RELATIONSHIPS BETWEEN CUSTOMER SATISFACTION

AND SERVICE LOYALTY: USERS’ PERCEPTION ON

TELECOMMUNICATION SERVICE PROVIDERS IN

MALAYSIA

CHONG HUI LING

Relationships between Customer Satisfaction and Service

Loyalty: Users’ Perception on Telecommunication Service

Providers in Malaysia

Chong Hui Ling Bachelor of Arts

Deakin University

Melbourne, Victoria

Australia

2000

Submitted to the Graduate School of Business

Faculty of Business and Accountancy

University of Malaya, in partial fulfilment

Of the requirements for the Degree of

Master of Business Administration

5th December 2008

ii

Abstract

This dissertation reports the results of a yearlong study focused on describing and

coming to understand the perceptions of mobile phone users on relationships between

customer satisfaction and service loyalty towards telecommunication service

providers in Malaysia. This study seeks to contribute to the development of a

conceptual framework that integrate service quality, corporate image, price, customer

satisfaction, and service loyalty.

The study was conducted using based on non probability sampling in Malaysia with

focus point is on Klang Valley area. The research sample was selected from a range

of demographic elements for processing based on convenience sampling. Methods of

data-collection included online questionnaire, and self-administered questionnaire.

Quantitative data obtained and the data gathered were being treated by using the

statistical software program namely Statistical Package for Social Research (SPSS)

version 14.0 for analysis and summarization purposes.

In preparation for the study, a comprehensive literature review was performed. The

literature review informed the theoretical framework which guided the study.

Additional literature, where needed, was introduced through the data collection and

analysis processes. The study uncovered that service quality, corporate image, and

price are found to act on service loyalty via customer satisfaction. Price has been

found to be the most important input to customer satisfaction. It gives implications for

differentiated marketing strategies according to the perceived value and type of

customer loyalty and summative overview topics for further study.

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Acknowledgment The work of this thesis represents the concerted efforts of many individuals over the

past one year. One of the features of the paper is collaboration and certainly, it

required many acts of collaboration by quite a few people in order to come to fruition.

First, I would like to express my thanks to my supervisor, Prof. Madya Dr. Sharifah

Latifah Syed A. Kadir, for her guidance and supervision in completing this thesis

project. There would not be a thesis if it were not for you.

I owe a debt of gratitude to my family who sacrificed time with their daughter and

wife so that she could climb her own personal Mount Everest. A special thank to my

loving husband, Tan Chee Leong, who especially supportive in listening to my ideas

and helping me work out logistical details throughout this long process.

I would also like to acknowledge my thanks to Mr. Chang Peng Kee for his guidance

and helpful recommendations concerning statistical procedures. I am deeply indebted

and much grateful to my employer, CompuMed Services Sdn Bhd, for the unreserved

support and understanding rendered during this period.

Finally, I would like to acknowledge all the people who participated in my thesis

project.

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Table of Contents Topic Page 1. 1.0 Introduction 1 1.1 Purpose and Significance of the Study 3 1.2 Objectives and Questions of the Study 4 1.3 Scope of the Study 5 1.4 Limitations of the Study 6 1.5 Organization of the Study 7 2. 2.0 Literature Review 9 2.1 Service Quality 9 2.1.1 Parasuraman’s SERVQUAL 11 2.1.2 Gronroos’s Methodology 14 2.1.3 Cronin’s SERVPERF 16 2.1.4 Service Quality and Customer Satisfaction 18 2.1.5 Recent Findings 20 2.2 Corporate Image 21 2.2.1 Corporate Image and Customer Satisfaction 24 2.2.2 Recent Findings 25 2.3 Price 26 2.3.1 Price Sensitivity 26 2.3.2 Price Acceptance 27 2.3.3 Price Perception 28 2.3.4 Price Fairness 29 2.3.5 Price and Customer Satisfaction 30 2.3.6 Recent Findings 30 2.4 Customer Satisfaction 31 2.4.1 Customer Satisfaction and Service Loyalty 33 2.4.2 Recent Findings 34 2.5 Service Loyalty 35 2.5.1 Recent Findings 37 3. 3.0 Research Methodology 39 3.1 Theoretical Framework 39 3.2 Research Hypotheses 39 3.3 Selection and Measures 40 3.4 Sample Design 41 3.5 Development of Test Measures 42 3.5.1 Items to Measure Service Quality 42 3.5.2 Items to Measure Corporate Image 43 3.5.3 Items to Measure Price 43

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Table of Contents (Continued)

Topic Page 3.5.4 Items to Measure Customer Satisfaction 44 3.5.5 Items to Measure Service Loyalty 45 3.6 Data Analysis Techniques 45 3.6.1 Reliability Test 45 3.6.2 Factor Analysis 46 3.6.3 ANOVA Test 47 3.6.4 Correlation 47 3.6.5 Partial Correlation 48 3.6.6 Multiple Regression 48 3.7 Pilot Test 49 4.0 Research Results 50 4.1 Respondents’ Demographic Profiles 50 4.2 Analysis of Measures 53 4.2.1 Reliability Test 53 4.2.2 Factor Analysis 53 KMO and Bartlett’s Test 53 4.2.3 ANOVA Test 56 4.2.4 Correlation 57 4.3 Testing of Hypotheses 57 Independent Variables as Predictors to Service Loyalty 58 Independent Variables as Predictors to Customer Satisfaction 59 Partial Correlation 60 Customer Satisfaction as Predictor to Service Loyalty 61 Independent Variables and Customer Satisfaction as Predictors to Service Loyalty

62

4.4 Summary of Research Results 64 5.0 Conclusion and Recommendations 68 5.1 Summary and Conclusion 68 5.2 Suggestions for Future Research 69 5.3 Implications 69 5.3.1 Service Quality 69 5.3.2 Corporate Image 70 5.3.3 Price 71 5.3.4 Customer Satisfaction 72 5.3.5 Service Loyalty 73

vi

Table of Contents (Continued)

Topic Page 6. 6.0 References 74 7. 7.0 Appendix 92 Appendix A – Questionnaire Appendix B – Report in CD

vii

List of Figures Title Page

Figure 2.1 Main Research Streams on Service Quality 9

Figure 2.2 Gaps in Service Quality 13

Figure 2.3 Perceived Service Quality 15

Figure 2.4 Relationship between Customer Satisfaction and Service Quality

19

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List of Tables Title Page Table 1 Respondents’ Demographic Profiles 52

Table 2 KOM & Barlett’s Test 54

Table 3 Factor Analysis and Reliability 55

Table 4 Descriptive Summary for the Three Telecommunication Service Providers

57

Table 5 Correlations Matrix between Variables 57

Table 6 Model Summary (Independent Variables as Predictors to Service Loyalty)

58

Table 7 ANOVA (Independent Variables as Predictors to Service Loyalty)

58

Table 8 Coefficients (Independent Variables as Predictors to Service Loyalty)

59

Table 9 Model Summary (Independent Variables as Predictors to Customer Satisfaction)

59

Table 10 ANOVA (Independent Variables as Predictors to Customer Satisfaction)

59

Table 11 Coefficients (Independent Variables as Predictors to Customer Satisfaction)

60

Table 12 Correlations – Control Variables (Corporate Image and Price) 61

Table 13 Correlations – Control Variables (Service Quality and Corporate Image)

61

Table 14 Model Summary (Customer Satisfaction as Predictor to Service Loyalty)

62

Table 15 ANOVA (Customer Satisfaction as Predictor to Service Loyalty)

62

Table 16 Coefficients (Customer Satisfaction as Predictor to Service Loyalty)

62

Table 17 Model Summary (Independent Variables and Customer Satisfaction as Predictors to Service Loyalty)

63

Table 18 ANOVA (Independent Variables and Customer Satisfaction as Predictors to Service Loyalty)

63

Table 19 Coefficients (Independent Variables and Customer Satisfaction as Predictors to Service Loyalty)

64

Table 20 Result Table of the Tested Hypotheses 64

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1.0 Introduction

Asia's telecommunications industry has seen rapid development in the past decade

and looks poised for further expansion, charting growth rates of 25% in 2006 (The

Star, 21 July 2007). While for the Malaysian telecommunications industry, growth

rate is mainly driven by the mobile services segment. In general, there will be wider

subscriber base, increases in international calls and increased popularity in the usage

of mobile data (SMS, ringtones and songs downloads, GPRS) supported the growth in

the Malaysian mobile services segment.

As per the report by The Star dated 21st July 2007, the number of cellular phone

subscribers has risen to 19.464 million as at end-2006 vs. 5.122 million in

2000. Mobile phone subscribers are expected to reach 24.4 million by 2010. Cellular

phone penetration rate per 100 population stood at 72.3% as at end-2006 vs. 21.8% in

2000. Mobile penetration rate is expected to trend higher to 85% by 2010, driven by

convenience, affordability and in keeping with changing lifestyles. In terms of market

share of telecommunication players, Maxis dominated the cellular services market at

40%, followed closely by TM-Celcom at 35% and Digi at 25%.

The following information was found from the Malaysian Communications and

Multimedia Commission’s “Handphone Users Survey 2007” report. The report stated

that Selangor continues as the state with the highest number of hand phone users at

22.1 percent followed by Johor (13.5 percent), Federal Territory of Kuala Lumpur

(8.6 percent) and Perak (7.8 percent). Among other states, Sabah (including Federal

Territory of Labuan), Penang, Kedah, and Sarawak have between 6 and 7 percent of

hand phone users, while Pahang, Kelantan, Negeri Sembilan, Terengganu and Melaka

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have between 4 and 5 percent users. Perlis has the smallest number of users with only

0.8 percent.

In June 2003, the Malaysian Communications and Multimedia Commission launched

an independent study to assess dominance within the communications and multimedia

industry in Malaysia. The study was conducted as part of the Commission’s role as

industry regulator, a key function of which is to promote effective competition in the

communications and multimedia industry. The study showed that the mobile market is

very competitive. A high percentage of “churn” experienced by the mobile operators

indicates that consumers are willing to switch operators rather easily. To stay ahead,

quality of service and cost will be a key competitive advantage for the mobile

operators in order to retain customer loyalty.

Competition between mobile providers is getting stronger nowadays by citing

evidence of reductions in the price of pre –paid starter kits, free airtime offers for pre-

paid customers, rebates on monthly access fees for post-paid customers, more

attractive call tariff packages (such as “family and friends”), and lower SMS tariffs. It

also argued that this competition has been to the benefit of customers not only in

terms of lower prices, but also in terms of quality of services. Expenditure on capital

(to enhance service coverage and quality of service) and the introduction of initiatives

to better manage relationships with customers are both further evidence of this

competition.

This situation makes telecommunication service providers pay less attention on or

ignore other factors that might affect customer satisfaction and retention. Mobile

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phone users have been increasingly demand for affordable and reliable services that

correspond exactly to their specific individual needs, lifestyle and preferences.

Telecommunication service providers require good knowledge of the needs and

perceived quality of the user segments. It is essential for service providers to

understand how their service brings value to users’ everyday life.

1.1 Purpose and Significance of the Study

The purposes of the study are to examine the determinants of customer satisfaction

and the loyalty intentions for the mobile service providers. In addition, the study aims

to investigate the characteristics of the mobile consumers with regards to their

satisfaction and loyalty.

Service quality, corporate image and price are the identified independent variables in

this study. As mentioned by Albert Caruana (2002), “an important reason for the

interest in service quality by practitioners results from the belief that this has a

beneficial effect on bottom-line performance for the firm.” It gives indications to

telecommunication service providers as to where best to devote marketing attention

and scare their resources.

While for corporate image, if a service provider has a positive image in the eyes of

customers, minor mistake will be forgiven but the image will be damaged if mistakes

often occur. On the other hand, if a service provider’s image is negative, the impact of

any mistake will be significant and affect level of satisfaction. Davies et al. (2002)

demonstrated the positive impact of corporate image on customer satisfaction in the

retailing context. It can be assumed that this kind of positive influence will also hold

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in the mobile phone service sector as image represents an essential factor for the

perception of satisfaction.

Huber et al. (2001) stated that if the central role of pricing in consumer behaviour as

well as cost effectiveness is considered as one of the criteria that consumers rank as

being particularly important when selecting a product or service, the fact that the price

has received little attention when analyzing customer satisfaction is astonishing.

Huber reiterated that service marketing is different to goods marketing, and is usually

more complex to manage. In this circumstance, price is an important factor in

purchasing and post-purchasing processes. As such, it is an important variable in

services. It is also crucial for organizations to set and manage price which it directly

influence an inflow of resources.

1.2 Objectives and Questions of the Study

This study seeks to contribute to the development of a conceptual framework that

integrate service quality, corporate image, price, customer satisfaction, and service

loyalty. As mentioned by Albert Caruana (2002), work that integrates the role of

service loyalty within the context of other service marketing variables like service

quality and customer satisfaction have received less attention. As a result, a survey of

consumers will be conducted to provide insight into these issues in Malaysian context.

This study tries to answer to the following questions:

1. Does service quality, corporate image and price influence customer satisfaction?

2. Is there a trade-off between price and service quality which is most often

materialized in term of customer satisfaction?

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3. Does customer satisfaction mediates the relationship among service quality,

corporate image and price towards service loyalty?

The research objectives of the study are:

1. To investigate the determinants of perceived service quality, corporate image and

price and which is more significantly affecting customer satisfaction.

2. To investigate the effect of customers’ satisfaction on service loyalty of

telecommunication service providers.

1.3 Scope of the Study

This study focuses on telecommunication service providers in Malaysia, which has

three major players at time of writing: Celcom, Digi, and Maxis. The research sample

will be selected from a range of demographic elements for processing based on non

probability sampling in Malaysia with focus point is on Klang Valley area.

The data for this study was collected through self-administered questionnaire during

the period from 16th May 2008 to 30th June 2008. Extra effort has been made by using

a survey website (http://freeonlinesurveys.com) for respondents to participate in this

study through internet.

Periodical researches have been referred in justifying and supporting the design of an

effective research study. Reviewing the literatures could provide a basis for revising

the proposed study by extending parts of previous studies. It also gives an idea to

researchers on how to conduct a study.

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Based on literature review, the scope of this study uses perceived service quality

determinants, corporate image, price as the independent variables while customer

satisfaction as the mediating variable and service loyalty as dependent variable.

1.4 Limitations of the Study

All researches have their limitation and it is no exception on this study. The survey is

only conduct in Klang Valley, therefore base on the collected sample size and the

regional distribution of the population concerned, the questions will be whether the

findings can be generalized. Such generalization requires further in depth studies with

larger samples and a variety of industries. In a strict sense the results pertain only to

the respondents and generalizations to a wider population or industry should be done

with caution. The sample size is not large enough but shall be adequate for the type of

analysis undertaken.

Another limitation is on the scope of study. From a theoretical point of view, the

framework of this research is restricted to its own objectives. This study has pondered

the relationship among service quality, corporate image, price, customer satisfaction,

and service loyalty. While other antecedents or consequences, such as “relationship”

(Guan Xi in Chinese), promotions, employees behavior, have not been considered.

Factors affecting consumers’ satisfaction and service loyalty on mobile phone

services could be examined in many perspectives and in more details.

Additionally, this research and the model propose have been devised as a basis for

future studies. It would be interesting to analyze how the proposed relationships may

differ when compared with other service sectors or tangible products. In addition, due

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to the fact that service industries are heterogeneous, presenting a wide variety of

pricing structures, further research should be carried out in respect of other services,

concentrating on analyzing other antecedents and consequences. Finally, it should be

noted that the study focused on mobile phone service sector alone, ignoring fixed-

lines service sector. Future research may derive benefit from focusing on consumer

behavior in the fixed-line industry.

1.5 Organization of the Study

This paper is divided into five chapters that covered “Introduction”, “Literature

Review”, “Research Methodology”, “Research Result”, and “Conclusion &

Recommendation”. The outlines of the five chapters are as below.

Chapter 1: Introduction

This chapter gives an overview of the study. It contains general introduction to the

issues with which the study is concerned, purposes and significance of the study,

followed by the research objectives, scope of the study and limitation.

Chapter 2: Literature Review

This chapter assesses to previous literature and studies relevant to the fields and

related topics. A literature review also provides a rationale for the proposed study by

placing it next to previous studies.

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Chapter 3: Research Methodology

It describes and explains the research methodology used in the study. Key topics of

this chapter include theoretical framework, methodologies, hypotheses, selection of

measures, sampling design, data collection procedures, and data analysis techniques.

Chapter 4: Research Result

This chapter describes overall findings, summarizes the statistics of respondents,

result of statistical analysis, and discussion of the research result. Results and data

analysis are presented in the form of text, figures, tables, etc.

Chapter 5: Conclusion and Recommendation

In this chapter, the findings are summarized and implications of the findings are being

discussed. It looks at the implications of the findings practise, accepted theoretical

model or paradigm and indicate the overall importance of the research to the field.

This chapter also outlines recommendation for future research.

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2.0 Literature Review

This chapter assesses to previous literature and studies relevant to the fields and

related topics. A literature review also provides a rationale for the proposed study by

placing it next to previous studies.

2.1 Service Quality

Research into service quality research has followed various lines of enquiry. The

present study has identified five main research streams, as illustrated in Figure 2.1.

Figure 2.1: Main Research Streams on Service Quality (Source: Manuel Sanchez Perez, Juan Carlos Gazquez Abad, Gema Maria Marin

Carrillo and Raquel Sanchez Fernandez (2007), “Effects of Service Quality

Dimensions on Behavioural Purchase Intentions: A Study in Public-Sector

Transport”.)

First, there have been many studies of the concept and nature of service quality. Those

involve are Gronroos (1982), Berry et al. (1985), Parasuraman et al. (1985), and

Zeithaml et al. (1985). Although there is no general consensus about the nature or

10

content of the dimensions of service quality (Morrison, 2004), there is a general

recognition that service quality is a multi-dimensional construct (Cronin and Taylor,

1992; Gronroos, 1990; Parasuraman et al., 1985, 1988; Brady and Cronin, 2001).

A second research stream into service quality has focused on the strategic

consequences of quality. It has been claimed that an improvement in quality has a

measurable effect on customer retention, market share, and profitability as a result of

increased sales, lower prices, and decreased costs (Manuel Sanchez Perez, 2007).

However, it should be noted that some authors like Rust have analyzed the return on

quality and concluded that not all quality efforts are equally valid.

A third research stream has focused on the measurement of service quality. According

to Manuel Sanchez Perez (2007), important work in this area has been conducted by:

v Parasuraman et al. (1988), who developed the SERVQUAL scale;

v Cronin and Taylor (1992), who presented the SERVPERF scale and the weighted

SERVPERF scale;

v Parasuraman et al. (1991) and Vandamme and Leunis (1993), who revised and

weighted SERVQUAL;

v Koelemeijer (1991), who developed the Q scale (equivalent to SERVQUAL based

on the subjective non-confirmatory paradigm), IPE scale (equivalent to

SERVQUAL weighted by the importance scores), and IP scale (equivalent to

SERVPERF weighted by the importance scores);

v Teas (1993a), who evaluated a alternative perceived quality model (EP); and

v Parasuraman et al. (2005) who developed E-S-QUAL scale for measuring the

service quality delivered in the context of electronic service.

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Despite considerable work undertaken in this research stream, there is no consensus

as to which of the measurement scales is best suited to measure service quality

(Morrison, 2004).

The fourth research stream has analyzed how an organization can improve service

quality. Authors such as Berry, Hensel, Harvey, Johnston and Heineke, Reicheld and

Sasser, and Rust are involved both normative formulations and empirical studies.

The fifth research stream has focused on the effects of service quality on consumer

behavior. Authors involved in this research stream such as Zahorik and Rust have

concentrated on the link between service quality and an improvement in the

profitability of the company. While others like Boulding, Zeithaml, and Liu have

studied the antecedents of consumer loyalty, and the effect on the profitability of a

service organization. These studies supported the contention that an improvement in

service quality has a positive influence on behavioral intentions, but they also showed

that superior levels of service quality should be achieved in a cost-effective manner

(Manuel Sanchez Perez, 2007).

2.1.1 Parasuraman’s SERVQUAL

According to Parasuraman et al. (1985), a perception of service quality is a result of a

comparison between what consumers consider the service should be and their

perceptions about the actual performance offered by the service provider.

Parasuraman et al. (1985) postulated five dimensions of the service experience in their

well-known SERVQUAL model: reliability, responsiveness, empathy, assurance, and

tangibility.

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Reliability is defined as the ability to deliver the promised service dependably and

accurately. It is about keeping promises - promises about delivery, pricing, complaint

handling, etc. Responsiveness can be described as the willingness to help customers

and provide prompt service. Assurance is the service quality dimension that focuses

on the ability to inspire trust and confidence. Empathy is the service aspect that

stresses the treatment of customers as individuals. Finally, tangibles are the service

dimension that focuses on the elements that represent the service physically.

Parasuraman et al. (1985, 1988, 1994) has made use of qualitative and quantitative

research following psychometric procedures which resulted in the development of the

original 22-item SERVQUAL (based on the five dimensions of service quality -

tangibles, reliability, responsibility, assurance, and empathy) instrument that

representing operationalizing of the service quality paradigm. Since then, the

SERVQUAL measurement has been applied to measure the service quality in various

service industries by many researchers.

It has provided researchers with the possibility of measuring the performance-

expectation gap or Gap 5 ostensibly composed of five determinants (Albert, 2000).

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Figure 2.2: Gaps in Service Quality

(Source: Fitzsimmons, James A., and Fitzsimmons, Mona J. (2001), Service

Management: Operations, Strategy, and Information Technology.)

Bery & Parasuraman (1991) and Zeithaml et al. (1993) have further developing the

gap model and argue that expectations can be conceptualized to exist at desired level

and the adequate level. In between the two levels, there is a zone of tolerance

reflecting the degrees of heterogeneity individual customers are willing to accept.

While the SERVQUAL instrument has been widely used, it has been subject to

criticism. Criticisms include the use of difference scores, dimensionality, applicability

and the lack of validity of the model, especially with respect to the dependence or

independence of the five main variables (Cronin & Taylor, 1992). Another criticism is

the point that SERVQUAL focuses on the service delivery process and does not

address the service encounter outcomes (Gronroos, 1990). The developers of

Word -of-mouth communications

Expected service

External communications

to consumers

Perceived service

Service delivery (including pre- and post-contacts)

Translation of perceptions into service quality specifications

Management perceptions of consumer expectations

GAP 5

GAP 3

GAP 2

GAP 1 GAP 4

Customer

Provider

Past experience Personal needs

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SERVQUAL were initially suggested that service quality consists of functional and

technical dimensions (Parasuraman et al., 1985). However, the SERVQUAL

instrument does not include any measure of the technical quality dimension (Gi-Du &

Jeffrey, 2004). Basically, according to Gi-Du and Jeffrey (2004), technical quality has

been neglected in efforts to study and measure service quality.

2.1.2 Gronroos’s Methodology

Gronroos (1984) relates definition of service quality with the result of the comparison

that customers make between their expectations about a service and their perception

of the way the service has been performed.

Services differ from physical goods in several characteristics (Gronroos, 2000):

v Services are intangible and heterogeneous;

v The production, distribution, and consumption of services are simultaneous

processes;

v Service is an activity or process;

v Service is a core value created in buyer-seller interactions;

v Customers participate in the production of services;

v Services cannot be kept in stock; and

v There is no transfer of ownership in service transactions.

Services are thus produced, distributed, and consumed in the interaction between the

service provider and the service receiver. Accordingly, services must be viewed from

an interactive perspective.

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The model proposed by Gronroos (1984, 1990) focuses on the role of technical

quality (or output) and functional quality (or process) as occurring prior to and

resulting in outcome quality. In the model, technical quality refers to what is delivered

to the customer while functional quality is regarding with how the end result of the

process was transferred to the customer. The model states that the consumer is not

interested only on what he/she receives as an outcome of the production process, but

also on the process itself. The perception of the functionality of the technical outcome

(technical quality) is a major determinant of the way he/she appreciates the effort of

the service provider.

In this context, technical quality can be quite easily evaluated objectively but it is

more difficult to do with functional quality because services are intangible, consumers

assess quality subjectively. The “perceived service” is the result of a customer’s view

of a bundle of service dimensions, some of which are technical and some of which are

functional in nature. Perceived service quality is the outcome of perceived service

when compared with expected service.

Figure 2.3: Perceived Service Quality

(Source: Fitzsimmons, James A., and Fitzsimmons, Mona J. (2001), Service

Management: Operations, Strategy, and Information Technology.)

Word of mouth Personal needs Past experience

Expected Service (ES)

Perceived Service (PS)

Service Quality Dimensions Reliability

Responsiveness Assurance Empathy Tangibles

Service Quality Assessment 1. Expectations exceeded ES<PS (Quality surprise) 2. Expectations met ES~PS (Satisfactory quality) 3. Expectations not met ES>PS (Unacceptable quality)

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In Gronroos’s model, he also recognizes that customers have some type of image of

an organization that has a quality impact in itself and functions as a filter. According

to Gronroos, quality as experienced by a customer is based on two dimensions –

technical and functional – moderated by the company image. The customers’

perceived quality is the result of the evaluation they make of what was expected and

what was experienced, taking into account the influence of the organization’s image

(Albert, 2000).

2.1.3 Cronin’s SERVPERP

SERVQUAL, grounded in the Gap model, measures service quality as the calculated

difference between customer expectations and performance perceptions of a service

encounter (Parasuraman et al., 1988, 1991). Cronin and Taylor (1992) challenged this

approach and developed the SERVPERF scale based on Parasuraman's SERVQUAL

methodology which directly captures customers’ performance perceptions in

comparison to their expectations of the service encounter.

SERVPERF only measures performance perceptions and operationalizes service

quality as customers’ evaluations of the service encounter. It uses only performance

data because it assumes that respondents provide their ratings by automatically

comparing performance perceptions with performance expectations. As a result,

SERVPERF uses only the performance items of the SERVQUAL scale (Brady et al.,

2002; Cronin and Taylor, 1992, 1994).

Arguments in favour of SERVPERF are based on the notion that performance

perceptions are already the result of customers’ comparison of the expected and actual

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service (Babakus and Boller, 1992; Oliver and DeSarbo, 1988). Therefore,

performance only measures should be preferred to avoid redundancy. Thus,

SERVPERF assumes that directly measuring performance expectations is

unnecessary. Cronin and Taylor (1992) built their argument for the superiority of

SERVPERF over SERVQUAL by empirically showing that SERVPERF is a better

predictor of overall service quality than SERVQUAL.

Nevertheless, many authors concur that customer’ assessments of continuously

provided services may depend solely on performance. Hence, the authors suggesting

that performance-based measures explain more of the variance in an overall measure

of service quality (Oliver, 1989; Bolton and Drew, 1991a, b; Cronin and Taylor,

1992; Boulding et al., 1993; Quester et al., 1995). These findings are consistent with

other research that have compared these methods in the scope of service activities,

thus confirming that SERVPERF (performance-only) results in more reliable

estimations, greater convergent and discriminant validity, greater explained variance,

and consequently less bias than the SERVQUAL and EP scales (Cronin and Taylor,

1992; Parasuraman et al., 1994a; Quester et al., 1995; Llusar and Zornoza, 2000).

Whilst its impact in the service quality domain is undeniable, SERVPERF being a

generic measure of service quality may not be a totally adequate instrument by which

to assess perceived quality. This research bears on these conclusions and adopts the

performance-based SERVPERF paradigm.

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2.1.4 Service Quality and Customer Satisfaction

The relationship between service quality and individual service loyalty dimensions

has been examined empirically by Boulding et al. (1993), Cronin, and Taylor (1992).

Cronin and Taylor (1992) focused solely on repurchase intentions, whereas Boulding

et al. (1993) focused on both repurchase intentions and willingness to recommend. In

the study by Cronin and Taylor (1992) service quality did not appear to have a

significant (positive) effect on intentions to purchase again, while Boulding et al.

(1993) found positive relationships between service quality and repurchase intentions

and willingness to recommend.

Customer satisfaction often depends on the quality of product or service offering. In

the context of services, some describe customer satisfaction as an antecedent of

service quality (Bitner, 1990; Cronin and Taylor, 1992). Service quality is thus

related, though not equivalent, to satisfaction (Oliver, 1980). For this reason, research

on customer satisfaction is often closely associated with the measurement of quality

(East, 1997). Customer satisfaction can thus be based not only on the judgment of

customers towards the reliability of the delivered service but also on customers'

experiences with the service delivery process (Naser et al., 1999).

De Ruyter et al. (1997) summarized the conceptual gap between the two constructs as

the following: customer satisfaction is directly influenced by the intervening variables

of disconfirmation (the difference between perceptions and expectations), while

service quality is not; satisfaction is based on predictive expectation while service

quality is based on an ideal standard expectation; and the number of antecedents of

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the two concepts differ considerably. Therefore, it is worthwhile to investigate the

relative importance of service quality dimensions to customers’ satisfaction.

In summary, satisfaction and quality seem like twin concepts, both revolving around

expectation, experience, perception and evaluation of service as key variables (Jamali,

2007). The conclusion by Jamali (2007) is that satisfaction is a super-ordinate

construct to service quality, and that a management-by-satisfaction approach will

necessarily need to integrate the various quality dimensions. Satisfaction is a super-

ordinate construct because it can result from a large variety of dimensions that may lie

beyond those specified in the gap model and the SERVQUAL instrument. As

illustrated in Figure 2.4, aside from an assessment of the basic service quality

dimensions, a number of affective processes (equity considerations, emotions,

attributions, cost benefit analyzes, and tolerance zones) have also been found to

influence customers’ subjective assessments and their overall satisfaction (DeRuyter

et al., 1997).

Figure 2.4: Relationship between Customer Satisfaction and Service Quality

(Source: Jamali, D. (2007), “A Study of Customer Satisfaction in the Context of a

Public Private Partnership”.)

20

2.1.5 Recent Findings

Many practitioners and academicians in service quality aspects have recently focused

on how to improve online services to attract potential customers and on how to retain

current customers with the development and popularity of electronic channels.

Zeithaml (2002) has emphasized that companies should focus on online service

encompassing all cues and encounters that occur before, during, and after the

transactions.

It is important for online service providers to understand in depth what online

customers perceive to be the key dimensions of service quality and what impacts the

identified dimensions have on customers’ satisfaction. According to Cox and Dale

(2001), traditional service quality dimensions, such as competence, courtesy,

cleanliness, comfort, and friendliness, are not relevant in the context of online

retailing, whereas other factors, such as accessibility, communication, credibility, and

appearance, are critical to the success of online businesses.

Because electronic channels are a recently emerging field, little academic literature in

this field has addressed in-depth online systems quality. Online systems quality can be

divided into information systems quality and information quality. Information systems

quality refers to the quality of software development while information quality is

related to the accuracy, timeliness, currency, and reliability of information (DeLone

and McLean, 1992). To measure end-users’ satisfaction with information systems,

Doll and Torkzadeh (1988) have purified 13 items proposed by Baroudi and

Orlikowski (1988) into 12 items that gauge five quality dimensions influencing end-

user satisfaction: content, accuracy, format, ease of use, and timeliness.

21

Beyond the five attributes employed in the measurement scale, other attributes unique

to the Internet, such as security and privacy can also be considered important in

assessing online systems quality. Another important aspect of online systems is to

enable customers to function more independently and conduct transactions on their

own. As end-users, consumers often seek desired products/services information or

perform other activities through web sites. Thus, in this online market, customers are

essentially “self-served” much of the time. Basically, the Internet has created a new

form of relationship marketing that provides direct linkage between target customers

and service providers.

2.2 Corporate Image

A favorable image is considered as a critical aspect of an organization’s ability to

maintain its market position as image has been related to core aspects of

organizational success such as customer patronage. Corporate image has been

identified as an important factor in the overall evaluation of a firm (Bitner, 1990) and

is argued to be what comes to the mind of a customer when they hear the name of a

firm (Nguyen, 2006).

The theme “building the corporate image” has been referred to in the Market

Research Society Conference in March 1970 (Worcester, 1970), and in the Consumer

Market Research Handbook entitled simply “Corporate image research”. In these

papers the author defined the “corporate image” as “the net result of the interaction of

all experiences, impressions, beliefs, feelings and knowledge people have about a

company”.

22

The corporate image is based on what people associate with the company or all the

information (perceptions, inferences, and beliefs) about it that people hold (Rita,

2007). Some researchers use image and reputation as substitutes, others such as

Fombrun (1996) sees reputation as the esteem in a long-term perspective that the

company has, as opposed to image that can be more short-term in nature. Rita (2007)

proposed that image and reputation could be used as substitutes, since it is likely that

the early studies on corporate image would have used the concept “reputation” had

they been done today.

According to McInnis and Price (1987), the research on “image” field shows that

image is a process originating from ideas, feelings and the previous experience of an

organization that are recalled and transformed into metal pictures (Yuille &

Catchpole, 1977). As a rule, people are exposed to realities created by the

organization and may consciously or unconsciously select facts that are well suited

with their configuration of attitudes and beliefs. These facts are retained and later

retrieved from memory to reconstruct an image when the organization is brought to

mind. Dobni and Zinkhan (1990) conclude that image is a perceptual phenomenon

that is formed by rational and emotional interpretation and that has cognitive

components, the beliefs, and affective components, the feelings.

There are two principal components of corporate image according to Kennedy (1997):

functional and emotional. The functional component is related to those tangible

characteristics that can easily be measured, such as the physical environment offered

by the hotel; the emotional component is associated with those psychological

23

dimensions that are manifested by feelings and attitudes towards an organization (Jay

& Hui, 2007).

These feelings are derived from the numerous experiences with an organization and

from the processing of information on the attributes that constitute functional

indicators of image (Kennedy, 1977). Although the quality of service is “defined” by

the customer, but “created” by the employees, it is the “human factor” that holds the

ultimate balance of quality in service industries (Jay & Hui, 2007).

Researchers have found image to be a very complicated concept because it is more

than just the summing up of all the factual attributes of an organization. Image is

influenced by the interactions among all factual and emotional elements of an

organization in generating consumer’s impression and suggesting a “gestalt” view of

the firm’s image (Jay & Hui, 2007). Moreover, many studies have reported that the

organization’s ability to consistently offer superior service and the resulting customer

satisfaction has a strong positive influence on the firm’s image.

A growing number of service companies have embarked on a journey of positioning

through the communication channel (i.e. advertising and personal selling)

(Andreassen and Bredal, 1996), with the objective of building strong corporate

images in order to create relative attractiveness. This development is in line with

Lovelock (1984) who claims that:

(images) … are likely to play only a secondary role in customer choice

decisions unless competing services are perceived as virtually identical on

performance, price, and availability…

24

Consequently, we would expect that corporate image under current market conditions

will play an important role in both attracting and retaining customers.

An organization does not project a unique image rather; it may posses various images

that different according to specific groups, such as clients, employees and

shareholders, each of whom has different types of experiences and contacts with the

organization (Gray, 1986). Since incongruent perceptions can counteract favorable

impressions related to an organization’s image, the harmonization of activities is

consequently important (Nguyen & LeBlanc, 2001). Often related to symbols and

values, the building of institutional image is a lengthy process that can be improved

rapidly by technological breakthroughs and unexpected achievements or destroyed by

neglecting the needs and expectations of the various groups who interact with the

organization (Dichter, 1985; Herbig et al., 1994).

2.2.1 Corporate Image and Customer Satisfaction

According to Nguyen & LeBlanc, satisfaction has no significant direct effect on

corporate image. However, it contradicts with other findings that indicate that

corporate image is a function of the accumulated effect of satisfaction or

dissatisfaction (Bolton & Drew, 1991; Fornell, 1992). In other way, image acts as a

filter of satisfaction in a simplification of the decision process that was indicated in

the works of Weiner (1985) and Folkes (1998).

However, it can be seen that in the study of Nguyen & LeBlanc (1998), there is an

indirect effect on image through the perceived value of the service. It reinforces the

assertion of Barich & Kotler (1991) that a company has a strong image if the clients

25

believe that they receive good value in their transactions with the company.

Andreassen & Lindestad (1998) verified that corporate image has a string influence

on customer satisfaction, especially if the customer has little knowledge about the

service.

2.2.2 Recent Findings

The majority of existing empirical studies treated corporate reputation as a uni-

dimensional construct (e.g. Doney and Cannon, 1997), whereas more recent approach

recognize its multi-dimensional nature (e.g. Fombrun et al., 2000; Davies et al.,

2002). Fombrun et al. (2000) define corporate reputation as a “collective assessment

of a company’s ability to provide valued outcomes to a representative group of

stakeholders”. In this context, reputation can be taken to be the aggregate of the

perception of all relevant stakeholders. This might refer to the services, persons and

communicative activities of a company as well as the result over time of corporate

activity in the minds of the stakeholders.

Walsh, Dinnie & Widemann (2006) report that corporate reputation is rightly

regarded as a multidimensional construct, with a diverse range of stakeholders, the

current study focuses strictly on customer based corporate reputation (i.e. corporate

reputation as perceived by customers). Focusing on customers (as opposed to other

stakeholder groups) is in agreement with more recent work on customer reputation

and customer satisfaction that focuses on the stakeholder group of customers (Walsh

and Wiedmann, 2004). It is assumed that corporate reputation has a positive effect on

various commercially relevant economic and pre-economic dimensions.

26

However, Rose and Thomsen (2004) term the conventional wisdom that corporate

reputation has an impact on firm value – the market to book value of equity. Rose and

Thomsen contend that corporate financial performance affects reputation rather than

vice-versa. While not questioning that reputation is vital for the survival of an

organization in long-term basis, they argue that reputation may influence stock market

performance via profitability and growth rather than having a direct effect on the

stock markets.

2.3 Price

It is common knowledge that price influences a customer’s buying decision. Although

companies offering superior service levels are able to charge a slightly higher price

than their competitors are, the marginal difference is often modest and requires a

better than average performance on service quality (Gale, 1992), which then

jeopardizes the cost effectiveness.

Among the several factors that affect to customers’ buying behaviour, two important

ones are “price” and “quality of service” (Jacoby & Olson, 1977). This means that

there is trade-off between price and service quality (Tse, 2001) which is most often

materialized in terms of customer satisfaction. As such, price has been observed as an

important element affecting to customer satisfaction paradigm.

2.3.1 Price Sensitivity

Fornell et al. (1996) have stated that through satisfaction there can be increased or

decreased price sensitivity. At an aggregated level, price sensitivity is often used as a

synonym for price elasticity (Link, 1997). Sensitivity demand refers to how volume-

27

sensitive a product or a service is to price changes. Sensitivity represents a valuable

strategic tool in pricing (Tucker, 1966).

Price sensitivity on the individual adopter level appears to be equivalent to the

concept of price consciousness for a potential buyer of a product or service. Price

consciousness has been defined as “the degree to which he or she is unwilling to pay a

high price for a product and willing to refrain from buying a product whose price is

unacceptably high” (Monroe, 1990). Price consciousness is related to the price

acceptability level as well as to the width of latitude of price acceptability

(Lichtenstein et al., 1998). Individuals who are price conscious are generally not

willing to pay high prices for the product in question. Furthermore, the range of

acceptable price is relatively narrow for price conscious individuals (Link, 1997).

2.3.2 Price Acceptance

Measurements of consumer price acceptance represent a direct attempt to establish the

potential buyers' willingness to purchase as a function of various prices (Monroe,

1990). The level of acceptance can thus be defined as the maximum price, which a

buyer is prepared to pay for the product (Monroe, 1990). Several different methods

are suitable for determining the price that the consumer subjectively presumes to be

appropriate observations of the market, experimentation with prices and surveys

(either direct or indirect) of experts' or customers' opinions (Monroe, 1990).

Price acceptance is based on the assimilation-contrast theory (Sherif, 1963). This

theory suggests that a new stimulus encountered by an individual is judged against a

background of previous experience (reference scale) in the category. Subsequent

28

stimuli are judged in relation to a reference scale and this provides the basis for

comparisons and evaluations. The level of price acceptance can thus be defined as the

maximum price that a buyer is prepared to pay for the product or service (Monroe,

1990).

Marshall (1980) indicates that the excess of price that a customer would be willing to

pay, rather than go without having a thing, over what he actually pays is the economic

measure of his satisfaction surplus. It means that customers could have a greater price

acceptance for products or services providing greater satisfaction. In this field,

Anderson (1996) investigates whether the association between satisfaction and price

acceptance is positive or negative, as well as gauging the degree of association

between these two important constructs.

2.3.3 Price Perception

Price perception has made important contributions to understanding of consumer

behaviour (Kalyanaram and Winer, 1995). When a consumer plans to make a

purchase, the price perception process can be described as follows: if the selling price

of the brand is greater than the internal reference price, the selling price is perceived

negatively by the consumer. Conversely, if the product is being sold at a lower price

than what was expected to be paid, the selling price is perceived positively, thereby

increasing the consumer’s purchase intent (Kalwani and Yim, 1992).

Zeitham et al. (1990) have suggested that improving service quality in the eyes of

customers creates “true customers” through higher customer satisfaction. Although

Nagle and Holden (2002) believe that price merely represents the monetary value a

29

buyer must give to a seller as part of a purchase agreement, customers’ price

perception is closely related on their perception of quality, value and other beliefs.

It is more or less known how customers of mobile service perceive the charged prices

and what are the dynamics affecting to price perceptions. The perceived price is

formed from the bases of a customer’s experience about mobile services and in

comparison to prices of other optional service delivery channels.

2.3.4 Price Fairness

Garbarino and Slonim (2003) propose that fair price will always be lower than

expected price because consumers, without knowledge of the firm’s actual profit

margins, assume the firm is making a reasonable profit even at the lowest observed

price. It was found that both customers and firms compare the selling price with the

prices paid by other customers for the same products or services (Martins and

Monroe, 1994). To sum up, consumers evaluate the fairness of a quoted price by

making appropriate comparisons with other references, but also taking into account

situational circumstances (Beldona and Namasivayam, 2006).

Perceptions of customer value and perceptions of price fairness share the dimension

of price as a reference for comparison; the two perceptions are closely related.

Customer value is the customer’s assessment of what the customer actually receives

in benefits against what he or she sacrifices in terms of price and other non-monetary

resources. On the other hand, perceptions of price fairness assess what the customer

pays against what the company is making from the product or service. Therefore, as

customer value increases (decreases), it can be expected that customers’ perceptions

30

of price fairness will also increase (decrease). It is because there will be greater

(lower) distributive justice between the two.

2.3.5 Price and Customer Satisfaction

The marketing literature emphasizes price as an important factor of consumer

satisfaction, because whenever consumers evaluate the value of an acquired product

or service, they usually think of the price (Fornell, 1992; Cronin et al., 2000). As for

the relationship of price to satisfaction, Zeithaml and Bitner (1996) indicated that the

extent of satisfaction was subject to the factors of service quality, product quality,

price, situation, and personal factors.

However, price has not been fully investigated in previous empirical studies (Bei and

Chiao, 2001). According to Zeithaml (1988) price is something that must be sacrificed

to obtain certain kinds of products or services from consumers’ cognitive conception.

In other words, the lower the perceived price there will be the lower the perceived

sacrifice. In addition, a sense of price fairness should be generated. If customers view

a firm’s practices as unfair, negative consumer responses are likely to occur (Wirtz

and Kimes, 2007). Immediate attitudinal and affective responses include

dissatisfaction (Oliver and Swan, 1989), lower purchase intentions (Campbell, 1999),

heightened price consciousness and focus on the monetary sacrifice of a purchase

(Xia et al., 2004).

2.3.6 Recent Findings

Since the internet is becoming an important channel for commerce, organizations can

benefit from a multi-channel sales strategy. Multi-channel pricing strategy is

31

becoming a very important issue. Some of the studies specifically focus on the price

competition between online retailers and brick and mortar organizations. For instance,

Smith et al. (1999) conducted an empirical study to show that online prices for digital

products are 9-16 percent lower than traditional brick and mortar prices.

Dolan and Moon (2000) studied the pricing and market making on the internet and

found that it is optimal for the multi-channel organizations to use a different pricing

mechanism on different channels. Baker et al. (2001) and Kung et al. (2002) did a

research to show that the internet is not driving prices down and may help firms to

design better pricing strategies. Ancarani and Shankar (2004) did an empirical study

to reveal that multi-channel organizations have the highest prices and pure play e-

tailers may have the lowest prices if shipping costs are included.

2.4 Customer Satisfaction

With reference to the various relevant aspects of customer behavior, satisfaction

represents a central determinant from which come different types of influence on

other variables and the economic success of an organization. Customer satisfaction is

perceived as being a key driver of long-term relationships between suppliers and

buyers (Geyskens et al., 1999), as it is positively related to customer loyalty (Johnson

et al., 2001) and customer profitability (Zeithaml, 2000). Customer satisfaction has

become an important marketing metric in the last two decades.

Customer satisfaction is generally described as the full meeting of one’s expectations

(Oliver, 1980). Customer satisfaction is the feeling or attitude of a customer towards a

product or service after being used. Customer satisfaction is a major outcome of

32

marketing activity whereby it serves as a link between the various stages of consumer

buying behavior. If customers are satisfied with a particular service offering after its

use, then they are likely to engage in repeat purchase and try line extensions (East,

1997).

Giese and Cote (2000) suggest in their literature review that consumer satisfaction

comprises three basic components:

(1) the type of response, that is to say, whether the response is cognitive, affective or

conative, and its level of intensity, although those authors concluded from their

validation, carried out by means of group and personal interview data, that satisfaction

is a summary affective response which varies in intensity;

(2) the centre of interest or the subject on which the response is focused, which could

be based on an evaluation of product-related standards, product consumption

experiences and/or purchase-related attributes (e.g. salesperson); and

(3) the moment in time at which the evaluation is made, which may be before choice,

after choice, after consumption, after extended experience, or at just about any other

time.

Along with Giese and Cote’s suggestion, Halstead et al. (1994) consider satisfaction

as an affective response, focused on product performance compared to some pre-

purchase standard during or after consumption. Mano and Oliver (1993) establish that

satisfaction is an attitude or evaluative judgment varying along the hedonic continuum

focused on the product, which is evaluated after consumption. Fornell (1992)

identifies satisfaction as an overall evaluation based on the total purchase and

consumption experience focused on the perceived product or service performance

33

compared with pre-purchase expectations over time. Oliver (1997, 1999) regards

satisfaction as a fulfillment response or judgment, focused on product or service,

which is evaluated for one-time consumption or ongoing consumption.

Customer satisfaction is widely recognized as a key influence in the formation of

customers’ future purchase intentions (Taylor & Baker, 1994). Satisfied customers are

also likely to tell others about their favorable experiences and thus engage in positive

word of mouth advertising (Richens, 1983; File & Prince, 1992). While for

dissatisfied customers, they are likely to switch brands and engage in negative word

of mouth advertising. Levesque and McDougall (1996) confirmed that unsatisfactory

customer service leads to a drop in customer satisfaction and willingness to

recommend the service to a friend. This would in turn lead to an increase in the rate of

switching by customers.

Hence, the customer feels satisfied if the perceived performance exceeds a customer’s

expectations (or a positive disconfirmation). In contrast, if the perceived performance

unable to meet a customer’s expectations (or a negative disconfirmation), then the

customer feels dissatisfied. Churnchill & Surprenant (1982) reported that

disconfirmation positively affected satisfaction. That is, when customers perceived

the product performing better than expected, they became on more satisfied

(Churnchill & Suprenant, 1982).

2.4.1 Customer Satisfaction and Service Loyalty

Customer satisfaction is a central element in the marketing exchange process, because

it undoubtedly contributes to the success of service providers (Darian et al., 2001).

34

Furthermore, satisfaction is one of the essential factors to predict consumer behavior

and, more specifically, purchase repetition. Oliver (1997) defines loyalty as a deeply

held commitment to repeat purchases of a preferred product or service consistently in

the future, despite situational influences and marketing efforts (e.g. pricing policies)

having the potential to bring out change. The more consumers fulfill their

expectations during the purchase or service use, the higher the probability that

consumers will repeat purchase in the same establishment (Wong and Sohal, 2003).

Thus, customer satisfaction along with other antecedents is essential factors in order

to acquire loyal customers who would also recommend their regular product or

service provider to other customers. Many related empirical studies reported that

satisfied consumers demonstrate more loyal behavior (Gwinner et al., 1998; Henning-

Thurau et al., 2002). Therefore, consumer satisfaction leads to customer loyalty.

2.4.2 Recent Findings

Recent studies recognize that emotion is a core attribute in satisfaction and suggest

that customer satisfaction should include a separate emotional component (Cronin et

al., 2000). Stauss & Neuhaus (1997) argue that most satisfaction studies only focus on

the cognitive component and the omission of the affective (or emotional) component

is one of the main issues in satisfaction research.

According to Yu et al. (2001), it is important to note that emotional component is a

form of affect, and it is response to service delivery. In this context, “consumption

emotions are the affective responses to one’s perceptions of the series of attributes

that compose a product or service performance” (Dube & Menon, 2000). Such

35

emotions are usually intentional (have an object or referent) and are different to the

concept of mood, which is a generalized state induced by a variety of factors, and is

usually diffused and non-intentional (Bagozzi et al., 1999).

Emotions and mood (and attitudes) are all elements of a general category for mental

feeling processes, referred to as “affect” (Bagozzi et al., 1999). The emotional

component in the satisfaction judgment is therefore independent from the overall

affective sense present in the respondent at the time of the service (DeRutyer &

Bloemer, 1998). In summary, positive emotions [such as happiness, surprise, etc] may

lead an individual to share the positive experience with others, while negative

emotions [such as depression] may result in complaining behaviour (Bagozzi et al.,

1999; Liljander & Strandvik, 1997).

2.5 Service Loyalty

Customer loyalty has been largely treated by researchers as either repurchase

behaviour or repurchases behaviour combined with an attitudinal component. While

the first of these two approaches remains popular with services researchers, other

researchers have recognized the problems associated with treating loyalty as

repurchase behaviour exclusively because measures do not distinguish spuriously

loyal customers (Moulson, 1965). By focusing on purchase, shoppers who are

retained customers by default are aggregated with truly loyal customers who shop as a

positive choice (Denison and Knox, 1995).

Normally, customers are retained for long periods but without a genuine relationship

ever being developed. The problem with spurious loyalty is not alleviated by the

36

alternative approach of adding attitudinal components to repurchase behaviour. The

weakness of the repeat purchase with attitude model was demonstrated by Iacobucci

et al. (1994) as the attitude component is not unique in this form of additive model.

As oppose to the additive model, Blodgett et al. (1997) distinguish loyalty as a

psychological outcome and repurchase intentions as a behavioural outcome. It means

that a psychologically loyal customer may not intend to purchase from a service

provider because their circumstance prevent them (Barnes, 1997). Czepiel (1990) and

Kingstrom (1983) support this paradigm and argue that for loyalty to be treated as a

psychological construct. Oliver (1999) extends the notion of incorporating repeat

purchase with loyalty by suggesting that psychological strategies are needed to

achieve ultimate loyalty.

The relationship building between customers and service provider produces a sense of

ownership over the service with customers referring to “my accountant”, “my

hairdresser”, or “my mechanic” (Grabbott and Hogg, 1994). Bhattacharya et al.

(1995) found that membership of an organization “creates a sense of belongingness”.

Both Oliver (1999), and Crosby and Taylor (1983) stated that identification is linked

to the customer’s resistance to change. Crosby and Taylor (1983) argue that resistance

is maximized when the customer identifies strongly with the service provider and that

these values are important to the customer.

According to Oliver (1999), loyalty is an attained state of enduring preference. This

key role of preference is also supported by social identity theory which indicates that

group membership leads to consistent in-group favouritism because it boots self-

37

esteem (Lippa, 1990). When the customer identifies with the service provider’s

values, involvement or ego defence will maintain consistent in-group favouritism

(Crosby and Taylor, 1983). Loyal customers need to be seen as acting out of volition

(Barnes, 1997) in making their preferred choice.

Loyalty, with its high repeat patronage and high relative attitude, would obviously be

the ultimate goal for marketers. Raj (1985) found that firms with large market shares

also have larger groups of loyal consumers. Loyal customers are less motivated to

search for alternatives, they are more resistant to counter-persuasion from other

brands, and are more likely to pass along positive word-of-mouth communication

about the service to other consumers (Dick and Basu, 1994). Marketers with loyal

consumers can expect repeat patronage to remain high until competitors find a way to

close the gap in attitude among brands. Competition can close the gap in three main

ways (Dick and Basu, 1994). They can:

(1) try to reduce the differential advantage of the leading brand,

(2) increase the differentiation of their own brand, or

(3) encourage spurious loyalty from consumers.

2.5.1 Recent Findings

More recently, three-dimensional conceptualizations have been proposed where

loyalty includes a behavioral, attitudinal, and a cognitive. The majority of research in

marketing now represents loyalty as a multi-dimensional construct; however,

agreement on whether it has two or three dimensions is lacking.

38

Researchers are increasingly recognizing the importance of interpersonal relationships

that develop between service providers and service consumers (Bendapudi and Berry,

1997; Gwinner et al., 1998). A number of relational variables such as commitment,

closeness, and relationship quality have been empirically linked to a variety of service

loyalty-related outcomes such as repurchase intentions, advocacy, and consumers’

willingness to pay more (Hennig-Thurau et al., 2002).

Fournier’s (1998) ground-breaking work on brand relationships found utility in the

use of the interpersonal relationship literature to examine loyalty-related outcomes

with consumer durables. Because of the interpersonal nature of most services, it is

likely that this literature would provide theoretical guidance for the conceptualization

of service loyalty.

In sharp contrast to the increasingly complicated approaches to conceptualizing and

measuring loyalty, Reichheld (2003) has recently argued that it is possible for many

service firms to adequately assess loyalty using only one measure. That is

“willingness to recommend”. He reports that for many of the firms he studied, this

one indicator of loyalty was a strong predictor of a firms’ growth rate. In essence, his

results imply a uni-dimensional conceptualization of loyalty.

39

3.0 Research Methodology

This chapter outlines the methodology used for this study. Key topics of this chapter

include theoretical framework, methodologies, hypotheses, selection of measures,

sampling design, data collection procedures, and data analysis techniques.

3.1 Theoretical Framework

The theoretical framework was established based on literature review in the previous

chapter – Chapter 2: Literature Review.

3.2 Research Hypotheses

The research hypotheses were developed based on the conceptual framework above.

Hypothesis 1: Service quality has a positive effect on service loyalty.

Hypothesis 2: Corporate image has a positive effect on service loyalty.

Hypothesis 3: Price has a positive effect on service loyalty.

Hypothesis 4: Service quality has a positive effect on customer satisfaction.

Hypothesis 5: Corporate image is significantly related to customer satisfaction.

(Independent variables) (Mediating variable) (Dependent variable)

H7

H6

H5

H4

H3

H1

H2

Service quality

Corporate image

Price

Customer satisfaction

Service loyalty

40

Hypothesis 6: The pricing plans are significantly related to customer satisfaction.

Hypothesis 7: Customer satisfaction has a positive effect on service loyalty.

Hypothesis 8: Customer satisfaction is the mediator of the relationship among service

quality, corporate image, and price and service loyalty.

3.3 Selection and Measures

The most frequent use of data collection is by way of questionnaires. It is used to

measure the past behaviour, and respondent characteristics (Kinnear & Tiylor, 1996).

It is very versatile and enables to gather wide range of information required for the

study. Chrinsnall (1997) defines that “questionnaire is a method of obtaining specific

information about a defined problem, so that the data, after analysis and

interpretation, result in better appreciation of the problem.”

The questionnaire designed for this research was formulated as closed-end questions

which were normally structured for respondents to select their choices of statement

from a list of questions presented to them. The popularity of the closed-end method

provides less effort by respondents to complete the questionnaire and it is easy for

analysis.

The questionnaire was divided into three sections. First section was on profiling of

telecommunication service provider. It stated number of mobile phone service

providers the respondent is using and to name the most frequently used network.

Second section was regarding perception towards telecommunication service

provider. It consisted of 52 items split between five instruments that each measured

service quality, corporate image, price, customer satisfaction and service loyalty.

41

Seven-point scales described at either end by “strongly agree” and “strongly disagree”

were used. The last section of the questionnaire represented demographic profile of

respondents.

One of the advantages of self-administered questionnaire is it can reach a

geographically dispersed sample simultaneously. In addition, respondents can fill up

questionnaire when they have time. Thus, there is a better chance that respondents

will take time to think about their replies. Extra effort was made to get as much

respondents as possible through distributing the questionnaire via email.

In addition to distributing questionnaire by hand and through email, respondents also

have a choice to participate in this research study via an internet link

(http://freeonlinesurveys.com/rendersurvey.asp?sid=apeh2b5rsplzvgi439982). This

facility is considered perfectly anonymous as the system unable to track who are the

respondents. Unlike email, the name of senders will appear on the email itself.

Internet facility spans through time and space barriers whereby respondents can

submit their completed questionnaire anytime without the physical appearance of the

researcher.

3.4 Sample Design

The research sample was selected from a range of demographic elements for

processing based on non probability sampling in Malaysia with focus point is on

Klang Valley area. Non probability sampling techniques are in which units of the

sample are selected on the basis of personal judgement or convenience; the

42

probability of any particular member of the population being chosen is unknown

(Zikmund, 1997).

The technique employed under non probability sampling for this study was

convenience sampling. Zikmund (1997) mentions that convenience sampling is the

sampling procedure of obtaining those people or units those are most conveniently

available. It is also called haphazard or accidental sampling. Researchers generally

use convenience samples to obtain a large number of completed questionnaires

quickly and economically. According to Hair (1998), the critical sample size for the

intended analysis is considered to be 200 replies. Hence, the pre-determine sample

size is 200.

3.5 Development of Test Measures

Selection of questions for the survey questionnaire was based on empirical research

questions. There were 22 items to measure service quality, 5 items to measure

corporate image, 11 items to measure price, 7 items for customer satisfaction and

service loyalty, respectively.

3.5.1 Items to Measure Service Quality No. Items Source 1. Provides services as promised. Albert Caruana (2002) 2. Dependable in handling customer service problem. Albert Caruana (2002) 3. Performs services right at first time. Albert Caruana (2002) 4. Provides services at the promised time. Albert Caruana (2002) 5. Keeps customers informed. Albert Caruana (2002) 6. Provides prompt service to the customer. Albert Caruana (2002) 7. Willing to help customers. Albert Caruana (2002) 8. Ready to respond to customers’ requests. Albert Caruana (2002) 9. Instill confidence in customers. Albert Caruana (2002) 10. Feel safe in transactions. Albert Caruana (2002) 11. Consistently courteous. Albert Caruana (2002) 12. Knowledgeable to answer customer questions. Albert Caruana (2002) 13. Individual attention. Albert Caruana (2002)

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3.5.1 (continued) Items to Measure Service Quality 14. Caring manner. Albert Caruana (2002) 15. Has best customers’ interest at heart. Albert Caruana (2002) 16. Understand the needs of customers. Albert Caruana (2002) 17. Opening hours convenient to customers.

Riichan Kayaman & Hnseyin Arasli (2007)

18. Modern looking equipment.

Riichan Kayaman & Hnseyin Arasli (2007)

19. Visually appealing physical facilities.

Riichan Kayaman & Hnseyin Arasli (2007)

20. Neat appearance. Albert Caruana (2002) 21. Visually appealing materials. Albert Caruana (2002) 22. Insists on error-free service. Albert Caruana (2002)

3.5.2 Items to Measure Corporate Image No. Items Source 1. Innovative and pioneering.

Nizar Souiden, Norizan M. Kassim, Heung-Ja Hong (2006)

2. Successful and self-confident.

Nizar Souiden, Norizan M. Kassim, Heung-Ja Hong (2006)

3. Persuasive.

Nizar Souiden, Norizan M. Kassim, Heung-Ja Hong (2006)

4. Does business in an ethical way.

Nizar Souiden, Norizan M. Kassim, Heung-Ja Hong (2006)

5. Open and responsive to consumers.

Nizar Souiden, Norizan M. Kassim, Heung-Ja Hong (2006)

3.5.3 Items to Measure Price No. Items Source 1. Continue if prices increase. Teemu Santonen (2007) 2. Willing to pay a higher price. Teemu Santonen (2007) 3. Switch to a competitor that offers better prices. Teemu Santonen (2007) 4. Paid a fair price. David Martin-Consuegra,

Arturo Molina and Agueda Esteban (2007)

5. Fair Pricing policy.

David Martin-Consuegra, Arturo Molina and Agueda Esteban (2007)

44

3.5.3 (continued) Items to Measure Price 6. Ethical pricing policy.

David Martin-Consuegra, Arturo Molina and Agueda Esteban (2007)

7. Acceptable pricing policy.

David Martin-Consuegra, Arturo Molina and Agueda Esteban (2007)

8. Willing to pay more. David Martin-Consuegra, Arturo Molina and Agueda Esteban (2007)

9. Accept changes in price. David Martin-Consuegra, Arturo Molina and Agueda Esteban (2007)

10. The price meets my expectations. Andreas Herrmann, Lan Xia, Kent B. Monroe & Frank Huber (2007)

11. The price is good value for money. Andreas Herrmann, Lan Xia, Kent B. Monroe & Frank Huber (2007)

3.5.4 Items to Measure Customer Satisfaction No. Items Source 1. Meets pre-purchase expectations.

Serkan Aydin and Gokhan Ozer (2005)

2. Completely meets my expectations. Serkan Aydin and Gokhan Ozer (2005)

3. Again decide in favour of this service provider. Gianfranco Walsh and Keith Dinnie and Klaus-Peter Wiedmann (2006)

4. Customer-oriented.

Gianfranco Walsh and Keith Dinnie and Klaus-Peter Wiedmann (2006)

5. Wise choice. Gi-Du Kang & Jeffrey James (2004)

6. Good experience. Gi-Du Kang & Jeffrey James (2004)

7. Satisfied with this service provider. Gianfranco Walsh and Keith Dinnie and Klaus-Peter Wiedmann (2006)

45

3.5.5 Items to Measure Service Loyalty No. Items Source 1. I will go on using this service provider.

Serkan Aydin and Gokhan Ozer, (2005)

2. I would prefer this service provider. Serkan Aydin and Gokhan Ozer, (2005)

3. Recommend to others. Serkan Aydin and Gokhan Ozer, (2005)

4. Even if the other service providers’ billing is cheaper, I would go on using this service provider.

Serkan Aydin and Gokhan Ozer, (2005)

5. My first choice in using this service provider. Riichan Kayaman & Hnseyin Arasli (2007)

6. Strongly committed.

David Martin-Consuegra, Arturo Molina and Agueda Esteban (2007)

7. Loyal to this service provider. David Martin-Consuegra, Arturo Molina and Agueda Esteban (2007)

3.6 Data Analysis Techniques

Appropriate measures were identified based on empirical researchers to test the

hypothesized relationship. Quantitative data obtained and the data gathered were

being treated by using the statistical software program namely Statistical Package for

Social Research (SPSS) version 14.0 for analysis and summarization purposes.

Several techniques of analysis were used including Reliability test, Factor Analysis,

ANOVA test, Correlation, Partial Correlation, and Multiple Regression.

3.6.1 Reliability Test

In statistics, reliability is the consistency of a set of measurements or measuring

instrument, often used to describe a test. This can either be whether the measurements

of the same instrument give or are likely to give the same measurement (test-retest),

46

or in the case of more subjective instruments, such as personality or trait inventories,

whether two independent assessors give similar scores. Reliability is inversely related

to random error (Coakes & Steed, 2007).

There are several different reliability coefficients. One of the most commonly used is

called Cronbach’s Alpha. Cronbach’s Alpha is based on the average correlation of

items within a test if the items are standardized. It has an important use as a measure

of the reliability of a psychometric instrument. It was first named as alpha by

Cronbach (1951), as he had intended to continue with further instruments. It is the

extension of an earlier version, the Kuder-Richardson Formula 20 (or KR-20), which

is the equivalent for dichotomous items.

3.6.2 Factor Analysis

According to Coakes & Steed (2007), Factor Analysis is a data reduction technique

used to reduce a large number of variables to a smaller set of underlying factors that

summarize the essential information contained in the variables. Factor Analysis is

more frequently used as an exploratory technique when to achieve the objective of

summarize the structure of a set of variables.

Coakes & Steed (2007) also mention that for testing a theory about the structure of a

particular domain, confirmatory Factor Analysis is appropriate. This technique is an

additional means of determining whether items are tapping into the same construct if

this technique is used to construct a reliable test.

47

3.6.3 ANOVA Test

In statistics, analysis of variance (ANOVA) is a collection of statistical models, and

their associated procedures, in which the observed variance is partitioned into

components due to different explanatory variables. The initial techniques of the

analysis of variance were developed by the statistician and geneticist R .A. Fisher in

the 1920s and 1930s, and is sometimes known as Fisher's ANOVA or Fisher's

analysis of variance.

The basic procedure is to derive two different estimates of population variance from

the data, then calculate a static from the ratio of these two estimates (Coakes & Steed,

2007). One of these estimates (between-groups variance) is a measure of the effect of

the independent variable combined with error variance while within-group variance is

a measure of error variance by itself. A significant F-ratio indicates that the

population means are probably not all equal.

3.6.4 Correlation

In statistic, correlation, (often measured as a correlation coefficient), indicates the

strength and direction of a linear relationship between two random variables. In

general statistical usage, correlation or co-relation refers to the departure of two

variables from independence. In this broad sense there are several coefficients,

measuring the degree of correlation, adapted to the nature of data (Coakes & Steed,

2007).

A number of different coefficients are used for different situations as mentioned by

Coakes & Steed (2007). The best known is the Person product-moment correlation

48

coefficient, which is obtained by dividing the covariance of the two variables by the

product of their standard deviations. Pearson's correlation reflects the degree of linear

relationship between two variables. It ranges from +1 to -1.

A correlation of +1 means that there is a perfect positive linear relationship between

variables. A correlation of -1 means that there is a perfect negative linear relationship

between variables. A correlation of 0 means there is no linear relationship between the

two variables. Correlations are rarely if ever 0, 1, or -1. A certain outcome could

indicate whether correlations are negative or positive.

3.6.5 Partial Correlation

Partial correlation provides a single measure of linear association between two

variables while adjusting for the effects of one or more additional variables (Coakes

& Steed, 2007). The partial correlation represents the actual importance of attribute,

with the effect of a set of controlling random variables removed.

3.6.6 Multiple Regression

According to Coakes & Steed (2007), multiple regression is an extension of bivariate

correlation. They state that the result of regression is an equation that represents the

best prediction of a dependent variable from several independent variables.

Regression analysis is used when independent variables are correlated with one

another and with the dependent variable.

49

3.7 Pilot Test

Before the official distribution of questionnaire to the population, a pilot test activity

has been deployed. Pilot test involves administering a questionnaire to a small group

of respondents to detect ambiguity or bias in the questions or to iron out fundamental

problems in the instructions or administrative procedure (Zikmund, 1997). Pilot test

also used to measure the reliability of those questions stated in questionnaire.

According to Zikmund (1997), reliability is the degree to which measures are free

from random error and therefore yield consistent results.

Usually the questionnaire is tried out on a group selected on a convenience basis and

similar in makeup to the one that ultimately will be sampled later. Pilot test allows the

researchers to determine whether respondents have any difficulty in understanding the

questionnaire or if there are any ambiguous or biased questions.

A total of 50 questionnaires have been sent out to test the level of reliability. The pilot

test exercise gathered 33 respondents replies. Reliability was measured through an

examination of Cronbach’s Alpha coefficients. For scale acceptability, Nunnally

(1978) suggested should be over 0.7. Overall Cronbach’s Alpha coefficients were

found at 0.917 and which exceed the threshold value, conforming to Nunnally’s

(1978) criterion.

Although the overall Cronbach’s Alpha coefficients were found at 0.917, some

questions have been amended as per the comments from the respondents. Questions

have been reviewed to eliminate bias and ambiguity before the distribution to the

population.

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4.0 Research Result

This section first describes the respondents’ demographic profiles, and provides

statistical results of the variables described. It follows by hypotheses testing and

summary of the result findings.

4.1 Respondents’ Demographic Profiles

241 replies were received for the survey. Respondents were almost equally split

between males (52.7%) and female (47.3%). From the total replies, 66% of

respondents were Chinese, followed by Malay (26.1%), Indian (6.6%), and other

ethnic group (1%). However, there were two missing values for ethnic group, which

represented 0.8% of the total respondents.

The above ethnic group result did not represent the overall population of Malaysia as

the survey was conducted based on convenience sampling. It depends on willingness

of respondents to participate in this study and the convenience to seek participation

from respondents.

The majority (45.6%) of the respondents were between 21 and 30 years old. It

followed by age group between 31 and 40 years old (38.2%). The minority (0.8%) of

the respondents were above 50-year-old. There was 0.4% of missing value in ethnic

group whereby a respondent did not indicate the age group.

Majority of the respondents were single which represented 55.6% of the total

respondents. Only one respondent indicated that he or she has divorced. The majority

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were executive (44.0%) and managerial (21.6%) level, which in line with the

educational backgrounds as most of them (73.9%) have obtained tertiary education.

64.7% of respondents were currently using only one telecommunication service

provider. Only 13 of respondents (or 5.4%) using more than two service providers.

The most frequently used network among respondents was Maxis (64.3%), followed

by Digi (23.2%) and Celcom (11.6%) while 0.8% of respondents did not answer

which is their most frequently used network.

52

The Table 1 below shown the results discussed on respondents’ demographic profiles.

Frequency Percent Gender Female 114 47.3 Male 127 52.7 Total 241 100.0 Ethnic Group Chinese 159 66.0 Indian 16 6.6 Malay 63 26.1 Other 1 .4 Total 239 99.2 Missing 9.00 2 .8 Total 241 100.0 Age Group 20 and below 12 5.0 21 - 30 110 45.6 31- 40 92 38.2 41 - 50 24 10.0 Above 50 2 .8 Total 240 99.6 Missing 9.00 1 .4 Total 241 100.0 Marital Status Single 134 55.6 Married 106 44.0 Divorced 1 .4 Total 241 100.0 Educational Level Primary 5 2.1 Secondary 23 9.5 Diploma 57 23.7 Degree 101 41.9 Master 49 20.3 PhD 4 1.7 Total 239 99.2 Missing 9.00 2 .8 Total 241 100.0 Occupation Top Management 17 7.1 Manager 52 21.6 Executive 106 44.0 Non-executive 44 18.3 Other 17 7.1 Total 236 97.9 Missing 9.00 5 2.1 Total 241 100.0 Number of line One 156 64.7 Two 72 29.9 More than two 13 5.4 Total 241 100.0 Name of telecommunication Celcom 28 11.6 service provider Digi 56 23.2 Maxis 155 64.3 Total 239 99.2 Missing 9.00 2 .8 Total 241 100.0

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4.2 Analysis of Measures

4.2.1 Reliability Test

A reliability analyses was conducted to each variable of the instrument. The reliability

of the measures was examined through the calculation of Cronbach’s alpha

coefficients. For scale acceptability, Hair et al. (1998) suggested that Cronbach’s

alpha coefficient of construct is 0.6 if each domain obtains the value 0.6; it means that

the items in each domain are understood by most of the respondents.

On the other hand, if the findings are far from the expected value of 0.6, this might be

caused by respondents’ different perception toward each item of the domain. The

corrected item correlation at 0.3 and above is accepted as a good item to explain a

domain (Hair et al., 1998).

The Cronbach’s alpha and correlation value are reported as follow. Service quality

yield Cronbach’s alpha = .971, corporate image yield Cronbach’s alpha = .888, the

Cronbach’s alpha for price was at .874, Cronbach’s alpha for customer satisfaction

was at .920, and Cronbach’s alpha for service loyalty was at .918. Please refer to

Table 3: Factor Analysis and Reliability for more details.

4.2.2 Factor Analysis

KMO and Bartlett's Test

Bartlett’s test of sphericity is significant for all domains. The Kaiser-Meyer-Olkin

measure of sampling adequacy is greater than .6 for all domains with a value of .953

for service quality, .824 for corporate image, .886 for price, .891 for customer

satisfaction, and .892 for service loyalty.

54

Table 2: KMO and Bartlett’s Test Variable Service quality Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .953 Bartlett's Test of Sphericity Approx. Chi-Square 5179.545 df 210 Sig. .000 Corporate image Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .824 Bartlett's Test of Sphericity Approx. Chi-Square 712.839 df 10 Sig. .000 Price Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .886 Bartlett's Test of Sphericity Approx. Chi-Square 1738.856 df 55 Sig. .000 Customer satisfaction Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .891 Bartlett's Test of Sphericity Approx. Chi-Square 1350.397 df 21 Sig. .000 Service loyalty Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .892 Bartlett's Test of Sphericity Approx. Chi-Square 1152.454 df 21 Sig. .000

The validity of measurements was tested by running factor analysis (Principle

Component Analysis). Since the domain of the measurements had been identified, the

aims of performing factor analysis were to determine whether items tapping into the

same construct and measuring the construct (Coakes, 2005).

Before conducting factor analysis, items have been classified into five domains,

namely service quality, corporate image, price, customer satisfaction, and service

loyalty. Factor analysis was run by using Principle Component Analysis according to

items in each domain across. Since this analysis would study whether items tapping

into the domain itself, the extracted variables will be used and explained according to

eigenvalue and factor loading of items in each domain. The eigenvalue is used to

55

determine which factors or components to keep in the solution and percentage of

variances is the variances that could be explained by the factor.

The extracted variables in this analysis will be identified based on the loading factor

that was extracted by Component Matrix and Rotated Component Matrix. However,

the researcher might make decision based until the Component Matrix Output if each

variable gives acceptable factor loading towards a factor (Hinton et al., 2004). The

result of the factor analysis is enrolled as follows.

Table 3: Factor Analysis and Reliability Variable

Factor

Loading Reliability

Service Provides prompt service to the customers .881 .971 Quality Provides services at the promised time .877 Willing to help customers .873 Ready to respond to customers' requests .865 Dependable in handling customer service problem .856 Performs services right at first time .852 Feel safe in transactions .837 knowledgeable to answer customer questions .829 Keeps customer informed .827 understand the needs of customers .822 Provides services as promised .816 Has customers' best interest at heart .814 Individual attention .797 Consistently courteous .787 Caring manner .786 Instill confidence in customers .751 Insists on error-free service .719 Neat appearance .705 Visually appealing physical facilities .595 Business hours convenient to customers .586 Modern looking equipment .664 Corporate Successful and self-confident .832 .888 Image Persuasive .830 Innovative and pioneering .823 Does business in an ethical way .729 Open and responsive to consumers .716 Price Acceptable pricing policy .870 .874 Fair pricing policy .849 Ethical pricing policy .837 The price meets my expectation .808 The price is good value for money .751 Paid a fair price .704 Willing to pay more .630 Continue if its prices increase .614 Accept changes in price .609 Willing to pay a higher price .597 Switch to a competitor that offers better prices .400

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Table 3(continued): Factor Analysis and Reliability

Customer Good experience .910 .920 Satisfaction Satisfied with this company .899 Customer-oriented .861 Wise choice .840 Completely meets my expectations .799 Meets my pre-purchase expectations .717 Again decide in favor of this service provider .524 Service Strongly .863 .918 Loyalty Loyal to this service provider .825 Recommend to others .818 My first choice in using this service provider .813 I would prefer this service provider .786 I will go on using this telecommunication company .785 Even if the other telecommunication companies'

billing is cheaper, I would go on using this telecommunication company

.620

4.2.3 ANOVA Test

ANOVA analysis has been conducted to test mean difference among the

telecommunication service providers.

The result of analysis in each variable in Table 4. Digi received highest mean score in

all the five variables. It followed by Maxis and Celcom. Although Maxis having the

largest user population in the study (64.3%), the level of customer satisfaction and

service loyalty of Maxis users were still lower than Digi.

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Table 4: Descriptive Summary for the Three Telecommunication Service Providers

4.2.4 Correlation

In Table 5, the output indicated that a significant positively relationship among all the

variables and that all the correlation coefficients were significant (p < 0.05).

Table 5: Correlations Matrix between Variables

Service Quality

Corporate Image Price

Customer Satisfaction

Corporate Image .785(**) Price .655(**) .585(**) Customer Satisfaction .808(**) .748(**) .781(**) Service Loyalty .691(**) .598(**) .792(**) .835(**)

** Correlation is significant at the 0.01 level (1-tailed).

4.3 Testing of Hypotheses

To test the hyphothesized relationship, correlation and then a series of multiple

regression analyses were be conducted. The output from this analysis, a beta

Variable Telecommunication Service Provider Mean Std. Deviation Sig.

Service Celcom 2.6542 .86274 .025 Quality Digi 3.2508 1.08932 Maxis 2.8830 1.05884 Corporate Celcom 2.7214 .98333 .523 Image Digi 2.9857 1.09136 Maxis 2.8335 1.09919 Price Celcom 3.0909 .84233 .030 Digi 3.6445 .92308 Maxis 3.6047 1.02557 Customer Celcom 2.7551 1.04173 .375 Satisfaction Digi 3.1148 1.11606 Maxis 3.0175 1.12407 Service Celcom 2.8571 1.06266 .093 Loyalty Digi 3.4566 1.11705 Maxis 3.1917 1.25224

58

coefficient, provides an assessment of the significance and the impact of the predictor

variables on the dependent variable.

Independent Variables as Predictors to Service Loyalty (To test H1 to H3)

The hyphothsis number one to three of the study was tested and the result summarized

in Table 6. The independent variables (service quality, corporate image, and price)

together explained 68% of the variance (R squared) on service loyalty, which was

highly significant, as indicated by the F-value of 167.642 in the following tables:

Table 6: Model Summary (Independent Variables as Predictors to Service Loyalty) R R Square Adjusted R Square Std. Error of the Estimate

.824(a) .680 .676 .69065 a Predictors: (Constant), Price, Corporate Image, Service Quality Table 7: ANOVA(b) (Independent Variables as Predictors to Service Loyalty) Model

Sum of Squares df Mean Square F Sig.

Regression Residual Total

239.896 3 79.965 167.642 .000(a) 113.049 237 .477 352.946 240

a Predictors: (Constant), Price, Corporate Image, Service Quality b Dependent Variable: Service Loyalty

The coefficients table (Table 8) below presented the strength of the three predictors

(service quality, corporate image, and price) toward service loyalty. It yielded the

following result:

a) service quality yielded β = .0318, Std. Error = .074, sig. (p) = .000 < .05,

b) corporate image yielded β = .041, Std. Error = .067, sig. (p) = .538 > .05, and

c) price yielded β = .718, Std. Error = .060, sig. (p) = .000 < .05.

59

Table 8: Coefficients(a) (Independent Variables as Predictors to Service Loyalty)

Unstandardized Coefficients

Standardized Coefficients t Sig.

B Std. Error Beta (Constant) -.396 .168 -2.355 .019 Service Quality .318 .074 .276 4.288 .000

Corporate Image .041 .067 .037 .617 .538

Price .718 .060 .589 11.965 .000 a Dependent Variable: Service Loyalty

Independent Variables as Predictors to Customer Satisfaction (To test H4 to H6)

The hyphothsis number four to six of the study was tested and the result summarized

in Table 9. The independent variables (service quality, corporate image, and price)

together explained 78.2% of the variance (R squared) in customer satisfaction, which

was highly significant, as indicated by the F-value of 282.858 in Table 10.

Table 9: Model Summary (Independent Variables as Predictors to Customer Satisfaction)

R R Square Adjusted R Square

Std. Error of the Estimate

.884(a) .782 .779 .52428 a Predictors: (Constant), Price, Corporate Image, Service Quality Table 10: ANOVA(b) (Independent Variables as Predictors to Customer Satisfaction)

Model Sum of

Squares df Mean Square F Sig. Regression 233.244 3 77.748 282.858 .000(a) Residual 65.143 237 .275 Total 298.388 240

a Predictors: (Constant), Price, Corporate Image, Service Quality b Dependent Variable: Customer Satisfaction

60

The coefficients table (Table 11) below presented the strength of the three predictors

(service quality, corporate image, and price) toward customer satisfaction. The

multiple regression shown values of contribution of each predictor as follow:

a) service quality yielded β = .383, Std. Error = .056, sig. (p) = .00 < .05,

b) corporate image yielded β = .228, Std. Error = .051, sig. (p) = .00 < .05, and

c) price yielded β = .465, Std. Error = .046, sig. (p) = .00 < .05.

Table 11: Coefficients(a) (Independent Variables as Predictors to Customer Satisfaction)

Model

Unstandardized Coefficients

Standardized Coefficients t Sig. Correlations

B Std. Error Beta

Zero-order Partial Part

(Constant) -.419 .128 -3.289 .001 Service Quality .383 .056 .363 6.814 .000 .808 .405 .207

Corporate Image .228 .051 .221 4.458 .000

Price .465 .046 .414 10.196 .000 .781 .552 .309 a Dependent Variable: Customer Satisfaction

Partial Correlation

Partial correlation provides a single measure of linear association between two

variables while adjusting for the effects of one or more additional variables (Coakes

& Steed, 2007). The partial correlation represents the actual importance of attribute,

with the effect of a set of controlling random variables removed. It is used to test the

trade-off relationship between price and service quality in term of customer

satisfaction.

When corporate image and price were entered as the controlling variables, a

significant positive relationship existed between service quality and customer

satisfaction (r = .405, p < .05). However, it is interesting to note that controlling for

corporate image and price did lower the strength of the relationship between service

61

quality and customer satisfaction by r = .403 if compared to no controlling taking

place as indicated in Table 12 below.

Table 12: Correlations – Control Variables (Corporate Image & Price) Control Variables

Customer Satisfaction

Service Quality

Corporate Image & Price

Customer Satisfaction Correlation 1.000 .405

Significance (1-tailed) . .000 df 0 237 Service Quality Correlation .405 1.000 Significance (1-tailed) .000 . df 237 0

When corporate image and service quality were entered as the controlling variables as

shown in Table 13 below, the postive relationship level between price and customer

satisfaction has been reduced to r = .552 from r = .781.

Table 13: Correlations – Control Variables (Service Quality & Corporate Image)

Control Variables

Customer Satisfaction Price

Service Quality & Corporate Image

Customer Satisfaction

Correlation

1.000 .552

Significance (1-tailed) . .000 df 0 237 Price Correlation .552 1.000 Significance (1-tailed) .000 . df 237 0

Customer Satisfaction as Predictor to Service Loyalty (To test H7)

The hyphothsis number seven of the study was tested and the result summarized in

Table 14. The independent variable (customer satisfaction) explained 69.7% of the

variance (R squared) in service loyalty, which is highly significant, as indicated by the

F-value of 549.754 in the following tables:

62

Table 14: Model Summary(b) (Customer Satisafaction as Predictor to Service Loyalty)

R R Square Adjusted R Square Std. Error of the

Estimate .835(a) .697 .696 .66893

a Predictors: (Constant), Customer Satisfaction b Dependent Variable: Service Loyalty Table 15: ANOVA(b) (Customer Satisfaction as Predictor to Service Loyalty)

Model Sum of

Squares df Mean Square F Sig. Regression 246.000 1 246.000 549.754 .000(a) Residual 106.946 239 .447 Total 352.946 240

a Predictors: (Constant), Customer Satisfaction b Dependent Variable: Service Loyalty

The coefficients table below presented the strength of the predictor (customer

satisfaction) towards service loyalty. The multiple regression shown value of

contributions of customer satisfaction yield

β = .908, Std. Error = .039, sig. (p) = .00 < .05.

Table 16: Coefficients(a) (Customer Satisfaction as Predictor to Dependent Variable)

Model

Unstandardized Coefficients

Standardized Coefficients t Sig.

B Std. Error Beta (Constant) .477 .124 3.849 .000 Customer Satisfaction .908 .039 .835 23.447 .000

a Dependent Variable: Service Loyalty

Independent Variables and Customer Satisfaction as Predictors to Service

Loyalty (To test H8)

The hyphothsis number eight of the study was tested and the result summarized in

Table 17. The independent variables and mediating variable (service quality,

63

corporate image, price, and customer satisfaction) together explained 75% of the

variance (R squared) on service loyalty, which was highly significant, as indicated by

the F-value of 176.948 in the following tables:

Table 17: Model Summary (Independent Variables and Customer Satisfaction as

Predictors to Service Loyalty)

a Predictors: (Constant), Customer Satisfaction, Corporate Image, Price, Service Quality

Table 18: ANOVA(b) (Independent Variables and Customer Satisfaction as Predictors

to Service Loyalty)

Model Sum of

Squares df Mean

Square F Sig. Regression 264.690 4 66.172 176.948 .000(a) Residual 88.256 236 .374 Total 352.946 240

a Predictors: (Constant), Customer Satisfaction, Corporate Image, Price, Service Quality b Dependent Variable: Service Loyalty

The coefficients table (Table 19) below presented the strength of the four predictors

(service quality, corporate image, price, and customer satisfaction) toward service

loyalty. It yielded the following result:

a) service quality yielded β = .081, Std. Error = .072, sig. (p) = .258 > .05,

b) corporate image yielded β = -.099, Std. Error = .062, sig. (p) = .112 > .05,

c) price yielded β = .432, Std. Error = .064, sig. (p) = .000 < .05, and

d) customer satisfaction yielded β = .617, Std. Error = .076, sig. (p) = .000 < .05

R

R Square

Adjusted R Square

Std. Error of the Estimate

.866(a) .750 .746 .61153

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Table 19: Coefficientsa (Independent Variables and Customer Satisfaction as

Predictors to Service Loyalty)

Model

Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta (Constant) -.137 .152 -.900 .369 Service Quality .081 .072 .071 1.133 .258

Corporate Image -.099 .062 -.088 -1.595 .112

Price .432 .064 .354 6.771 .000 Customer Satisfaction .617 .076 .567 8.142 .000

a Dependent Variable: Service Loyalty

4.4 Summary of Research Results

The findings indicate that the questionnaire identified to measure service quality,

corporate image, price, customer satisfaction, and service loyalty exhibit acceptable

psychometric properties in terms of both reliability and validity. The results confirm

the hypothesised relationship in the model as reported in Table 20.

Table 20: Result Table of the Tested Hypotheses

Hypothesis Hypothesis result 1: Service quality has a positive effect on service loyalty. Supported 2: Corporate image has a positive effect on service loyalty. Not Supported 3: Price has a positive effect on service loyalty. Supported 4: Service quality has a positive effect on customer satisfaction.

Supported

5: Corporate image is significantly related to customer satisfaction.

Supported

6: The pricing plans are significantly related to customer satisfaction.

Supported

7: Customer satisfaction has a positive effect on service loyalty.

Supported

8: Customer satisfaction is the mediator of the relationship among service quality, corporate image, and price and service loyalty.

Supported

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Service quality, corporate image, and price are found significantly influence customer

satisfaction. It answered the first research question (Does service quality, corporate

image and price influence customer satisfaction?).

Correlation and partial correlation analysis have been used to find out if there is any

trade-off between price and service quality (research question number two). The result

confirmed that there is a trade-off between price and service quality in terms of

customer satisfaction. Under correlation analysis, the Coefficient of Determination

(r2) indicated 65% shared variance between service quality and customer satisfaction

while price served to explain 61% of the variance in respondents’ scores on the

customer satisfaction. It shows that the correlation is higher for service quality if

compared to price.

However, the percentage of variance did change when partial correlation was being

used. The shared variance between service quality and customer satisfaction has been

reduced to 16% and the shared variance between price and customer satisfaction has

been reduced to 30%. The changes indicated that price is now contributing more than

service quality towards customer satisfaction. In short, consumers are influenced by

price then trade-off service quality. Although the statistical result shown not very high

significant on the trade-off relationship, it is still consider significant.

There are evidences showing that customer satisfaction performs a mediating role on

the link among service quality, corporate image and price towards service loyalty

through multiple regression testing. The mediating effect was tested based on

procedure provided by Baron & Kenny (1986). This involves the computation of four

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regression equations. First, the regression of the independent variables (service

quality, corporate image, and price) on the dependent variable (service loyalty) as per

Independent Variables as Predictors to Service Loyalty.

Second, the regression of the mediator (customer satisfaction) on the independent

variables (service quality, corporate image, and price) as reported in Independent

Variables as Predictors to Customer Satisfaction. Third, the regression of the

dependant variable (service loyalty) on the mediator (customer satisfaction) as stated

in Customer Satisfaction as Predictor to Service Loyalty. Lastly, the regression of the

dependant variable (service loyalty) on both the independent variables (service

quality, corporate image, and price) and on the mediator (customer satisfaction) as

stated in Independent Variables and Customer Satisfaction as Predictors to Service

Loyalty.

There are few conditions for mediation to hold. In the first regression equation, the

independent variables must be shown to affect the dependent variables. In the second

regression equation, the independent variables must affect the mediator. In the third

regression equation, the mediator must be shown to affect the dependent variable; and

the final equation the mediator must affect the dependent variable to the exclusion of

the independent variable (Baron & Kenny, 1986).

From the computed regression equations, the conditions required for mediation to

hold are present. When the direct effect between the independent variable and the

dependent variable is no longer statistically different from zero fixing the mediator

variable, the mediation effect is said to be complete. However, from the above

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regression equations, the absolute size of the direct effect between the independent

variable and the dependent variable is reduced after controlling for the mediator

variable, but the direct effect is still significantly different from zero, the mediation

effect is said to be partial (Baron & Kenny, 1986). Through the tests and analysis, it

answered the research question number three (does customer satisfaction mediates the

relationship among service quality, corporate image and price towards service

loyalty?).

Among the independent variables, price has been found to be the most important input

to customer satisfaction and explains standardized coefficients (β) of 0.414. It follows

by service quality (β = 0.363) and corporate image (β = 0.221). It represented that the

first research objective in this study has been answered. However, corporate image is

found not significantly affecting service loyalty with sig. (p) > .05 although the

relationship is positive. As explained by Bailey & Ball (2006), corporate image is not

a key dimension of service loyalty. Corporate image alone is not a guarantee of

success and there is little opportunity for organizations to develop a strong reputation.

While for customer satisfaction, it explains 0.835 of standardized coefficients towards

service loyalty. Result has shown that customer satisfaction is positively and

significantly influences loyalty. It answered research objective number two, that is to

investigate the effect of customer satisfaction on service loyalty.

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5.0 Conclusion and Recommendations

In this section, the findings are summarised and their implications discussed. This

chapter also outlines recommendation for future research.

5.1 Summary and Conclusions

The study examines the relationship among service quality, corporate image, price,

customer satisfaction, and service loyalty and found a positive relationship among

these variables. From the study, it is confirmed that service quality, corporate image,

and price are factors that contributing to customer satisfaction in the

telecommunication industry of Malaysia.

Among the established variables, price is found to be the most important factor for

telecommunication consumers when choosing telecommunication service provider. It

is therefore has a high significant level on consumers’ satisfaction judgement. The

results indicated that price is directly influenced by satisfaction judgements and

loyalty followed by service quality and corporate image.

In conclusion, the results demonstrate the importance of improving the quality

management of mobile phone services, and show that customer satisfaction depends

on the perceived level of quality delivered. Finally, this study of the mobile telephone

market in Malaysia supports the contention in the general marketing literature that the

main factor creating and improving customer loyalty is customer satisfaction. It gives

implications for differentiated marketing strategies according to the perceived value

and type of customer loyalty.

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5.2 Suggestions for Future Research

This study was conducted in a single service industry, mobile phone service sector.

While the environment of this industry may be considered representative of issues

faced by the general population of service industries, care should be taken in applying

the findings of this study to other industries. Alternatively, in the future research,

researchers might include the fixed line consumers and pre-paid telecommunication

service users in order to wider the scope of telecommunication service providers.

Ideally, research should be conducted using multiple industries in order to eliminate

peculiarity of a single industry and to ensuring the observed relationships are

generalizable to a broader population. However, in exploratory studies such as this

study, the use of a single industry may provide more accurate results in terms of

gaining a basic understanding of the nature of specific relationships.

In addition to examining whether the proposed loyalty conditions typically exist for

specific industries, service loyalty research needs to link loyalty with the issues

identified in the discussion of implications. Loyalty can be measured before and after

changes are made at service organizations to test empirically the relationships

between marketing strategies and the building and retention of service loyalty.

5.3 Implications

5.3.1 Service Quality

One of the primary implications of this study is that quality is not an end in itself; but

a means to an end ... namely, enhanced company performance and sustained

competitive advantage (Molly & Brent, 1998). For many years, firms have sought to

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improve customer service in order to avoid potential problems. The result is that many

people view quality as merely a support mechanism, rather than a viable competitive

strategy (Molly & Brent, 1998). In contrast, successful firms define their strategy

around the pursuit of quality. Results indicate that this singular pursuit has a positive

impact on company performance.

A strategy built on quality can be sustainable for several reasons. First, quality is

something that not all firms do extremely well. Providing quality services require a

commitment in terms of planning, leadership, and implementation. This commitment

leads to the development of a corporate culture that internalizes a quality orientation

in all activities. Thus, organizations that possess the requisite skills and resources are

better able to pursue a quality-based strategy that less-adept firms cannot. The pursuit

of quality should be motivated by a desire to build competitive advantages that can be

uniquely translated into superior organizational performance.

5.3.2 Corporate Image The results from the current study confirm the role of corporate image as a factor in

the perception of customer satisfaction. One implication of these findings for

managers is to assess corporate image as part of an assessment of perceptions of

customer satisfaction. A positive corporate image makes it easier for organizations to

communicate effectively, and it makes people more perceptive to favorable word-of-

mouth messages. It is very important for organizations to have a clear, favorable

image (Gi-Du & Jeffrey, 2004).

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A good corporate image can positively affect a firm’s sales and market share

(Shapiro, 1982), and the establishment and maintenance of a loyal relationship with

customers (Andreassen and Lindestad, 1998; Nguyen and Leblanc, 2001). As reported

by Keller and Aaker (1997), a strong corporate image can be used to increase

communication efficiency. De Ruyter and Wetzels (2000) state that the corporate

image is an information cue that consumers use to judge matters such as credibility,

perceived quality and purchase intentions. Additionally, some researchers affirm that

a corporate image builds the reputation of the company and that a favorable corporate

image leads to a positive corporate reputation in the minds of the public (Alessandri,

2001).

5.3.3 Price

The study findings indicate clearly the complexity and multidimensionality that

characterizes pricing decisions given that different pricing behavior patterns. This fact

has been also supported from a normative perspective within the existing literature on

pricing in that different categories of services necessitate formulating different pricing

strategies (e.g. Zeithaml & Bitner, 1996). This complexity is also reflected on the fact

that different service, organizational and environmental characteristics were found to

lead to different pricing policies especially in different service contexts (Zeithaml &

Bitner, 1996).

Within this context, there does not seem to be a solely method for pricing decisions,

which can be applied to all circumstances and service contexts. Formulating the

pricing strategy seems to be a business activity that requires managers to place their

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emphasis on the unique characteristics of the services that they render in the market

together with their companies’ overall strategy and goals and their market structure.

A number of different authors (e.g. Shipley and Jobber, 2001) have stressed the

significance of incorporating customers’ needs and characteristics into the pricing

process if effective pricing decisions are to be made. After all, as Narver and Slater

(1990) have suggested better performance can be achieved only if every business

activity is implemented by having the customer in mind. Therefore, an implication for

managers responsible for pricing decisions within their firms is to always have their

customers in mind and design their pricing strategies from a customer perspective.

5.3.4 Customer Satisfaction

For the customer to remain satisfied, everyone in the organization has to take the

responsibility for helping the customer (Goldzimmer, 1990). Berry (1995) talks of

competing for talent in employees, setting high standards and sticking to those

standards, whilst Berry and Parasuraman (1991) highlight the importance of bringing

purpose and meaning to employees’ jobs and of empowering them without the fear of

reprisal. Additionally, changing the organizational culture to encourage employees to

adopt the “right first time” philosophy is essential (Oakland, 2000).

It is apparent that a multidimensional construct of service quality explains consumer

behavioral intentions in service industry. Managers should therefore be aware of the

need to include all service-quality dimensions in their efforts to improve service

quality. Organizations should not wait until complaints arise from customers about

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service quality. An organization that continuously monitors the satisfaction of its

customers can improve its services by listening to the evaluations of customers.

5.3.5 Service Loyalty

The foregoing statement about what drives loyalty should be understood with the

proviso that loyalty is not entirely divorced from satisfaction (Mittal & Lassar, 1998).

The disloyalty/loyalty groups contrasted are from a subpopulation that is already

satisfied. In separating disloyal versus loyal customers, therefore, managers have to

ask what drives loyalty beyond satisfaction. In addition to measuring satisfaction,

managers must also measure customer intention to patronize the organization in the

future (Mittal & Lassar, 1998).

Another implication of this finding is to emphasize the importance of sustaining and

developing customer loyalty based on a differentiated approach to retain customers

who have different levels of loyalty development. It is important for manager to

remember that customers benchmark not just from what similar service companies are

doing, but what the best service providers in general are doing. Loyalty is built

through a positive differentiation that is usually achieved by providing superior

customer service.

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7.0 Appendix - Appendix A: Questionnaire

- Appendix B: Report in CD

Appendix A – Questionnaire

Perception towards Telecommunication Service Providers in Malaysia

Dear Sir / Madam, The following questionnaire is conducted as part of my fulfillment of the Master of Business Administration degree with University of Malaya. The general purpose of this study is to understand mobile phone users’ perception towards telecommunication service providers in Malaysia. Please be assured that all information will be treated with strictest confidentiality and only the aggregate data will be analyzed. I am therefore inviting you to participate in this survey by filling up the attached questionnaire. The said questionnaire is constructed in a straightforward manner and easy to answer which should take not more than 15 minutes of your valuable time to complete the attached questionnaire. As the successful completion of this study is largely dependent upon obtaining an adequate and representative sample, your participation in this survey is highly appreciated. If you have any concerns regarding this study, please feel free to contact the undersigned at hlingchong@yahoo.com. Thank you for your time and participation. Sincerely, Chong Hui Ling (Matrix number: CGA040034)

UNIVERSITY OF MALAYA Faculty of Business and Accountancy Master of Business Administration

Celcom

Instructions This survey consists of three sections: Section A: Profiling of Telecommunication Service Provider Section B: Perception Towards Telecommunication Service Provider Section C: Demographic Profile Please select only ONE (1) answer to each statement which best suit your opinion.

Section A: Profiling of Telecommunication Service Provider 1. How many telecommunication service providers are you currently using?

2. Please specify the most frequently used telecommunication service provider.

Section B: Perception Towards Telecommunication Service Provider

The following are some statements about your perception towards issues in the telecommunication service industry in Malaysia. Please indicate the degree of your agreement or disagreement based on your experience with your most frequently used network. My telecommunication company 1 7

Strongly Strongly agree disagree

1. has business hours convenient to all of its customers. 1 2 3 4 5 6 7

2. has modern looking equipment. 1 2 3 4 5 6 7 3. has visually appealing physical facilities. 1 2 3 4 5 6 7 4. uses visually appealing materials associated with

the service. 1 2 3 4 5 6 7

5. is innovative and pioneering. 1 2 3 4 5 6 7 6. is successful and self-confident. 1 2 3 4 5 6 7 7. is persuasive. 1 2 3 4 5 6 7

One Two More than two

Digi Maxis

Other (Please specify)

My telecommunication company 1 7

Strongly Strongly agree disagree

8. does business in an ethical way. 1 2 3 4 5 6 7 9. is open and responsive to consumers. 1 2 3 4 5 6 7 10. meets my pre-purchase expectations. 1 2 3 4 5 6 7 11. completely meets my expectations compared to

other telecommunication companies. 1 2 3 4 5 6 7

My telecommunication customer service employees

1 7 Strongly Strongly agree disagree

12. instill confidence in customers. 1 2 3 4 5 6 7 13. are consistently courteous. 1 2 3 4 5 6 7 14. have the knowledge to answer customer

questions. 1 2 3 4 5 6 7

15. give customers individual attention. 1 2 3 4 5 6 7 16. deal with customers in a caring manner. 1 2 3 4 5 6 7 17. understand the needs of their customers. 1 2 3 4 5 6 7 18. have a neat appearance. 1 2 3 4 5 6 7 19. provides services as promised. 1 2 3 4 5 6 7 20. is dependable in handling customer service

problem. 1 2 3 4 5 6 7

My telecommunication customer service 1 7 Strongly Strongly agree disagree

21. performs services right at first time. 1 2 3 4 5 6 7 22. provides services at the promised time. 1 2 3 4 5 6 7 23. keeps customers informed when service will be

provided. 1 2 3 4 5 6 7

24. provides prompt service to the customer. 1 2 3 4 5 6 7 25. is always willing to help customers. 1 2 3 4 5 6 7 26. is always ready to respond to customers’

requests. 1 2 3 4 5 6 7

27. makes customers feel safe in their transactions. 1 2 3 4 5 6 7 28. has the customers’ best interest at heart. 1 2 3 4 5 6 7 29. insists on error-free service. 1 2 3 4 5 6 7

Personal factor

1 7 Strongly Strongly agree disagree

30. I will continue to do business with the telecommunication company if its prices increase.

1 2 3 4 5 6 7

31. I am willing to pay a higher price for the benefits of services. 1 2 3 4 5 6 7

32. I will switch to a competitor that offers better prices. 1 2 3 4 5 6 7

33. I paid a fair price for my telecommunication service. 1 2 3 4 5 6 7

34. I consider my telecommunication company’s pricing policy as fair. 1 2 3 4 5 6 7

35. I consider my telecommunication company’s pricing policy as ethical. 1 2 3 4 5 6 7

36. I consider my telecommunication company’s pricing policy as acceptable. 1 2 3 4 5 6 7

37. If I had the choice, I would again decide in favor of my current telecommunication company. 1 2 3 4 5 6 7

38. In my view, my telecommunication company is customer-oriented. 1 2 3 4 5 6 7

39. My choice to use this telecommunication company was a wise one. 1 2 3 4 5 6 7

40. Using this telecommunication company has been a good experience. 1 2 3 4 5 6 7

41. I am satisfied with my telecommunication company. 1 2 3 4 5 6 7

42. I will go on using this telecommunication company. 1 2 3 4 5 6 7

43. If I bought a new mobile phone line, I would prefer this telecommunication company. 1 2 3 4 5 6 7

44. I recommend this telecommunication company to others. 1 2 3 4 5 6 7

45. Even if the other telecommunication companies’ billing is cheaper, I would go on using this telecommunication company.

1 2 3 4 5 6 7

46. I usually use this telecommunication company as my first choice compared to other companies. 1 2 3 4 5 6 7

47. I am strongly committed to my telecommunication company. 1 2 3 4 5 6 7

48. I am very loyal to my telecommunication company. 1 2 3 4 5 6 7

49. Sometimes I am willing to pay more. 1 2 3 4 5 6 7 50. I usually accept changes in price. 1 2 3 4 5 6 7 51. The price of the telecommunication company

meets my expectation. 1 2 3 4 5 6 7

52. The price of the telecommunication company is good value for money comparing to other telecommunication companies.

1 2 3 4 5 6 7

Other (Please specify):

Section C: Demographic Profile 1. Please indicate your gender.

2. Please indicate your ethnic group.

3. Please indicate your age group.

4. What is your marital status?

□ Single 5. What is your highest education level?

□

6. How does your present job fit into your organization’s structure?

Male Female

20 and below 21 - 30 31 - 40 41 - 50 Above 50

Chinese Indian Malay

Single Married Divorced Widow

Primary Secondary Diploma Degree

Master PhD

Top management Manager Executive

Other (Please specify):

Non-executive

Other (Please specify):

~ Thank you for your participation ~