FACTORS AFFECTING LOYALTY OF INTERNET CUSTOMERS EVIDENCE FROM VIETNAM

According to the findings of this research, in order to retain internet service customers, providers need to take into consideration with factors such as network quality, price perceptio

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

Nguyen Thi Kim Quyen

FACTORS AFFECTING LOYALTY OF INTERNET CUSTOMERS: EVIDENCE FROM VIETNAM

MASTER OF BUSINESS (Honours)

Ho Chi Minh City – Year 2012

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

Nguyen Thi Kim Quyen

FACTORS AFFECTING LOYALTY OF INTERNET CUSTOMERS: EVIDENCE FROM VIETNAM

ID: 60340102

MASTER OF BUSINESS (Honours)

SUPERVISOR: DR DINH THAI HOANG

Ho Chi Minh City – Year 2012

ACKNOWLEDGEMENTS

I would not have been able to complete my thesis without the advice, assistance, understanding and encouragement of a number of people I would like to gratefully and sincerely acknowledge their assistance and support First of all, the most important person I would like to thank is my supervisor, Dr Dinh Thai Hoang Thanks to his valuable advice and generous guidance throughout the process of completing this thesis Secondly, I would like to express my gratefulness to Dr Nguyen Dinh Tho for his kindness in supporting me to deal with analyzing data and other issues of the thesis

Furthermore, I would like to thank all of the staff at International School of Business – University of Economics Ho Chi Minh City who are always enthusiastic and give me a lot of administrative support, assistance and understanding

Finally, I would like to give my gratefulness to all classmates who have been sharing with me all their knowledge and experience as well as happiness and difficulties during MBA course I would not complete my thesis without their encouragement and support

In brief, it has been a long journey and I have grown in so many ways I would like

to say “thank you” again for the involvement of everyone who has helped me to complete this thesis

ABSTRACT

For Internet service providers (ISP), it is essential for them to understand the critical factors that influence customer loyalty These issues are critical to the long-term business success of any service provider Based on the literature reviewed in the thesis, this study empirically investigates the impact of factors on customer loyalty

A quantitative method via questionnaire survey was used to obtain the views of approximately 300 Internet users in Ho Chi Minh city regarding their opinions and perceptions about their current ISP and their intention to stay with them Multiple linear regression analysis was used to investigate the relationship between customer loyalty and influencing factors mentioned above

According to the findings of this research, in order to retain internet service customers, providers need to take into consideration with factors such as network quality, price perception, perceived value and trust The results of this research are important for ISP to enhance and improve their competitiveness, in other words, to become successful and have more loyal customers, which will ultimately result in more profitability

Keywords: customer retention, customer loyalty

TABLE OF CONTENTS

ACKNOWLEDGEMENTS 3

ABSTRACT 4

CHAPTER 1: INTRODUCTION 5

CHAPTER 1: INTRODUCTION 5

1.1 Introduction 5

1.2 Research background 5

1.3 The research objectives 7

1.4 The research questions 7

1.5 The research model 7

1.6 The research methodology 7

1.7 The research structure 8

1.8 Conclusion 8

CHAPTER 2: LITERATURE REVIEW 10

2.1 Introduction 10

2.2 Customer loyalty with internet service provider 10

2.2.1 Network quality and customer loyalty 11

2.2.2 Price perception and customer loyalty 11

2.2.3 Perceived value and customer loyalty 12

2.2.4 Trust and customer loyalty 13

2.3 Controlling factors 13

2.4 The research model 13

2.5 Conclusion 15

CHAPTER 3: RESEARCH METHODOLOGY 16

3.1 Introduction 16

3.2 The research approach 16

3.3 Measurement 16

3.4 Sample and Data collection 19

3.5 Data analysis 20

3.6 Conclusion 22

CHAPTER 4: DATA ANALYSIS AND RESULT 23

4.1 Introduction 23

4.2 Preliminarily data analysis 23

4.2.1 Cleaning and screening data 23

4.2.2 Profile of respondents 23

4.3 Evaluating the measuring scales 25

4.4 Multiple Linear Regression analysis 32

4.4.1 Introduction 32

4.4.2 Computing variables 32

4.4.3 Assumption for Multiple Regression 32

4.4.4 Testing hypotheses 35

4.4.5 Controlling variables 37

4.5 Conclusion 39

CHAPTER 5: CONCLUSION AND IMPLICATIONS 40

1.1 Introduction 40

1.2 Conclusion 40

1.3 Implications of the study 41

1.4 Limitations and suggestions for further research 42

REFERENCES 43

APPENDIX A: QUESTIONAIRE 47

APPENDIX B: DATA ANALYSIS 53

LIST OF FIGURES

Figure 1: The theoretical model 14

Figure 2: The Histogram 33

Figure 3: The Nomal P-P Plot of Regression Standardized Residual 34

Figure 4: Scatterplot 34

LIST OF TABLES

Table 1: Research questions and hypotheses 15

Table 2: Measuring scale for variables 19

Table 3: The profile of respondents 25

Table 4: The reliability statistics 27

Table 5: KMO and Barlett’s test 29

Table 6a: The pattern matrix of EFA result 30

Table 7b: The pattern matrix of EFA result 31

Table 8: The Cronbach’s alpha result - retest 31

Table 9: Collinearity statistics 35

Table 10: Hypotheses testing 36

Table 11: Regression with controlling variable of gender 37

Table 12: Regression result with controlling variable of income level 38

Table 13: Regression result with controlling variable of using experience 38

CHAPTER 1: INTRODUCTION 1.1 Introduction

This research examines the driving forces of internet users’ loyalty and their intention to stay with their current provider among existing Internet Service Providers (ISP) in the context of Vietnam telecommunication sector This chapter will provide general information of research problem as well as research background, identify research objectives and research questions This chapter also briefly outlines research structure

1.2 Research background

High-speed internet services are becoming more and more popular and the rapid development of information technologies affects every aspect of our lives The importance of information and communication technology is undeniable as it has been applied in various fields for the purpose of service enhancement Although basic Internet services had existed in Vietnam since the early nineties, until 1997, the first commercial Internet Service Provider (ISP) opened for business – Vietnam Data Communication Company (VDC) which belongs to Vietnam Posts & Telecommunication Groups (VNPT) Since then, Vietnam has been connected by two gateways: one in Hanoi connecting with Hong Kong and Australia, and the other in Ho Chi Minh City, which connects with the United States by Sprint Internet usage remains low in comparison with that of other Asian nations, yet connectivity has increased rapidly over the past few years, thanks to an initiative by the Ministry of Post and Telecommunications According to the internet statistic report of VNIC (Vietnam Internet Center), up to June 2012, the number of internet users in Vietnam is more than 31 million which is equivalent to the scale of 35.4 percent users per capita Over more than fifteen years of formation and development, together with the development of internet services, the number of ISPs has also remarkably increased, which leads to severe competition among ISPs, especially in a developing country like Vietnam Until now, there are more than ten ISPs operating in Vietnam including VDC/VNPT, Viettel, FPT, Netnam, SPT,

Hanoi Telecom, VTC, G-Tel, Vishiped and CMC TI in which three of the leading companies: VDC/VNPT, Viettel, FPT have obtained more than 85 percent of total Internet service market share in Vietnam As a result, ISPs must try their best to develop their marketing strategy and improve their business performance to increase their level of competitiveness From the above statistics, we can understand that the competition of Internet services in Vietnam is a severe war among three big ISPs: VDC/VNPT, Viettel and FPT Beside the diversification of services, enhancing the customer satisfaction and customer loyalty is considered to be the most effective way to compete in the market, especially in telecommunication industry which is on the verge of saturation point in some years’ time Customer loyalty are believed to be the most effective weapons for providers to complete with other rivals because these factors are the primary variables that impact customers’ intention to stay with their current providers (Khatibi, Ismail & Thyagarajan, 2002) The providers which satisfy customers can expect higher market shares and greater profitability and, in turn, encourage their customers to become loyal (Khatibi, Ismail & Thyagarajan, 2002) Aaker (1991) has discussed the role of loyalty in the brand equity process and has specifically noted that brand loyalty leads to certain marketing advantages such as reduced marketing costs, more new customers and greater trade leverage Expanding loyal customers can assist in generating a business’s profitability because the cost of retaining existing customers is less than that of acquiring new ones (Reichheld, Teal, 1996) Therefore, understanding how and why a sense of loyalty develops in customers remains one of the crucial management issues of our day By assessing the Internet service users in Ho Chi Minh city, this research will give useful information of a range of factors impact on Vietnamese internet users’ perceptions of their current ISPs, from which factors effecting customer loyalty, especially in telecommunication sector, will be derived

In other words, this research provides ISPs the direction and valuable understandings of what factors should be taken into account to become successful

and have more loyal customers, which ultimately result in more profitability and leads to their strong competitiveness and stable growth in the future

1.3 The research objectives

Arising from the research problem, this research aims to explore the main attributes

in internet service provisioning - customer loyalty in the context of Vietnam telecommunication market More specifically, the main objective of this research is

to identify the factors influencing customer loyalty in Internet services in Vietnam

We also examine the affecting level of each factor on Vietnamese internet users’ loyalty

1.4 The research questions

Based on the research objectives, we accordingly give two main questions as follow:

- What are the factors that influence customer loyalty in Internet services in Vietnam?

- How do these factors influence on loyalty of Internet customers?

1.5 The research model

Based on the literature review, a model with four hypotheses are established in order to explore the research problems and develop the hypotheses Figure 1 – The research model – in Chapter 2 shows the proposed model for this research regarding customers’ intentions to stay with their current ISP in Vietnam This model leads to four hypotheses tested that show the relationship between network quality, price perception, perceived value and trust and customer loyalty

1.6 The research methodology

An overview of the research methods used to collect and analyze the data are briefly discussed In this research, a survey with questionnaire in was used to collect data The questionnaire was made in English and then translated into Vietnamese because all of respondents are Vietnamese Random sampling was chosen to reduce bias in

the sample The data collected from the survey was coded, analyzed and interpreted

by SPSS software More details of the research methodology are provided in Chapter 3 and the result of the research is presented in Chapter 4

1.7 The research structure

This research begins with Chapter 1 – Introduction, which provides general introduction and brief background of internet services in general and in the context

of Vietnam in particular to the research including research background, research objectives, research questions, research model, research methodology and structure

of the research

Chapter 2 – Literature review - screens the literature of customer loyalty from previous researches Basing on these literature reviews, a model with four hypotheses is developed We examine the relationship between customer loyalty and its affecting factors including network quality, price perception, perceived value and trust Besides, demographic factors such as gender, income, and experience of service using are also tested their impact on customer loyalty

Chapter 3 – Research methodology - presents methods to conduct this research, consisting of three sections Firstly, measuring scale with items for each factor is provided Next, sample and data collection are explained in detail The last one describes the process and analytical techniques used for data analysis

Chapter 4 – Data analysis - reports the results from data analysis process and confirms the value of hypotheses mentioned in Chapter 2 and relationship among factors

Chapter 5 – Conclusion, implications and limitations – repeats the result derived from this research Moreover, this chapter also discusses limitations of the research and suggestions for future researches

1.8 Conclusion

This chapter presents the background to the research in order to introduce the key research problem, research objectives, research questions, research model and

research methodology By reviewing the existing literature, this research aims to test the relationship between customer loyalty and its affecting factors in Vietnamese Internet service market Four factors are assumed to have positive effect on loyalty of Internet customers Data are collected by questionnaire and analyzed by SPSS software

CHAPTER 2: LITERATURE REVIEW2.1 Introduction

This chapter presents a review of the literature in the main areas of customer retention which concentrates on factors influencing customer loyalty for internet service providers, especially in the context of Vietnam telecommunication industry

At first, from the tested relationship between customer loyalty and relating factors including network quality, price perception, perceived value and trust, four hypotheses derived from which (H1, H2, H3, H4) are proposed Then, the controlling variables such as gender, income and service using experience are also tested their effect on customer loyalty

2.2 Customer loyalty with internet service provider

Customer loyalty is an outcome of a customer’s purchase and use resulting from the comparison of the reward and the costs of the purchase in relation to the anticipated consequences (Churchill & Surprenant 1982) Jacoby (1975) advises that loyalty is

a biased behavioral purchase process caused by the customer’s emotional processes Loyalty can be measured by several factors including proportion of purchase, purchase sequence, and probability of purchase (Dick & Basu 1994) The meaning

of customer loyalty can be explained as the customer’s intention to stay with the current service provider and, at the same time, their behavior to make frequent repeat purchases of their preferred brands As a result, most businesses prefer to retain their valued customers and persuade them to become more loyal because this can result in greater income and profit Without customer loyalty, service providers may not be able to retain their competitive advantage This can be explained as loyal customers are easier to serve and make fewer demands on employees since they already know and understand the company’s working processes (Chow & Holden 1997) Loyal customers appear to provide more repeat patronage and are less likely to shop around with competitors for better deals (Bowen & Chen 2001)

In order words, companies create profit from their long-term relationship The

longer loyal and profitable customers stay with a business, the more profit that the business can gain (Reichheld & Teal 1996)

In general, a range of advantages arise when businesses have loyal customers including increasing profitability, increasing price premiums, increasing long-term relationship and commitment, increasing purchase intention and positive word-of-mouth, reducing marketing and operating costs and increasing switching barriers to prevent customers from defecting their current service provider (Reichheld & Teal 1996) Therefore, customer loyalty cannot be neglected and most companies must try their best to satisfy their customers in order to develop long-term relationships with them and to ensure their customers become loyal

2.2.1 Network quality and customer loyalty

Network quality is one of the most important drivers of overall service quality which leads to customer satisfaction in the context of telecommunication (Chun & Hahn, 2007; Wang, Lo & Yang, 2004) Previous literature suggested that stability, transmission speed and network coverage are the core attributes of network quality (Woo & Fock, 1999; Mohd R.B Yaacob, 2011) The stability and transmission speed of internet service were important to users and they will consider changing to other providers due to stability and speed factor (Mohd R.B Yaacob, 2011) Moreover, the uptime of service was tested to have impact on customer satisfaction as well as customer loyalty (Wang, Lo & Yang, 2004) The results of Wang, Lo & Yang’s (2004) study suggested that, in order for service providers to

be successfully competitive, they must try to improve the availability of service

We, therefore, hypothesize that:

H1: Network quality has a positive impact on customer loyalty

2.2.2 Price perception and customer loyalty

With regards to price perception, although Internet broadband users are willing to pay more for better service, they will consider changing to other provider because

of the price factor (Mohd R.B Yaacob, 2011) Therefore, we believe that customers

of Internet services are sensitive to price and the higher price level could lead to low demand, accordingly Ranaweera & Neely (2003) showed that price perception has

a direct linear relationship with customer loyalty in telecommunications sector We therefore believe that such relationship may be more explicit in the fierce price competitive in telecommunication market like Vietnam Hence, we formulate the following hypothesis:

H2: Service price is positively related to customer loyalty

2.2.3 Perceived value and customer loyalty

Perceived value can be defined as the customers’ overall assessment of the utility of products or services based on perceptions of what is received and what is sacrificed (Monroe 1991, Parasuraman, Zeithaml & Berry 1988) Simply stated, perceived value is trade-off between benefits and sacrifices The perceived sacrifice includes all the costs the customer faces when they are in the process of purchasing such as purchase price, acquisition costs, installation, repair and maintenance, risk of failure

or poor performance (Monroe 1991, Parasuraman, Zeithaml & Berry 1988) The perceived benefits include physical and service attributes, technical support, and other indicators of perceived service quality Monroe 1991, Parasuraman, Zeithaml

& Berry (1988) point out that perceived value is subjective and individual, and therefore varies among customers Research evidence suggests that customers who perceive that they receive value for money are more satisfied and tend to become loyal customers more often than ones who do not (Zeithaml, Berry & Parasuraman 1996) Customers who remain with a service provider for a longer period of time because they are pleased with the perceived quality and value of the services tend to buy more additional services and spread favorable word-of-mouth messages and have a willingness to recommend the firm to others (Boulding 1993, Zeithaml & Berry 1988) Perceived value, from the service providers’ standpoint, should be viewed as a major competitive weapon and can be used to create and improve their sustainable competitive advantage (Khatibi, Ismail & Thyagarajan 2002) By adding

more perceived value to the service, customer loyalty can be increased We, therefore, hypothesize that:

H3: Perceived value has a positive effect on customer loyalty

2.2.4 Trust and customer loyalty

Trust can be viewed as an antecedent of customer loyalty (Dick & Basu, 1994) To create customer loyalty toward a brand, building long-term relationships with customers in order to win their trust is considered advantageous (Morgan & Hunt, 1994) When customers have trust in the products or services of their preferred brand, they are willing to purchase more of the brands without the need to be heavily persuaded, and this can result in lower advertising and other related costs (Murphy, 2001) Trust can be viewed as being complementary to satisfaction, in ensuring long-term relationships, and strengthening customer loyalty (Hart & Johnson, 1999) In addition, trust is a willingness to rely on other parties in whom one has confidence, when the buyers trust the sellers, it affects their purchasing behavior (Chow & Holden, 1997) This leads to the following hypothesis:

H4: Trust positively influences customer loyalty

2.3 Controlling factors

Choudrie, Jyoti (2005) find there are strong influences of demographic variables such as gender, income on customer loyalty In this research, the relationship between gender, income also were tested Besides, the customer’s experience with

service should be examined its impact on customer loyalty

2.4 The research model

The research model is the foundation that the entire research is based on and a good model should help in identifying and labeling the underlying variables in the circumstances that are related to the research problem (Sekaran 2000) This section

is built basing on the existing literature to propose a model linking the correlations between customer loyalty and relating variables To appropriately answer the

research questions, we develop the model with five main variables including network quality, price perception, perceived value and trust, which are considered

to be dependent variables affecting customer loyalty Furthermore, controlling variable of demographic is tested its influence on the relationship among these

to be tested in the research:

1 What are the factors that influence

customer loyalty in Internet

H1: Network quality has a positive impact

on customer satisfaction

Controlling variables (Gender, Experience, Income)

H2: Price perception is positively related

to customer loyalty

H3: Perceived value has a positive effect

on customer loyalty

services in Vietnam?

2 How do the factors influence

customer loyalty in Internet

In addition, we also examine the effect of demographic factors on customer loyalty

CHAPTER 3: RESEARCH METHODOLOGY 3.1 Introduction

The purpose of this chapter is to introduce the research methods and approaches used to investigate customers’ perceptions of Internet service users in Ho Chi Minh city Specifically, this chapter will give you some general information about the way we conducted the research including the research approach, measurement, sampling, data collection, and data analysis technique

3.2 The research approach

Quantitative approach primarily involves statistical analysis and relies on numerical data to ensure objective and accurate results are obtained in order to draw conclusions or to test hypotheses (Ticehurst & Veal, 2000) This research involves quantifying the relationship between variables and will use quantitative research to test the research assumptions and hypotheses in order to solve the research problem This is a quantitative research because it seeks to answer set hypotheses from reviews of previous literature rather than attempting to develop new theory

3.3 Measurement

This section presents the items for measurement of all relating factors Items of each factor are developed from previous literature review mentioned in Chapter 2

Measuring scale of network quality from Mohd R.B Yaacob (2011) and Wang, Lo

& Yang (2004) were used:

- The upload and download speed of network is always strong

- The uptime of network is always available without interruption

- The connection quality is always reliable

- I can access the network at anytime without delay

Items for price perception from Ranaweera & Neely (2003):

- The price charged by X is reasonable

- The service’s price of X is cheaper than others

- Service supplied by X is equivalent to its price

- Service offered by X is better value for money than what I would pay for the same service of others

- I’m willing to pay more for better service quality

Based on Wang, Lo & Yang (1988), five items for measuring the effect of perceived value on customer loyalty are adopted:

- The customer service staff of my ISP gives me adequate support

- Whenever I have problem with services, X takes corrective action without delay

- X keeps me informed of things that I need to get the best use of the service

- I feel comfortable with the willingness of assistance and support from X

- Overall, the chosen offerings are worth for my money, effort and time Items for measuring trust from Dick & Basu (1994)

- I believe that X will be ready and willing to offer me assistance and support

- I believe that X always fulfills the promises that it makes to its customers

- I believe that X has necessary ability and knowledge to fulfill its tasks

- I believe that X always puts interests of its customers first of all

Items for customer loyalty from Nguyen and Leblanc (1991)

- I will recommend X as the best ISP in HCMC

- I will continue to do business with X

- X is my first choice in my future internet service needs

- I will purchase other services offered by X in the future

- I will encourage friends and relatives to do business with X

Items for demographic of respondents:

No Variables Literature review Measuring items

quality

Mohd R.B Yaacob (2011) and Wang,

3 The connection quality is always reliable

4 I can access the network at anytime without delay

perception

Ranaweera &

Neely (2003):

1 The price charged by X is reasonable

2 The service’s price of X is cheaper than others

3 Service supplied by X is equivalent to its price

4 Service offered by X is better value for money than what I would pay for the same service of others

5 I’m willing to pay more for better service quality

2 I believe that X always fulfills the promises that

it makes to its customers

3 I believe that X has necessary ability and knowledge to fulfill its tasks

4 I believe that X always puts interests of its customers first of all

5 Customer

loyalty

Nguyen and Leblanc (1991)

1 I will recommend X as the best ISP in HCMC

2 I will continue to do business with X

3 X is my first choice in my future internet service needs

4 I will purchase other services offered by X in the future

5 I will encourage friends and relatives to do business with X

Table 2: Measuring scale for variables

3.4 Sample and Data collection

Sampling can be described as the process of selecting a sufficient proportion of people from the entire population (Sekaran, 2000) The process of random sampling was used in order to reduce bias in the sample of Vietnamese Internet users According to DeCoster, J (2004), minimum sample size used in statistics analysis should be equal to or greater than five times of the number of independent variables, but not less than 100 to generate reliable results: n ≥ 100 and n ≥ 5k (where k is the number of items) This research has 23 items, as a result, the minimum sample size required to run EFA in this research is: n = 5 x 23 = 115 Otherwise, Tabachnick & Fidell (2001) stated that the minimum sample size in case of multiple regression should be: n = 50+8m (where m is the number of independent variables) Apply this formula for 4 independent variables of this research, we have the minimum sample size for multiple regression: n = 50 + 8 x 4 = 82 In summary, this research needs

115 samples at least to take EFA and multiple regression analysis With quantitative approach, in order to ensure the reliability and validity, the adequate sample size for this research was about three hundreds of internet service users The survey was conducted from August to October with Internet service users in Ho Chi Minh city The questionnaire was sent to more than 500 potential respondents to get the target sample size of around 300 respondents

Data was collected by questionnaire survey which consists of three sections The first section was questions about customers’ experience with ISPs; the questions in the second section focused on respondents’ opinions on service and their future decision with the current ISP; and the last one were demographic questions Basically, the questionnaire contained statements that could be answered through ranking and open-ended questions as well Respondents were asked some fundamental questions about their experiences with ISP and which companies were their current ISPs In the second section, a seven-point Likert scale ranging from

“Strongly disagree” (1) to “Strongly agree” (7) was used to measure respondents’ perceptions about their current ISP’s service quality and intention to stay with or leave for another one The questionnaire was made in English at first and translated into Vietnamese because the respondents were all Vietnamese

3.5 Data analysis

Following data collection, the next step is the process of data analysis in order to address the research questions The procedure of converting raw data into information consists of several processes including editing, coding, data entry and data analysis (Zikmund 2000) In this research, the SPSS software was chosen to analyze the data in terms of descriptive statistics Data processing procedures and analytical techniques used in this research are discussed as below:

Firstly, the Cronbach alpha was used to examine the reliability of measuring scale Cronbach alpha is a statistical test if correlation of the items in the scale relative to each other (Hair 2006) So, this method of analysis can remove inappropriate variables and limit junk variables in the research process and assess the reliability of

the scale through the Cronbach alpha coefficient (Hair 2006) The scales are reliable when Cronbach’s alpha coefficient of each scale is equal to or bigger than 0.7 (Pallant 2005)

Secondly, Effecting Factor Analysis (EFA) was conducted to test the number of factors extracted Factor analysis is a multivariate statistical technique which defines the underlying structure among a large number of variables (Hair 2006) The two fundamental purposes of factor analysis are to summarise the information contained in a large number of variables and condense the data into smaller number

of factors (Hair, 2006) In this research, there were five factors that were assumed to have impact on customer loyalty of Internet services Factor analysis was used to create factors for each of the five measuring scale related In addition, factor analysis helped the researcher to determine which factors were highly correlated to customer’s loyalty The result is considered to be acceptable when following conditions are met (Pallant, 2005):

 The sample size should be equal to or greater than five cases for each variable

 Factor analysis is appropriate to data if:

 The Kaiser-Meyer-Olkin value (KMO) is 0.6 or greater

 The Bartlett’s test of sphericity is statistically significant: p < 0.05

 The number of factors is determined when:

 The total variance explained by these components should be above 50%

 Factor loading criteria should be 0.5 or more to ensure a practical significance

Thirdly, Pearson’s correlation coefficient was used to examine the relationships between two or more research variables (Veal 2005) According to Veal (2005), the relationship between the variables can take different forms If the value of correlation coefficient is 1.0, then there is a perfect positive correlation between two variables In contrast, if the value of correlation coefficient is -1.0, it can be

concluded that there is a perfect negative correlation between two variables In addition, there is no relationship between two variables of the value of correlation coefficient is zero

Finally, multiple regression analysis was conducted to analyze the relationship among variables Multiple regression analysis is a statistical technique that is used

to analyze the relationship between several independent variables and a single dependent variable (Hair et al.2006) It was used to examine the simultaneous effects of several independent variables on a dependent variable In this research, Multiple Linear Regression method was used to test the research model and hypotheses Pallant (2005) explains the conditions to accept the result are:

 The sample size is: n > 50 + 8m (where m is the number of independent variables)

 No multicollinearity is found

 Normality and linearity should exist

 We also use R-square value to express how much of the variance in the dependent variable was explained by the model

3.6 Conclusion

This chapter introduces the research methods and general information about the way

we conducted the research including the research approach, measurement, sampling, data collection, and data analysis technique More detailed discussion of the analytic methods used and results are provided in the Chapter 4

CHAPTER 4: DATA ANALYSIS AND RESULT

4.1 Introduction

This chapter provides the results of the data analysis step by step and interpretations

of research findings The purpose of this chapter is to answer the research questions and test the study hypotheses This chapter consists four main parts: (1) preliminarily data analysis, (2) evaluating the measuring scales and (3) testing the hypotheses and the research model

4.2 Preliminarily data analysis

The quantitative research was conducted by using a survey questionnaire which was completed by Internet service users in Ho Chi Minh city At first, 100 samples were used for pilot test which was specifically mentioned above Then, 286 completed questionnaires were collected and analyzed in the main study Preliminarily data analysis consists of cleaning and screening data and summarizing profile of respondents

4.2.1 Cleaning and screening data

This step helps us to detect inappropriate samples which were completed by careless respondents For example, the respondent chose the same range of scale for all statements in the questionnaire Moreover, missing data were also considered to have negative impact on the result In this research, missing data was not a problem because the questionnaire survey was designed and completed online Respondents could not submit their answers with any missing data in the questionnaire So, in this step, we only checked inappropriate ones After cleaning and screening data, 11 samples were distorted by the first error – out of range values

4.2.2 Profile of respondents

The sample size should be large enough to make sure coverage of collected data In general, the ratio of observations to independent variables should never fall below five to one Nevertheless, the desired level is between 15 and 20 observations for

each independent variable (Hair et al.1998) This research has 5 variables with 23 measuring items Therefore, according to this standard, the minimum sample size for this research is about 194 However, in order to make sure the sample size was proportionally distributed among ISP’s market share, the desired sample size for this study was around 300 samples The link of the online designed questionnaire was sent to more than 500 Internet service users Then, 297 samples were recorded

by google tools After cleaning and screening data, 286 samples were used for official analysis in which (1) VNPT: 148 samples equal to 52%, (2) Viettel: 72 samples, equal to 25%, (3) FPT: 58 sample equal to 20% and (4) remaining 3% for other providers such as SCTV, SPT, The profiles of respondents are outlined as following table:

From above 35 to 50 years

Less than 1 year 42 15%

Table 3: The profile of respondents

In summary, gender of respondents was equal between male and female Most of respondents belonged to the age group from 25 to 35 years old and average monthly income from more than 10M to 15M In addition, there were 47% of respondents had been experienced with their current ISP for more than 3 years

4.3 Evaluating the measuring scales

Measuring scales were preliminarily evaluated the reliability and validity by Cronbach alpha and Exploratory Factor Analysis (EFA) Firstly, Cronbach alpha was used to test scales’ reliability Reliability can be defined as the dependability or consistency of the variable’s measurement that is the degree to which measures are free from error and therefore provide consistent results (Neuman 2006) The Cronbach alpha coefficient is a commonly used method to examine the reliability for multipoint-scaled items It can be considered a perfectly adequate index to test the consistency reliability (Sekaran 2000) Therefore, the Cronbach alpha coefficient was used in this research as the key test to measure scale reliability The alpha coefficient ranges from 0 to 1 and where the alpha coefficient is greater than 0.7, this can be considered an acceptable reliability (Hair et al 1998) In this research, items with alpha coefficient less than 0.6 and corrected item-total correlation lower than 0.30 would be deleted In this research, cronbach alpha coefficient of all factors were acceptable because they are greater than 0.8, ranging from 882 to 901 The Cronbach’s alpha analysis was summarized as the table 4 below:

Item-Total Statistics

Items

Scale Mean

if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Item-Squared Multiple Correlation

Cronbach's Alpha if Item Deleted

Table 4: The reliability statistics

Network quality was measured by 4 items with good overall alpha coefficient by 901 Cronbach alpha if item deleted of all items were less than alpha coefficient of factors (.901), which means that deletion of any item from questionnaire would not improve the factor’s reliability Besides, Corrected Item-Total correlation of all showed good indication, that was much more than 0.3 We, therefore, concluded that all items for network quality variable were reliable

Cronbach’s alpha of price perception variable indicated reliable coefficient by 888 Moreover, the alpha coefficient of each item showed its useful contribution to overall coefficient alpha and Corrected Item-Total Correction column of this factor consisted of high number Hence, price perception variable and five of its measuring scales were accepted and used for further analysis

The alpha coefficient of perceived value was 879 which presented an acceptable reliability as mentioned above Furthermore, Cronbach’s alpha if Item Deleted showed that no improvement in the overall reliability of the scale occurred when any of these questions were deleted and the Corrected Item-Total Correlation of all items above 0.3 Thus, all of items represented for this factor and the factor was included in subsequent analyses

The general alpha coefficient of trust variable was 879, which was higher than the required standard (.70), which indicated for its reliability All items also reflected