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Journal of Hospitality & Leisure Marketing, Vol. 17(1–2) 2008
Available online at http://www.haworthpress.com
© 2008 by The Haworth Press. All rights reserved.
doi:10.1080/10507050801978265
121
WHMM1050-70511541-0897Journal of Hospitality & Leisure Marketing, Vol. 17, No. 1-2, Jul 2008: pp. 0–0Journal of Hos pitality & Leisure Marketi ng
Customer Reviews of Hotel
Experiences through Consumer
Generated Media (CGM)
Miyoung Jeong and Myunghee Mindy JeonJournal of Hos pitality & Leisure Marketi ng
Miyoung Jeong
Myunghee Mindy Jeon
ABSTRACT. As consumer generated media (CGM) are burgeoning
online marketing techniques as a form of interpersonal and informal
communications, many hotel guests have a chance to provide their can-
did and voluntary reviews of hotel experiences through these channels.
However, little research has been documented to evaluate the overall
theme of guests’ reviews posted through CGM such as Tripadvisor.
com. This study explores how consistent the posted reviews (i.e., com-
pliments and complaints) were with the expected level of service and
room rate. Examining guests’ reviews of hotels in New York City
posted on TripAdvisor. com, this study attempts to uncover generaliz-
able suggestions for hotel management. Results of this study indicated
that value was one of the key predictors for guest satisfaction, which
leads to return intentions. Regardless of hotel classes and average daily
rate (ADR), location appeared to have the highest mean value among seven
performance attributes. Obviously, hotel classes (i.e., star ratings) and
ADR appeared to influence the relationships of selected hotel
performance attributes with both overall guest satisfaction and return
Miyoung Jeong, PhD, is Associate Professor, Hotel, Restaurant, and
Institution Management, Iowa State University, Ames, IA.
Myunghee Mindy Jeon is a Doctoral Student, Hotel, Restaurant, and
Institution Management, Iowa State University, Ames, IA.
Address correspondence to: Miyoung Jeong, PhD, Iowa State University,
5 MacKay Hall, Ames, IA 50010 (E-mail: mjeong@iastate.edu).
122 JOURNAL OF HOSPITALITY & LEISURE MARKETING
intentions. Some managerial implications surrounding this new online
marketing media are discussed.
KEYWORDS. Consumer generated media, online hotel review, elec-
tronic word-of-mouth, guest review
INTRODUCTION
Consumer generated media (CGM) is one of the fastest-growing chan-
nels of interpersonal and informal communications. The Internet is pro-
viding the momentum for the accelerated growth in popularity of these
new word-of-mouth (WOM) communications. Up until now, WOM has
been a widely used channel of interpersonal communication that allows
consumers to share information and opinions, directing buyers towards
and away from specific products, brands, and services (Hawkins, Best, &
Coney, 2004). The WOM communication channel is becoming more
intensified with the help of the advancing information technology that is
bringing people into the virtual environment from the physical environ-
ment, the phenomenon called electronic WOM (eWOM) (Litvin,
Goldsmith, & Pan, in press) or online WOM (oWOM) (Fong & Burton,
2006). By participating in different forms of eWOM, individual consum-
ers become powerful opinion leaders who exert influences on one another
in finding right products and services (Litvin, Goldstein, & Pan, in press).
Given the marketing power of consumers’ online communications, the
hospitality industry needs to take immediate action to become part of vir-
tual interaction communities and listen to how the industry performs from
the eyes of consumers.
The hospitality industry is increasingly dependent upon WOM by
enabling customers to share their consumption experiences with prospec-
tive customers and service providers through various online communica-
tion channels. In particular, when purchasing a new product or service,
customers tend to turn to this mode of communication channel as a more
reliable source of information (Folkes, 1984). In that sense, customers’
voluntary and liberal reviews that are open to the anonymous public on
the Internet are powerful avenues of WOM, due to their capabilities to
spread to a multitude of prospective customers in a few clicks. Today, cus-
tomers obtain travel-related information from the Internet more often than
ever before and they also collect others’ first-hand experiential reviews of
Miyoung Jeong and Myunghee Mindy Jeon 123
particular hospitality offerings before making their final purchase deci-
sions (Pitta & Fowler, 2005). In the lodging industry, for example, numer-
ous sources indicate that the Internet is increasingly used not only as a
medium for making reservations but also as a channel of open forums
about customers’ lodging experiences (Pitta & Fowler, 2005). The con-
tinuing success of online communication sites (e.g., TripAdvisor.com,
wheretostay.com, Zoomandgo.com, etc.) is indicative of widespread use
of these sites by customers and, consequently, by managers who are con-
scious of market responses to their company’s performance. Moreover,
the “voluntary” reviews posted on these sites are believed to be much
more valuable and trustworthy than typical survey-based customer
responses in that they are based on the customer’s free and voluntary
opinions about what he or she experienced and that they are neither elic-
ited nor framed by the company or researchers (Stieghorst & Ridder,
2004).
While the significance of these online communication sites is expected
to grow every day as a primary source of information for both company
performance reviews and customer purchase decisions, little research has
been conducted to understand the validity of the information posted on
these sites. To the extent which these Websites provide valid information
to both prospective customers and hospitality management, a systematic,
public feedback system can be established through these sites to aid hospi-
tality companies in improving their future performance. To respond to
such research needs, especially in the hotel industry, this study undertook
an exploratory step to examine the validity of the reviews posted on these
sites. In particular, the study focused on understanding how consistent the
posted compliments and complaints were with the expected level of ser-
vice and room rate. More specifically, the objectives of this study were to
(i) assess whether or not the hotel industry as a whole met guest expecta-
tions framed by a widely adopted service rating system (i.e., Mobile Star
Rating system), (ii) determine whether guests’ evaluations of hotel offer-
ings differed by hotels’ operational or business indicators such as owner-
ship, hotel class, ADR, and popularity index, (iii) identify key attributes
that affected guests’ satisfaction and return intentions, and, thereafter, (iv)
develop operational recommendations for hotel management.
TripAdvisor.com as a Form of CGM in the Hospitality Industry
CGM are a collection of online media that contain customer-created
information and that are made available to other online users via interactive
124 JOURNAL OF HOSPITALITY & LEISURE MARKETING
technology applications (Starkov & Price, 2006). Included in CGM are
various forms of communication modes such as discussion boards, blogs,
social network sites, customer review sites, the target company’s
customer testimony pages, and many other independent companies’
online forums covering a vast number of different products and services
(Chipkin, 2005/2006). With varied formats of CGM, the hospitality
industry is becoming more open minded about listening to customers’
unfiltered and candid experiences with its offerings. In doing so the
industry immediately addresses issues and acts appropriately to establish
a lifelong relationship with its customers (Starkov & Price, 2006).
TripAdvisor.com has been positioned as one of the leading global
travel information advice Websites, based on its database containing
independent customers’ testimonies and evaluations of their real experi-
ence with hotels and other travel-related products (TripAdvisor.com,
2007). Many unique characteristics and services are available on Tripadvisor.
com to help its customers make better and more accurate travel plans in
regard to their needs and budgets (Tripadvisor.com, 2007). A variety of
filtering services selectable on the site are designed to help customers easily
narrow down their hotel selections and sort hotels by price, location, and
level of service (e.g., star rating). If the customer wants to find one of the
most popular 3-star hotels in the Back Bay area of Boston with room rates
between $100 and $200, for example, search results would pop up within
a second with up-to-date room rates and a brief overview of the hotel that
includes its address, photos, level of service, number of rooms, typical
room rates, and a QuickCheck for an immediate hotel reservation through
partnering travel intermediary sites. Guest reviews of the hotel are fea-
tured services helping prospective guests choose a hotel with ease and
confidence while planning a future trip. Based on both the quantity and
quality of posted reviews on the site, a popularity index shows a ranking
of all listed hotels as well. More than 135,000 hotels worldwide are com-
pared via more than one million reviews in this ranking (TripAdvisor.com,
2007). On this site, reviewers provide open-ended comments and ratings
of the hotel based on a set of attributes including room, value, cleanliness,
location, check-in and check-out, service, and business service. In addi-
tion, they also rate their overall satisfaction with the hotel and intentions
to return to the hotel.
Despite TripAdvisor’s unique and various features as a hub for
hospitality-related reviews, there are controversial issues related to its
authenticity and creditability (McGrath & Keenan, 2007). In particular,
controversy often arises if a destination has few accommodation options
Miyoung Jeong and Myunghee Mindy Jeon 125
and extremely opposite reviews about the accommodation. It would be a
tough job for a review Website such as TripAdvisor to identify fraudulent
reviews out of the plethora of reviews posted. However, according to the
recent report by Marc Charron, a senior executive of TripAdvisor (McGarth &
Keenan, 2007), TripAdvisor has been implementing various techniques to
improve its integrity and credibility, such as the use of sophisticated detect-
ing algorithms, spot checks, and readers’ abuse investigation. The com-
pany’s continuous efforts for further enhancement like this make the review
site a valuable and reliable source. A survey by TimesOnline indicated that
82% of public users trust reviews posted on a travel review site like Tri-
pAdvisor.com (McGarth & Keenan, 2007).
It is logical to expect that, dependent upon the popularity index of a desti-
nation hotel, the nature and frequency of reviews about a hotel are expected
to be different and they are likely to determine, at least partially, future
demands for the hotel. Bearden and Oliver (1985) reported that both compli-
ments and complaints played key roles in determining customers’ future atti-
tudes and purchase behaviors. Cadotte and Turgeon (1988) analyzed the
frequency and type of compliments and complaints received by lodging exec-
utives from their customers in order to identify key satisfiers and dissatisfiers.
Typically, attributes such as helpful attitudes of employees, cleanliness and
neatness of the property, service quality, employee knowledge, spaciousness
of the property, and quietness of the surrounding were key satisfiers from the
perspectives of hotel guests. Meanwhile, among most frequently received
complaints were attributes such as room rate, meals or other services, speed
and quality of service, parking availability, employee knowledge and service,
quietness of the surrounding, and availability of accommodations. Even
though these compliment and complaint attributes did not represent the
customers’ complete experience with a hotel, they shed light on the key
performance attributes that were generalizable across lodging properties.
Although there is almost a 20-year gap between Cadotte and Turgeon’s
study (1988) and the present study, the key performance attributes on
which hotel guests express their compliments and complaints are much
alike. Their study found that hotel guests frequently raised compliments
and complaints on employee service, cleanliness, value, and other avail-
able facilities of hotels. In comparison, TripAdvisor.com has been evalu-
ating hotels’ offerings by using seven performance attributes such as
room, value, cleanliness, location, check-in & check-out, service, and
business service. An underlying assumption in this case is that guests’
ratings on these seven attributes would largely determine their overall
satisfaction with the hotel and their intentions to return to the hotel.
126 JOURNAL OF HOSPITALITY & LEISURE MARKETING
Industry’s Service Rating System: An Example of Mobil Travel
Guide’s Star System
The hotel industry has widely adopted standard rating systems such as
Mobil Travel Guide’s Star system and American Automobile Associa-
tion’s (AAA) Diamond system to distinguish levels of service across
properties. These two systems are nearly parallel in their evaluation crite-
ria and processes (Nobles, 2004). Since TripAdvisor.com adopts the Star
system to indicate the level of each hotel’s service, this study briefly
reviews the Star rating system.
The Star rating system assesses availability and quality of hotels’ phys-
ical facilities, service, atmosphere, and price in a consistent and credible
manner. Generally, the system classifies all hotels into five different cate-
gories from 1 star to 5 stars to signify the level of service and perquisites a
guest can expect. Mobil Travel Guide defines each of the five ratings as
follows (Mobil Travel Guide, 2005):
• The 1 star rating is for limited service hotels/motels that are consid-
ered clean, comfortable and reliable establishments.
• The 2 star rating is for hotels/resorts that are considered not only
clean, comfortable, and reliable establishments but they also have
expanded amenities, such as a full-service restaurant on their
property.
• The 3 star rating is for hotels/resorts that are well-appointed, with a
full-service restaurant and expanded amenities including a fitness
center, golf course, tennis courts, 24-hour room service, and optional
turndown service.
• The 4 star rating is for hotels/resorts/inns that provide a luxury expe-
rience with expanded amenities in a distinctive environment. Ser-
vices may include, but are not limited to, automatic turndown
service, 24 hour room service, and valet parking.
• The 5 star rating hotels/resorts/inns provide consistently superlative
services in an exceptionally distinctive luxury environment with
expanded services. Attention to details is evident throughout the
properties from the bed linens to staff uniforms.
As mentioned by Nobles (February 1999), the 1, 2, and 3 star-rated
establishments focus more on the physical facilities, while the 4 and 5
star-rated establishments do more on intensive, high level services. Thus,
the first three level hotels pay more attention to clean, well-maintained,
Miyoung Jeong and Myunghee Mindy Jeon 127
and well-managed accommodations in a safe and secure environment
with minimum requirements for hospitality and professional services. The
4 and 5 star properties particularly emphasize the scope and quality of ser-
vices offered to their customers with maximum requirements for décor,
furnishings, and other physical attributes. The consistent delivery of ser-
vice as well as its quality is critical for distinguishing between 3 and 4 star
hotels.
METHODS
This study chose Tripadvisor.com to analyze guest reviews of hotels in
New York City (NYC). The reason to choose NYC as a destination for
this study was that NYC is a world renowned metropolitan city where
both business and leisure traveler markets equally attract hotel guests all
year around. Due to the frequent updates of the Website, this study set the
time frame to collect guests’ reviews from July 19 through December 31,
2006. At the point of the data collection, a total of 324 hotels were listed
on TripAdvisor.com. (data were retrieved from http://www.tripadvisor.
com/Hotels-g60763-New_York_City_New_York-Hotels.html).
TripAdvisor.com offers two different formats for guest reviews of a
hotel: written comments and ratings of nine attributes (room, value,
cleanliness, location, check-in & check-out, service, business service,
guests’ satisfaction, and intentions). Through the careful comparison
between written comments and ratings, it is believed that the ratings of
each attribute are most likely to be reflected in the guest’s written com-
ments. Therefore, this study focused on the quantitative ratings of each
attribute by minimizing the authors’ subjective judgments on the written
comments.
Two different analytical approaches were used in this study. First,
hotels in NYC were evaluated separately by their ownership (i.e., chain
vs. independent), hotel classes (i.e., 1–2 star, 3 star, and 4–5 star), number
of rooms, average room rates (ADR), and the popularity index (i.e., most
popular, moderately popular, and least popular). The study analyzed guest
ratings of each eligible hotel in order to define key satisfiers of hotel per-
formance attributes. Aggregate mean scores of the nine attributes, includ-
ing room, value, cleanliness, location, check-in & check-out, service,
business service, guests’ satisfaction, and intentions were calculated for
comparisons. Secondly, the relationships of the eight attributes with
guests’ return intentions to the hotel were evaluated. The eight attributes
128 JOURNAL OF HOSPITALITY & LEISURE MARKETING
were measured with a 5-point scale, anchored from 1 = strongly disagree
to 5 = strongly agree, while the guest’s return intentions were measured
with a 4-point scale, ranged from 1 = no way, 2 = probably not, 3 = most
likely, and to 4 = absolutely.
Descriptive analyses were conducted to better understand the overall
characteristics of hotels. The t-test was employed to determine major per-
formance attributes of guests’ overall satisfaction which distinguished
independent hotels from chain affiliated hotels. Next, a series of ANOVA
tests was conducted to assess whether hotels’ operational/business indicators
such as hotel class, ADR, and popularity index made differences in
guests’ evaluations of hotel offerings, guests’ satisfaction, and their
return intentions. Due to the lack of homogeneity of variances of the
sample (p > .05), Bonferroni’s multiple group comparisons were selected
and employed to examine whether there existed differences between the
sub-groups of each operational/business indicator in all nine attributes.
Finally, regression analyses were used to understand key predicting
attributes of guests’ overall satisfaction and return intentions.
RESULTS
As of January 16, 2006, a total of 324 hotels in NYC were listed on
Tripadvisor.com, including unranked 20 hotels. Of the 304 hotels ranked
by the popularity index, 139 hotels containing more than 100 guest
reviews were selected to increase generalizability of the study’s findings.
These 139 selected hotels represented approximately 46% of all ranked
hotels on the Website in NYC.
Table 1 summarizes operational and business characteristics of the 139
hotels. Of the 139 hotels, 83 (60%) were classified as independent estab-
lishments. Approximately 34 hotels (29%) were categorized as upscale
and/or luxury properties. Middle class hotels (i.e., 3 star hotels) outnum-
bered both economy and upscale/luxury hotels. Ninety hotels (66%) had
fewer than 350 guest rooms and more than 94 hotels (67%) charged a
room rate higher than $270 (the average room rate was $322). Based on
the popularity index, 69 hotels (50%) were regarded as most popular
hotels ranked within 100th place, 42 hotels (30%) were moderately popu-
lar hotels ranked between 101st and 200th, and the remaining 28 hotels
(20%) were the least popular hotels ranked between 201st and 300th.
More popular hotels tend to generate more reviews than less popular
hotels in the NYC case.
Miyoung Jeong and Myunghee Mindy Jeon 129
As a result of t-test, there existed significant mean differences in
rooms, check-in & check-out, service, and business service by the hotel’s
ownership (p < .05) (see Table 2). Chain-affiliated hotels performed bet-
ter in these four attributes than independent hotels, which indicated that
chain-affiliated hotels tended to comply more with the standard operating
procedures and provide better service for their guests, as compared to
TABLE 1. Hotels’ operational and business characteristics
Item / Variables Categories Number of Hotels Percent (%)
Ownership (n = 139) Chain 56 40.3
Independent 83 59.7
Star rating (n = 116) 1–2 star 23 19.8
3 stars 59 50.9
4–5 stars 34 29.3
Number of Rooms (n = 137) Fewer than 150 42 30.9
150–350 48 35.3
More than 350 46 33.8
Room Rates (n = 139) Lower than $270 45 32.4
$270–$360 46 33.1
Higher than $360 48 34.5
Popularity Index (n = 139) Most popular 69 49.7
Moderately popular 42 30.2
Least popular 28 20.1
TABLE 2. Different mean scores of nine attributes by ownership
Performance attributes Chain hotel (50)
Mean (std.)
Independent hotel
(85) Mean (std.)
t-value
Rooms
a
3.82 (0.39) 3.50 (0.82) 2.51*
Value
a
3.75 (0.69) 3.63 (0.73) 1.01
Cleanliness
a
4.04 (0.66) 3.86 (0.79) 1.42
Location
a
4.44 (0.32) 4.36 (0.44) 1.22
Check-in & Check-out
a
3.91 (0.53) 3.66 (0.67) 2.33*
Service
a
3.93 (0.57) 3.67 (0.68) 2.35*
Business Service
a
3.72 (0.64) 3.40 (0.46) 2.68*
Satisfaction
a
3.84 (0.73) 3.35 (0.84) 1.88
Return Intentions
b
3.29 (0.50) 3.15 (0.64) 1.51
*p < .05.
a
Measured on a 5-point scale (1 = bad; 5 = good).
b
Measured on a 4-point scale (1 = no way; 2 = probably not; 3 = most likely; and
4 = absolutely).
130 JOURNAL OF HOSPITALITY & LEISURE MARKETING
independent hotels. Chain-affiliated hotels in NYC appeared to charge
higher room rates and to have more rooms than independent hotels
(p <.05).
According to the results of ANOVA, the popularity index of TripAdvisor.
com seems to work well with the star rating system from guests’ perspec-
tives. The most popular hotels (i.e., ranked within top 100 hotels)
appeared to be at least 3 star hotels, while the least popular hotels (i.e.,
ranked lower than 200
th
place) were classified as either 1 or 2 star hotels
(p < .001). We assumed that there might be a distinct performance gap
between the two groups (1 and 2 star hotels vs. 3, 4, and 5 star hotels) in
light that, according to the results of Bonferroni’s multiple group compar-
isons, there also were significantly different mean scores in all nine
attributes by the groups of the popularity index (p < .05) (see Table 3).
The most popular hotels seemed to maintain clean properties, offer rooms
in a working order, and provide better service for their guests, which led
to higher mean scores for satisfaction and return intentions. The least pop-
ular hotels (below ranking 200) seemed to perform undesirably on all the
attributes, as indicated in the significantly low mean scores, as compared
to those of popular (within ranking 100) and moderately popular hotels
(between ranking 101 and 200). Interestingly, regardless of hotels’ popu-
larity index, location of the hotel appeared to have the highest mean score
TABLE 3. Different mean scores of nine attributes by the popularity index
Performance
attributes
Most popular (69)
Mean (std.)
Moderately
popular (42)
Mean (std.)
Least popular
(28) Mean (std.)
F
Rooms
a
4.17 (0.39) 3.46 (0.39) 2.51 (0.62) 142.24**
Value
a
4.15 (0.35) 3.51 (0.35) 2.75 (0.61) 120.07**
Cleanliness
a
4.42 (0.34) 3.80 (0.40) 2.90 (0.73) 111.08**
Location
a
4.56 (0.28) 4.31 (0.35) 4.10 (0.53) 17.44**
Check-in &
Check-out
a
4.18 (0.36) 3.62 (0.37) 2.95 (0.53) 95.96**
Service
a
4.21 (0.36) 3.63 (0.33) 2.85 (0.48) 133.25**
Business Service
a
3.94 (0.64) 3.40 (0.46) 2.47 (0.64) 61.92**
Satisfaction
a
4.25 (0.34) 3.49 (0.27) 2.59 (0.61) 185.20**
Return Intentions
b
3.62 (0.23) 3.09 (0.27) 2.35 (0.56) 150.63**
**p < .01.
a
Measured on a 5-point scale (1 = bad; 5 = good).
b
Measured on a 4-point scale (1 = no way; 2 = probably not; 3 = most likely; and
4 = absolutely).
Miyoung Jeong and Myunghee Mindy Jeon 131
among nine attributes, indicating that most hotels in NYC were located in
good proximity to other tourism or business-related areas.
Based on hotel class, results of ANOVA indicated that there existed
significantly different mean scores in eight attributes except for value
(p < .05) (see Table 4). The hotel class was categorized into three groups,
in a sense that the 1 and 2 star-rated establishments focused on hotels’
physical conditions (Group A), the 3 star-rated ones offered full services
(Group B), and the 4 and 5 star-rated ones emphasized the consistency of
service delivery and high quality (Group C) (Nobles, 1999). Of the three
groups, hotels in Group A consistently showed significantly lower mean
scores (2.96 – 4.17) than those in Group B (3.20 – 4.44), and hotels in
Group B consistently showed significantly lower performance scores than
those in Group C (3.35 – 4.49) on all nine attributes. As the results of
Bonferroni’s multiple group comparisons indicated, however, only one
attribute, rooms, appeared to have significant differences among three
groups. Between Groups A and C, cleanliness, check-in & check-out,
business service, satisfaction, and return intention showed significant dif-
ferences (p < .05). However, there were no significant mean differences
in location and service between Group B and Group C but between Group
A and Group C (p < .05). Consequently, it is believed that higher star-
rated hotels resulted in more favorable guest perceptions than their lower
counterparts.
TABLE 4. Hotel performance by hotel classes
Attributes 1–2 (23) 3 (59) 4–5 (34) F Bonferroni’s Multiple
Range Test
a
Rooms 3.18 3.57 4.10 12.35** A,B, C**
Value 3.43 3.64 3.82 2.38 ABC
Cleanliness 3.53 3.93 4.24 7.24** A,C**
Location 4.17 4.44 4.49 5.20** A,BC**
Check-in & Check-out 3.51 3.82 3.99 5.31** A,C**
Service 3.45 3.80 4.07 7.91** A,BC**
Business Service 3.15 3.48 3.76 4.30* A,C*
Satisfaction 3.29 3.68 4.02 7.45** A,C**
Return Intentions 2.96 3.20 3.35 3.19* A,C*
*p < .05; **p < .01.
a
A = 1–2 star hotels; B = 3 star hotels; C = 4–5 star hotels. The hotel groups with a
significant mean difference were separated by a comma; those without a significant mean
difference were not.
132 JOURNAL OF HOSPITALITY & LEISURE MARKETING
With regards to hotels’ ADR, this study classified hotels into three
groups: Group 1 with ADR lower than $270; Group 2 with ADR
between $270 and $360; Group 3 with ADR greater than $360. All three
groups showed significantly different mean scores in eight attributes
except for value (see Table 5). According to Bonferroni’s multiple
group comparisons, two attributes, rooms and service appeared to have
significantly different mean scores among all three groups (p < .05).
Dependent upon ADR, hotels in NYC seemed to have better room
amenities and quality rooms and provide high quality service. Location,
satisfaction, and return intentions were unique attributes that distin-
guished between Group 1 and Group 3, whereas there existed signifi-
cantly different mean scores between Group 1 and Group 3 for
cleanliness, check-in & check-out, and business service (p < .05). Nota-
bly, there were no significantly different mean scores in value by both
hotel class and ADR. Thus, value itself is not a good indicator to differ-
entiate one group from other group of the hotel class and ADR. Also,
guests’ perceptions of value are believed to have no linear relationship
with hotel class and ADR.
As shown in Table 6, approximately 97% of total variance in guests’
satisfaction can be explained by four attributes: rooms, value, cleanliness,
and check-in & check-out (p < .001). In particular, value was the key
TABLE 5. Hotel performance by ADR
Attributes <$270 (45) $270 – $360 (46) >$360 (48) F Bonferroni’s
Multiple Range
Test
a
Rooms 3.20 3.59 4.05 17.10** 1,2,3**
Value 3.53 3.67 3.80 1.99 123
Cleanliness 3.56 3.93 4.27 12.32** 1,23**
Location 4.24 4.39 4.53 6.59** 1,3**
Check-in &
Check-out
3.45 3.78 4.04 12.20** 1,23**
Service 3.40 3.77 4.09 16.00** 1,2,3**
Business Service 3.08 3.49 3.84 11.80** 1,23**
Satisfaction 3.35 3.69 4.01 9.94** 1,3**
Return Intentions 3.02 3.21 3.36 3.98* 1,3*
*p < .05; **p < .01.
a
1 = hotel room rates <$270; 2 = hotel room rates between $270 and $360; 3 = hotel room
rates >$360. The grouping was done in the same way as in the star rating case.
Miyoung Jeong and Myunghee Mindy Jeon 133
predictor of guests’ satisfaction in NYC, followed by rooms and cleanli-
ness. As expected, guests’ satisfaction appeared to be the most important
indicator to predict their return intentions (p < .001). Consequently,
rooms, value, and cleanliness were also key predicting variables for
return intentions but the relationship between rooms and return intentions
was mediated by satisfaction. Overall, the models exhibited strong
explanatory abilities with squared multiple correlations ranging from 0.94
to 0.97, respectively.
CONCLUSIONS AND DISCUSSIONS
This exploratory study analyzed one of numerous hotel review Web-
sites available on the Internet to determine how consistent customer
review compliments and complaints posted on the Website were with
hotel class (i.e., star rating), ADR, and popularity index, as well as to
assess key satisfiers of guests’ purchase behavior. Based on the TripAdvi-
sor’s popularity index, the more popular the hotel is, the higher service
level that is offered. The most or moderately popular hotels typically were
ranked with at least 3 stars, while the least popular hotels were either 1 or
2 star establishments. In particular, guests’ evaluations of hotel offerings
TABLE 6. Regression of hotel offerings on guest
satisfaction and return intentions
Dependent Variables Satisfaction Return Intentions
Independent Variables ß t-value ß t-value
(Constant) −3.64 1.08
Rooms 0.29** 5.78 −0.17* −2.17
Value 0.31** 8.41 0.42** 6.62
Cleanliness 0.19** 4.11 0.17* 2.46
Location 0.01 0.70 0.02 0.58
Check-in & Check-out 0.11* 2.36 −0.03 −0.48
Service 0.10 1.74 −0.05 −0.57
Business Service 0.05 1.79 0.01 0.28
Satisfaction 0.62** 4.96
F-value 605.97** 254.90**
R
2
0.97** 0.94**
*p < .05; **p < .001.
134 JOURNAL OF HOSPITALITY & LEISURE MARKETING
on the nine attributes were significantly lower for 1 or 2 star-rated hotels
than their 3 star counterparts, and those nine attributes for 3 star hotels
were lower than their 4 or 5 star counterparts. These findings implied that
most upscale and luxury hotels indeed performed better than lower rated
hotels. It also indicates that the popularity index coincides with the hotel
star rating system. This result also partially indicates that the widely
adopted hotel star rating system seems to have empirical validity from
guests’ perspectives.
Results of this study indicate that chain-affiliated hotels performed
somewhat better than independent hotels in rooms, check-in & check-out,
service, and business service. Typically, chain-affiliated hotels seem to
offer more room amenities, speedier check-in and check-out procedures,
more friendly and helpful services, and better equipped business service
for their guests, as opposed to independent hotels. In this way, guests who
stayed in chain-affiliated hotels were willing to pay more and seemed to
enjoy staying in chain hotels served by well-trained employees.
Grouping hotels by hotel class and ADR provided interesting results
with regards to guests’ evaluations of hotel performance. In general, it was
believed that ADR was considered a potential agent of influencing guests’
value perceptions about a hotel stay. Bonferroni’s multiple comparisons
showed (see Tables 4 and 5), however, that value was independent from
hotel class and ADR. This implies that guests’ perception of value of hotel
accommodations is not strongly related to hotels’ star ratings and ADR.
For example, an expensive 4-star hotel is not necessarily perceived as val-
ued accommodations by guests unless the hotel offers accommodation
experiences matching its high room rates and star ratings. Among the hotel
performance attributes, rooms was a distinct attribute to differentiate three
groups of hotel class and ADR. By the hotel’s ADR, as expected, service
was another distinct attribute to distinguish hotels into three groups.
Obviously, guests’ evaluations of cleanliness, check-in & check-out, and
business service were significantly different between 1–2 star rated estab-
lishments and 4–5 star rated establishments. Interestingly, an ADR of $270
seems to be a threshold point in NYC, as two ADR Groups (2 and 3) had
no significant different mean scores in cleanliness, check-in & check-out,
and business service, but had significantly different mean scores when
compared to ADR Group 1. Guests were more satisfied with and had
strong return intentions to upscale and luxury hotels with at least a $360
ADR than economy and budget hotels charging less than a $270 ADR.
The results also consistently showed that mean differences in location
were significantly different among the nine attributes, regardless of hotel
Miyoung Jeong and Myunghee Mindy Jeon 135
class and ADR. The mean scores of location in each hotel class and each
ADR category were between 4.17 and 4.53, with a range of 0.36. This
implies that convenience of location of hotels from the guest’s interest
points is a key element in hotel choice regardless of hotel class, ADR, and
ranking in the popularity index, specifically in New York City. Also,
hotels in NYC seem to be truly located in the prime business district.
Regardless of hotels’ ownership, hotel class, ADR, and popularity
index, among the seven hotel offering attributes, value was the most
powerful predictor of guests’ satisfaction, which in turn leads to the
guest’s return intentions. Compared to the 2006 industry ADR of $97.61
(Chappell, 2007), selected NYC hotels’ ADR for this study ($322) was
comparatively high. Thus, special efforts (i.e., marketing campaign,
employee training, and value package deals) should be made by each
hotel to meet or exceed guests’ expectations and offer enhanced service or
facility features, compared to what they paid for.
LIMITATIONS OF THE STUDY
This study uniquely attempted to identify how consistent guests’ per-
ceptions of hotel performance were with the popularity index, hotel class,
and ADR through their reviews on CGM. However, interpretation of the
results should be done with caution. This study selected hotels only in
NYC and evaluated selected reviews in a limited time frame. Findings of
this study might not be the same as those in different metropolitan cities
in the U.S., which could limit generalizability of its findings.
Since this study evaluated the secondary data available on TripAdvisor.
com, issues related to the secondary data are still unresolved including
integrity of guest reviews, limited data accessibility, and no control of
data collection. In particular, key demographic variables were not avail-
able due to the reviewer’s privacy issue.
IMPLICATIONS AND SUGGESTIONS
FOR FUTURE RESEARCH
Findings of this study provide hotel management with a chance to
understand guests’ perceptions of hotel performance by hotel class, ADR,
and TripAdvisor’s popularity index, and to know what performance
attributes contribute to guest satisfaction and lead to guests’ intention to
136 JOURNAL OF HOSPITALITY & LEISURE MARKETING
return to hotels or recommend to others. In particular, independent hotels
in NYC should pay more attention to improve room amenities and check-
in and check-out procedures and maintain high quality services in order to
compete with chain hotels, as these areas appeared to be one of the under-
performing attributes for independent hotels.
This study also points to major directions for improvement in hotel
offerings. Since room-related features are one of the distinguishing
attributes of hotel class and ADR, hotels in each class and ADR category
should diversify their features by utilizing their available resources to
meet each individual’s needs (e.g., technology related features, environ-
ment-conscious features, kid–friendly features, so forth). Interestingly,
hotels in the middle class and middle ranges of ADR seem to do their
business on average, compared to the other two extreme classes and ADR
categories, which seems in line with the nature of their class and category.
However, special marketing efforts should be made by hotel management
to distinguish their offerings from other hotel groups in order to maintain
their unique operational characteristics.
In order to satisfy guests and encourage them to return, hotels, in gen-
eral, need to differentiate their offerings from those of other levels of
star-rated accommodations. For example, the 4 or 5 star hotels may be
able to differentiate themselves from the lower star hotels by assuring
provision of more personalized and stylish employee services beyond
high quality rooms and other basic functional services. Lower-rated
hotels in 1 and 2 star ratings need to develop different management
approaches to make their guests happy and satisfied by providing decent
accommodations at reasonable prices. As mentioned in our results above,
it is clear that guests already establish firm expectations about the hotels
they want to stay before they arrive. Regardless of hotel classes and
ADR, they expect to have a clean and friendly environment. However,
value to hotels must be different depending upon guests’ predetermined
standards. Since value is one of key predictors of guests’ satisfaction,
each hotel must develop its own unique marketing and/or operational
strategies that exceed guests’ expectations of hotel performance based on
what they pay for.
Hotel management is advised to consider regularly visiting hotel
review sites such as TripAdvisor.com to glean industry-wide trends in
guest voices. By listening to guests’ voluntary voices about their hotel
experiences in general, managers have an excellent opportunity to review
and re-evaluate their operational strategies and management goals against
industry norms and performance averages. This is one of the most
Miyoung Jeong and Myunghee Mindy Jeon 137
important functions of CGM as well as it provides guests with opportuni-
ties to speak out about their (un)pleasant experiences with particular
hotels they stayed. Findings of this study indicate that there still exist siz-
able gaps between guest expectations and hotel offerings, especially when
the hotel offerings are classified by levels of service and room rates
charged. Finally, such hotel review sites seem to provide hotel manage-
ment with valuable market information that is not directed by researchers,
but freely volunteered by guests, thereby offering a raw opportunity to
read industry performance trends as well as benchmark a hotel against the
industry in general.
Since CGM is becoming more diversified in the way it reaches poten-
tial customers, it would be of great interest to conduct a comparative
study among different hotel review sites in order to cross validate hotel
performance from guests’ candid eyes. Additionally, findings of this
study suggest that future research develop more systematic research
agenda on CGM with regard to the roles of CGM, impact of CGM on real
hotel operations, and potential users’ perceptions of CGM for their pur-
chase behavior.
REFERENCES
Anderson, E.W. (2001). Customer satisfaction and word-of-mouth. Journal of Service
Research, 1(1), 5–17.
Bearden, W.O., & Oliver, R.L. (1985). The role of public and private complaining in
satisfaction with problem resolution. Journal of Consumer Affaires, 19, 222–240.
Cadotte, E.R., & Turgeon, N. (1988). Key factors in guest satisfaction. The Cornell Hotel
and Restaurant Administration Quarterly, 45–51.
Chappell, J. (2007, June). STR study: U.S. industry pockets $26.6 billion in 2006. Hotel &
Motel Management Week in Review. Retrieved June 25, 2007, from http://www.hotelmotel.
com/hotelmotel/News+Wire/STR-study-US-industry-pockets-266-billion-in-2006/Article
Standard/Article/detail/436475?contextCategoryId=1227
Chipkin, H. (2005/2006). Online communities: Word of mouth goes high tech. HSMAI
Marketing Review, 22(4), 22–28.
Davidow, M., & Leigh, J.H. (1998). The effects of organizational complaint responses on
consumer satisfaction, word-of-mouth activity, and repurchase intentions. Journal of
Consumer Satisfaction, Dissatisfaction, and Complaining Behavior, 11, 91–102.
Folkes, V.S. (1984). Consumer reactions to product failure: An attribution approach.
Journal of Consumer Research. 10, 398–409.
Fong, J., & Burton, S. (2006). Online word-of-mouth: A comparison of American and
Chinese discussion boards. Asia Pacific Journal of Marketing and Logistics, 18(2),
146–156.
138 JOURNAL OF HOSPITALITY & LEISURE MARKETING
Hawkins, D., Best, R., & Coney, K. (2004) Consumer behavior: Building marketing
strategy (9th ed). Boston: McGraw-Hill.
Litvin, S., Goldsmith, R., & Pan, B. (2008). Electronic word-of-mouth in hospitality and
tourism management. Tourism Management, 29(3), 458–468.
Mobil Travel Guide (2005). Mobil stars: Lodging star definitions. Retrieved January 12, 2006,
from http://www.mobiltravelguide.com/mtg/index.jsp?menu=mobil_stars&bodytid=1031
Mohl, B. & Ridder, K. (2003). Consumer hotel reviews on the Web, not so easy to find.
Retrieved December 17, 2005, from http://www.hotel-online.com/News/PR2003_2nd/
Jun03_HotelReviews.html
Naylor, G., & Kleiser, S.B. (2000). Negative versus positive word-of-mouth: An
exception to the rule. Journal of Consumer Satisfaction, Dissatisfaction, and
Complaining Behavior, 13(1), 26–36.
Nobles, H. (2004). 5 star vs. 5 diamond: What’s the difference? Retrieved October 15, 2006,
from http://www.hotel-online.com/News/PR2004_4th/Nov04_StarsDiamonds.html
Nobles, H. (1999). What the diamond ratings mean. Retrieved October 3, 2006, from http://
www.hotel-online.com/Neo/News/PressReleases1999_1st/Feb98_DiamondRatings.html
Pitta, D.A., & Fowler, D. (2005). Internet community forums: An untapped resource for
consumer markets. Journal of Consumer Marketing, 22(5), 265–274.
Starkov, M., & Price, J. (2006). Consumer generated media (blogs, discussion boards,
review sites), a threat or an opportunity. Retrieved December 17, 2006, from http://
www.hotel-online.com/News/PR2006_4th/Dec06_ConsumerMedia.html
Stieghorst, T., & Ridder, K. (February 2004). Hotel executives starting to review online
lodging reviews; comments like “god awful” and “run away as fast as you can” may
or may not be objective. Retrieved February 4, 2004, from http://www.hotel-
online.com/News/PR2004_1st/Feb04_OnlineReviews.html
Susskind, A.M. (2002). I told you so! Restaurant customers’ word-of-mouth communication
patterns. Cornell Hotel and Restaurant Administration Quarterly, 43(2), 75–85.
Swan, J.E., & Oliver, R.L. (1989). Postpurchase communication by consumers. Journal of
Retailing, 65, 516–533.
TripAdvisor (2007). Retrieved October 23, 2007, from http://www.tripadvisor.com/Hotels-g
191-United_States-Hotels.html
