Ⅰ. Introduction

Medical tourism is defined as the act of travelling abroad

to obtain various types of health and wellness treatments

(Reddy, York, & Brannon, 2010). As the level of income

and the average quality of life have greatly increased,

medical tourism has become one of the fastest-growing

business sectors globally (Han, 2013; Han & Hyun, 2015;

Yu & Ko, 2012). For instance, recent studies have shown

that the worldwide medical-tourism industry generated

profits of US$60 billion per year, growing at a rate of about

20% annually (Heung, Kucukusta, & Song, 2011; Yu & Ko,

2012). In addition, the number of medical tourists is

* This work was supported by the National Research Foundation

of Korea Grant funded by the Korean Government(NRF-2014S1A

5A8015954).

** Assistant professor, The College of Hospitality and Tourism

Management, Sejong University, e-mail: jhwang@sejong.ac.kr

† (Corresponding author) Assistant Professor, Department of Tourism

Management, College of Economics and Business Administration,

Daegu University, e-mail: kw.lee@daegu.ac.kr

expected to increase to twenty-three million by 2017

(Deloitte, 2009). These statistical figures encourage many

countries to focus more on the medical-tourism industry by

providing various medical/healthcare locations and

enhancing related products/services (Crozier & Baylis,

2010; Han, 2013; Heung et al., 2011).

Medical tourists need to make plans for many facilities

(e.g. medical treatment, healthcare services, and lodging)

separately when choosing a medical tourism destination

because such facilities are independently operated (Han,

2013; Yu & Ko, 2012). To overcome this difficulty, meditels

rapidly rose as a superior alternative. A meditel provides

integrated services such as a hospital, healthcare esthetic

centers, and a hotel, which have the important function of

satisfying international medical tourists’ various wants and

needs (Han, 2013). For instance, medical tourists can

receive professional medical treatment and healthcare

services while staying in their accommodations. Through

such integrated services, medical tourists can save time and

money (Docrates, 2011; Largent, 2011; Oh, 2011).

International Journal of Tourism and Hospitality ResearchVolume 30, Number 10, pp. 29-41, 2016 ISSN(Print): 1738-3005Homepage: http://www.ktra.or.kr DOI: http://dx.doi.org/10.21298/IJTHR.2016.10.30.10.29

A study of customer segmentation based on perceived value in the meditel industry using decision tree analysis*

Jinsoo Hwang**⋅Kwang-Woo Lee†1)

The College of Hospitality and Tourism Management Sejong University, Seoul, 05006, Korea

Department of Tourism Management, College of Economics and Business Administration, Daegu University,

Gyeongsan-si, Gyeongsangbuk-do, 38453, Korea

AbstractThe objectives of this paper were to (1) examine the types of perceived value in the meditel industry, (2) investigate

whether or not respondents can be grouped into distinct subsegments based on the types of perceived value, and (3) explore whether or not statistical differences exist among the subsegments based on socio-demographic and travel-related profiles. First, using principal component factor analysis, 23 perceived value items were divided into three factors. Second, after conducting K-means cluster analysis based on the three perceived value factor scores, three groups were categorized as “monetary and convenience advantages seeker,” “availability of products/services seeker,” and “personal security seeker.” Lastly, the results of the decision tree analysis indicated that there were statistically significant differences among the three groups in terms of both socio-demographic and travel-related profiles. The results of this study have significant implications for the management of meditels.

Key words: Meditel, Perceived value, Segmentation, Travel-related profile, Decision tree analysis

30 A study of customer segmentation based on perceived value in the meditel industry using decision tree analysis

Unlike previous studies on meditels, this study is the first

to aim to identify the differences of perceived value based on

socio-demographic and travel-related profiles. To achieve

this purpose, the concept of value-based segmentation was

applied to this study. Value-based segmentation has its origin

in customer segmentation, which has been widely used in the

marketing area because it plays an important role in

developing effective marketing strategies (Cermakr, File, &

Prince, 1994; Wu & Chou, 2011). Customer segmentation

involves characterizing subgroups based on specific values

(Kotler, Bowen, & Makens, 2005). For example, certain

customers commonly prefer similar values in the

products/services; thus, if the company divides such

customers into subgroups based on similar values, the

company can manage their customers more efficiently. For

this reason, customer segmentation has been in the spotlight

as an effective tool for understanding target customers (e.g.

Bowen, 1998; Gad Mohsen & Dacko, 2013).

Despite the importance of meditels, this area has

received little attention. More importantly, there has been

no research exploring the importance of socio-demographic

and travel-related profiles in the meditel industry even

though personal characteristics are highly correlated with

international patient-travelers’ decision formation (Han,

2013). Therefore, this study attempts to fill this research gap

by identifying the differences of perceived value based on

socio-demographic and travel-related profiles. More

specifically, this study focuses on (1) investigating the types

of perceived value in a meditel, (2) exploring whether or not

respondents can be grouped into distinct sub-segments

based on the values, and (3) identifying whether or not there

are statistical differences in socio-demographic and

travel-related profiles among the sub-segments. The results

of the study will help meditel managers to better understand

value-based segmentation and use this understanding in

developing effective marketing strategies based on socio-

demographic and travel-related profiles.

Ⅱ. Literature review

1. The meditel and its differentiated values

A meditel is a new form of hotel and a new niche market

that has recently emerged in the medical tourism industry.

Therefore, there is a lack of research on meditels. A meditel

(also known as medical hotel) refers to lodging facilities,

including hospitals and various healthcare/esthetic

facilities within a single property (Docrates, 2011; Han,

2013; Han & Hyun, 2014). As shown in the definition, a

meditel provides both the hotel services/products (e.g. hotel

room, F&B, spa and sauna facilities, fitness facility, etc.)

and hospital services/products (e.g. major surgery, cancer

treatment, emergency rooms, eye surgery, dental

care/surgery, physical therapy, etc.) (Han, 2013; Hume &

DeMicco, 2007; Sheehan-Smith, 2006). For this reason, a

meditel is known as an integrated facility.

A meditel provides some differentiated values compared

with other facilities. First, meditel customers can benefit

from physical conveniences as they can receive various

types of medical treatment/healthcare in their rooms

without moving to other facilities (Han, 2013). Second,

meditel customers can reap monetary values (Han, 2013;

Han et al., 2015). The meditel offers the package prices

including both medical facilities and hotel services

(Docrates, 2011; Largent, 2011; Oh, 2011). Therefore,

meditel customers can use medical facilities and hotel

services with discounted prices at a time. Third, medical

tourists enjoy more specialized services in the meditel. For

instance, most meditel customers are international

travelers, so a meditel provides medical-tourism translators

and medical-tourism-specialized coordinators, which make

meditel customers comfortable (Docrates, 2011; GHN,

2011; Han, 2013; Hwang, 2011; Medical Hotels, 2011; Oh,

2011). In addition, a meditel consists of highly trained

medical teams with advanced medical technology and

equipment, so international travelers can receive

specialized health care services (Docrates, 2011; Han,

2013; Han & Hwang, 2013; Largent, 2011; Medical Hotels,

2011). Because of the various values discussed above, it is

expected that more medical tourists will use meditels (Han,

International Journal of Tourism and Hospitality Research 30(10), 2016 31

2013). However, very little research has focused on

meditels compared to other types of hotels. Therefore, the

results of this research are highly meaningful and useful in

understanding the characteristics of the meditel industry.

2. Value-based segmentation

Customer segmentation is an important part of today’s

overly competitive business landscape (Gad Mohsen &

Dacko, 2013; Jonker, Piersma, & Van den Poel, 2004). The

concept of customer segmentation was first introduced by

Wendell R. Smith in the 1950s. Customer segmentation

refers to “dividing a market into distinct groups who might

require separate products and/or marketing mixes” (Kotler

et al., 2005, p. 262). Customer segmentation involves

characterizing subgroups according to shared characteristics

or behaviors (Floh et al., 2014; Marcus, 1998). Its purpose is

to ensure the effective and efficient use of marketing

planning and funding and the creation of a marketing

strategy that targets particular segments (Bowen, 1998; Wu

& Lin, 2005). Therefore, customer segmentation has the

following benefits: (1) it saves expenses and time in

understanding and managing a certain segment and (2)

facilitates the creation of efficient management involving

the targeting groups (Baalbaki & Malhotra, 1993; Kim et al.,

2006; Wu & Lin, 2005).

In the same vein, value-based segmentation is a method

used to divide customers into subgroups based on specific

values that customers seek in the products/services (Kotler

et al., 2005). Value-based segmentation aids in the planning

of marketing strategies by making it easier to address the needs

of particular value segments, finding a niche market that

allows a new company or new product to target less

competitive market areas, and making more efficient and

effective use of marketing resources by focusing on segments

(Kotler et al., 2005; Musyoka et al., 2007). Therefore, if

value-based segmentation is not handled correctly, marketing

efforts may be less effective and less profitable.

3. Effects of socio-demographic and travel-related

profiles on value-based segmentation

Psychological values differ from individual to individual

(Bloch, Brunel, & Arnold, 2003), so personal characteristics

have been widely used in identifying the differences among

value segments in the marketing field (Mittal & Kamakura,

2001). Empirical studies further support this theoretical

argument. For instance, Jang, Morrison, and O’Leary (2002)

investigated the effects of socio-demographic and trip-

related profiles on value segments using empirical data

collected from 496 tourists. Based on data analysis results,

they found the important role of socio-demographic and

trip-related profiles in identifying the differences among three

value segments: (1) novelty/nature seekers, (2) escape/

relaxation seekers, and (3) family/outdoor activities seekers.

In addition, Kim, Timothy, and Hwang (2011) examined the

role of socio-demographics and travelers’ shopping patterns

in understating the differences among two value segments:

(1) tourists seeking attractiveness of a shopping destination,

and (2) tourists seeking quality of shopping products. They

analyzed empirical data collected from 300 tourists and found

that socio-demographics and travelers’ shopping patterns

play an important role in identifying the differences among

the two value segments. More recently, Lyu and Lee (2013)

conducted a value segmentation study on golf event tourists.

By analyzing the data collected from 211 tourists, they found

the effect of socio-demographics and golf-related profiles on

four types of value segments: (1) escape seekers, (2) exercise

seekers, (3) interest seeker, and (4) excitement seekers. As

revealed in theoretical and empirical research, previous

studies have clearly shown that personal characteristics are

important in identifying the differences among value

segments.

Ⅲ. Methodology

1. Measurement

The questionnaire was designed to measure the perceived

value of meditels and socio-demographic and travel-related

32 A study of customer segmentation based on perceived value in the meditel industry using decision tree analysis

profiles. Unfortunately, there is no previous study focusing

on the perceived value of meditels, so a focus-group meeting

was conducted to develop measurements of the perceived

value of meditels. The focus-group consisted of a total of 15

individuals (e.g. medical-tourism experts in a related

organization, healthcare-hotel managers, operators of

various medical/healthcare clinics, hospitality/tourism

academics, and frequent medical travelers who have previous

experience staying at a meditel). All participants freely shared

ideas, opinions and thoughts regarding the perceived value

of meditels during the focus-group meeting. Consequently,

a total of twenty-three perceived values of meditels were

developed through this focus-group meeting. To assess

content validity (e.g. Hinkin,Tracey, & Enz, 1997), a total of

20 copies of the questionnaire were sent to experts in

hospitality and tourism management as well as medical-

tourism and healthcare-hotel practitioners. As a result, there

was no measurement item excluded from the initial survey

questionnaire. All the items were measured by asking

respondents to indicate their level of importance (very

unimportant (1), neutral (4), and very important (7)). In

addition, respondents’ socio-demographic and travel-related

profiles were measured as categorical variables.

The initial survey questionnaire was in English and then

was translated into Korean, Chinese, and Japanese through

a blind translation-back-translation process because most

tourists using the Gimhae International Airport (located on

Busan, Korea) can speak one of these languages.

Consequently, a total of four different language-related

versions of the questionnaire were used for data collection.

2. Data collection

An on-site survey was administered at an international

airport located in Busan, a city deemed one of the largest

medical/healthcare-tourism cities in Korea. All interviewers

were highly trained in order to understand the purposes of the

study and survey collection techniques. First, the interviewers

Variable n PercentageGender Male 105 39.8 Female 159 60.2Age 20s 57 21.6 30s 110 41.6 40s 65 24.7 50s or older 32 12.2Income Under US$25,000 70 26.5 US$25,001- US$40,000 87 33.0 US$40,001- US$60,000 59 22.3 US$60,001- US$80,000 26 9.8 Over US$80,001 22 8.3Education Level High school diploma 58 22.0 Some college, but no degree 32 12.1 Bachelor’s degree 154 58.3 Graduate degree 20 7.6Nationality Korean 98 37.1 Chinese 76 28.8 Japanese 47 17.8 American 43 16.3

Table 1. Respondents’ socio-demographic profile(n=264)

International Journal of Tourism and Hospitality Research 30(10), 2016 33

asked to get permission from international travelers waiting

for a flight. After receiving their consent, the interviewers

asked whether they had experienced medical tourism such as

medical treatment, healthcare/aesthetic services, or

beautification purposes. Before starting the questionnaire

survey, the purposes of this study were explained to the

participants, and the questionnaire survey was implemented.

Additional questions which the respondent could not

understand were well explained during the survey. On

completion of the survey, questionnaires were returned onsite

in order to ensure a higher response and usable rates. Through

these processes, a total of 423 questionnaires were collected.

However, 159 questionnaires were removed due to

incomplete questionnaires and multivariate outliers.

Consequently, a total of 264 questionnaires were used for

further analysis.

Ⅳ. Result

1. Profile of the sample

The sample consisted of 159 female respondents and

30s were 41.6%. Regarding the annual household income,

the highest percentage of respondents earned between

US$25,001 and US$40,000 (33.0%). In terms of education,

the largest categories were bachelor’s degree (n = 154,

58.3%) followed by high school diploma (n = 58, 22.0%)

group. In addition, the majority of the respondents were

Korean (n = 98, 37.1%) followed by Chinese (n = 76,

28.8%). Table 1 presents details of the socio-demographic

profiles.

Table 2 shows respondents’ travel-related profiles. Forty

respondents indicated that the purpose of travel was

medical treatment/healthcare (15.2%). The respondents’

frequency of travel for medical treatment/healthcare

showed that the majority had visited between 2 and 4 times

(n = 126, 47.7%). In addition, 30.7% of the respondents (n

= 81) traveled abroad for medical treatment/healthcare

within 6 months. With regard to information on meditels,

35.2% of respondents (n = 93) had ever heard of the

healthcare before completing this survey. Finally, 42

respondents (15.9%) have experienced a meditel.

2. Principal component analysis, reliability, and validity

Principal component factor analysis with varimax rotation

was carried out to identify the dimension of the perceived

Variable n PercentageHow many times you have traveled abroad for medical treatment/healthcare in the last 5 years: _______ time(s) One time 86 32.6 Two times 108 40.9 More than three times 70 26.5When was the last time you traveled abroad for medical treatment/healthcare? Within 1 month 41 15.5 Within 6 month 81 30.7 Within 1-2 years 78 29.5 Within 3-4 years 43 16.3 Within 5 years or more 21 8.0Had you ever heard of meditel and did you know what they were before completing this survey? Yes 93 35.2 No 171 64.8Have you ever stayed in a meditel? Yes 42 15.9 No 222 84.1

Table 2. Respondents’ travel-related profiles(n=264)

34 A study of customer segmentation based on the perceived value in the meditel industry using decision tree analysis

Factors (Staying in a healthcare hotel when traveling abroad for medical treatment/healthcare would enable me to~)Factor

loadingsEigen value

Explained variance

Cronbach’s alpha

Factor 1. Monetary and convenience advantages 6.844 29.755 .955 Pay a reduced rate for receiving medical treatment/healthcare and using hotel room/meal services together. .675 Be affordable thanks to the reduced expense or using multiple medical treatment/healthcare facilities together. .668 Save time for medical treatment/healthcare and recovery together in one building. .741 Reduce the time required to locate various types of treatment centers individually. .794 Enjoy physical convenience because of the relatively short distance between medical treatment/healthcare facilities

and rooms/restaurants..774

Reduce the effort needed to find medical/healthcare clinics and hotels separately. .790 Make it easier to access various types of medical treatment/healthcare facilities. .751 Possibly receive treatment in my room from highly trained professionals. .642 Easily communicate using my own language because of capable specially trained medical tourism translators. .702 Easily make staff members/coordinators understand my needs and wants related to medical treatment/healthcare because

of their good level of medical/healthcare knowledge..659

Factor 2. Availability of products/services 5.460 23.738 .929 Use a package involving various medical treatment and healthcare programs together (surgery, aesthetic services,

healthcare services, etc.) while staying in a hotel..611

Use a medical tourist package that relates medical treatment/healthcare to hotel room use and meal services to suit my individual needs.

.618

Stay in a hotel with greater privacy than other clinics. .576 Have greater confidentiality for surgery (e.g., cosmetic/plastic surgery) and aesthetic healthcare (e.g., diet programs). .521 Stay in a comfortable hotel room of better quality than other places. .790 Stay in rooms of various sizes/types with my family/friends/others if necessary. .809 Enjoy a wider range of quality foods and beverages at a reasonable price. .779 Possibly use various hotel services (e.g., room service, concierge service, business center, valet parking). .774Factor 3. Personal security 4.189 18.212 .917 Receive treatment by more reliable medical specialists and highly trained professionals compared to other clinics. .890 Reduce the uncertainty of medical quality such as surgical outcomes (e.g., less malpractice/medical accidents) and

nurse-patient ratio..832

Be secure in case of emergency because of the high availability of various medical personnel (nurses, physicians, etc.) 24 hours a day and 7 days a week.

.690

Receive reliable post-care service remaining in the hotel longer if necessary. .680 Select more credible international medical tourism insurance. .610Note: Total explained variance = 71.704%, KMO measure of sampling adequacy = .944, Bartlett’s test of sphericity (p<.001)

Table 3. Results of factor analysis for perceived values of meditel

International Journal of Tourism and Hospitality Research 30(10), 2016 35

value of a meditel. A factor loading cut-off of .40 was used

to retain items in the principal component factor analysis. In

addition, the communality established for each variable was

medium to high, ranging from .565 to .820. The communality

shows the proportion of common variance within a variable

(Field, 2000). Therefore, the score of communality in this

research suggested that the variance of the original values was

properly extracted by the three factors. The reliability was

evaluated by Cronbach’s alpha and was found to exceed the

recommended minimum level of .70 (ranging from .917 to

.955) (Nunnally, 1978). All factor loadings were greater than

.50, as recommended by Anderson and Gerbing (1988),

suggesting that convergent validity was also acceptable. The

appropriateness of factor analysis was assessed by the

Kaiser-Meyer-Olkin (KMO = .944) measure of sampling

adequacy and Bartlett’s test of sphericity (p < .001). As a result,

three factors were derived from the twenty-three items,

explaining 71.704% of the variance (see Table 3). Based on

the content of the factors, they were named as (1) “monetary

and convenience advantages” (eigenvalue = 6.844, explained

variance = 29.755%), (2) “personal security” (eigenvalue =

5.460, explained variance = 23.738%), and (3) “availability

of products/services” (eigenvalue = 4.189, explained variance

= 18.212%).

3. Cluster analysis

Cluster analysis was conducted to classify respondents

based on similarities in perceived value sought. The three

perceived value factors extracted in the principal

component factor analysis were conducted as clustering

variables. First, factor scores estimated from a three-factor

rotated solution were used to identify the number of similar

groups through hierarchical cluster analysis, suggesting

that either the two-cluster solution or the three-cluster

solution was optimal based on agglomeration schedules.

Then, K-means cluster analysis was used based on the two

different cluster solutions (n = 2 and 3). As a result, three

clusters were utilized for further analysis because definite

differences between the clusters were satisfactorily found.

In addition, each cluster was named according to the

characteristics of its composites. The characteristics of the

three clusters are as follows: Cluster 1: Monetary and

convenience advantages seekers (n = 43, 16.28%); Cluster

2: Personal security seekers (n = 71, 26.89%); and Cluster 3:

Availability of products/services seekers (n = 150, 56.81%).

4. Chi-square automatic interaction detection method

The major statistical analysis used in this study was the

Chi-square Automatic Interaction Detection (CHAID)

method in order to examine the role of socio-demographic

and travel-related profiles in identifying the differences

among the three segments. Kass (1980) first developed the

original CHAID method, which is applicable to situations

in which both independent and dependent variables are

nominal. The CHAID method is useful to (1) gain greater

information of potential customers and (2) identify which

customer groups purchase specific products (SPSS, 2009).

In the first phase of the CHAID method, a dependent

variable including more than two groups and two more

independent variables are chosen. The most significant

independent variable in dividing dependent groups into

homogeneous groups will be placed on the first node. In

other words, the order of independent variables is decided

based on the statistical significance of its homogeneous

effect on dependent groups. The number of categories of

independent variables is determined based on whether or

not the results of the chi-square test are statistically

significant.

Since the Decision Tree Analysis (DTA) program, which

provides the CHAID method, is the most suitable statistical

analysis for comparing the differences between groups

(SPSS, 2009), the DTA program was used to examine the

differences of socio-demographic and travel-related profiles

among the three segments in this study. There were three

groups in the dependent variable: (1) monetary and

convenience advantages seekers (n = 43), (2) availability of

products/services seekers (n = 71), and (3) personal security

seekers (n = 150). Three dependent groups were divided by

socio-demographic and travel-related profiles (independent

variables) (see Tables 1 and 2). Therefore, this study has

two models to test. That is, the dependent variables in the

two models were divided by socio-demographic and

36 A study of customer segmentation based on the perceived value in the meditel industry using decision tree analysis

travel-related profiles, respectively. All variables used in

this study were categorical measurements with two or more

categorical levels. The stopping rules for the DTA program

were a maximum tree depth of 3, minimum number of 25

for a given node, and a significant level for splitting of 0.05.

5. Results of DTA program for the perceived value

of meditel based on socio- demographic profiles

Figure 1 shows the results of DTA program for the

perceived value of meditels based on socio-demographic

profiles. In Node 0, there were three groups: (1) monetary

and convenience advantages seeker (n = 43, 16.29%), (2)

availability of products/services seeker (n = 71, 26.89%),

and (3) personal security seeker (n = 150, 54.82%). The first

division was based on the variable of “nationality” (χ2 =

43.28, d.f. = 6, p < .05). Node 0 was divided into four

groups: Nodes 1 (Korean), Node 2 (Chinese), Node 3

(Japanese), and Node 4 (American). Among four groups,

Node 3 and 4 explained the features of Japanese and

American, respectively. Node 3 indicated that most

Japanese are personal security seekers (n = 42, 86.36%). In

addition, Node 4 showed that the majority of American

were personal security seekers (n = 25, 58.14%) followed

by availability of products/services seekers (n = 14,

32.56%). The second division was based on the variable of

“education” (χ2 = 6.94, d.f. = 2, p < .05). Node 1 was

divided into two groups: Nodes 5 (high school diploma,

some college, but no degree) and 6 (bachelor’s degree and

graduate degree). The majority of Node 5 were personal

security seeker (n = 11, 64.71%) whereas the majority of

Node 6 were availability of products/services seeker (n =

30, 37.04%) followed by monetary and convenience

advantages seeker (n = 26, 32.10%). The third division was

based on the variable of “age” (χ2 = 16.93, d.f. = 2, p < .05).

Node 2 was divided into two groups: Nodes 7 (20s, 30s) and

8 (40s, 50s or older). In Node 7, the largest categories were

personal security seeker (n = 22, 44.90%) followed by

Note: A = monetary and convenience advantages seeker, B personal security seeker, C = availability of products/services seeker

Figure 1. Result of the CHAID method: Perceived values of meditel based on demographic factors

International Journal of Tourism and Hospitality Research 30(10), 2016 37

availability of products/services seeker (n = 20, 40.82%). In

the case of Node 8, personal security seeker was the largest

group (n = 25, 92.59%).

6. Gain chart and risk results for the perceived value

of meditels based on socio-demographic profiles

A gain chart provides a gain index (%). A node with a gain

index of over 100% well represents the features of a group

(Kim et al., 2011). That is, if a node has a gain index of over

100%, that node is considered a significant segment. The

percentage of respondents belonging to node 6 was 197.1%;

thus, respondents (n = 26) in Node 6 most represent the

characteristics of monetary and convenience advantages

seeker. In addition, Node 7 and Node 8 most represent

availability of products/services seeker and personal security

seeker, respectively.

The risk estimate predicted the risks occurring from

misclassification of the respondents in the DTA program

(SPSS, 2011). A lower risk estimate shows a more precisely

classified model. As shown in Table 6, the risk estimate was

.41, indicating that the precision of classifying respondents

in the DTA program was 59% (1- risk estimate). That is,

approximately 59% of the respondents were classified

accurately on split nodes.

Note: A = monetary and convenience advantages seeker, B personal security seeker, C = availability of products/services seeker

Figure 2. Result of the CHAID method: Perceived values of meditel based on travel-related profiles

38 A study of customer segmentation based on the perceived value in the meditel industry using decision tree analysis

7. Results of DTA program for the perceived value

of meditel based on travel-related profiles

Figure 2 indicates the results of DTA program for the

perceived value of meditel based on travel-related profiles.

As mentioned earlier, In Node 0, there were three groups: (1)

monetary and convenience advantages seeker (n = 43,

16.29%), (2) availability of products/services seeker (n = 71,

26.89%), and (3) personal security seeker (n = 150, 54.82%).

The first division was based on the variable of “frequency of

travel abroad” (χ2 = 18.67, d.f. = 2, p < .05). Node 0 was

divided into two groups: Node 1 (2-4 times) and 2 (more than

5 times). In the case of Node 1, personal security seeker was

the largest group. The second division was based on the

variable of “whether they have heard about a meditel” (χ2

= 11.55, d.f. = 2, p < .05). Node 2 was divided into two groups:

Nodes 3 (yes) and 4 (no). The majority of Node 3 were

availability of products/services seeker (n = 30, 48.39%)

whereas the majority of Node 4 were personal security seeker

(n = 44, 57.89%). The third division was based on the variable

of “recent experience of medical tourism” (χ2 = 13.29, d.f.

= 2, p < .05). Node 3 was divided into two groups: Nodes 5

(within 6 months-4years) and 6 (within 1 month). In Node 5,

the largest category was availability of products/services

seeker (n = 30, 52.36%) followed by monetary and

convenience advantages seeker (n = 14, 24.56%). In the case

of Node 6, personal security seeker was the largest group (n

= 5, 100.00%). The last division was based on the variable

of “frequency of medical tourism” (χ2 = 8.18, d.f. = 2, p <

.05). Node 4 was divided into two groups: Node 7 (less than

7 times) and 8 (more than 8 times). In the case of Node 7,

personal security seeker was the largest group (n = 44,

60.27%). In addition, in Node 8, the largest category was

availability of products/services seeker (n = 3, 100.00%).

8. Gain chart and risk results for the perceived value

of meditel based on travel-related profiles

The percentage of respondents belonging to Node 5 was

150.8%, suggesting that respondents (n = 14) in Node 5

most represent the characteristics of monetary and

convenience advantages seeker. In addition, Node 8 and

Node 6 most represent personal security seeker and

availability of products/services seeker, respectively. In

addition, the risk estimate was .35. In other words, the

precision of classifying respondents in the DTA program

was 65% (1- risk estimate).

V. Discussions and implications

As a first attempt to test the differences of the perceived

value based on socio-demographic and travel-related

profiles, the concept of value-based segmentation was

applied to this study. More specifically, this study examined

(1) the perceived value in the meditel industry using

principal component analysis, (2) whether or not

respondents can be grouped into distinct sub-segments

based on the perceived value utilizing cluster analysis, and

(3) whether or not there are statistical differences in

socio-demographic and travel-related profiles among the

sub-segments using the DTA program. The results of data

analysis provide key theoretical and managerial

implications.

First, twenty-three perceived values of a meditel were

extracted by three factors: (1) monetary and convenience

advantages, (2) personal security, and (3) availability of

products/services. After conducting a K-means cluster

analysis based on the three factor scores, three clusters were

indentified: (1) monetary and convenience advantages

seekers, (2) personal security seekers, and (3) availability of

products/services seekers.

In addition, the DTA program was used in order to discover

the differences in socio-demographic and travel-related

profiles among the three groups. In the case of perceived value

of meditels based on socio-demographic profiles, the first

division was based on the variable of nationality, and the

results showed that Koreans (Node 1, 36.73%, n = 98),

Chinese (Node 2, 61.84%, n = 47), Japanese (Node 3, 89.36%,

n = 42), and Americans (Node 4, 58.14%, n = 25) tend to seek

availability of products/services when using meditels. Thus,

it is meaningful and valuable to promote package programs

focusing on the availability of products/services to these

groups.

International Journal of Tourism and Hospitality Research 30(10), 2016 39

Another key finding of this study is to clarify the

differences of perceived value based on age. Considering the

Chinese, although most of them are more likely to seek

availability of products/services seeker (Node 2, 61.84%), the

results of perceived value were much different based on age.

For instance, older people hope to have a high level of

availability of products/services seeker (Node 8, 92.59%). On

the contrary, young people are more likely to seek personal

security (Node 7, 40.82%) when compared with Node 2

(27.63%). These findings have key practical implications for

meditel managers. First and foremost, meditel managers need

to develop different marketing strategies for each target

market based the age. For example, it is better to emphasize

personal security to young Chinese. The main purpose of

using meditels is to undergo an operation, so most respondents

put great importance on personal security. In addition, it is not

an easy decision to undergo an operation abroad, so they feel

anxiety towards the operation. Therefore, it is very important

to provide a high level of medical services for meditel

customers.

In the case of perceived value of meditel according to

travel-related profiles, the first division was based on the

variable of frequency of travel abroad. As shown in Figure

2, Node 1 indicated that people with low frequency of travel

abroad seek availability of products/services (69.84%). On

the other hand, people with high frequency of travel seek

personal security (Node 2, 36.96%) when compared with

Node 0 (26.89%). Among them, people who have heard about

meditels are more likely to seek personal security (Node 3,

48.39%), while people who have not heard about meditels

tend to seek availability of products/services (Node 4,

57.89%). In particular, people who have experienced

meditels seek more personal security seeker (Node 5,

52.36%).

These findings also provide important practical

implications for meditel managers. From a managerial

standpoint, it is important to consider travel-related profiles

when providing services and producing advertisements. For

instance, people who are familiar with meditels and medical

tourism are more likely to focus on availability of

products/services when using the meditel, so it is required to

provide comprehensive medical services ranging from

medical treatment and healthcare programs to hotel services.

The following limitations for this study should be borne

in mind. This study focused on the meditel industry only.

Thus, findings might not be generalized to other industries.

In addition, although this study conducted the DTA program

with 264 samples, it may not enough sample size for the DTA

program. Thus, future research needs to use the DTA program

with a larger sample size.

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Received August 30, 2016.Revised October 27, 2016.

Accepted October 28, 2016.