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Benefit Segmentation of International Travelers to Macau, China

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The purpose of this study is threefold: (1) to identify the underlying benefits sought by international visitors to Macau, China, which has emerged as a popular gambling destination in Asia; (2) to segment tourists visiting Macau by employing a cluster analysis based on the benefits sought; and (3) to examine any salient differences between the segment groups with regard to their behavioral characteristics, socio-economic characteristics, and demographic profiles. A convenience sample was used to collect data in the Macau International Airport, in the Macau Ferry Terminal, and at the border gate with Mainland China. A total 1,513 useful surveys were retained for data analysis. Cluster analysis discloses four distinct clusters: “convention and business seekers,” “family and vacation seekers,” “gambling and shopping seekers,” and “multi-purpose seekers.” Based on the results of our findings, several managerial implications are discussed.
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Benefit Segmentation of International Travelers to Macau, China
Woo Gon Kim
a
; Yumi Park
b
; Gabriel Gazzoli
c
; Edmund Sheng
d
a
Robert H. Dedman Professor of Hospitality Management & Director of International Center for
Hospitality Research, Dedman School of Hospitality, College of Business, Florida State University,
Tallahassee, Florida, USA
b
Oklahoma State University, School of Hotel and Restaurant
Administration, Stillwater, Oklahoma, USA
c
Aston Business School, Aston University, Birmingham,
United Kingdom
d
Institute For Tourism Studies, Colina de Mong-Ha, Macao
Online publication date: 06 February 2011
To cite this Article Kim, Woo Gon , Park, Yumi , Gazzoli, Gabriel and Sheng, Edmund(2011) 'Benefit Segmentation of
International Travelers to Macau, China', Journal of Quality Assurance in Hospitality & Tourism, 12: 1, 28 — 57
To link to this Article: DOI: 10.1080/1528008X.2011.541813
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Journal of Quality Assurance in Hospitality & Tourism, 12:28–57, 2011
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ISSN: 1528-008X print/1528-0098 online
DOI: 10.1080/1528008X.2011.541813
Benefit Segmentation of International
Travelers to Macau, China
WOO GON KIM
Robert H. Dedman Professor of Hospitality Management & Director of International
Center for Hospitality Research, Dedman School of Hospitality, College of Business,
Florida State University, Tallahassee, Florida, USA
YUMI PARK
Oklahoma State University, School of Hotel and Restaurant Administration,
Stillwater, Oklahoma, USA
GABRIEL GAZZOLI
Aston Business School, Aston University, Birmingham, United Kingdom
EDMUND SHENG
Institute For Tourism Studies, Colina de Mong-Ha, Macao
The purpose of this study is threefold: (1) to identify the underlying
benefits sought by international visitors to Macau, China, which
has emerged as a popular gambling destination in Asia; (2) to
segment tourists visiting Macau by employing a cluster analysis
based on the benefits sought; and (3) to examine any salient differ-
ences between the segment groups with regard to their behavioral
characteristics, socio-economic characteristics, and demographic
profiles. A convenience sample was used to collect data in the
Macau International Airport, in the Macau Ferry Terminal, and
at the border gate with Mainland China. A total 1,513 useful
surveys were retained for data analysis. Cluster analysis dis-
closes four distinct clusters: “convention and business seekers,”
“family and vacation seekers,” “gambling and shopping seekers,”
and “multi-purpose seekers.” Based on the results of our findings,
several managerial implications are discussed.
KEYWORDS benefit segmentation, cluster analysis, Macau, desti-
nation management
Address correspondence to Woo Gon Kim, Ph.D., 288 Champions Way, UCB 4116, PO
Box 3062541, Tallahassee, FL 32306-2541. E-mail: wkim@cob.fsu.edu
28
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International Travelers to Macau, China 29
INTRODUCTION
The travel and tourism industry has become an essential factor in the devel-
opment of many cities, regions, and countries (Weber & Telišman-Košuta,
1991). According to a study conducted by the World Travel and Tourism
Council (2008), the total expected tourism demand reached $7.8 trillion in
economic activities worldwide in 2008, and this number is forecasted to
increase to $14.8 trillion in 2018. The same study reported that the tourism
sector is expected to contribute 9.9 % of the global gross domestic product
(GDP) in 2008, as well as employ more than 238 million people directly
and indirectly (Weber & Telišman-Košuta, 1991). In light of such astonish-
ing statistics, the tourism industry is widely recognized as a major economic
and social contributor to many destinations, and therefore, a focus on this
industry’s growth has become an important component in the development
strategy of any destination.
As the tourism industry develops in new areas of the world, destina-
tion choices for consumers continue to expand. As a result, travelers have
more choices when making travel decisions, and these destinations, there-
fore, must compete more than ever for tourist dollars. Consequently, tourism
marketers are faced with more complex and competitive marketplaces. In
order to develop a competitive advantage and improve returns from market-
ing investments, destinations must develop appropriate market segmentation
strategies. Following a basic principle of marketing strategy proposed by
Kotler (1967), destinations should segment their markets in order to identify
their most attractive customers. The importance of segmentation is so crucial
for an effective strategy that some scholars have suggested that “if you’re not
thinking segments, then you’re not thinking” (Levitt, 1983).
One criterion for destination market segmentation is to analyze the
benefits sought by tourists (Sarigollu & Huang, 2005). Kotler and Turner
(1993) suggested that benefit segmentation is a powerful tool for putting
consumers into more homogeneous groups. In addition, Haley (1968) pro-
posed that benefit segmentation provides more accurate determinants of
human behavior than other approaches because the benefits that tourists
seek are the basic reasons for the existence of true market segments.
The purpose of this study, then, is to examine the benefits sought by
tourists at a particular destination, one which has gained popularity as a
gaming paradise and an emerging tourist destination in Asia: Macau, China.
Research Site
Macau is located on the South coast of China. Its territory is within a 60 km
reach of Hong Kong and 145 km from the city of Guangzhou (on Mainland
China). In the early 1500s, Macau was colonized by Portugal. The Portuguese
rule lasted until December 1999, when Macau was handed over to China.
Today, Macau is a Special Administrative Region (SAR) of China, and, like
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30 W.G.Kimetal.
TABLE 1 Macau Economic and Tourism Indicators (2000–2008)
Indicator 2000 2001 2002 2003 2004 2005 2006 2007 2008
Unemployment rate (%) 6.75 6.39 6.23 6.02 4.75 4.1 3.72 3.04 3.02
Nominal GDP (USD
billion)
6.1 6.2 6.9 8.0 10.3 11.5 14.2 18.8 21.7
GDP per capta (USD
000s)
14253 14348 15671 17898 22554 24263 28536 35786 39577
Visitor arrival (million) n.a n.a 11.5 11.8 16.6 18.7 22 27 22.9
Gross gaming revenue
(USD billion)
n.a n.a n.a n.a n.a 5.9 7.2 10.5 13.8
Rooms available (from
guest houses to 5
)
9,201 9,030 8,954 9,188 9,168 10,832 12,982 16,148 17,490
Hotel occupancy (%) 57.5 67.1 73.8 77.4 78.5 76.1 78.1 83.0 79.0
Number of MICE events n.a n.a 136 125 278 305 360 1,117 1,240
Note: GDP = Gross Domestic Product
USD1 = MOP 7.98 as of December 12, 2009.
Source: Statistics and Cesus Services, Macao SAR Government
Hong Kong, it benefits from the principle of one country and two sys-
tems (Macau Government Tourist Office, 2008). The resident population of
Macau has increased from 425,200 in 1998 to 541,200 in the third quarter of
2009 (Macau Statistics and Census Services, 2009a). Macau has experienced
a phenomenal growth in tourist arrivals in the past decade. In 1998, the
region registered 6.9 million arrivals and the numbers grew annually until
2007, when Macau achieved a record high number of 27 million arrivals.
However, in 2008, the region registered a decrease in the number of tourist
arrivals, totaling 22.9 million visitors. Tourists from Mainland China repre-
sented 50% of the total arrivals in 2008, while 30% were from Hong Kong, 6%
from Taiwan, and all other countries represented the remaining 14% (Macau
Statistics and Census Services, 2009b). The contribution of Travel & Tourism
to the Gross Domestic Product (GDP) of Macau is expected to change
from 69.9% (USD 19.3 billion) in 2009 to 70.7% (USD 45.3 billion) in 2019
(World Travel & Tourism Council, 2009). Macau’s tourism industry currently
employs 177,000 people, representing 65.3% of the region’s total employ-
ment. According to the World Travel & Tourism Council’s (2009) world
ranking, Macau’s tourism is listed as the 39th place in absolute size, third
in contribution to national economy, and 35th in growth forecast among 181
other countries. Table 1 presents the major economic and tourism indicators
of Macau, and it shows how this destination evolved over the years from
2000 to 2008.
LITERATURE REVIEW
The Need for Segmentation Research
Scholars in the field of consumer behavior focus their efforts on explaining
the decision-making processes of different consumers, and the foundation
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International Travelers to Macau, China 31
theories used in their research are generally embedded and linked to
microeconomics and psychology (Voorhees, 2006). Although consumers’
decision-making process is an exclusive process, theories used to justify
these processes rely on the idea that consumer markets are heterogeneous.
This heterogeneity can be explained by the argument that consumers have
different and individual characteristics that are related to diverging eco-
nomic motivations and personal decision-making criteria (Voorhees, 2006).
Psychological theories that explain consumer behavior focus on key differ-
ences of need fulfillment whereas economic-based explanations tend to rely
on the theory of imperfect competition (Robinson, 1938). Both psychological
and economic theories provide support for the argument that market seg-
mentation is a critical process that is needed in order to develop a product
and a service and, in the case of this paper, to select a tourist destination.
The economic and psychological theories used in market segmentation are
explained in detailed below.
The imperfect competition theory proposed by Robinson (1938) sug-
gests that markets become heterogeneous due to the fact that consumers
have different needs and unique preferences (Robinson, 1938; Smith, 1956).
It also suggests that discrepancies in customers’ preferences for, and per-
ceptions of, products may lead to drastic shifts in the demand curve
(Chamberlin, 1965), and if service providers for a particular tourist des-
tination do not adapt to and embrace these consumer preferences, then
market friction occurs. However, demand curves could be shifted to the
right and force markets to become less price elastic if markets are segmented
properly (Chamberlin, 1965; Dickson & Ginter, 1987), and this process aids
marketers in transforming heterogeneous markets into smaller homogenous
targets.
Psychologists also suggest that consumers posses unique needs and
objectives when purchasing a product, and therefore, they may take on
different approaches to fulfill their needs and wants (Voorhees, 2006). For
example, Maslow (1943) suggested that consumers’ needs are on a con-
tinuum process, whereas their motivations for purchases are presented in
different levels, depending on the needs and goals that the consumers are
trying to accomplish. In addition, the consumers’ personal values play a key
role in the attainment of the needs that they seek, and these values may
affect the benefits that consumers are looking for when making their buying
decisions (Maslow, 1943). For example, travelers who value entertainment,
night life, and social approval may be driven to visit “hot-spot” destinations,
such as Miami and Ibiza. Similarly, travelers who are price conscious or who
value educational culture may make travel arrangements according to these
values and goals, such as? Therefore, some of the reasons behind the het-
erogeneity of consumer markets are affected by the benefits that consumers
seek when making purchases (Haley, 1968).
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32 W.G.Kimetal.
Market Segmentation Research in the Tourism Industry
As discussed earlier, market segmentation helps marketers break down het-
erogeneous markets and define smaller segments of homogeneous groups
according to one or several variables. In the tourism field, the criteria
used for segmentation can be divided into two different groups: 1) gen-
eral consumer characteristics that include psychographic, geographic, and
demographic variables; and 2) situation-specific characteristics, such as
the consumers’ perceptions, preferences, and attitudes toward products or
services; the modes of product usage and the benefits sought; and the
purchasing frequency and actual expenditure (Legoherel, 1998).
The literature shows that benefits have been defined and conceptual-
ized differently by several scholars (Sarigollu & Huang, 2005). On one side,
researchers have defined benefits as visitor ratings of amenities and activities
(Tian, Crompton & Witt, 1996). This definition has been used in destination
image research where the objective was to measure visitors’ impressions of
destinations (Crompton, 1979). On the other side, in order to capture the
tourists’ psychological benefit outcomes, researchers have focused on the
motivations to travel (Bieger & Laesser, 2002). The present study adopts a
broader view of benefit segmentation as it incorporates the desired activities
and motivations that international travelers seek when considering Macau
as a travel destination.
Besides different definitions and conceptualizations of benefit segmen-
tation, the literature shows that this segmentation strategy can be classified as
either destination-specific or non-destination-specific. In destination-specific
research, tourists to a common destination are classified into segments based
on the benefits they seek (desired activities or motivations). For example,
Kim and Agrusa (2009) interviewed Japanese visitors in Honolulu, Hawai,
and defined five groups on the basis of the tour-purpose segmentation
method, namely: 1) Honeymoon tourism; 2) Fraternal association tourism; 3)
Sports tourism; 4) Tourism for rest and relaxation; and 5) Business/VFR
tourism. In addition, Li, Huang, and Cai (2009) collected data from adult vis-
itors to a rural community in the state of Indiana, USA, and found 6 factors
(out of 32 motivation variables), including escape; novelty; nostalgia and
patriotism; event excitement; family togetherness; and socialization.
Non-destination studies, on the other hand, explain the general char-
acteristics (benefits) that tourists seek when planning to visit a destination.
The data for this type of study are usually collected from specific regions
(Sarigollu & Huang, 2005). Past non-destination-specific research includes
Bieger and Laesser (2002), who studied the general motivations of Swiss
travelers in Switzerland and found motives such as nightlife, nature, culture,
sports, and sun. Further, Shoemaker (1994), who segmented the US travel
market by benefits, adopted 39 different variables including sun, sports,
entertainment, family, convenience, and scenery. Finally, Cha, McCleary, and
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International Travelers to Macau, China 33
Uysal (1995) explored the travel motivation of Japanese overseas tourists and
found six motivational dimensions (e.g., relaxation, knowledge, adventure,
travel bragging, family, and sports) out of a total of 30 motive variables.
According to the literature, the majority of published work within this
domain is destination-specific (e.g., Andreu, Kozak, Avei, & Cifter, 2005;
Davis & Sternquist, 1987; Frochot, 2005; Huang & Sarigöllü, 2007; Johns &
Gyimóthy, 2002; Lang & O’Leary, 1997; Loker & Perdue, 1992; May, Bastian,
Taylor, & Whipple, 2001; Moscardo, Pearce, Morrison, Green, & O’Leary,
2000; Sarigöllü & Huang, 2005; Tian et al., 1996; Woodside & Jacobs, 1985).
Past research also shows an array of statistical techniques used in seg-
mentation studies. Most of the studies have applied cluster analysis, as this
technique has proven to be an effective marketing strategy tool because
it yields viable market segments (Arimond & Elfessi, 2001). Besides cluster
analyses, other statistical techniques were added to complement the initial
cluster investigation. For example, May et al. (2001) used canonical discrimi-
nant analysis to further analyze the differences between the clusters. Boo and
Jones (2009) applied discriminant analysis, and Bieger and Laesser (2002),
as well as Sirakaya, Uysal, and Yoshioka (2003), used multiple discriminant
analysis (MDA) to further identify discriminating factors for each cluster.
Kim and Agrusa (2009) added analysis of variance (ANOVA) and correspon-
dence analysis to assess the differences in the travelers’ preferences and
other travel-related, attitudinal, behavioral, and socio-demographic charac-
teristics related to each tour purpose. Table 2 provides an overview of extant
research on benefit segmentation within the tourism field.
Tourism Research on Macau
The literature shows several recent studies related to tourism development
in Macau. For example, Gu (2006) highlighted the importance for Macau
to focus on product differentiation through a revenue management strategy
as a mean to compete effectively against the emerging gaming destination
in nearby Asian countries. According to Gu, Macau should concentrate its
efforts on differentiated gaming service products, such as its VIP rooms
operations, in order to maximize the future revenue potential.
Along the same line of thinking, Gu (2004) conducted a SWOT analysis
of Macau before answering the question as to whether or not the destination
should follow the Las Vegas style when developing its own gaming strategy.
The author concluded that the Las Vegas business model is not a suitable
approach for Macau, as it will force Macau to compete against Las Vegas and
other Las Vegas-type destinations in Asia. Moreover, the study suggested
that if Macau follows the Las Vegas colossal “gaming, entertainment, con-
vention, and shopping” model, it would also compete against non-gaming
destinations, such as Hong Kong and other nearby Chinese cities. Therefore,
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TABLE 2 Summary of the Past Research on Segmentation and Statistical Analysis
Authors (Year) Subject and study region
Benefits sought dimensions
(factors) Segments
Different segmentation
criteria (Delineators)
Boo & Jones (2009) Travelers to the major
metropolitan area who
visited tourism-related
sites
6 factors (out of a total 20
items)—Social/Interaction;
Excitement/Fun; Relaxation;
Sightseeing; Family/Friends
Togetherness; and Sports
3 Clusters—Social-seeking
travelers;
Excitement-seeking
travelers; and
Relaxation-seeking travelers
None/Discriminant
analysis of each group
Kim & Agrusa
(2009)
Japanese tourists to
Honolulu, Hawaii, USA
5 groups on the basis of the
tour purpose segmentation
method—Honeymoon
tourism; Fraternal
association tourism; Sports
tourism; Tourism for rest
and relaxation; and
Business/VFR tourism
Socio-demographic and
Behavioral
characteristics/Corres-
pondence analysis
Li, Huang, & Cai
(2009)
Adult visitors from outside
the host community in the
rural destination in the
Midwest (Indiana) of the
United States.
6 factors (out of a total of 32
benefits)—Escape; Novelty;
Nostalgia and Patriotism;
Event Excitement; Family
Togetherness; and
Socialization.
5 Clusters-Family Travelers;
Event (festival) Enthusiasts;
Loyal Festival Goers;
Escapers; and Social
Gathering Lovers.
Demographics and
Traveler Behavior
Huang & Sarigöllü
(2007)
Tourists to the Caribbean 5 factors (out of a total of 21
items)—Sightseeing; Sports;
Night Life; Beach; and Parks
&Arts
4 Clusters—Sun & Fun
Seekers; Active
Sportspeople; Variety
Seekers; and Sightseers
Demographics, Travel
behavior, Decision
drivers, and
Personalities and
interests.
34
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Andreu, Kozak,
Avci, & Cifter
(2005)
British tourists to Mugla,
Turkey
5 factors (out of a total of 17
motivations)—Enjoy tourist
attractions; Diversity of
entertainment in a value for
money destination; Different
cultural environment; Ease
of access; and Getting away
from routine
5 Clusters—Fuzzy tourists;
Active tourists; Recreation
seekers; Escape seekers; and
Relax seekers
Socio-demographic
characteristics and
holiday-taking patterns
Frochot (2005) Tourists to two rural areas,
Scotland
4 factors (out of a total of 13
benefits)—Outdoors;
Rurality; Relaxation; and
Sport
4 Clusters—Actives; Relaxers;
Gazers; and Rurals
Activities’ preferences,
Socio-economic and
behavioral (holidaying)
characteristics,
Sarigöllü & Huang
(2005)
North American tourists to
Latin America
5 factors (out of a total of 24
motives)—Fun and Sun;
Ecotourism; Performing Arts
& Events; Outdoor
adventure; and General
sightseeing
4 Clusters—Adventurer;
Multimfarious; Fun and
Relaxation; and Urbane
Demographics, Travel
behavior, Decision
drivers (e.g., Health
service, Child day care,
Telecom s ervice etc.),
and Personalities and
interests.
Kang, Hsu, & Wolfe
(2003)
Travelers, who visited one of
the three Travel
Information Centers (TIC)
on the borders of Kansas,
U.S
3 Clusters—Intergenerational
(ITG) travelers; Business-
mixed-with-pleasure (BMP)
travelers; and Visiting friends
and relatives (VFR) Travelers
Family decision-making
process
Sirakaya, Uysal, &
Yoshioka (2003)
Japanese travelers to Turkey 8 factors—Love of Nature;
Enhancement of Kinship;
Experiencing Culture; Living
the Resort Lifestyle; Escape;
Education in
Archeology/History; Living
the Extravagant Lifestyle;
and Travel Bragging
2 Clusters—Escapers and
Seekers
None/Multiple
Discriminant analysis
(MDA)
(Continued)
35
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TABLE 2 (Continued)
Authors (Year) Subject and study region
Benefits sought dimensions
(factors) Segments
Different segmentation
criteria (Delineators)
Bieger & Laesser
(2002)
Swiss travelers in
Switzerland
10 motivation factors including
nightlife, comfort, partner,
family, nature, culture,
liberty, sports, and sun.
4 Clusters—Compulsory
Travel; Cultural Hedonism;
Family Travel; and Meet
Marketing
Demographics and Travel
behavior (e.g., means
of transportation,
round trip distance,
length of visit etc./
Discriminant analysis
of each group
Johns & Gyimóthy
(2002)
Visitors to Bor nholm,
Denmark
4 factors (out of a total of 19
activities)—Outdoor/social;
Outdoor/nature; Relaxing;
and Sightseeing
2 Clusters-Active and Inactive
group
Amenities, Activities,
Attraction visit
May, Bastian, Taylor,
& Whipple (2001)
Wyoming snowmobile
owners, Wyoming, U.S.
26 benefits including enjoying
nature, achievement,
stimulation, escape,
personal/social pressure,
and being with family and
friends
5 Clusters—
Achievement/stimulation;
Escape personal/social;
Enjoy nature/ learning;
Being with similar family
and friends; and Escape
Physical Pressure
Socio-economic
characteristics and
Behavior (e.g., number
of days snowmobiling
per year, amount of
spent on last trip,
etc.)/Canonical
Dicsriminant analysis
of each group
36
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Moscardo, Pearce,
Morrison, Green,
& O’Leary (2000)
Visitors to Queensland,
Australia. (from a
secondary data from the
Queensland Tourist and
Travel Corporation)
20 benefits including
relaxation, resort, warm
sunny weather, beach
activities, and environmental
activities
4 Clusters—Beach Relaxation
group; Inactive group;
Active Nature Lovers group;
and Active Beach Resort
group.
Demographics and Travel
behavior (e.g., travel
party, expenditure,
length of stay, means
of transportation, etc.)
Formica & Uysal
(1998)
Visitors to the Spoleto
Festival in Italy
6 factors (out of a total of 23
motives)—Socializing;
Cultural/historical
significance; Group
togetherness; Site novelty;
Event attraction &
excitement; and Family
Togetherness
2 Cluster—Enthusiasts and
Moderates group
Demographics and Travel
behavior (e.g., repeat
or first-time visitor)
Lang & O’Leary,
1997
Australian nature travelers to
outside of Australia and
New Zealand (outbound
nature travel market)
7 benefit factors (out of a total
of 25 benefits)—New
Experience; Escape and
Entertained; Show and tell;
Family Oriented; Cultural
Groups Interest; Physical
Challenge and Nature; and
Relax
6 Clusters—Physical Challenge
Seekers; Family Vacationers;
Culture and Entertainment
Seekers; Nature Tourists;
Escape and Relax
Vacationers; and Indifferent
Travelers
‘Motivation-participation-
preference’ multi-
segmentation approach
Tian, Crompton, &
Witt (1996)
Museum goers in Galveston,
Texas
18 benefits including
relaxation, entertainment,
socializing, bonding, social
recognition, selfesteem, and
education
4 clusters Demographics and Travel
behavior (e.g.,
frequency of travel,
type of museums
visited, etc.)
Cha, McCleary, &
Uysal (1995)
Japanese overseas tourists 6 factors (e.g. relaxation,
knowledge, family, and
sports) out of a total of 30
motive variables
3 Clusters- Sports seekers;
Novelty seekers; and
Family/relaxation seekers
Demographics
(Continued)
37
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TABLE 2 (Continued)
Authors (Year) Subject and study region
Benefits sought dimensions
(factors) Segments
Different segmentation
criteria (Delineators)
Shoemaker (1994) US travel market 39 different variables including
educational possibilities,
environmental aspects,
resort set, sun sports,
popularity of destination,
value, scenery, friend,
relatives, entertainment,
family, and convenience
Demographics and Travel
behavior (e.g., number
of trips per year, plans
for future trip etc.)
Loker & Perdue
(1992)
North Carolina 12 benefits including escape,
relaxation, natural
surroundings, excitement
variety, family, and friends
6 Clusters
Davis & Sternquist
(1987)
Traverse city, U.S. 10 benefits including sports,
sightseeing, rest, shopping,
food, entertainment, and
culture
Demographics and Travel
behavior (e.g.,
destination, total size of
travel group, length of
visit etc.)
38
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International Travelers to Macau, China 39
creating its own model and focusing on the niche gaming segment would
help Macau differentiate itself from similar Las Vegas-type destinations (Gu,
2004). Further, Nadkarni and Leong (2007) indicated that the development
of MICE (Meeting, Incentive, Convention, and Exhibition) facilities, cou-
pled with other leisure and entertainment factors, will create a competitive
advantage for Macau over its regional competitors, and it will yield higher-
spending business tourists. Lastly, many other researchers argued that Macau
can be re-created as the Las Vegas of Asia (McCartney 2003; McCartney &
Nadkarni, 2003; Tang, Choi, Morrison, & Lehto, 2009). This vision has been
embraced by the Macau Government and some casino operators, such as
Las Vegas Sands, who opened The Venetian in 2007: an integrated gaming
and MICE resort (McCartney, 2008a).
Several studies related to Macau as a destination have centered their
research questions towards Macau’s image. The literature shows two
research streams within its destination image. The first stream focused on
Macau’s projected online images from different websites (e.g., Choi, Lehto,
& Morrisson, 2007; Tang et al., 2009). Choi et al. (2007) attempted to iden-
tify the image attributes of Macau on the internet by examining 61 websites
divided into five different categories, namely 1) Macau official tourism web-
site (MGTO), 2) travel guides, 3) travel magazines, 4) travel blogs, and 5)
travel trade. The results from the content and correspondence analysis
showed that Macau has many faces, and its projected image varied according
to the different online information sources. For example, the word “casino”
was the fourth and fifth most frequent word in travel magazines and blogs,
respectively, and 47th on the MGTO website, whereas the word “museum”
was the second most frequent word on the MGTO website, sixth on travel
trade sites, 25th on the blogs, and 57th in magazines. These findings suggest
that the MGTO website is trying to move away from a “gaming” image by
focusing its communication efforts on a more diverse set of activities, such as
culture/sightseeing, shopping, and other leisure activities (Choi et al., 2007;
Tang et al., 2009).
On the other hand, the second research stream has tried to capture
the image perceptions from actual and potential visitors to Macau (e.g.,
McCartney, 2005; McCartney, 2008b; McCartney, Bluter, & Bennett, 2008).
McCartney (2005) studied the impact of the 50th Macau Grand Prix event
on visitors’ destination image perceptions. His findings showed that the
Grand Prix itself did not change the image perceptions of tourists, and that
tourists sometimes have a negative perception of Macau as being exclusively
a gaming destination. McCartney (2008b) compared data from travelers rep-
resenting the four major tourist markets in Macau—Hong Kong, Beijing,
Taiwan, and Shanghai—and found significant differences between the mar-
kets in all 33 measured image attributes. Overall, the attributes “gambling
opportunities,” “good night-life/adult oriented,” and “restful and relaxing”
showed the highest mean ratings across all regions. Weaker perceptions
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40 W.G.Kimetal.
across the respondent groups were related to attributes such as “place to
do business,” “place to have meeting/exhibition,” “rich cultural heritage,”
and “important museums.” The same study also examined the differences
in travel motives between the four regions, and the results showed that
significant differences exist between Macau’s major travel markets. In gen-
eral, the highest motives for travel were “relax physically and mentally” and
“experience a new culture,” whereas “visit friends and relatives” and “able
to gamble legally” were the weakest motives, respectively.
In sum, our literature review shows that Macau’s image remains some-
what perceived as solely a gaming place (McCartney, 2008a), despite
governmental efforts to reposition this destination as a place where one can
enjoy different activities, such as MICE, culture, and entertainment. Since
learning what drives tourists’ activities and motivations becomes crucial for
an effective destination positioning (McCartney et al., 2008), this study seeks
to answer the following three research questions:
1. What are the underlying benefit factors sought by Macau visitors?
2. How best? to segment tourists who visit Macau by employing cluster anal-
ysis, based on their specific activities and the benefits they seek during
their stay in Macau?
3. What are the salient differences between the different segments of
visitors with regard to their behavioral characteristics, socio-economic
characteristics, and demographic profiles?
METHODOLOGY
This study conducts a benefits market segmentation analysis of international
tourists visiting Macau. The benefit factors are generated through the desired
activities and motivations of tourists when they consider Macau as a travel
destination. The information required to perform this research was obtained
by questionnaire.
Questionnaire Development and Data Collection
The questionnaire was developed to collect a wide rage of information
from international tourists to Macau and was comprised of two major parts.
The first part of the questionnaire assessed behavioral, socio-economic, and
demographic variables, such as party size and composition, purpose of trip,
length of stay, entry mode, country of origin, age, household income, accom-
modation type, package users vs. non-package users, and occupation and
educational levels. The second part of the questionnaire was composed of
25 items, representing the activity attributes that international visitors per-
ceive as most important when considering Macau as a travel destination.
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International Travelers to Macau, China 41
The activity variables were measured on a 7-point Likert-type scale (from
1 = strongly disagree to 7 = strongly agree) and selected after an extant
literature review in academic journals, interviews with Macau residents, and
consultation with tourism scholars from that region.
Due to the large number of visitors coming from Mainland China and
Hong Kong, the English questionnaire was also translated into traditional
and simplified Chinese by an employee from a local university. It was then
presented to staff members and students of the same university, as well
as employees of a local hotel, for verification purposes. After verifying the
translations, the three versions of the questionnaire were pre-tested on 18
different students for validity purposes.
Nine paid students from the university were hired to support the data
collection phase. These students attended a 2-hour training session given
by one of the researchers, who was also on-site. The field researchers were
instructed to perform the following three steps: 1) to approach international
travelers; 2) to introduce the purpose of the study; and 3) to request their
participation in the survey. The data was collected during July and August
2007, and a convenience sample method with a self-administered ques-
tionnaire was applied. The locations used for data collection were in the
Macau Inter national Airport, on the Macau Ferry Terminal, and at the border
gate with Mainland China. In total, the researchers gathered 1,812 question-
naires, but due to a substantial amount of missing information in many of
the questionnaires, 1,513 useful surveys were retained for data analysis.
RESULTS
Factor Analysis and Reliability Test of Macau Visitors’ Activities
Factor analysis was used to identify the underlying constructs of the 25 activ-
ities performed by visitors to Macau. Three items were deleted after factor
analysis, and two more were eliminated after a reliability test, resulting in 20
items (of the original 25) used in the survey. A Principal Component Analysis
(PCA) with a Varimax rotation was used with a pre-determined cut-off eigen-
value equal to or greater than 1.0 (Heung & Cheng, 2000). Only factors with
more than .4 loading were retained and included in the factor identifica-
tion. The Cronbach’s alpha coefficient of each factor ranged from .63 to .92,
which was considered acceptable. In relation to the reliability of the scale,
the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.805) was
quite high, and Bartlett’s test of sphericity was significant (Approx. χ
2
=
13198.473, df = 210, p < .001). As a result, the factor model was considered
satisfactory.
The six factors having eigenvalues greater than 1.0, which explained
64.6% of the total variance, were identified and named as follows: “gam-
bling,” “convention and business,” “pleasure,” “cultural exploration,” “family
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42 W.G.Kimetal.
togetherness,” and “shopping” (see Table 1). The first dimension, labeled
“gambling,” accounted for 22.62% of the total variance with a reliability coef-
ficient of .91. The second dimension, labeled “convention and business,”
explained 12.65% of the variance with a reliability coefficient of .92. The
third dimension, labeled “pleasure,” explained 10.91% of the total variance
with a reliability coefficient of .74. The fourth dimension, labeled “cultural
exploration,” accounted for 7.60% of the variance with a reliability coeffi-
cient of .64. The fifth dimension, labeled “family togetherness,” accounted
for 5.77% of the variance with a reliability coefficient of .63. The sixth and
final dimension, labeled “shopping,” explained 5.09% of the variance with a
reliability coefficient of .69.
Cluster Analysis for Market Segmentation of Macau Visitors
Cluster analysis is a multivariate analysis technique, which is also called seg-
mentation analysis or taxonomy analysis. It is a statistical tool that classifies
objects into a set of groups according to the characteristics of the objects.
It seeks to identify a cluster, which both minimizes within-group variation
and maximizes between-group variation (Hair, Black, Babin, Anderson, &
Tatham, 2006).
To enhance our understanding of the factor structure, cluster analy-
sis was employed to classify Macau visitors into mutually exclusive groups,
based on a K-means clustering method. A non-hierarchical algorithm (Hair,
Anderson, Tatham, & Black, 1998) was used to determine the best num-
ber of clusters based on the activity factors. Cluster analysis suggested that
a four-cluster solution was most appropriate for organizing the data con-
cerning Macau’s visitors as well as the benefits they sought. Multivariate
statistics indicated that significant differences existed between the four
clusters (p < .001). An ANOVA test also indicated that all six factors con-
tributed to differentiating the four activity clusters (p < .001). In addition,
a multivariate of analysis of variance (MANOVA) test indicated that all six
factors contributed to differentiating the four activity clusters (Pillai Trace
= 1.565, p < .001; Wilks’ Ramda = .100, p < .001; Hotelling-Lawley Trace
= 3.702, p < .001; Roy’s Greatest = 2.110, p < .001). Furthermore, a post
hoc analysis—in this case, a Scheffe multiple-range test—was employed
to explore any differences between clusters with respect to each benefit
factor. The results of the Scheffe test indicated that there were statisti-
cally significant differences between clusters. The mean importance scores
for each benefit factor were calculated, and an examination of the mean
scores suggested the labels of Cluster 1: “convention and business seekers,”
Cluster 2: family and vacation seekers,” Cluster 3: gambling and shopping
seekers,” and Cluster 4: multi-purpose seekers.” This finding generally sup-
ports the appropriateness of each category shown in Table 2 and described
below.
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International Travelers to Macau, China 43
Cluster 1: convention and business seekers.” This cluster contained 554
visitors, representing the largest sample of respondents. This cluster was
named “convention and business seekers” based on the mean score charac-
teristics with respect to the factors. This cluster had the highest mean score
on “convention and business (mean = 4.93) among the four cluster groups.
Besides participating in business conferences and events, visitors from this
cluster also had interests in “culture exploration” (mean = 4.76) and “family
togetherness” (mean = 4.82).
Cluster 2: family and vacation seekers.” This cluster contained
311 visitors, and “family togetherness” showed the highest mean score
(mean = 4.96) among all cluster groups. In addition, with respect to six
factors, this cluster was found to have the second largest mean score
(mean = 4.71) on “culture exploration” but had the lowest mean score on
“gambling” (mean = 1.79). Thus, this cluster was labeled the “family and
vacation seekers.” Visitors in Cluster 2 preferred to spend their time with
family, friends, and relatives, while shopping in Macau. Generally, this group
of visitors seeks to experience a different culture and to mix with other
tourists, as well as to visit Macau’s many historical landmarks filled with a
variety of colonial Portuguese and traditional Chinese architecture.
Cluster 3: gambling and shopping seekers.” This cluster contained 324
visitors. This cluster appeared to have the highest mean score on “gambling”
(mean = 4.18) and “shopping” (mean = 5.50) among the four cluster groups.
This cluster was labeled “gambling and shopping seekers” based on the
mean score characteristics with respect to the factors. Cluster 3 is generally
satisfied with all the factors of motivations except “business and convention
(mean = 1.64).” As gambling and shopping seekers, they are particularly
interested in betting at the city’s several casinos as well as taking advantage
of the traditional street markets and the high-end luxury boutiques. Macau is
a free port zone where goods are sold at duty-free prices with no sales taxes.
The shopping scene in Macau is also known for its bargain deals; therefore,
visitors to this destination may enjoy additional savings on their purchases.
Cluster 4: multi-purpose seekers.” This cluster contained 324 visitors.
This cluster had the lowest mean score across three activity factors—“Culture
exploration” (mean = 3.80), “Family togetherness” (mean = 3.02), and
“Shopping” (mean = 3.00)—when compared to the other three clusters.
Thus, Cluster 4 was named the “multi-purpose seekers.” Interestingly, one
of the main activities in Macau, “Gambling,” is the lowest mean score among
all motivation factors in Cluster 4. It reasons, therefore, that visitors in this
cluster do not visit Macau for the purpose of gambling.
Cluster Differences by Macau Visitors’ Characteristics
To further understand the characteristics comprising the four clusters, each
cluster was cross-tabulated with the socio-economic and demographic
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44 W.G.Kimetal.
profiles of Macau visitors. In Table 4, the results of χ
2
tests indicate that
there were statistically significant differences among the four clusters with
respect to visitors’ socio-economic, demographic, and travel behavioral
characteristics.
TABLE 3 Results of Factor Analysis of Macau Visitors’ Activities and Motivations
Factor label and attributes Mean
a
Factor
loadings Eigenvalue Variance (%)
Reliability
coefficient (α)
Benefit Factor 1: Gambling 3.20 5.20 22.62 .91
To play other table games 3.23 .86
To play blackjack 3.42 .86
To play baccarat 3.47 .85
To play slot machines 3.48 .79
To bet on horse racing 2.83 .78
To play other sport
betting
2.79 .76
Benefit Factor 2:
Convention and business
3.12 2.91 12.65 .92
To do business 3.14 .92
To attend meetings and
conventions
3.10 .92
Benefit Factor 3: Pleasure 3.64 2.51 10.91 .74
Be entertained at the
night life
3.55 .73
Do exciting things 3.72 .72
Getting away from
pressures and
responsibilities
3.35 .69
To visit new and exciting
place
3.93 .55
Benefit Factor 4: Culture
exploration
4.24 1.75 7.60 .64
To experience a different
culture
4.18 .85
To visit its cultural and
historical setting
4.87 .84
To mix with other tourists 3.67 .43
Benefit Factor 5: Family
togetherness
4.19 1.33 5.77 .63
Do something with family 4.55 .77
Visiting friends and
relatives
3.71 .75
To spend time with
family and friends
4.31 .68
Benefit Factor 6: Shopping 4.09 1.17 5.09 .69
To buy clothing 3.14 .84
Go shopping 5.04 .79
Total % of variance 64.64
Note: Principal component factor analysis (PCA) was employed in each category with iterations: Varimax
rotation in SPSS/PC routine.
a
Mean values were computed on the basis of 7-point Likert-type scale from 1 (Strongly disagree)to7
(Strongly agree).
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TABLE 4 Results of Cluster Analysis for Macau Visitors’ Activities and Motivations
Scheffe multiple range tests
Variable/Motivator
Cluster 1
(n = 554)
Cluster 2
(n = 311)
Cluster 3
(n = 324)
Cluster 4
(n = 324) F-value 1–2 1–3 1–4 2–3 2–4 3–4
Gambling 3.98
a
1.79 4.18 2.26 401.33
∗∗∗ ∗∗∗ n.s.b ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗
Business and
convention
4.93 2.22 1.64 2.39 736.00
∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ n.s. ∗∗∗
Pleasure 4.16 3.15 3.64 3.21 66.78
∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ n.s. ∗∗∗
Culture exploration 4.76 4.71 4.32 3.80 51.89
∗∗∗ n.s. ∗∗∗ ∗∗∗ ∗∗ ∗∗∗ ∗∗∗
Family togetherness 4.82 4.96 3.50 3.02 260.79
∗∗∗ n.s. ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗
Shopping 4.77 5.32 5.50 3.00 344.57
∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ n.s. ∗∗∗ ∗∗∗
Cluster name Business and
convention
seekers
Family and
vacation
seekers
Gambling and
shopping
seekers
Multi-purpose
seekers
Pillai Trace = 1.565
∗∗∗
Wilks’ Ramda = .100
∗∗∗
Hotelling-Lawley Trace = 3.702
∗∗∗
Roy’s Greatest = 2.110
∗∗∗
a
Mean values were computed on the basis of 7-point Likert-type scale 7 (Strongly agree)to1(Strongly disagree).
b
n.s. indicates “not significant.”
∗∗∗
Significant at p < .001.
45
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46 W.G.Kimetal.
The r esults in Table 5 disclose that “convention and business seekers”
were primarily originated from other Asian countries (47.8%) and, to a lesser
extent, China (28.8%), while “family and vacation seekers” mainly originated
from China (40%). A majority of “gambling and shopping seekers” were
from China (55%), followed by Hong Kong residents (28.8%), while a clear
majority of “multi-purpose seekers” were from Hong Kong (37.6%), followed
by visitors coming from Europe, North America, and Australia/New Zealand
(23.7%). A majority of each of the four clusters reported that they did not fly
to Hong Kong before coming to Macau. In total, only 30% of visitors flew to
Hong Kong before coming to Macau. The primary mode of transportation,
however, of “convention and business seekers” was by plane, while “family
and vacation seekers” and “gambling and shopping seekers” was dominated
by boat, followed by car. “Multi-purpose seekers” overwhelmingly used boat
as their main transportation mode.
Primarily, “convention and business seekers” traveled alone, while “fam-
ily and vacation seekers” and “gambling and shopping seekers” traveled
with two or more companions. A majority of “multi-purpose seekers” vis-
ited by themselves or with only one companion. A majority of “convention
and business seekers,” “family and vacation seekers,” and “gambling and
shopping seekers” visited Macau as day visitors, while “multi-purpose seek-
ers” stayed one night or more. Both “convention and business seekers” and
“multi-purpose seekers” mostly stayed at hotels, while “family and vaca-
tion seekers” mainly lodged at friends’ or relatives’ houses. A majority of
“gambling and shopping seekers” stayed at casino properties. Most of the
four groups did not purchase package trips during their visit to Macau,
and surprisingly the main purpose for visiting Macau was non-gambling
activities.
“Family and vacation seekers” was comprised mostly of female visitors,
while males dominated the “convention and business seekers,” “gambling
and shopping seekers,” and “multi-purpose seekers.” “Gambling and shop-
ping seekers” were slightly older crowds, mostly in their 30s and 40s and
had low incomes, while the remaining three clusters were largely in their 20s
and 30s. The annual income of “multi-purpose seekers” was higher than the
other three groups; approximately one-fourth of this cluster’s respondents
reported an annual income of $48,000 or above. On the other hand, only
approximately one-tenth of “gambling and shopping seekers” belonged to
the highest income group of $48,000 or above. “Convention and business
seekers” were largely single, while the majority of the other groups’ mem-
bers were married. “Convention and business seekers” were relatively highly
educated, most frequently at the level of bachelor’s degree. The remain-
ing three groups’ education levels were mainly high school degrees or
partial completion of undergraduate degrees. The primary job of most of
the “convention and business seekers” and “multi-purpose seekers” was
professional/administrative. The remaining two groups’ main occupation
was clerical employees.
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International Travelers to Macau, China 47
CONCLUSION AND IMPLICATIONS
The purpose of this study is to examine, by using benefit-sought market
segmentation, the differences between four cluster groups of tourists visit-
ing Macau with regard to their behavioral (i.e., travel party type, length of
stay, etc.), socio-economic, and demographic profiles. We believe that our
study adds value to the tourism management literature related to Macau.
First, we consider our benefit segmentation analysis to be unique, because
previous research on tourism development related to Macau has focused
mainly on destination image and branding. Second, although one could
argue that the segments found in this research may have been predictable
prior to the study; our exclusive investigation of the differences between the
four cluster groups complements past image studies and raises important
managerial implications. Third, this study is different from other segmen-
tation research carried out in other gambling destinations. For example,
Park et al. (2002) segmented casino gamblers in Colorado, USA, based
on involvement patterns in order to develop market segmentation profiles.
Unfortunately, Park et al. (2002) failed to show significant differences among
clusters for behavioral (i.e., travel party type, length of stay, etc.), demo-
graphic, and socio-economic variables. Given both the results of Colorado
and Macau, this current study finds significant differences among the four
groups concer ning Macau visitors’ socio-demographic and travel behavioral
characteristics. Therefore, this benefit segmentation analysis makes a con-
tribution to finding the uniqueness of tourists who visit Macau not only
for gambling purposes, but also for convention, business, pleasure, cultural,
family togetherness, and shopping reasons as well. In addition, the find-
ings of this study should be valuable to help Macau’s destination marketers
develop marketing strategies, such as package products in order to attract
a wider base of travel segments and to diversify the tourist mix in terms of
various perspectives. Cluster analysis indicated four distinct clusters: “con-
vention and business seekers,” “family and vacation seekers,” “gambling and
shopping seekers,” and “multi-purpose seekers.”
The “convention and business seekers” cluster was mainly from other
Asian countries with airfare as a major transportation tool. The main charac-
teristics of the cluster are summarized as follows: relatively highly educated,
high income, male-dominated, and traveled alone. To attract more of these
visitors, hotel operators should focus their marketing efforts on attracting
more convention businesses by targeting major companies in the Asia-Pacific
region. With the development of the new “Cotai Strip,” which is composed
of several large-scale lodging and casino properties with over three million
square feet of meeting and convention space as well as the new interna-
tional routes from the local airport, Macau will be able to position itself as
Asia’s premier entertainment and MICE destination. Business travelers are
recognized as one of the most important segments of the travel market due
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TABLE 5 Cluster Differences by Macau Visitors’ Characteristics (%)
Cluster 1 (n = 554) Cluster 2 (n = 311) Cluster 3 (n = 324) Cluster 4 (n = 324)
Characteristics
Convention and
business seekers
Family and
vacation seekers
Gambling and
shopping seekers
Multi-purpose
seekers χ
2
Country (n = 1513)
China 28.88% 40.19% 55.56% 19.14% 272.04
∗∗∗
Hong Kong 12.27% 20.90% 21.60% 37.65%
Other Asia 47.83% 24.12% 11.73% 19.44%
Europe/America/Australia 13.86% 14.79% 11.11% 23.77%
Fly to Hong Kong (n = 1513)
Yes 20.58% 24.44% 41.98% 39.81% 64.90
∗∗∗
No 79.42% 75.56% 58.02% 60.19%
Transportation to Macau (n = 1235)
Car 25.65% 35.14% 33.84% 9.64% 226.45
∗∗∗
Boat/ferry 21.77% 35.52% 48.67% 67.07%
Air/flying 51.08% 24.71% 15.97% 21.69%
Others 1.51% 4.63% 1.52% 1.61%
Accompany number ( n = 1510)
1 Person 47.74% 25.89% 25.93% 44.14% 69.329
∗∗∗
2 People 28.93% 37.54% 42.28% 29.94%
3 People and over 23.33% 36.57% 31.79% 25.93%
Stay number ( n = 1513)
Day visit 23.52% 27.97% 28.09% 41.36% 31.797
∗∗∗
1 night or more 76.48% 72.03% 71.91% 58.64%
Accommodation type (n = 1071)
Casino property 36.94% 25.99% 74.68% 50.54% 163.53
∗∗∗
Non-casino property
a
35.76% 34.80% 18.45% 39.78%
Friend/relatives’ house 26.82% 38.77% 6.44% 9.14%
Others 0.47% 0.44% 0.43% 0.54%
48
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Package trip to Macau (n = 1513)
Yes 6.86% 9.65% 24.69% 11.93% 62.105
∗∗∗
No 93.14% 90.35% 75.31% 88.07%
Gender (n = 1513)
Male 63.00% 41.80% 64.81% 61.30% 64.74
∗∗∗
Female 37.00% 58.20% 35.19% 38.70%
Age, years (n = 1513)
19 and under 5.60% 8.68% 4.32% 5.56% 74.50
∗∗∗
20–29 34.30% 35.69% 27.16% 31.48%
30–39 40.43% 27.65% 30.25% 25.93%
40–49 14.08% 18.97% 30.86% 25.31%
50–59 4.69% 7.07% 7.41% 9.57%
60 and over 0.90% 1.93% 0.00% 2.16%
Marital status (n = 1513)
Single 52.89% 44.37% 39.51% 46.30% 19.48
∗∗
Married 44.77% 54.66% 58.02% 50.93%
Other 2.35% 0.96% 2.47% 2.78%
Education (n = 1513)
Elementary school 1.44% 1.61% 2.47% 2.47% 53.04
∗∗∗
High school 27.98% 32.48% 36.11% 30.56%
Undergraduate students 27.44% 22.51% 36.11% 25.93%
Bachelor’s degree 30.87% 29.90% 18.21% 24.07%
Graduate students 5.05% 6.11% 4.63% 5.86%
MS/PhD degree 6.32% 6.43% 1.85% 10.49%
Other 0.90% 0.96% 0.62% 0.62%
Occupation
b
(n = 1513)
Professional/administrative 39.71% 28.62% 32.10% 35.49% 43.99
∗∗∗
Agricultural worker 1.44% 0.64% 2.16% 1.54%
Clerical employee 26.35% 30.87% 37.35% 25.62%
Government employee 5.60% 8.04% 4.63% 3.40%
In-house worker 20.94% 28.94% 18.21% 27.78%
Other 5.96% 2.89% 5.56% 6.17%
(Continued)
49
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TABLE 5 (Continued)
Cluster 1 (n = 554) Cluster 2 (n = 311) Cluster 3 (n = 324) Cluster 4 (n = 324)
Characteristics
Convention and
business seekers
Family and
vacation seekers
Gambling and
shopping seekers
Multi-purpose
seekers χ
2
Annual income (US$) (n = 829)
Below $11,999 26.10% 28.21% 27.61% 12.43% 27.14
∗∗∗
$12,000-$23,999 30.21% 30.13% 26.38% 31.36%
$24,000-$35,999 14.08% 12.18% 20.86% 18.93%
$36,000-$47,999 10.26% 10.26% 13.50% 13.02%
$48,000 and over 19.35% 19.23% 11.66% 24.26%
a
Non-casino property includes hotel, motel, and guest house.
b
Clerical employee includes salesman, clerical employee/production, or service worker; government employee includes military employee; and in-house worker
includes unpaid worker, student/ retired, or unemployed.
∗∗
Significant at p < 0.01.
∗∗∗
Significant at p < 0.001.
50
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International Travelers to Macau, China 51
to their large travel expenditure budget . Therefore, it is important for MICE
managers and tourism policy makers in Macau to understand the motivation
drivers and satisfaction levels of business and convention visitors.
A recently published study on attendees’ motivation and satisfaction of
a mega-business event held in Hong Kong (Bauer, Law, Tse, & Weber, 2008)
highlighted that the major motivational factors to attend the event were
the opportunities for business and networking as well as the business and
educational content of the event. According to Bauer et al. (2008), similar
studies have found that the safety, location, and infrastructure of the destina-
tion influenced the decision-making process of business and events’ visitors.
Their study also found that event attendees were mostly satisfied with the
accessibility, cleanliness, safety, and security of the destination, as well as
the tolerance for other cultures, quality of the exhibition, and the opening
hours of shops. Hence, these findings may serve as a foundation for the
Macau tourist bureau and hospitality managers to enhance the motivation
and satisfaction levels of their business and convention guests.
In addition, the Macau tourism bureau should consider offering more
value-added tourism products, such as post-convention tour packages for
visitors who are affluent and traveling alone. Moreover, night life activities
could be major attractions for groups of tourists, and information about night
shows should be easily available to this segment of tourists.
The second group, “family and vacation seekers,” was mainly from
China with boat/ferry or car as their major transportation mode. The main
characteristics of this cluster are summarized as follows: visited mainly for
sightseeing/culture exploration; traveled with two or more companions; pre-
ferred to stay at friends’ or relatives’ homes rather than a hotel; and worked
primarily as clerical employees and in-house workers. Due to their relatively
low income and their desire to stay with friends or relatives, they may not
provide much impact on the hotel industry. However, this cluster group may
have a significant impact on Macau’s restaurant and entertainment industries.
This group may go out with their friends and family to visit local restaurants,
bars, and entertainment complexes.
Since Mainland Chinese travelers account for 40.1% of the “family and
vacation seekers,” it is crucial for restaurant managers and operators to
understand how visitors from China choose restaurants. A recent study from
Law, To, and Goh (2008) investigated the perception of Chinese visitors
on the importance of attributes on restaurant selection in Hong Kong. The
attributes loaded into five different factors, namely 1) food and beverage; 2)
service; 3) price; 4) environment; and 5) attraction. Under food and bever-
age, the most important attributes for Mainland Chinese travelers were the
quality and variety of menu items. Respondents claimed that restaurants in
Hong Kong do not provide as many menu items as restaurants in China and
that the taste of the food was lighter than the restaurants on the Mainland. As
far as service, the most important attributes were servers’ attitudes and speed
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52 W.G.Kimetal.
of service. Value for money was also a important factor for the respondents
as they viewed that restaurants in Hong Kong were very expensive. The
environment factor showed that hygiene/cleanliness and comfort were the
two most important attributes for restaurant selection. Finally, respondents
were most attracted to restaurants through word-of-mouth. Therefore, in
order to captivate this cluster, Macau restaurant operators should provide an
extensive list of menu items with the stronger flavors accustomed by Chinese
residents. Food should be reasonably priced to appeal to this group of trav-
elers, and restaurants must show signs of cleanliness from an environment
and food production point of view. In addition, Macau restaurant employees
must be trained to better communicate and interact with their customers. By
taking these steps, and by enhancing the promotional efforts geared toward
providing more information about the different cuisines at these outlets,
Macau may result in a larger number of visitors, thereby increasing their
revisit-repurchase intention.
The third cluster, “gambling and shopping seekers,” was visiting pri-
marily for the purpose of gambling, traveled with two or more companions,
preferred to stay at casino hotels, purchased non-packaged trips, had lower
incomes, and were male-dominated. Casino hotels rely heavily on this mar-
ket segment as a major revenue source and a primary customer base.
Shopping outlets inside the casino properties will benefit from this segment.
In order for Macau to boost its fashion retailing industry, it is important
that retail owners and operators understand shopping behaviors and pref-
erences of Mainland Chinese visitors, because they compose 55% of this
cluster group. As the Chinese economy continues to develop, Mainland res-
idents will tend to become more sophisticated and knowledgeable; thus,
Chinese people will increase their standards when choosing apparel prod-
ucts. Yuan and McDonald (1990) defined Mainland travelers to Hong Kong
as “ethnic, arts, and people” and “urban entertainment oriented.” In their
study, the researchers concluded that both types of people like spending a
considerable time of their time during travel in fashion stores. In addition,
they also found that Chinese visitors enjoy interacting with sales personnel
when shopping. In a more recent study, Choi et al. (2008) found that Chinese
visitors to Hong Kong were not satisfied with the interaction with the stores
sales’ personnel because they were not able to describe the product charac-
teristics in detail. This problem may exist because many of the sales agents
cannot speak Mandarin. Therefore, formal training for sales personnel and
hiring applicants who can speak Mandarin are two important factors to be
considered by retail owners based in Macau.
The fourth group, “multi-purpose seekers,” was primarily from Hong
Kong, arrived via boat/ferry, visited mainly for sightseeing/culture, traveled
with only one companion, stayed at casino or hotel, had modest incomes,
and were mostly male. The Macau tourist bureau should target this group
of visitors by promoting cultural heritage products combined with souvenir
Downloaded By: [Oklahoma State University] At: 12:26 7 February 2011
International Travelers to Macau, China 53
sales. Due to their short stay, however, these tourists may not generate high
revenues for the lodging industry; thus, they do not comprise an especially
lucrative cluster group. The casino industry would be better rewarded tar-
geting tourists who are potential high rollers, though upscale casino hotels
or independent restaurants may develop special promotional packages to
attract couples who are looking for a romantic atmosphere.
“Gambling and shopping seekers” showed the lowest percentage of
the highest income group, while the largest portion of “multi-purpose seek-
ers” fell into the highest income group. One plausible reason for this fact
might be the visitors’ country of origin. Many “multi-purpose seekers” are
from Hong Kong, while a large number of “gambling and shopping seekers”
originated from Mainland China. There still exists a significant difference
between the average annual incomes of Hong Kong and Chinese citizens.
Another possible reason might be that a large number of low-income gam-
blers visit Macau to take advantage of the heavy promotional efforts of the
casino industry. Thus, it is critical for the Macau tourism bureau to attract
the rapidly growing number of high income tourists from China, who may
currently prefer to visit other tourist destinations for gambling and shopping.
LIMITATIONS AND FUTURE RESEARCH
As with any research, ours is not free of limitations. Due to time and budget
constraints, the data collection was conducted during the summer period
of 2007; thus, this study may not have been able to avoid the seasonality
effect. In addition, a convenience sample method was applied, and there-
fore, the results of our findings may contain some biases. Consequently,
future research in this area should be conducted on two occasions, both
the low and high seasons, and should apply some form of random sam-
pling in order to eliminate bias. Nevertheless, we believe that the size of
our sample supports any statistical analysis performed in this study, thereby
capturing the reality of summer travelers to Macau. Finally, our study did not
capture visitors’ expenditures and loyalty levels. By including these types of
data in the investigation, important managerial implications could be drawn
from the findings. Therefore, future studies may analyze the relationship
between tourist benefits sought and expenditure profiles of travelers, and
compare the results of first-time visitors with repeat tourists and their impact
on loyalty and satisfaction with the destination.
Our study has found distinct benefit clusters of international travelers
visiting Macau. Future research in this area must be continued since Macau
is a special destination. First, Macau is a “new” destination and its tourism
industry is developing at an extraordinary rate. Consequently, the benefits
sought and the motives of travelers when considering Macau as destination
may change over time. Second, due to the destination’s unusual nature and
Downloaded By: [Oklahoma State University] At: 12:26 7 February 2011
54 W.G.Kimetal.
culture, different clusters may be formed as Macau itself develops. Thus,
destination marketers from Macau should further this research in order to
improve its marketing strategy, and thereby to gain the highest return from
their investment.
The results of this proposed analysis should enhance the knowledge of
destination marketers, which in turn will be able to develop homogenous
markets through benefit segmentation as well as to attract the big spenders.
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... As an a posteriori approach, benefit segmentation relies on the analysis data to gain insight into the market structure and decide which segmentation base is the most suitable one (Dolnicar, 2008:3). Sheng, 2011;Rudež, Sedmak & Bojnec, 2013;Dong, Wang, Morais & Brooks, 2013;Almeida et al., 2014). However, the focus has been solely on using benefits to promote a destination (Frochot & Morrison, 2000): integrating benefits, attractions and activities available at a destination to develop product and marketing planning tools has not been done. ...
... Sarigöllü and Huang (2005) found that security was affecting the Latin-American tourism industry, as security and the friendliness of the locals were considered more important than other factors. A study by Kim et al. (2011) examined differences between four cluster groups visiting Macau, China with regard to their behaviour, socio-economic and demographic segments using benefit segmentation. Amongst clusters identified by Kim et al. (2011), significant differences related to socio-economic, demographic and travel behaviour characteristics. ...
... A study by Kim et al. (2011) examined differences between four cluster groups visiting Macau, China with regard to their behaviour, socio-economic and demographic segments using benefit segmentation. Amongst clusters identified by Kim et al. (2011), significant differences related to socio-economic, demographic and travel behaviour characteristics. Their study therefore suggests that further analysing benefit segments contributes to finding the specific characteristics of tourists who visit a destination and passing them on to the destination' marketer, which will assist in developing homogeneous markets. ...
... Previous tourism studies have successfully adopted the approach of segmenting tourists according to benefits (Almeida et al., 2014;Dong et al., 2013;Frochot, 2005;Jang et al., 2002;Kim et al., 2011;Molera and Albaladejo, 2007;Sarigö llü and Huang, 2005;Yannopoulos and Rotenberg, 2000;Rudež et al., 2013). The emphasis of previous studies has solely been on using benefits to promote a destination (Frochot and Morrison, 2000). ...
... Frochot and Morrison (2000) maintain that a focus on tourist motivations is attributed to a growing interest in benefit segmentation in travel and tourism studies (Frochot and Morrison, 2000, p. 23). Various scholars (Almeida et al., 2014;Dong et al., 2013;Frochot, 2005;Jang et al., 2002;Kim et al., 2011;Molera and Albaladejo, 2007;Rudež et al., 2013;Sarigö llü and Huang, 2005;Yannopoulos and Rotenberg, 2000) have identified diverse benefits, which are unique to each segment. These scholars agree that even though a destination specialises in a niche product such as nature or rural tourism, this does not necessarily mean that such benefits will be the most sought after (Frochot, 2005;Molera and Albaladejo, 2007;Dong et al., 2013;Almeida et al., 2014). ...
... Therefore, destination marketing managers need to uncover tourists' true motivation for visiting a destination, to segment, target and position a destination strategically (Frochot, 2005, p. 344;Rudež et al., 2013, p. 139). Studies such as those of Kim et al. (2011) andJang et al. (2002) highlight the importance of discovering other factors, such as expenses, attractions visited and activities participated in to prioritise marketing efforts further, thus offering tourism destination marketers more information. As one of their recommendations for future research in benefit segmentation, Jang et al. (2002) suggest that benefit segmentation studies should incorporate other variables, such as activities, to offer a richer segment. ...
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... Second, some studies focused the issue of travel benefits on domestic travel (Shoemaker, 1994;Yannopoulos & Rotenberg, 2000), whereas some were interested in international tourists' perceived benefits (Goodrich, 1977;Kim et al., 2011). Based on foreign travel, specific concerns in travel benefits have been proposed, such as airfare cost (Goodrich, 1977), safety and security (Moscardo et al., 1996), culture appreciation (Ahmed et al., 1997), and learning factor (Almeida et al., 2014). ...
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