Islamic Banking Segmentation in Indonesia

8/8/2019 Islamic Banking Segmentation in Indonesia

1/21Electronic copy available at: http://ssrn.com/abstract=1729542

[JOURNALOFISLAMICBUSINESSANDECONOMICS] Vol.2No.2,2008

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ISLAMIC BANKING SEGMENTATION IN INDONESIA:

THE RELATIONSHIP BEETWEEN DEMOGRAPHIC AND

CONSUMER BENEFIT1

Rovvy Ocktora2

Department of Management, Faculty of Economics and Business, Gadjah Mada University

Indonesia

ABSTRACT

Islamic banking industry in Indonesia has developed quite rapidly in last decade. Nowadays,

the Islamic bank only used differentiation strategy in order to compete with conventional

bank, that is free of riba. To be able to compete between Islamic banks, they need to have

appropriate segmentation strategy. There are two segmentation strategy that can be use by

Islamic bank, benefit segmentation and demographic segmentation.

This research is used Wedel and Kamakura (1998) segmentation based. The demographic

segmentation is included in observable product specific based. And the benefit segmentationis included in unobservable product specific based.

The objective of this research is to observe the relationship between demographic and benefit

of Islamic bank costumer. Before that, the desire consumer benefit must be found. Factor

analysis and cluster analysis are used to make the benefit segmentation. Then chi square test

are used to find the relationship between these two variables. This research is conducted in

Yogyakarta, Indonesia. The result is only age and occupation that have relation with the

benefit segmentation.

Keyword: segmentation, demographic segmentation, benefit segmentation, Islamic bank.

1 This paper was published in Journal of Islamic Business and Economics (JIBE), Laboratory of Islamic

Business and Economics (LIEB), Faculty of Economics and Business, Gadjah Mada University in December

2008. This paper originally in Bahasa Indonesia, and then translated into English with minor revision.2 Researcher in Syariah Center P2EB, Faculty of Economics and Business, Gadjah Mada University. Address

correspondence to [email protected]


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Background

The developments of Islamic banking in Indonesia are cannot be separate from the

appearance of the first Islamic bank, Bank Muamalat. This Bank Muamalat is existed

from 1991. The existence of this Islamic based bank is initiated by Majelis Ulama

Indonesia (MUI) and supported by Ikatan Cendekiawan Muslim Indonesia (ICMI).

The upcoming of Islamic bank in Indonesia actually too late if compared in other

countries in Middle East. But, the existence of Islamic bank gives an alternate choice

on Indonesian banking industry. That because Islamic banks are using profit and

loss sharing rather than the conventional banks are still using interest based.

In their first appearance, public are still skeptic with this Islamic bank. When

economic crisis strike Indonesia in 1998, a lot of national bank got the effect. So many

bank must be liquidated and merge with another bank in order to survive from high

inflation rate. But, bank Muamalat, the Islamic bank is survive from this economic

crisis. One of the reasons why these banks survive is not using interest system that

very fragile to inflation.

Some of bank practitioners are try to develop Islamic bank after they are successfully

again the crisis. Some of conventional bank started to open Islamic Banking Unit.

The government are begin to acknowledge this Islamic banking industry. In 1998,

the law no.10 year 1998 are obtained as replacement of law no.7 year 1992. With that

law, Islamic bank have a gold opportunity to grow bigger. The conventional bank

can also open a branch office with Islamic based system.

Based on Islamic banking statistic, if in year 1992-1998, there is only one Islamicbank, and then on March 2007 there are twenty four Islamic banks. There are

consists of three Islamic Commercial Bank and twenty one Islamic Banking Unit.

Besides that, the number of Islamic Rural Bank reached 105 units in the same period.

The developments of Islamic bank can be seeing on table 1 and graphic 1.


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Table1. Islamic banking share to total bank, December 2007

(Billion rupiah)

Islamic Bank Total Bank

Nominal Share

Total asset 36,539 1.84% 1,996,501

Deposit Fund 28,012 1.85% 1,501,834

Credit/Financing Extended 27,944 2.79% 1,002,012

Source: Islamic banking statistic Bank Indonesia

Graphic1. The development number of office and deposit of Islamic bank,

January 2007 - January 2008.

Source: Islamic banking statistic Bank Indonesia.

Watching this development of Islamic banking industry, there are good businessstrategy needs to be applied. Even though Islamic banking market share is still less

than 5% from overall national bank, but the growth are increasing year by year. This

fact is very important and needs to be done by Islamic banking practitioners in order

to get costumer as much as possible.

Nowadays, Islamic banks are only made a differentiation against conventional

banks. They made positioning to costumers that they are free-interest bank. They see

that Muslims are prohibited to riba, and bank interest is part of riba. But, only some


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of the people in Indonesia are aware of this fact. The problem is, differentiation

between Islamic banks is still not clear. The effect is competition in order to get the

costumer become hard. That why a clear positioning between Islamic bank is

needed.

In more developed economic, the importance of market segmentation in financial

service sector has been well established. As competition between bank increases,

each financial service adopted an interesting segmentation strategy (Speed and

Smith, 1992; Harrison, 1994). Unfortunately Indonesian banking sector segmentation

that based on needs, wants, and preference are rarely found. Its need to understand

though, in the developed country, the numbers of segmentation variables arelimited. Its different in western country, where market segmentation from

costumers has developed rapidly. Lifestyle segmentation or geo-demographic

segmentation is common in western country.

Problem Identification

According to the facts above, the purpose of this research to make an alternative

segmentation that can be applied in Islamic banking industry in Indonesia. This

research is trying to do segmentation on Islamic bank customers with some

variables. There are two kind classifications of segmentation based that used, that is

demographic and benefit (Wedel and Kamakura ,1998). This research also tries to

find the relationship between those two variables.

Segmentation

Market segmentation is the way to increase companys marketing by grouping the

costumer into a group that have a similar needs and wants. Marketer cannot made a

segment, but a marketer job is to identified segment and determine where is to be

the target. The point is market segmentation offering more benefit than mass

marketing (Kotler, 2003).

Wedel Smith (1956) first time define market segmentation as viewing a

heterogeneous market as a smaller homogeneous market, in response to differing


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preference, attributable to the desire of consumer for more precise satisfaction of

their varying wants. Based on the other definition of expert, its can generally

explain that segmentation appear because of heterogeneity of needs and desire of the

consumer.

There are many researches about segmenting the financial institution. To facilitate a

brief analysis of the most pertinent to the financial service sector, the author follow

Frank et al. (1972) and Wedel and Kamakura (1998). They suggest classifying those

segmentation variables according to whether they are product specific or

general (i.e. independent products or service), and also by the extent to which each

variable might be deemed observable. For more clear can see table2.

Table2. Classification of Segmentation Variables

General Product-specific

Observable Demographic, geographicand socio-economicsvariables

User status, usage rate,loyalty, stage of adoption

Unobservable Psychographic, values,personality and lifestyle

Benefit, perception,preference, intention

Source: Wedel and Kamakura (1998)

Demographic Segmentation

In a demographic segmentation, market divided into groups based on variables.

Age, gender, monthly income, occupation, and education are the most potential to

grouping the costumers. Demographic variables are also has very close relationship

with needs, preference, and consumer used level. Demographic variables are easy to

measure rather than the other variables. These variables are so important that ifmarket is divided into non-demographic variable, the demographic characteristic is

still needed. In order to measure segmented target and the medium effectively,

demographic variables are very important.

According to Wedel and Kamakura (1998), demographic variable are include in

general observable based. Information about demographic variable are easy to

collect and quite reliable. This variable also not gets much problem if its put in

marketing mix. Some of demographic variables that have been used in demographic


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segmentation research are: gender (Dikkens and Chappel, 1997; Frank 1989),

position in the family life cycle (Wells and Gubar, 1966; Lansing and Kish, 1957;

Reading, 1988; Jonak, 1988), culture (Joy et al., 1991), income (Allt, 1975; Slocum and

Mattews, 1970; Crisnall, 1992; Monk, 1970), and geographic location (Lunn, 1878). In

this research used age, gender, marital status, income, education and occupation

(Schiffman, 2004).

Benefit Segmentation

Benefit segmentation watching how the consumer satisfied from a product. Change

in a life style plays an important role in product benefit for consumer. This also gives

marketer a chance to create product and service. Main power of this benefit

segmentation is benefit has causal relationship with behavior in the future

(Schiffman, 2004).

Benefit is something that able to make someone to fell satisfied with their needs or

wants. Someone will choose one from many option because of the benefit from they

choose. Just like bank customers, they just hoping the benefit from the bank they

choose. There are many kind of benefit that they get from the bank they choose.

With many kind of benefit, that can be categorized into each segment.

Practically, a bank marketer will be successful if he is able to do benefit segmentation

combine with good marketing mix strategy. Banks are able to get their target

consumer with the benefit that they offer. With benefit segmentation that will be

easy.

According to Wedel and Kamakura (1998), benefit variable are include in

unobservable product-specific based. Some research must be done if wanted to

know what benefit that someone desired. There are some researches that using

benefits segmentation as variables (Tynan and Drayton, 1987; Loker and Perdue,

1992; McDougall and Levesque, 1994; Minhas and Jacobs, 1996).


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Theoretical Framework

This research replied from Alfansi and Sargeant (2004) research. The title of the

research is Market Segmentation in the Indonesian Banking Sector: the Relationship

Between Demographic and Desired Consumer Benefit. On that research said those

general observable based variables are close to segment criteria such as

identifiability, sustainability, accessibility, and stability, but weak at actionability,

and responsiveness. At unobservable product-specific based variables are close to

actionability and responsiveness, but this variable weak to the other criteria.

That will be interesting if there is any relationship between those general observable

based and unobservable product-specific based variable. If there is a relationship can

be found, there will be an interesting potential segment. As the conclusion of that

research is, there only one demographic variable that have relation with benefit

segment, and that is occupation.

This research want to know the relationship between general observable based and

unobservable product-specific based variable as Wedel and Kamakuras

segmentation criteria, if there will be different between conventional banking and

Islamic banking customers segment. This research tries to do segmentation based on

benefit from Islamic bank customer. And then if there is a significant correlation

demographic segmentation, such as age, gender, marital status, monthly income,

education, and occupation with those benefit segmentation.

Methodology

This research conducted in province Daerah Istimewa Yogyakarta, Indonesia. There

are 3.3 billion populations in this province. Yogyakarta is a representative place of

social strata existing in wider Indonesia. This area also has a highest development in

Islamic banking in Indonesia. Up now, there are 21 Islamic bank branch are open in

this area. Islamic banking growth is 40% per year, highest in Indonesia.

This research is use survey method, where the population is Islamic bank in

Yogyakarta. There are 300 questionnaires distributed as a sample, and only 275 are


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obtained. Sampling method that used are convenient sampling and stratified

sampling. Stratified sampling is used to get heterogeneity and balancing the sample.

There are two kind of strata that used, place and occupation.

This research is using primary data. There are two kinds of data that will be collect,

demographic variables and benefit variables. The demographic variables that used

are just like mentioned before. The result of respondent demographic data can be

seen at appendix 1.

There are three instrumental tests that used in this research. The first one, factor

analysis, is used to derive the factors that construct the benefit variable. The item

that construct benefit variable is from the benefit item from questionnaire. The

second is cluster analysis, is used to create segment cluster of benefit variables from

the factors that created. And the last one is chi square test is used to know the

signification of relationship between demographic variables and benefit segment

variables.

Factor Analysis of Benefit Variables

Factor analysis is statistical method that used to explain variability among observed

variables into smaller variable called factor. In this study, factor analysis used to

classify and simplify the variables benefits received by customers of Islamic banks

into the factors that shape it, so that can know what are the factors that underlie the

benefits of Islamic bank customers.

An interview is held before the questionnaire is distributed. The purpose is to

explore what are benefits that Islamic bank customer gets. Some of literature study is

used to complete the benefit item that a banking customer can get. From that

exploration, there are benefit item that used in this research. The detail benefit item

and their source are in appendix 2.

Benefit Factor

In a validity test, KMO value of 0.896 is obtained so that the research is feasible to be

tested with factor analysis because its value is more than 0.05. KMO value


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approaching 1 indicates that factor analysis can be used in the data. The method

used in the test reliability is Cronbach Alpha coefficient (). According Sekaran

(2000) the instrument is considered reliable if the alpha value greater than or equal to

0.7, the measured variables and items can be trusted or relied upon. While the alpha

value greater than or equal to 0.6 is considered fairly reliable (Hair et al., 1998). In

this study the Cronbach Alpha reliability of the test is 0.961. Thus, existing data are

considered highly reliable.

Based on the data grouping score coefficient matrix that has the greatest value, there

are 11 grouping factors. Benefits of grouping factors can be seen in appendix 3. All of

these factors can be named respectively as follows:

1. Factor 1 = appearance2. Factor 2 = ATM3. Factor 3 = cost4. Factor 4 = service5. Factor 5 = various products6. Factor 6 = sharia compliance7. Factor 7 = branch office8. Factor 8 = employee9. Factor 9 = location10.Factor 10 = reputation11.Factor 11 = extra facility

Thus, all of factors that underlie all of the benefit variables of Islamic bank customer

can already be known.

Benefit Segmentation

F ratio values and significance levels are used to compare the differences between

the mean clusters. Giving a label or name on the cluster done accurately describe the

nature of these clusters. This study used three clusters as analysis. Results from the

cluster analysis can be see in appendix 4.


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From the table note that the level of significance of the table shows that the level of

significance of the table shows that the ten variables were significantly different with

sig


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Table3. Signification Test

Variables Chi Square Df. Sig.

Gender 5.316 2 0.070

Age 23.936 8 0.002

Monthly income 8.082 6 0.002

Occupation 15.082 6 0.232

Marital status 8.8839 4 0.065

Last education 4.553 8 0.804

From Table 3 it can be seen that the value of 0.05 significance demographic variables

significantly related to the variable benefit with significance value 0.05.

Thus, demographic variables related to the variable benefits in segmenting

customers of Islamic banks are the variables of age and occupation. As for the

variables of sex, monthly income, and last education did not have the relationship

with the segmentation of variable benefit.

Discussion of Results

In this research can be concluded that age differences can be categorized into the

benefit segmentation that created. In a different age level, customers will tend to be

associated with one of the benefits offered by Islamic banks, whether its cost

advantages, the major product benefits, convenience or profit.

So it is with monthly income. At a different level of income, customers will tend to

be associated with one of the benefits offered by Islamic banks, whether its cost

advantages, the major product benefits, convenience or profit.


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Managerial Implication

The results of this study concluded that demographic segmentation variables that

have a relationship with the benefits segmentation variables are the age variables

and occupation variables. This is considered quite disappointing because it was still

less able to benefit segmentation targeting the consumer to do targeting based on age

and employment, especially if the Islamic banks would like to offer specific benefits

to the clients.

Although only age and occupation variables that can be targeted to offer the benefits

of Islamic banking, Islamic banking practitioners can still get a lot of customers if

they can make the most of the intended target market. By knowing the benefits that

can be offered and the right target market demographic, the marketing focus will be

more to produce than on mass marketing (Kotler, 2003). Islamic banking

practitioners can perform combinations to focus on the benefits offered or

demographic target market.

Viewing of the three segments that form, namely the cost segment, the main

products, and convenience, the practitioners of Islamic banking can take advantage

of the benefits sought by the character of the community by focusing on one segment

of those profits. At the focus of these segments, Islamic banking marketers can do

concentrated segmentation with segment targeting certain advantages with a specific

target market demographics, whether based on age or occupation.

If every Islamic banks successfully targeting a variety of target markets in each

segment, the development of Islamic banking in Indonesia will be more organizedand focused. With the increasing number of Islamic banks that hold more and more

customers will not occur because the seizure of any Islamic bank already has a

different focus positioning that will be devoted to other prospective customers.


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Suggestion

For further research on the same topic should be able to consider the suggestions as

follows:

1. Distribution of respondents demographic variables in order to more evenlyand to represent each of the variables such as gender, age, income,

occupation, marital status, and education last.

2. In finding the relationship between the general categories of variables that canbe observed with category-specific products that can not be observed in the

classification of Wedel and Kamakura (1998) not only between demographic

variables only, can also use the socio-economic variables.

3. To find out more about the relationship between demographic variables withthe variable benefit could use more information such as conjoint analysis


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Appendix 1.Respondent Demographic Data

Variables Frequency Percentation

Gender Male 165 60 %

Female 110 40 %Total 275 100 %

Age Less than 25 year 208 75,6 %

Between 26-34 year 33 12 %

Between 35-44 year 18 6,5 %

Between 45-54 year 15 5,5 %

More than 55 year 1 0,4 %

Total 275 100 %

Monthly income Less than Rp.500.000 83 30,2 %Between Rp.500.000 Rp.1.000.000 107 38,9 %

Between Rp.1.000.000 Rp.1.500.000 39 14,2 %

More than Rp.1.500.000 46 16,7 %

Total 275 100 %

Occupation Student 158 57,5 %

Employee 78 28,4 %

Entrepreneur 33 12 %

Others 6 2,2 %

Total 275 100 %

Marital Status Single 217 78,9 %

Married 57 20,7 %

Divorce 1 0,4 %

Total 275 100 %

Last education Junior High School 4 1,5 %

High School 168 61,1 %

DIPLOMA 25 9,1 %

Undergraduate 66 24 %

Master 12 4,4 %

Total 275 100 %


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Appendix 2. Benefit items that used

No Items Source

1 Bank reputation 1, 4, 6

2 Sharia compliance 7, 8

3 Free of riba 7, 8

4 Using profit and loss sharing system 8

5 Security of deposit 8

6 Fast and efficient service 4, 5, 6

7 Overall service 4, 6

8 Fast and accuracy transaction 2, 6

9 Financial counseling service provided 4

10 Bank employee wear an Islamic dress 8

11 Numbers of bank employee that ready to help 3

12 Knowledge of bank employee 3, 5

13 Friendliness of bank personnel 1, 4, 5, 6

14 The respect and consideration that shows bank

employee

3

15 Long banking hour 1, 5, 6

16 High profit and loss sharing deposit margin 8

17 Lower charges of monthly deposit 4, 5

18 Free drawing charges 4, 5, 8

19 Low charge in others service 4, 5

20 Gift that offered 1

21 Branch office facility 3

22 The numbers of branch office in the country 3

23 Size of branch office 3

24 Being able to pay bills 4

25 Wide range of service offered 4

26 Able to mobile banking 8

27 Able to internet banking 8


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28 Availability of ATMs 5, 6

29 Numbers of ATM booths 5, 6

30 Join in Union ATM 8

31 Free charge at Union ATM 8

32 Interesting ATM card 8

33 Convenience location 1, 4, 5, 6

34 Bank location that near resident 8

35 ATM location that near resident 8

36 Internal appearance of the bank 5

37 External appearance of the bank 5

38 Interior layout of the bank 2

39 The availability of parking space 1, 4

40 Confidentiality of the bank 2

41 Interesting advertising 6

42 Much known by people 1, 4, 5, 6

43 Recommended by friend or family 1, 4, 5, 6

44 Complete and open information in the bank 3, 6

45 No information being hide 3, 6

Source: 1 = Anderson et al. (1976); 2 = LeBlanc dan Nguyen (1988); 3 = Lewis (1991);

4 = Kaynak et al. (1991); 5 = Kaynak dan Kucukemiroglu (1992); 6 = Zineldin (1996);

7 = research of Bank Indonesia (2007); 8 = interview result


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Appendix 3. Factor Grouping

Factor VariableCoefficient

Matrix Score

Interesting ATM card 0.149

Internal appearance of the bank 0.274

External appearance of the bank 0.254

1 Interior layout of the bank 0.252

Confidentiality of the bank 0.139

Interesting advertising 0.144

Availability of ATMs 0.246

2 Numbers of ATM booths 0.269

Join in Union ATM 0.249

Free charge at Union ATM 0.244

High profit and loss sharing deposit margin 0.2143 Lower charges of monthly deposit 0.291

Free drawing charges 0.298

Low charge in others service 0.309

Fast and efficient service 0.337

4 Overall service 0.315

Fast and accuracy transaction 0.334

Being able to pay bills 0.295

5 Wide range of service offered 0.295

mobile banking 0.367internet banking 0.304

Sharia compliance 0.353

6 Free of riba 0.307

Using profit and loss sharing system 0.296

Bank employee wear an Islamic dress 0.282

Financial counseling service provided -0.125

Branch office facility 0.472

7 The numbers of branch office in the country 0.422

Size of branch office 0.160

Convenience location 0.190

Knowledge of bank employee 0.150

8 Friendliness of bank personnel 0.444

The respect and consideration that shows bank

employee0.562

Security of deposit -0.272

Numbers of bank employee that ready to help 0.307

9 Long banking hour 0.321

Bank location that near resident 0.403

ATM location that near resident 0.299


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Bank reputation 0.299

10 Much known by people 0.360

Recommended by friend or family 0.461

Gift that offered -0.211

11 The availability of parking space 0.283Complete and open information in the bank 0.551

No information being hide 0.392

Appendix 4. Cluster Grouping

VariableMean Score

F Ratio Sig1 2 3

appearance -.80816 .31498 -.16446 43.412 .000

ATM .33276 -.00554 -1.90842 31.617 .000

cost .46263 -.18511 .17060 12.052 .000

service -.26890 .13488 -.53341 6.281 .002

Various products -.65452 .27248 -.40981 28.188 .000

Sharia compliance .17903 -.04287 -.39188 2.272 .105

branch office .09174 .09963 -2.13620 35.931 .000

employee -.40444 .12559 .42759 8.987 .000

location -.48320 .13753 .71014 14.546 .000

reputation -.10569 .08699 -.75045 4.623 .011

Extra facility .32237 -.14272 .33739 6.631 .002

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