Indian Journal of Science · telecommunication is an inseparable part of our everyday life. Besides telephone, now-a-days ... of different company are shown in Table 1.Citycell is

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Assessment of Customer Loyalty: A Case Study of Banglalink

Publication HistoryReceived: 10 July 2016Accepted: 30 July 2016Published: 1 August 2016

CitationAnwarul Islam KM. Assessment of Customer Loyalty: A Case Study of Banglalink. Indian Journal of Science, 2016, 23(84),633-668

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Indian Journal of Science CASE STUDYThe International Journal for ScienceISSN 2319 – 7730 EISSN 2319 – 7749© 2016 Discovery Publication. All Rights Reserved

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Assessment of Customer Loyalty: A Case Study ofBanglalink

Asst.Prof. K. M. Anwarul Islam1

1Department of Business Administration, The Millennium University, Dhaka, Bangladesh

E-mail:[email protected]

Correspondence: C/O K. M. Kamal Uddin, Deputy Registrar, Registrar’s office, Room No-

201(K),Dhaka University, Dhaka-1000, Tel: +8801768343171.

Abstract

This present study aims to explore the influence of customer satisfaction (towards servicesoffered by the mobile telecom operators) on customer loyalty. Specifically, this study tries: tofind out customers satisfaction with a variety of services provided by operators; to find out theinterrelationship between satisfaction of services (communication, price, value added service,convenience, sales-promotion and customer service) and customer loyalty.

Keywords: Assessment, Customer Loyalty, Banglalink.

1. Introduction

Economic growth in Bangladesh has contributed significantly to improvements in the quality oflife and spending power of an increasing share of the population (Hossain, 2010a). Today,telecommunication is an inseparable part of our everyday life. Besides telephone, now-a-daysmobile phones are playing a great role to communicate from one place to another place. Thephone is not only used for making calls, among many other functions it is used forcommunicating through text-messages, multi-media messages, as well as to connect us to theinternet. The opportunities that lie in the telecom market seem endless and the growing demandfor mobile telephony systems is creating a world-wide market. Actors in this industry are seekingthe most profitable markets throughout the world.

In Bangladesh, mobile phone services are the fast growing services in telecommunicationindustry. This sector has been showing an inspiring growth for the last few years. “The number ofmobile phone subscribers has steadily increased and many have begun to think that having a mobilephone is a necessary, not a luxury” (Hossain, 2010b). It is projected that

Bangladesh will be the third biggest telecom market in Asia after China and India (Uddinand Akhter, 2012; Hasan, 2008). The total number of Mobile Phone subscribers has reached

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98.593 million at the end of February 2013 (BTRC, 2013). More than half of the people ofBangladesh have been engaged in using mobile phone services. This enormous market coverageby Wireless Telecom Industry has proved that, though the Peoples’ Republic of Bangladesh is acountry of a growing economy with a very low per-capita income, buying power of customercould not impose any hinder on peoples’ consumption of cellular data transmission technology’sservices provided by the service providing operators in this industry. Actually the market ofBangladesh, up to now, has enjoyed the wireless infrastructure of remote voice communicationin two main methods known as Code-Division Multiple Access (CDMA) and Global System forMobile communications (GSM).

However, there are only six service providing operators namely, ‘Grameen PhoneLimited (GP)’,‘Banglalink Digital Communications Limited (Banglalink)’, ‘Robi Axiata Limited(Robi)’, ‘Airtel Bangladesh Limited (Airtel)’, ‘Teletalk Bangladesh Limited (Teletalk)’ and‘Pacific Bangladesh Telecom Limited (Citycell)’ in this industry. The mobile phone subscribersof different company are shown in Table 1.Citycell is the sole service provider in CDMA methodand other five operators provide services to their customers in GSM method. Mobile phoneoperators provide voice service and Value Added Services (VAS) including Short MessageService (SMS), Multimedia Message Service (MMS), ringtone, games, electronic transaction andweb browsing. Different foreign companies: Telenor of Norway, Axiata Group Berhad ofMalaysia, NTT DOCOMO INC from Japan and Abu Dhabi Group and SingTel Group wereattracted to this growing market.

It is well accepted that customer satisfaction is both a goal and a marketing tool forcustomer-centered companies, (Kotler and Keller, 2012). Oliver (1997) defines customersatisfaction as the consumer’s fulfillment response. He also considers customer satisfaction as ajudgment that a product or service feature, or the product or service itself, provides a pleasurablelevel of consumption related fulfillment. In other words, customer satisfaction is “the customers’evaluation of a product or service in terms of whether that product or service has met their needsand expectation” (Zeithaml et al., 2008). It is believed that increasing levels of customersatisfaction can be associated with customer loyalty. “Loyalty is a deeply held commitment torebuy or repatronize a preferred product or service in the future despite situational influences andmarketing efforts having the potential to cause switching behavior”(Kotler and Keller, 2012).

“The situation makes mobile telecommunication companies not only to promote theirservice quality, but also change their marketing core strategy to holding their existing customersby enhancing and optimizing the customer loyalty” (Hao et al., 2009). On the one hand, thecompanies have to invest quite much time and money to attract new customers and this processalways go through a longer time period associated with uncertainty and risks. On the other hand,“the cost of attracting a new customer is estimated to be five times the cost of keeping a currentcustomer happy” (Kotler and Keller, 2012). So it becomes significant for telecom companies toidentify factors of services that affect on customer loyalty and in turn creates loyal customers bysatisfying them in the context of Bangladesh.

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2. Literature Review

The need for customer loyalty in business has been recognized by many scholars. Customerloyalty is one of the most frequently discussed subjects in the marketing and service literature(Eshghi et al., 2007; Heskett and Sasser, 2010). There is a plethora of definitions of loyaltyand/or customer loyalty in the extant literature. Customer loyalty is customer repeating purchaseintention to some specific products or services in the future (Jones et al., 1995). It is makingcustomers feel committed: When the benefits are meaningful to them, they will stay on(Grossman, 1998). Loyalty is used to describe the willingness of a customer to continuepatronizing a firm’s goods and services over a long period of time and on a repeated andpreferably exclusive basis, and voluntarily recommending the firm’s products to friends andassociates (Lovelock, 1996). Customer loyalty is the result of an organization’s creating a benefitfor customers so that they will maintain and increasingly repeat business with the organization(Anderson and Jacobsen, 2000). From the forgoing, loyalty in GSM market is concerned with thelength of time and the frequency with which customers stay and remain on a network. The longerthe time a customer remains on and the more frequently a customer patronizes a GSM network,the more that customer becomes loyal. It is therefore the desire of all GSM firms in Bangladeshto retain large number of their customers on their networks.

Customer loyalty provides the foundation for a company’s sustained competitiveedge.Different researchers have given credence to the reason why developing customer loyalty isbeneficial to firms, including GSM providers. Developing and increasing loyalty is a crucialfactor in companies’ growth and performance (Reichheld, 1996 and Lee and Cunningham,2001).Customer loyalty is one of the key factors and can help a company achieve long-term success(Andres, 2007). The significance of customer loyalty is that it is closely related to the company’scontinued survival and to strong future growth (Fornell, 1992). Hence, for a company tomaintain a stable profit level when subscription level has reached saturation point, the market ismature and competition is fierce, a defensive strategy which strives to retain existing customersis more important than an aggressive one (Fornell, 1992 and Ahmad and Buttle, 2002). Ndubisi(2005) and Pfeifer (2005) point out that the cost of serving a loyal customer is five or six timesless than a new customer.Walsh et al. (2005) state that it is better to look after the existingcustomer before acquiring new customers. From the above, it is evident that a telecom firm thatpromotes customer loyalty has a lot to benefit from. The current saturated level of GSM growthand intense competition in Bangladesh has left the operators with no option other than seeking tomaintain the existing customers and lock them into loyalty. Bulk of the current marketing effortsby these firms is aimed at retaining and making customers loyal.

Since customer loyalty has become paramount for organizations, a major concern is tofind out the determinants or drivers of customer loyalty (Kumar et al., 2011). This sectiondiscusses the determinants of customer loyalty.

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Defining the concept of service quality the most important criteria in the economicdevelopment of international companies, whereas under different circumstances it has beenprevented the emergence of a universal definition ( Reeves and Bednar, 1994). In addition, it isdifficult to define the service quality as opposed to the quality of good. The general definition of“Quality” is “Satisfying customer’s requirements”. (Ghobadian et al., 1994) The definition ofservice quality from the customer’s viewpoint is as follows (Parasuraman et al., 1998). “Servicequality is an inference regarding the superiority of a product or service based on a rationalassessment of characteristics or attributes, or an affective judgment or emotional response similarto an attitude”

It is a critical element of customer perceptions. In the case of pure service (e.g. healthcare, etc) service quality will be dominant element in the customer’s evaluation. (Valarie A.Zeithaml, Mary Jo Bitner, 2011)

Price is the amount of money charged for a product or service, or the sum of the valuesthat customers exchange for the benefits of having or using the product or service (Kotler andArmstrong, 2010). In a competitive market, service providers are expected to compete on bothprice and quality of services and also it is necessary for the service providers to meet theconsumers’ requirements and expectations in price and service quality (Melody, 2001).

Nowadays, due to breathtaking competition, the telecommunication service providerstend to offer innovative services as well as competitive prices just to attract handful magnitude ofcustomers (Haquea et al., 2011). Price plays a vital role in telecommunication market especiallyfor the mobile telecommunication service providers (Kollmann, 2000). The price here is notlimited to price of a SIM card, but also covers the price of recharge voucher, call rate, SMScharge, the Internet charge, price of phones, and so on. A network with lower prices has a hightendency to attract a large subscriber base leading to an impressive market and financialperformance. Kollmann (2000) states that income from the number of call minutes determinesthe basic commercial success for the network providers. He also adds that the success of thetelecommunication sector in a market place largely depends on continuing usage and pricingpolicies, which need to be considered on several levels. The implication of this is that offering ahigh service quality is not sufficient to attract and retain customers in the telecom market;offering the service at an attractive and affordable price is equally necessary to achieve acompetitive advantage in the market. Specifically, price has been used by all the firms in theGSM market of Bangladesh, as a strategic tool both to attract new subscribers and moreimportantly to retain current ones. In the market, where it is difficult to perceive any significantdifference in the service quality of most of the GSM firms, price competition has becomewidespread and an important competitive tool. However, the reality of the price competition inthe market is existence of price war with subscribers traversing from one network to another totake advantage of the latest price cut, thereby giving no room for any loyalty to be developed.The poser is can price be used to achieve customer loyalty in the telecommunication market? Inthe study concerning the behavior of mobile telecommunication consumers, it was found that the

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loyalty of individual customers is affected by price considerations (Bolton and Drew, 1991). Thisfinding was also corroborated by Athanassopoulos (2000) and Varki and Colgate (2001),whereby customer satisfaction from pricing was found to positively affect overall customersatisfaction. GSM firms in Bangladesh should charge tariff that is fair and acceptable to theirsubscribers, taking into cognizance their price sensitivity. This is because there is a relationshipbetween the level of customer loyalty and price sensitivity. According to Xia et al. (2007) pricefairness refers to consumers’ assessments of whether a seller’s price is reasonable, acceptable orjustifiable.

Customers are satisfied and become loyal when they feel that the price they paycorresponds to the quality of service they receive. Choi et al. (2006) found that disloyalcustomers were more price sensitive, in the sense that changes in price motivated them to moveto other organizations, whereas loyal customers were not affected by price. Martı´n-Consuegra etal. (2007) also found that perceived price fairness influences customer satisfaction and leads toloyalty.

3. Statement of the Problem

In this competitive telecom industry, customer retention is one of the most important factors forthe telecom companies in order to sustain in this market. It has been found that many subscribersswitch their mobile operator frequently. And this causes damages to the current mobile operator.So in order for telecom companies to have a smooth run, it must obtain loyal customers. And thestatement of the problem for this study is; “making an ordinary customer to a loyal customer”.

4. Objectives of the Research

The purpose of this study is to find what factor can make an ordinary customer in to a loyalcustomer. In doing so this paper can help the telecom companies to put emphasis on thevariables, preferred by the customers and increase the customer loyalty.

5. Research Design and Methodology

This study is descriptive in nature. Descriptive research is used to obtain information concerningthe current status of the phenomena to describe “what exists” with respect to variables orconditions in a situation (Zikmund, 2003). A conceptual model was developed to explainsatisfaction of services and loyalty that directs the proposed relationship between independentand dependent variables. This relationship, then, was tested with the empirical findings. Mostdata for these studies were collected by means of structured questionnaire. This study also usedsecondary data for shaping the theoretical background and depth of knowledge. The secondarydata were collected from the different journals, magazines, books and web-sites.

Sampling: Convenience sampling was employed to select the respondents. In total, 50 cell phoneusers (of different operators) of various age groups and occupation.

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The questionnaire had four sections. The first two sections contained the demographiccharacteristics and general information of the respondents: age groups, gender and occupation;duration of mobile phone usage and monthly expense for operating cell phone. The last twosections of the questionnaire included the dependent variable: customer loyalty and sixindependent variables- communication, price/tariff structure, value-added services, convenience,sales promotions and customer service/care. Measures for independent and dependent variablesused a five-point Likert-type response format, with “strongly disagree” and “strongly agree” asthe anchors. The users recorded their assessment of the items on five-point Likert-type scales (1= strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). This study focusedon six factors such as communication, price structure, value-added service, convenience, sales-promotions and customer service.

6. Hypothesis and Research Questions

Thus six hypotheses were used to determine the relationship between those factors and customerloyalty, considering customer loyalty as the dependent variable and other factors as independentsvariables:

H1: Satisfaction of communication has positive influence on customer loyalty. H2: Satisfactionof price/tariff structure has positive influence on customer loyalty. H3: Satisfaction of value-added service has positive influence on customer loyalty. H4: Satisfaction of convenience haspositive influence on customer loyalty.

H5: Satisfaction of sales-promotion has positive influence on customer loyalty.

H6: Satisfaction of customer service/care has positive influence on customer loyalty.

Quantitative statistical techniques were used to analyze the data. This study attempted todetermine the relationship between communication and customer loyalty, price structure andcustomer loyalty, value-added services and customer loyalty, convenience and customer loyalty,sales-promotion and customer loyalty; customer service and customer loyalty.

7. Data analysis and Findings

Demographic Breakdown of the respondents (n-40) (Appendix 1)

It can be seen that the total participants were 40. Among which 18 were male and 22 femaleresulting in a sex composition of 45% male and 55% female. The age distribution; 18-30, 31-39,40-49, 50 and above are 48.0%, 27.5%, 20.0%, and 7.5% respectively. So looking at thedemographics the respondents were mature enough and have enough experience to answer thesurvey.

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Reliability analysis for “Communication” (Appendix 2)

In the survey questioner (Appendix 21), the first three questions are related to the independentvariable Communication. The Cronbach Alpha Value for the Reliability analysis for“Communication” is 0.888, which is >0.7 that means it is desirable. Hence, the questions arereliable.

Reliability analysis for “Pricing” (Appendix 3)

In the survey questioner, question number 4, 5 and 6 are related to the independent variablePricing. The Cronbach Alpha Value for the Reliability analysis for “Pricing” is 0.783, which is>0.7 that means it is desirable. Hence, the questions are reliable.

Reliability analysis for “VAS” (Appendix 4)

In the survey questioner (Appendix 21), question number 7, 8 and 9 are related to theindependent variable VAS. The Cronbach Alpha Value for the Reliability analysis for “VAS” is0.846, which is >0.7 that means it is desirable. Hence, the questions are reliable.

Reliability analysis for “Convenience” (Appendix 5)

In the survey questioner (Appendix 21), question number 10, 11, 12 and 13 are related to theindependent variable Convenience. The Cronbach Alpha Value for the Reliability analysis for“Convenience” is 0.938, which is >0.7 that means it is desirable. Hence, the questions arereliable.

Reliability analysis for “Sales Promotion” (Appendix 6)

In the survey questioner (Appendix 21), question number 14, 15 are related to the independentvariable Sales Promotion. The Cronbach Alpha Value for the Reliability analysis for “SalesPromotion” is exactly 0.921, which is more than or equal to 0.7 that means it is desirable. Hence,the questions are reliable.

Reliability analysis for “Customer Care” (Appendix 7)

In the survey questioner (Appendix 21), question number 15,17 and 18 are related to theindependent variable Customer Care. The Cronbach Alpha Value for the Reliability analysis for“Customer Care” is 0.873, which is >0.7 that means it is desirable. Hence, the questions arereliable.

Reliability analysis for “Customer Loyalty” (Appendix 8)

In the survey questioner (Appendix 21), question number 19 and 20 are related to the dependentvariable Customer Loyalty. The Cronbach Alpha Value for the Reliability analysis for “Loyalty”is 0.767, which is >0.7 that means it is desirable. Hence, the questions are reliable.

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This part of the research paper is one of the most important. Because here we will findthe relationship and test the hypothesis of the research paper. And before stating theinterpretations, the standard for the Pearson’s correlation (How do I interpret data in SPSS forPearson's r and scatter plots?, 2008) When Pearson’s r is close to 1. This means that there is astrong relationship between the two variables. This means that changes in one variable arestrongly correlated with changes in the second variable. When Pearson’s r is close to 0. Thismeans that there is a weak relationship between the two variables. This means that changes inone variable are not correlated with changes in the second variable. If the Pearson’s r were 0.01,it can be said that the variables were not strongly correlated. When Pearson’s r is positive (+).This means that as one variable increases in value, the second variable also increase in value.Similarly, as one variable decreases in value, the second variable also decreases in value. This iscalled a positive correlation. When Pearson’s r is negative (-).This means that as one variableincreases in value, the second variable decreases in value. This is called a negative correlation. Ifthe Sig (2-Tailed) value is greater than .05. It means that that there is no statistically significantcorrelation between your two variables. That means, increases or decreases in one variable donot significantly relate to increases or decreases in the second variable. If the Sig (2-Tailed)value is less than or equal to 0.05 .It means that there is a statistically significant correlationsbetween the two variables. That means, increases or decreases in one variable do significantlyrelate to increases or decreases in the second variable.

Correlations between Customer Loyalty and Communication (Appendix 9)

Now looking at the values of Pearson’s Correlation value that is 0.88 and the Sig value is 0.038which meets the standard so it is proved that there is relation between Customer Loyalty andEmpathy. H1 has been proven.

Correlations between Customer Loyalty and Pricing (Appendix 10)

Now looking at the values of Pearson’s Correlation value that is 0.77, and the Sig value is 0.015,which meets the standard so it is proved that there is relation between Customer Loyalty andPricing. H2 has been proven.

Correlations between Customer Loyalty and VAS (Appendix 11)

Now looking at the values of Pearson’s Correlation value, that is 0.29 and the Sig value is 0.346,which does not meets the standard so it is proved that there is no relation between CustomerLoyalty and Empathy. H3 has not been proven.

Correlations between Customer Loyalty and Convenience (Appendix 12)

Now looking at the values of Pearson’s Correlation value that is 0.61 and the Sig value is 0.014,which meets the standard so it is proved that there is relation between Customer Loyalty andConvenience. H4 has been proven.

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Correlations between Customer Loyalty and Sales Promotion (Appendix 13)

Now looking at the values of Pearson’s Correlation value that is 0.015, and the Sig value is0.927, which does not meets the standard so it is proved that there is no relation betweenCustomer Loyalty and Sales Promotion. H5 has not been proven.

Correlations between Customer Loyalty and Customer Care (Appendix 14)

Now looking at the values of Pearson’s Correlation value that is 0.46, and the Sig value is 0.039,which meets the standard so it is proved that there is relation between Customer Loyalty andCustomer Care. H6 has been proven. Further analysis has been done in order to test thehypothesis. Regression analysis between the dependent variable and the independent variable.The standard for the regression analysis with the help of which we would interpret the values are,the value of R2 that represents how much a dependent variable is explained by the independentvariable, and if p ≤ 0.05 then the hypothesis will be accepted.

Regression between Customer Loyalty and Communication (Appendix 15)

A regression analysis has been done where the dependent variable is customer Loyalty and theindependent variable is communication. And the value of R2 is .0.477 which means that 47.7%of the customer Loyalty has been ‘explained’. In addition, the p value is 0.038 that is p ≤ 0.05.Hence, Communication has positive relation with customer loyalty.

Regression between Customer Loyalty and Pricing (Appendix 16)

A regression analysis has been done where the dependent variable is customer Loyalty and theindependent variable is Pricing. And the value of R2 is .0.338 which means that 33.8% of thecustomer Loyalty has been ‘explained’. In addition, the p value is 0.023 , that is p ≤ 0.05. Hence,Pricing has positive relation with customer loyalty.

Regression between Customer Loyalty and VAS (Appendix 17)

A regression analysis has been done where the dependent variable is customer Loyalty and theindependent variable is VAS. And the value of R2 is .0.023 which means that 2.3% of thecustomer Loyalty has been ‘explained’. In addition, the p value is 0.346 that is p > 0.05. Hence,VAS has no positive relation with customer loyalty.

Regression between Customer Loyalty and Convenience (Appendix 18)

A regression analysis has been done where the dependent variable is customer Loyalty and theindependent variable is Convenience. And the value of R2 is 0.168 which means that 16.8% ofthe customer Loyalty has been ‘explained’. In addition, the p value is 0.046 that is p ≤ 0.05Hence, Convenience has positive relation with customer loyalty.

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Regression between Customer Loyalty and Sales Promotion (Appendix 19)

A regression analysis has been done where the dependent variable is customer Loyalty and theindependent variable is Sales Promotion. And the value of R2 is .0.022 which means that 2.2%of the customer Loyalty has been ‘explained’. In addition, the p value is 0.273 that is p > 0.05.Hence, Sales Promotion has no positive relation with customer loyalty.

Regression between Customer Loyalty and Customer Care (Appendix 20)

A regression analysis has been done where the dependent variable is customer Loyalty and theindependent variable is Customer Care. And the value of R2 is 0.197 which means that19.7% ofthe customer Loyalty has been ‘explained’. In addition, the p value is 0.039 that is p ≤ 0.05Hence, Customer Care has positive relation with customer loyalty.

8. Conclusion and Recommendation

The administration of the independent variables that is; communication, pricing, vas,convenience, sales promotion and customer care and the subsequent analysis of the results haverevealed that the overall perception of the customer loyalty, provided by the data collected fromthe mobile phone users is acceptable. While the overall customer loyalty level provided by thedata collected from the mobile phone users was within the acceptable level, analysis of thedifference between the dependant and independent variables revealed that vas and sales are theareas where the most effort should be focused. So in brief, the communication, pricing,convenience, and customer care leads to customer loyalty because according to the data receivedand the analysis of the data, revealed that customer loyalty is gained through the our factorsmentioned above.

In light of the statistics, we can establish Banglalink is not sufficiently successful increating customer loyalty among its customers. It is evident that management in the future mustpay attention to these important issues because they represent some of the most importantrequisites for creating long-term relation with the customers. Business activities shouldcommence with understanding the need of the customers if their aim is to achieve customersatisfaction that eventually leads to customer loyalty.

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Appendixes

Appendix 1: Demographic analysis

Gender

Frequency Percent Valid Percent Cumulative Percent

Valid M 18 45.0 45.0 45.0

F 22 55.0 55.0 100.0

Total 40 100.0 100.0

Page | 654

Age

Frequency Percent Valid Percent Cumulative Percent

Valid 18-30 18 45.0 45.0 45.0

31-39 11 27.5 27.5 72.5

40-49 8 20.0 20.0 92.5

50+ 3 7.5 7.5 100.0

Total 40 100.0 100.0

Appendix 2: Reliability test for COMMUNICATION

Case Processing Summary

N %

Cases Valid 40 100.0

Excludeda 0 .0

Total 40 100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics

Cronbach's Alpha N of Items

.888 4

Page | 655

Appendix 3: Reliability test for PRICING


N %


Excludeda 0 .0

Total 40 100.0




.783 4

Appendix 4: Reliability test for VAS


N %


Excludeda 0 .0

Total 40 100.0


Page | 656



.846 4

Appendix 5: Reliability test for CONVENIENCE


N %


Excludeda 0 .0

Total 40 100.0




.938 5

Appendix 6: Reliability test for SALES PROMOTION


N %


Excludeda 0 .0

Total 40 100.0


Page | 657



.921 3

Appendix 7: Reliability test for CUSTOMER CARE


N %


Excludeda0 .0

Total 40 100.0




.873 4

Appendix 8: Reliability test for CUSTOMER LOYALTY


N %


Excludeda0 .0

Total 40 100.0

Page | 658




.767 3

Appendix 9: CORELLATION between CL & COMMUNICATION

Correlations

Communication Customer Loyalty

Communication Pearson Correlation 1 .840

Sig. (2-tailed) .038

N 40 40

Customer Loyalty Pearson Correlation .840 1


N 40 40

Appendix 10: CORELLATION between CL & PRICING

Correlations

Customer Loyalty Pricing

Customer Loyalty Pearson Correlation 1 .077


N 40 40

Pricing Pearson Correlation .077 1

Sig. (2-tailed) . 015

Page | 659

N 40 40

Appendix 11: CORELLATION between CL & VAS

Correlations

Customer Loyalty Value Added Service



N 40 40

Value Added Service Pearson Correlation .29 1


N 40 40

Appendix 12: CORELLATION between CL & CONVENIENCE

Correlations

Customer Loyalty Convenience



N 40 40

Convenience Pearson Correlation .610 1


N 40 40

Page | 660

Appendix 13: CORELLATION between CL & SALES PROMOTION

Correlations

Customer Loyalty Sales Promotion



N 40 40

Sales Promotion Pearson Correlation .015 1


N 40 40

Appendix 14: CORELLATION between CL & CUSTOMER CARE

Correlations

Customer Loyalty Customer Care



N 40 40

Customer Care Pearson Correlation .140 1


N 40 40

Page | 661

Appendix 15: Regression between CL & COMMUNICATION

Variables Entered/Removedb

Model Variables Entered Variables Removed Method

1 Communicationa . Enter

All requested variables entered.

Dependent Variable: Customer Loyalty

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .691 .477 -.024 .81346

a. Predictors: (Constant), Communication

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression .193 1 .049 .074 .038a

Residual 25.145 38 .662

Total 25.194 39

Predictors: (Constant), Communication


Coefficientsa

Standardized

Unstandardized Coefficients Coefficients

Page | 662

Model B Std. Error Beta t Sig.

1 (Constant) 3.028 .511 5.932 .000

Communication .037 .135 .044 .272 .787

a. Dependent Variable: Customer Loyalty

Appendix 16: Regression between CL & PRICING



1 Pricinga . Enter



Model Summary


1 .581a .338 -.020 .81183

a. Predictors: (Constant), Pricing

ANOVAb


1 Regression .149 1 .149 .226 .023a

Residual 25.045 38 .659

Page | 663

Total 25.194 39

Predictors: (Constant), Pricing


Coefficientsa

Standardized



1 (Constant) 2.815 .742 3.794 .001

Pricing .102 .215 .077 .475 .637


Appendix 17: Regression between CL & VAS



1 Value Added Servicea . Enter



Model Summary


Page | 664

1 .153a .023 -.002 .80467

a. Predictors: (Constant), Value Added Service

ANOVAb


1 Regression .589 1 .589 .910 .346a

Residual 24.605 38 .647

Total 25.194 39

Predictors: (Constant), Value Added Service


Coefficientsa

Standardized



1 (Constant) 3.672 .549 6.691 .000

Value Added Service -.150 .157 -.153 -.954 .346


Appendix 18: Regression between CL & CONVENIENCE



Page | 665

1 Conveniencea . Enter



Model Summary


1 .411a .168 -.014 .80923

a. Predictors: (Constant), Convenience

ANOVAb


1 Regression .309 1 .309 .473 .046a

Residual 24.884 38 .655

Total 25.194 39

Predictors: (Constant), Convenience


Coefficientsa

Standardized



1 (Constant) 2.858 .461 6.201 .000

Page | 666

Convenience .082 .119 .111 .687 .496


Appendix 19: Regression between CL & SALES PROMOTION



1 Sales Promotiona . Enter



Model Summary


1 .151a .022 -.026 .81415

a. Predictors: (Constant), Sales Promotion

ANOVAb


1 Regression .006 1 .006 .009 .273a

Residual 25.188 38 .663

Total 25.194 39

Predictors: (Constant), Sales Promotion


Page | 667

Coefficientsa

Standardized



1 (Constant) 3.134 .331 9.480 .000

Sales Promotion .012 .128 .015 .093 .927


Appendix 20: Regression between CL & CUSTOMER CARE



1 Customer Carea . Enter



Model Summary


1 .446a .197 -.006 .80626

a. Predictors: (Constant), Customer Care

Page | 668

ANOVAb


1 Regression .492 1 .492 .757 .039a

Residual 24.702 38 .650

Total 25.194 39

Predictors: (Constant), Customer Care


Coefficientsa

Standardized



1 (Constant) 2.671 .580 4.607 .000

Customer Care .134 .154 .140 .870 .390


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