneficial for
Atlanta to draw more international visitors to the city.
Recommendations
This thesis provided the direction ofhotel room rates analysis. One limitation of the
study was that it didn'tconsider all the economic factors and other unexpected factor such as war
or disaster. Further study ofother factors such as theinflation rate, customer expenditure index,
the social crime, and the tourism policy of the city would fill out the gap of this study.
This study only focused onfour major cities of four regions and 10 observations of each
variable. The limited sample size would affect the accuracy of the statistic analysis. In order to
37
provide better fit model ofhotel room rates in United States, I recommend larger sample and
extended time of the study. I believed that one could develop a very useful hotel marketing tool
by utilizing this study as a frame and combining above recommendations.
38
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