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MOBILE NUMBER PORTABILITY: ASSESSING AND ANALYZING FACTORS BEHIND

INTENTION TO SWITCH

ABSTRACT

Purpose

This research has been conducted to assess and analyze the factor behind intention to switch in telecommunication market of Pakistan. Study will analyze the effect of independent variables (service quality, price, switching cost, customer lock in, brand communication) on dependent variable (intention to switch) while having a mediating effect of mediating variables (customer satisfaction, perceived switching barriers, brand trust).

Design/methodology/approach

An online survey has been conducted to collect responses from 200 cellular service users in Rawalpindi/Islamabad. All of the respondents are users of one of the following cellular service provider Ufone, Telenor, Warid, Zong and Mobilink. The five-point Likert scale was used (where 1 equals strongly disagree and 5 equals strongly agree).

Finding

Limitations

Major limitation of the research is that it is done from consumer perspective rather than service provider perspective.

Practical implications

This study will spotlight the critical factors behind intention to switch through which telecom companies can reduce mobile number portability rate.

Originality/value

In this context of mobile number portability no research has taken place in telecommunication market of Pakistan. Study is first of its kind to assess and analyze the basic factor behind intention to switch in context of mobile number portability.

Keywords

Asia pacific, mobile number portability, brand switching, telecom sector

Paper type Research paper

INTRODUCTION

Pakistan has five major cellular service providing companies prevailing in very intense

competition, in this scenario every company is trying to retain its current customer as well as

attracting new potential customers. This study is basically conducted to examine Mobile Number

portability in context of Pakistan and how this network service affects the telecommunication

industry of Pakistan. This study aims to identify factors that why customers switch their cellular

service from one network to another, also influence of each factor on customer trust, perceived

switching barriers and customer satisfaction which ultimately leads towards intention to switch.

MNP occurs when a customer switches its current cellular service provider with another service

provider while keeping the mobile number same. By availing the mobile number portability

service your mobile number and code is shifted to another operator and you start enjoying

services. Basically it is circuit switch service provided by network operators to customers to

change their operator, location, service type while keeping the existing mobile phone number.

Every company’s success depends upon customer satisfaction and loyalty to their brand and

company can only achieve if they retain their customer with a satisfaction level.(Ahmed et al,

2010). Pakistan is the first country in South Asia to launch mobile number portability service in

March 2007.

Telecommunication industry of Pakistan operates under supervision of Pakistan

telecommunication Authority (PTA. Telecommunication sectors is fastest growing sector of

Pakistan and in 2013 it has reached its maturity and earned 445.7 Billion revenue which clearly

indicates the tremendous growth and boom of this industry in Pakistan (PTA, 2013). Industry

contributed 124 Billion to national exchequer. Groupe Speciale Mobile Association (GSMA)

revealed that there are 125 million active SIM cards and 70% people use mobile service on daily

basis. Teledensity has reached to 75.21% (135 million subscribers).

Pakistan has five big players of cellular service provider (Mobilink, Telenor, Ufone, Warid, and

Zong). In last 12 months Mobilink added 100,000 customers to its customer base, Zong up to

300,000 subscribers while Warid lost 70,000 subscribers per month. Mobilink has highest

customers base of 36.7 million customers and Ufone has 23.8 million customers. Companies in

last two years lost a number of customers due to mobile number portability or deactivation of

SIM. Statistics of December 2012 issued by Pakistan telecommunication Authority (PTA) shows

that Ufone lost 500000 subscribers, Mobilink lost 450000 subscribers, Telenor 205000, Zong

lost 229000 and Warid lost 211000 customers in last year.

Mobilink is the largest player of telecom industry found losing its market share over the years.

Mobilink had monopoly having more than 50% market share in 2004 has declined to only

28.9%. While Telenor is considered as second big player has maintained its momentum and

increased its market share to 26.1% from 24.9% in last year. Ufone having 18.6% market share

showed slight decline while Zong increased its market share by 2.4%. Warid despite of being

very old in industry is gradually losing its market share from last 5 years and now it has least

market share of 9.9%.

LITERATURE REVIEW

Companies are making aggressive marketing efforts to increase their market share while on the

other hand MNP service has made a mutual ground for companies to compete fairly. This

theoretical framework will assess and analyze the factors which actually develops the intention

to switch and through mediating and moderating effect of some factors.

Mobile number portability add definition

Sutherland conducted a depth study on mobile number portability to assess that how it works and

what are the basic parameters which drive this service. Mobile number portability allows

customers to keep their mobile number same while changing their network from one carrier to

another. Mobile number portability is promoted mainly by lowering switching cost by cellular

service providing companies and other parameters which actually drive this service was main

outcome of this study (Sutherland, 2007). But question raised that what type of costs customer

bears when port the number and in 2007, Garcia and Murrilo conducted a study to assess and

analyze that whenever a customer wants to port his/her number from one network to another

what kind of related costs need to be occur to avail the service. Whenever user want to exercise

mobile number portability carriers has to face two types of cost: cost to upgrade the network and

cost to port the number. These costs are occurred upon the request of customer which carrier or

customer has to pay. Either customer needs to pay for availing the service for upgrading or

porting number or carrier pays at their own just to promote the company by giving these offers at

no cost to customers (Garcia and Murrilo, 2007). Many questions were unanswered yet that what

is the influence of demographic factors on MNP and in this regard another study was presented

by Srinuin and bohlinin in 2011. In their undertaken research found that switching from one

brand to another is strongly influenced by some demographic factors which are as per industry

dynamics and strongly backed by the switching cost. Prior studies showed that demographics are

important factors in explaining switching behavior and switching behavior also backed by

switching cost of MNP (Srinuin and Bohlin, 2011).

Service Quality

In services marketing service quality is perceived to be most important factor which develops

customer loyalty. In this concern Shin, Kim and Lee came up with their significant result of their

research that in case of mobile number portability service quality plays a very vital role in

driving consumer preferences from one brand to another. They also found that price factor is

perceived to be the most critical factor in mobile number portability case and it is positively

related to MNP that if price is high MNP will also be high and vice versa. Value added services

are just secondary factors which drive consumer mind in the same direction but not actually

influence the core decision of mobile number portability (Shin, Kim and Lee, 2011). Another

study examined the impact of service quality and customer switching behavior in Chinese

telecom market and analysis shows that 7 critical service quality factors determine the switching

behavior in service market. This study contributed a lot to Chinese telecommunication

companyies that they had a clear idea that these two factors actually drive this industry and they

can more focus on improving service quality to change customer switching behavior in the

market and can increase their market share as well (Liang, Ma and Qi, 2012). A very recent

study which was undertaken by Nortey and other authors that what are the key factors in brand

switching in telecommunication market. Study shows that service quality, customer satisfaction,

trust, price and switching cost are very important variables in brand switching. Study revealed

that all these variables have good reliability greater than 0.60. Price, service quality, trust,

satisfaction, and switching cost are most important variables having a probability (p=0.000) and

(@ = 0.05). (Nortey, Amponsah, Madjitey, Ansah-Narh, 2013). But one question remained

unanswered that what are key factors which develop post purchase intention and another study

was found conducted by Kuo, Ming and Deng in 2009 to evaluate the basic factors which

develop post purchase intention. Service quality and perceived value are positively related to

customer satisfaction and customer satisfaction mediates the relationship and leads towards post

purchase intention. Service quality and perceived value also positively influences the post

purchase intention (Kuo, Ming, Deng, 2009). Particularly talking about Chinese

telecommunication market a study was undertaken by Liand, Zhenzhong and Qi to examine the

perceived importance of service quality and customer switching behavior in Chinese mobile

sector. Factors analysis of seven critical factors showed that service failure is more in males and

women’s are more tolerated towards service encounters. It clearly indicates the importance of

service quality in Chinese telecom market. Study also revealed that service failure, high price,

ethical problems is main 3 factors which influence mobile number portability behavior (Liang,

Zhenzhong, Qi, 2012). Another study was conducted also in Chinese telecommunication market

by Lai, griffin and Babin in 2008 to examine the relationship among service quality, value,

corporate image, satisfaction and loyalty in Chinese telecommunication industry. Results showed

that service quality directly influence satisfaction, perceived value and image, corporate image

and value and both affects satisfaction as well as loyalty and positively influence while

satisfaction itself directly and positively develops loyalty. Service quality directly develops

loyalty which clearly indicates that whether or not there is influence of other factors service

quality develops loyalty by itself (Lai, Griffin, Babin, 2008).

H1: There is a positive relationship between service quality and customer satisfaction.

Perceived Price

A study conducted in Bangladesh to assess the basic driving forces of customer satisfaction in

restaurant service industry. Service fairness and price fairness elements were found having a

great impact on customer satisfaction. Price fairness was considerably high driving force of

customer satisfaction in the industry with a significance level of 0.05 LSF. Findings suggested

that price of food items are not linked with cost of food therefore restaurant managers should

restructure their pricing strategies in order to grab market share (Rahman, Kalam, Rahman and

Abdullah 2012). Yet gap was also there related to price perception after purchase and their post

purchase behavior about price of the product. To fill this gap another study was presented by

Jiand and Rosenbloom to asses price fairness in post purchase behavior of online marketing.

Study found that after getting online order delivery there develops price perception about the

brand that whether they are giving value for money or not and develops customer repurchase and

satisfaction. Study results showed a positive effect between perceived price on overall customer

satisfaction and repurchase intention. So it is better for e.tailer to focus more on their pricing

strategies in order to develop a profitable relationship with customer (Jiang and Rosenbloom

2004).

H2: There is positive relationship between switching cost and perceived switching barrier.

Customer Satisfaction

Customer satisfaction has become one of key concern for companies to successfully compete in

the market. This study also based on the factors which influence customer satisfaction and take

customer away from the brand. Effect of anger, discontent, dislike, embarrassment, sadness and

worry are key emotions in undertaken study. Outcome was negative word of mouth and

switching complaints (Romani, Grappi and Dalli, 2011). While another study was conducted in

2013 that how negative word of mouth develops against a brand and they found that brand

commitment is moderator variable in this perspective. Yale model and Attribution theory

implemented and try to examine that whether receiver is influenced by negative word of mouth

and change its perception and cause dissatisfaction. External attributes have positive relationship

with source credibility but no relationship exists with information credibility while source

credibility has positive influence on receiver information credibility but no relationship exists

with negative e Word of mouth (Chang and Wu, 2013).

H3: There is negative relationship between customer satisfaction and intention to switch.

Switching Cost

Since MNP service has launched in the market telecommunication companies has leveraged their

packages and made switching cost very lower to gain a larger market share and switching cost

has become a key drive to use MNP service. Maicas, Polo and Sese in 2009 conducted a study to

investigates the effect of MNP on switching cost and it revealed that MNP has no effect in

lowering switching cost in adoption of cellular carriers in market for people who do not want to

keep their mobile number same. It only benefits those customers who use MNP service while

switching carrier. It clearly indicates that lowering of switching cost is useful for those customer

segments that have intention to switch the carrier in future not regular customer who wants to

continue with the same service provider (Maicas, Polo and Sese, 2009). Another study revealed

that switching cost influence has reduced since MNP came into market. However switching cost

has still influence in MNP. When this service came in to the market telecom companies lower

the switching cost to get maximum number of subscribers from other networks which ultimately

lowers its impact. But however switching cost is considered as major factor in MNP where

switching cost is higher (Lee, Kim, Lee and Park, 2006). Yen, Wang and Horng in 2010

conducted a research to investigate switching cost antecedents. Study revealed that perceived

trust has significant positive influence on perceived switching cost and customization has

negative influence while effective communication has also positive and significant influence on

perceived switching cost. It means that brand communication if effective can make MNP rate

very lower and brand trust can also make it lower (Yen,Wang and Horng, 2010). Barroso and

Picon in 2011 in their research identified the six basic dimensions which construct switching cost

and makes consumer perception which develops switching intention. Benefit loss cost,

relationship lost cost, economic risk cost, and evaluation cost, setup cost and monetary lost cost

are six basic antecedents. All these cost are based on some antecedents i.e. length, breadth,

involvement and propensity for switching when they influence on switching cost affective

loyalty, cognitive loyalty and behavioral loyalty are some outcomes (Barroso and Picon, 2011).


Customer Lock-in

As branding has become a driving force for a brand, companies now come up with a solid

customer lock in strategies that how to retain customer with company and a research was

conducted to examine switching cost and lock-in factor in Japanese telecom market. Marketing

strategies used to lock-in customer are quite useful and SIM unblock is highly compatible for

standard mobile phones while standardizations needs time and cost (Nakamura, 2010).

Andreasen in his book “Higher profits through customer lock-ins” examines different types of

switching cost that are either inherent or related to market enhancement. He stated 5 inherent

switching cost i.e. transaction, learning, acquisition, complementary products and network

effects (Andreasen, 2004).

H5: There is positive relationship of customer lock in on perceived switching barriers.

Switching Barriers

Switching barriers are considered to be a prime activity to retain your existing customer in your

customer base because in today’s business world customer has so many option and need only a

touch point to move on therefore companies try to imply switching barriers to stop them. In this

regard a study was conducted to find out that what the effects of switching barriers on customer

satisfaction are, repurchase intention and attitudinal loyalty. Research found that there are two

types of switching barriers i.e. positive switching barriers and negative switching barriers.

Positive switching barriers positively influence customer satisfaction while negative switching

barriers impinge negatively on customer satisfaction. So if proper planned switching barriers are

applied customer can be retained (Julander and Soderland 2003). To better explain switching

barrier another study came up with model illustrating the effect of switching barriers of the

relationship of customer satisfaction and customer retention. Model showed that switching

barriers are a combination of switching cost, interpersonal relationship, attractiveness of

alternative and service recovery. All these variables have positive effect on customer retention

and moderate positively the relationship between customer satisfaction and customer retention

except attractive of alternatives have negative effect on the relationship. Proper identification of

switching barriers which positively support customer satisfaction and customer retention can

lead towards a greater customer base (Kim, Park and Park 2007).

H6: There is negative relationship between perceived switching barriers and intention to switch;

Perceived switching barriers mediated the relationship of switching cost and customer lock in on

intention to switch.

H7: Perceived switching barriers moderate the relationship between customer satisfaction and

intention to switch.

Brand Communication

A study was presented by Zehir, Ahina, kitap and Mehtapin 2011 found brand communication

has and direct positive effect on brand trust and loyalty and build trust based relationship

between organization and customer. Service quality also has direct and positive influence on

brand trust and brand loyalty. Results showed that brand trust has mediating effect between

brand communication and brand loyalty (Zehir, ahina, Kitap, Mehtap, 2011). Another study was

presented by Vankaand study found the relationship between corporate branding and cellular

connection purchase having influence of some other factors. 20% of total sample selected service

quality as most important variable. 49% respondents said that they are somewhat loyal to the

brand, 58% selected price as most important factor. Finally switching was found as a result of

lower price offered by other brand or change in preference of brand (Vanka). Azize and Hakan

conducted a study to examine the effect of brand communication on brand trust and effect of a

mediating variable customer satisfaction on brand trust. Study through factor analysis revealed

that there is a positive and significant relationship between brand communication and customer

satisfaction, also revealed that mediating variable customer satisfaction also has positive and

significant relationship on brand trust. Brand communication was divided into two types of

communication i.e. one way communication, two way communication. Both of these

communication approaches have positive and significant effect on customer satisfaction (Azize,

Hakan, 2008).

H8: There is a positive relationship between brand communication and brand trust.

Brand Trust

In 2012 a study was undertaken by Karjluoto, Jayawardhena, Aniemi and Pihlstr to find the

impact of value and trust on loyalty and it revealed that value positively influence on loyalty and

trust as mediating variable also has positive effect on loyalty. Value was comprised of four types

i.e. functional, monetary, emotional, and social and trust was based on relationship age and usage

level loyalty was measure in terms of attitudinal and behavioral loyalty. These dimensions of

value and trust presents a depth understanding of each factor on loyalty and companies can focus

more on these critical success factors (Karjaluoto, Jayawardhena ,Aniemi and Pihlstr, 2012).

H9: There is negative relationship between brand trust and intention to switch, Brand trust

mediates the relationship between brand communication and intention to switch.

H10: there is a moderating effect of brand trust on relationship between customer satisfaction

and intention to switch.

Intention to switch

This undertaken study aims to assess and identify the variables behind intention to switch but

how does intention to switch develops? In this concern a study was presented by Weng-hua and

jing-vi in 2010 to check mobile number portability in Chinese telecommunication market and

identified that customer satisfaction, switching cost and attractive of alternatives are basic factors

behind mobile number portability. Customer satisfaction and switching cost negatively influence

switching intention while attractiveness of alternatives has no significant influence (Wen-hua

and Jing-yi, 2010). Shin and Kim in conduct a study on MNP in Korean cellular market and

identified subscription, perception and behavior as important factors behind MNP. Study

revealed that switching barrier has significant influence on MNP and make MNP lower.

Switching barriers can be in terms of perceived value, switching cost and other lock in strategies

to make MNP rate lower (Shin and Kim, 2008). Another study by Shin found that customer

satisfaction, switching barriers and demographics are key factors which have significant effect

on customer intention to switch. Customer satisfaction and switching barriers have negative

influence on intention to switch and companies can make switching cost higher to make MNP

rate lower (Shin and Kim, 2008). Another study by Gerpott, Rams and Schindler investigate that

customer satisfaction has a positive and significant influence in developing customer loyalty

which ultimately influence customer intention to breach on continue relationship with current

carrier (Gerpott, Rams and Schindler).

METHODOLOGY

To examine Factors behind intention to switch in telecommunication industry this research will

measure the influence of independent variables Price and Service Quality on mediating variable

customer satisfaction which leads towards intention to switch. Two other independent variables

switching cost and customer lock in which influence the dependent variable intention to switch

while this relationship is mediated by perceived switching barrier and mediating variable also

moderate the relationship between customer satisfaction and intention to switch. Another

independent variable brand communication develops brand trust and which leads towards

intention to switch and also moderates the relationship of customer satisfaction and intention to

switch.

Theoretical Framework


Intention to switch

H9

H1

H10

H6

H3

H8

H5

H4

H2 H7

For this purpose data through questionnaire is collected from 200 respondents between ages of

18 to 35 in Islamabad/Rawalpindi region. All responses collected through questionnaires and

analyzed by SPSS 20. For all variables present in hypothesis are assessed with 5 point likert

scale where 1=strongly disagree and 5=strongly agree. 3 questions for each variable are used to

develop questionnaire which is taken from literature.

Factors Scale Reference

Service Quality

Price


Customer Lock in

Switching Cost

Perceived Switching Barriers

Intention to Switch

(Shin and Kim 2007)

Brand Communication

Brand Trust

(Azize, Cemeal and Hakan 2012)

Many statistical methods will be used to analyze the effect of each variable on other variable.

Some statistical Methods which are used to analyze the relationship of these variables which are

descriptive Statistics, regression analysis, correlation analysis. Table 1.1 shows that 200

questionnaires were filled from respondents and number of male respondents is 147 and female

respondents are 53. Similarly Table 1.2 explains that 73% of the respondents were between the

age group of 18-24 and 23% responses were come from people in 25-30 age groups. Only 4%

people in above 30 age group filled the questionnaires. Now if we look at Table 1.3 it shows the

current level of respondent and it shows that 38.5% respondents are studying in their

undergraduate education while maximum respondents lie in the graduate and above category

with 42.5%. 19% of respondents are working people and employed at somewhere or running

their own business. Table 1.4 describes what is the percentage of each cellular network users in

this study. Ufone stands at number one with maximum users of 42.5% of total while Warid grabs

18% share and after that Telenor stands with a share of 17% and on fourth Mobilink has 15%

Service Quality

Price

Brand Communication

Customer Lock in

Switching Cost

Brand Trust

Perceived switching barriers

respondents and Zong stands at last position with only 9.5% respondents. Pie charts also explains

the same scenerio.

Table 1.1

What is your gender?

Frequency Percent Valid Percent Cumulative

Percent

Valid

Male 147 73.5 73.5 73.5

Female 53 26.5 26.5 100.0

Total 200 100.0 100.0

Table 1.2

Your age group in years?


Percent

Valid

18-24 146 73.0 73.0 73.0

25-30 46 23.0 23.0 96.0

30 years above 8 4.0 4.0 100.0

Total 200 100.0 100.0

Table 1.3

What is your current level?


Percent

Valid Undergraduate 77 38.5 38.5 38.5

Graduate and above 85 42.5 42.5 81.0

Employed 38 19.0 19.0 100.0

Total 200 100.0 100.0

Table 1.4

Which cellular network do you use?


Percent

Valid

Mobilink 30 15.0 15.0 15.0

Telenor 34 17.0 17.0 32.0

Ufone 81 40.5 40.5 72.5

Zong 19 9.5 9.5 82.0

Warid 36 18.0 18.0 100.0

Total 200 100.0 100.0

Descriptive statistics and comparison of mean is used to analyze the response of the sample. Value of Cronbach Alpha represents the reliability of data and a correlation model explains the

relationship between dependent and independent variables. All the relationships among variables are assessed through positive and negative values of correlation. For hypothesis testing regression analysis is used.

DATA ANALYSIS AND INTERPRETATION

DESCRIPTIVE ANALYSIS

Mean:

Table 2.1

Descriptive Statistics

Mean Std. Deviation N

Intention_to_Switch 2.7250 .95191 200

Service_Quality 3.6383 .93495 200

Percieved_Price 3.1667 .89854 200

Customer_Satisfaction 3.6067 .88587 200

Customer_Lockin 2.9233 .78206 200

Switching_Cost 3.1683 .94281 200

Switching_Barriers 3.1750 .99521 200

Brand_Communication 3.5867 .85670 200

Brand_Trust 3.5283 .91166 200

Table 2.1 explains mean of each variable and customer satisfaction has the highest mean of (3.6067) which shows that customer satisfaction is prime factor which develops intention to switch. While customer lockin has lowest mean (2.9233) which shows that it has least effect in developing switching intention.

Comparison of Mean

Table 3.1

Intention_to_Switch * What is your gender?

Intention_to_Switch

What is your gender? Mean N Std. Deviation

Male 2.7642 147 .96373

Female 2.6164 53 .91846

Total 2.7250 200 .95191

Table 3.1 shows that male respondents have higher mean (2.6742) as compared to female

respondents (2.6164). So we can say that male respondents are more intend towards switching

than females.

Table 3.2

Intention_to_Switch * Your age group in years?

Intention_to_Switch

Your age group in years? Mean N Std. Deviation

18-24 2.6667 146 .95010

25-30 2.9565 46 .90978

30 years above 2.4583 8 1.11181

Total 2.7250 200 .95191

Table 3.2 explains that respondents in 25-30 age group ave highest mean of (2.9565) while age

group 18-24 have (2.6667) and 30 years above age group have lowest mean of (2.4583). Which

explains that people between ages 25-30.

Intention_to_Switch * What is your current level?

Intention_to_Switch

What is your current level? Mean N Std. Deviation

Undergraduate 2.6667 77 1.01307

Graduate and above 2.7961 85 .86388

Employed 2.6842 38 1.02505

Total 2.7250 200 .95191

Table 3.3

Table 3.3 shows that graduate and above level respondents have highest mean (2.7961) and undergraduate level respondents have lowest mean (2.667) which means respondents with highest mean tend to switch more as compared to others.

Table 3.4

Intention_to_Switch * Which cellular network do you use?

Intention_to_Switch

Which cellular network do

you use?

Mean N Std. Deviation

Mobilink 2.4889 30 .98934

Telenor 2.9314 34 .87532

Ufone 2.8477 81 .85643

Zong 2.5439 19 1.19262

Warid 2.5463 36 1.01779

Total 2.7250 200 .95191

This table illustrates that Telenor respondents have highest mean (2.9314) which mean they have

high intention to switch while Ufone (2.8477), Warid (2.5463), Zong (2.5439) and Mobilink

(2.4889). So Mobilink respondents are said to least intention to switch.

INFRENTIAL STATISTICS

Cronbach's Alpha

Table 4.1

Reliability Statistics

Cronbach's

Alpha

N of Items

.825 27

Result of Table 4.1 clearly shows the value of Cronbach’s Alpha value (.825) which means that collection of data of 31 questions is highly reliable.

Table 5

Correlations

Intention to

Switch

Service

Quality Price

Customer

Satisfaction

Customer

Lockin

Switching

Cost

Switching

Barriers

Brand

communic

ation

Brand

Trust

Intention to

Switch

Pearson

Correlation

1 -.248** -.184** .079** .029** -.048** -.267**

Sig. (2-tailed) .000 .009 .000 .267 .685 .483 .503 .000

N 200 200 200 200 200 200 200 200 200

Service

Quality

Pearson

Correlation

-.248** 1 .357** .656** .019 -.001** .176** .303 .430**

Sig. (2-tailed) .000 .000 .000 .788 .990 .012 .000 .000

N 200 200 200 200 200 200 200 200 200

Price Pearson

Correlation

-.184** .357** 1 .527** .079** .030 .179** .234** .443

Sig. (2-tailed) .009 .000 .000 .268 .673 .011 .001 .000

N 200 200 200 200 200 200 200 200 200

Customer

Satisfaction

Pearson

Correlation

-.339** .656** .527** 1** .067** -.025** .170** .429** .562**

Sig. (2-tailed) .000 .000 .000 .342 .729 .016 .000 .000

N 200 200 200 200 200 200 200 200 200

Customer

Lock in

Pearson

Correlation

.079 .019 .079 .067 1 .473 .414 .092 .047

Sig. (2-tailed) .267 .788 .268 .342 .000 .000 .193 .509

N 200 200 200 200 200 200 200 200 200

Switching

Cost

Pearson

Correlation

.029 -.001 .030 -.025 .473 1 .521 .080 .032

Sig. (2-tailed) .685 .990 .673 .729 .000 .000 .258 .649

N 200 200 200 200 200 200 200 200 200

Switching Barriers

Pearson

Correlation

.050 .176* .179* .170 .414* .521* 1 .342* .210*

Sig. (2-tailed) .483 .012 .011 .016 .000 .000 .000 .003

N 200 200 200 200 200 200 200 200 200

Brand communication

Pearson

Correlation

-.048 .303** .234** .429 .092** .080** .342 1** .608**

Sig. (2-tailed) .503 .000 .001 .000 .193 .258 .000 .000

N 200 200 200 200 200 200 200 200 200

Brand Trust

Pearson

Correlation

-.267** .430** .443** .562** .047** .032** .210** .608** 1**

Sig. (2-tailed) .000 .000 .000 .000 .509 .649 .003 .000

N 200 200 200 200 200 200 200 200 200

H1: There is a positive relationship between service quality and customer satisfaction.

The results in the Table 5 shows that there is a positive correlation (R: 0.656) between Service

Quality and Customer Satisfaction which is also significant at 0.000 level. Therefore we accept

H1.

H2: There is a negative relationship between perceived price and customer satisfaction.

The results in the Table 5 shows that there is a positive correlation (R: 0.527) between perceive

Price and customer satisfaction which is also significant at 0.000 level. Therefore we accept H2.

H3: There is negative relationship between customer satisfaction between customer

satisfaction and intention to switch.

The results in the Table 5 shows that there is a positive correlation (R: -0.339) between

Customer Satisfaction and Intention to Switch Loyalty which is also significant at 0.000 level.

Therefore we accept H3.


The results in the Table 5 shows that there is a positive correlation (R: 0.521) between Switching

Cost and Switching Barriers which is also significant at 0.000 level. Therefore we accept H4.

H5: There is positive relationship of customer lock in on perceived switching barriers.

The results in the Table 5 shows that there is a positive correlation (R: 0.414) between Customer

Lockin and Switching Barriers which is also significant at 0.000 level. Therefore we accept H5.

H6: There is negative relationship between perceived switching barriers and intention to

switch; Perceived switching barriers mediated the relationship of switching cost and

customer lock in on intention to switch.

The results in the Table 5 shows that there is a positive correlation (R: 0.050) between Switching

Barriers and Intention to Switch which is also significant at 0.483 level. Therefore we reject H6.

H7: Perceived switching barriers moderate the relationship between customer satisfaction

and intention to switch.

H8: There is a positive relationship between brand communication and brand trust.

The results in the Table 5 shows that there is a positive correlation (R: 0.608) between Brand

communication and Brand Trust which is also significant at 0.000 level. Therefore we accept H8.

H9: There is negative relationship between brand trust and intention to switch; Brand

trust mediates the relationship between brand communication and intention to switch.

The results in the Table 5 shows that there is a positive correlation (R: -0.267) between Brand

Trust and Intention to switch which is also significant at 0.000 level. Therefore we accept H9.

H10: there is a moderating effect of brand trust on relationship between customer

satisfaction and intention to switch.