Research background
The internet service market is rapidly expanding globally, with Vietnam experiencing significant growth as well As of July 2011, approximately 29.5 million people in Vietnam were using the internet, representing 33.99% of the population This number is projected to rise to 40% by 2012, highlighting the increasing digital engagement in the country.
The internet has become a primary means of communication in Vietnam, accounting for 42% of daily interactions The global internet service market is rapidly expanding, with Asia leading in the number of users Notably, Vietnam ranks among the countries with the highest growth rates of internet users in the region Numerous service providers, including VNPT, FPT, Viettel, SPT, and SCTV, are active in the Vietnamese market, prompting increased research interest in this dynamic sector.
As competition intensifies and customer acquisition costs rise, firms increasingly prioritize customer retention to maintain market share This strategic shift emphasizes the importance of fostering long-term relationships with existing customers, as customer loyalty is crucial for a company's survival and future growth To sustain stable profits in a saturated market, businesses should adopt a defensive strategy focused on retaining current customers rather than pursuing aggressive market expansion efforts.
Numerous studies have been conducted on this critical issue, leading to the development of various dynamic models that examine the relationships and impacts of different antecedents on customer loyalty.
Problem statement
In today's highly competitive internet industry, service providers must allocate significant resources to enhance customer satisfaction and retention.
Customer retention is crucial for a company's survival and future growth To maintain stable profits, especially when subscription levels have saturated, a defensive strategy focused on retaining existing customers becomes more vital than an aggressive approach aimed at attracting new ones.
Numerous studies highlight that customer satisfaction and quality service are crucial for fostering customer loyalty in the internet service sector Additionally, factors such as perceived value, trust, corporate image, price perception, and switching costs significantly influence customer loyalty.
Customer satisfaction alone cannot fully account for customer loyalty, as consumers retain the freedom to choose their suppliers for various reasons, including switching costs, corporate image, and price perception.
This study investigates the factors influencing customer loyalty in the internet service market of Ho Chi Minh City, focusing on customer satisfaction, switching costs, price perception, and corporate image as key antecedents By analyzing these elements, we aim to understand their impact on fostering customer loyalty in this competitive sector.
Research questions and objectives
The research questions that are discussed in this study are as follows:
Key determinants influencing customer loyalty in the internet market of Ho Chi Minh City, Vietnam, include trust, service quality, and brand reputation By assessing the impact of these factors on customer loyalty, businesses can underscore the significance of fostering loyal customers This understanding will guide managers in making informed investment decisions and retaining their clientele amid a highly competitive landscape.
Question 2: Is there a significant difference in customer loyalty among studying and working people, working people, and studying people? This is a minor research question
Based on the above research question, the objectives of this study are outlined to examine key antecedents of customer loyalty and impact career on customer loyalty, it explores:
1 The impact of Customer Satisfaction, Switching Cost, Price Perception, and Corporate Image on Customer Loyalty in internet service in Ho Chi Minh city h
2 The difference in Customer Loyalty among the three career groups – This is a minor research objective.
Research limitation
This thesis serves as a foundational basis for future research in related service sectors; however, it has certain limitations Notably, it does not address additional factors that could affect customer loyalty, such as service quality, demographic characteristics, and customers' internet usage patterns.
Thesis structure
This research is organized in five chapters
Chapter 1 : the introduction chapter It includes a brief overview of the research background, problems and objectives The limitations and research methodology, the implications of research, and structure are also presented
Chapter 2: the literature review and conceptual model This chapter provides a deeply review of previous research on antecedents of customer loyalty Based on that, a conceptual model is proposed
Chapter 3 focuses on the research methodology, detailing the research design and the processes for collecting both primary and secondary data It clearly defines and appropriately applies measurement scales for the research factors involved.
Chapter 4 focuses on data analysis and results, examining the survey findings related to customer satisfaction, switching costs, corporate image, and price perception, and their impact on customer loyalty Additionally, it includes a comparative analysis among different survey groups to highlight variations in responses.
Chapter 5 serves as the conclusion of this dissertation, highlighting key recommendations for internet service provider managers in the Ho Chi Minh City market, emphasizing both theoretical and managerial significance Additionally, this chapter provides a concise summary of the dissertation's main content and suggests avenues for further research.
LITERATURE REVIEW
Customer loyalty
The term "customer" typically refers to the end-users of a product or service, encompassing anyone who receives goods or services from another individual or group Researchers offer various definitions of a customer, highlighting the diverse perspectives on this concept.
A customer is the most important person ever in this office … in person or by mail
A customer is not dependent on us… we are depend on him
Customers are not interruptions in our work; they are the very reason for it We are not merely doing them a favor by serving them; rather, they are granting us the privilege of providing our services.
A customer is not someone to argue or match wits with Nobody ever won an argument with a customer
A loyal customer is characterized by their frequent use of a service provider, a genuine appreciation for the provider, and a reluctance to seek alternatives In contrast, a non-loyal customer is unlikely to return, harbors negative feelings towards the provider, and is open to exploring other options This three-dimensional definition aligns with the operationalization presented by Zeithaml et al (1996).
Loyalty to a company is assessed through five key indicators: expressing positive sentiments about the company, recommending it to others in need of advice, encouraging friends and family to engage with the business, prioritizing it as the preferred choice for purchasing services, and committing to increased business transactions in the coming years.
Customer loyalty is a complex concept defined by various scholars According to Griffin (1996), it encompasses purchase behavior, distinguishing it from customer satisfaction, which is more about attitude Bowen and Shoemaker (1998) highlight that customer loyalty is linked to a customer's likelihood of returning, making referrals, and generating positive word of mouth Krishnamurthi and Raj (1991) emphasize its importance for a brand's long-term success Oliver (1999) describes customer loyalty as a strong commitment to consistently repurchase a preferred product or service, even in the face of marketing efforts that might encourage switching This loyalty is evident in behaviors such as recommending services to others and repeatedly choosing the same provider (Dwyer, Schurr, and Oh 1987; Fornell 1992; cited in Lam et al., 2004).
In generally, customer loyalty can be defined as occurring when customers regularly purchase goods or services, have word of mouth, and make advices to other customers h
Oliver (1999) proposes that customer loyalty has four phases
Cognitive loyalty occurs when customers develop a sense of loyalty to a brand based on their knowledge and perceptions of it This loyalty is often rooted in positive information about the brand's product or service quality, which aligns with their expectations and experiences.
The second phase is affective loyalty It refers to customer liking or positive attitudes toward a brand
The third stage is conative loyalty that consumers have a behavioral intention – committed deeply to buy The intention leads to the fourth stage of action
The fourth phase of customer engagement is action loyalty, where customers transform their intentions into tangible actions In this stage, they actively seek to overcome any obstacles that may hinder their ability to make a purchase, demonstrating a strong commitment to achieving their buying goals.
There are three kinds of customer loyalty approached as these conceptual perspectives: behavioral loyalty/perspective, attitudinal loyalty/perspective, and composite loyalty/perspective (Bowen & Chen, 2001; Zins, 2001)
Behavioral loyalty refers to the actual repurchase behavior or intention of consumers towards a specific brand, while attitudinal loyalty reflects their feelings about a product or service Although behavioral loyalty translates directly into purchases, attitudinal loyalty fosters a positive business image through word-of-mouth, contributing to long-term success even if it doesn't yield immediate profits The combined loyalty perspective integrates both behavioral and attitudinal elements, enhancing the predictive power of customer loyalty and serving as a robust alternative to affective loyalty.
Jacoby and Kyner (1973) define customer loyalty through six essential and collectively sufficient conditions that encompass both behavioral and attitudinal aspects They emphasize that brand loyalty involves a biased (i.e., random) behavioral response, specifically in terms of purchasing, which is consistently demonstrated over time.
(4) by some decision-making unit, (5) with respect to one or more alternative brands out of a set of such brands, and (6) is a function of psychological (decision making, evaluative) process
A study by Lam et al (2004) identifies loyalty as expressed through repeat patronage and recommendations Additionally, Zeithaml, Berry, and Parasuraman (1996) introduce a multi-dimensional framework for measuring customer loyalty, encompassing both attitudinal and behavioral aspects.
In this research, customer loyalty includes both recommending and patronizing actions In the other words, it is composite loyalty
Building customer loyalty is crucial for organizations as it leads to increased market share and higher returns on investment Asker (1991) highlights that brand loyalty reduces marketing costs, attracts new customers, and enhances trade leverage In competitive markets, fostering consumer loyalty is essential for gaining market share and achieving a sustainable competitive advantage Anderson et al (2004) emphasize that a loyal customer base strengthens an organization's bargaining power with suppliers and partners, positively impacting shareholder value by minimizing risks associated with future cash flows Dick and Basu (1994) note that customer loyalty fosters positive word-of-mouth communication and makes customers resistant to competitive strategies Consequently, strategists and marketers are encouraged to cultivate strong customer loyalty Oliver (1999) supports this view, reinforcing the idea that loyal customers engage in affirmative word-of-mouth According to Kotler and Keller (2005), the top 20% of customers can generate 80% of a company's profits, underscoring the importance of loyalty.
Establishing a strong relationship between a company and its customers is crucial for business success In the financial services sector, research indicates that a mere 5 percent increase in customer retention can result in a profit surge of 25 to 75 percent (Chan et al., 2001) Consequently, customer loyalty has emerged as a primary objective for firms operating in today's fiercely competitive market.
In conclusion, it is very necessary for a firm to focus on building loyal customer as its long term strategy
2.1.6 Loyalty programs and its benefits
Customer loyalty programs have significantly evolved in recent years, driven by advancements in information technology, and are now widely adopted by organizations to enhance customer retention According to Yi and Jeon (2003), these programs aim to foster customer loyalty, which has been positively received by consumers due to the associated benefits (O’Malley, 1998) The core concept of loyalty schemes is to reward repeat purchases and incentivize loyalty by establishing targets for various rewards (Gilbert, referencing O’Malley, 1998) Longer customer relationships lead to increased profitability (Reichheld and Sasser, 1990), influenced by factors such as the costs of acquiring new customers, higher purchase values, increased purchase frequency, and improved mutual understanding between customers and the organization, along with positive word-of-mouth Colgate et al (1996) noted that reducing customer defection can enhance profits more effectively than merely expanding market share, with a mere 5% increase in customer retention potentially doubling an organization's profits (Reichheld and Sasser, 1990; O’Malley, 1998).
Loyalty schemes can effectively reduce price sensitivity and enhance brand loyalty from a customer perspective They diminish the likelihood of customers considering alternative brands, promote word-of-mouth support and endorsements, attract a broader customer base, and increase overall product purchases (Uncle et al., 2003).
Customer loyalty programs are designed to create value for customers, which in turn fosters loyalty; however, the actual value perceived by customers can vary significantly due to individual differences and contextual factors To ensure the success of these programs, organizations must understand their customers' needs and desires The value delivered should be competitive across five key dimensions: cash value, aspiration value, relevance, convenience, and choice Cash value reflects the percentage of spending returned, aspiration value indicates how much the reward motivates customers, relevance pertains to the attainability of rewards, convenience measures the ease of participation, and choice refers to the variety of rewards available.
Antecedents of customer loyalty
Numerous studies highlight that customer satisfaction and quality service are crucial for fostering customer loyalty in internet and mobile phone services Factors such as perceived value, trust, corporate image, price perception, service quality, and switching costs significantly influence this loyalty (Cheng et al., 2008; Yang and Peterson, 2004; Lam et al., 2004; Aydin).
& ệzer, 2005; Kim et al., 2004; Julander and Soderlund, 2003; Nguyen and Leblanc, 2001; Jones et al., 2000; Zeithaml et al., 1996)
This study investigates the impact of four key antecedents—customer satisfaction, price perception, corporate image, and switching costs—on customer loyalty among internet service users in Ho Chi Minh City, Vietnam Due to the complexity of factors influencing customer loyalty, this research focuses specifically on these four elements to understand their effects in a targeted manner.
Some of the definitions given by scholars for customer satisfaction (CS) are as follows:
According to Anderson et al (1994), overall customer satisfaction hinges on the purchasing experience and satisfaction derived from goods or services This satisfaction involves an emotional assessment and a comparison between pre-consumption expectations and post-consumption perceived performance.
Tse and Wilton (1988) define satisfaction as the consumer's response to the assessment of the difference between their expectations and the actual performance of a product after use.
• Oliver (1997, 1999) proposes satisfaction as a fulfillment response or judgment on a product or service, which is evaluated for one-time or ongoing consumption
• Fornell (1992) suggests satisfaction as an overall evaluation based on the total purchase and consumption experience of the target product, or service performance compared with prepurchase expectations over time
• “Satisfaction is a person’s feeling of pleasure or disappointment resulting from comparing a product’s performance (outcome) in relation to his or her expectation.‟ (Kotler & Keller, 2006)
In this study we use definition of customer satisfaction from Oliver (1997,
High customer satisfaction offers numerous advantages for companies, as it is primarily shaped by the purchasing experience and the comparison between pre-consumption expectations and post-consumption perceptions (Anderson et al., 1994) Research by Reichheld and Saser (1990) indicates that enhanced customer satisfaction significantly increases the likelihood of repeat purchases Taylor and Baker (1994) found a positive correlation between service quality, customer satisfaction, and purchase intention across four service industries Furthermore, Fornell et al (1996) suggest that a customer’s satisfaction level influences their attitude post-purchase, with high satisfaction fostering repeat patronage and encouraging word-of-mouth recommendations In the internet services sector, studies consistently demonstrate that customer satisfaction is a key driver of customer loyalty (Cheng et al., 2008; Yang & Peterson, 2004; Chiou).
2003) Thus, the first research hypothesis is:
H1: There is a positive relationship between customer satisfaction and customer loyalty
Switching costs refer to the one-time expenses incurred by customers when changing from one service or product to another, encompassing not only measurable monetary costs but also the time and psychological effort associated with the uncertainty of a new provider These costs can be categorized into economic, psychological, and physical components, and include transaction costs, learning costs, and artificial switching costs Overall, switching costs involve various factors such as time, money, and emotional investment, highlighting their significance in customer decision-making.
In this study, we define switching costs as a combination of economic, psychological, and learning costs This aligns with the definition by Jones et al (2000), which describes switching costs as the consumer's perception of the time, money, and effort required to change service providers.
Switching costs for customers can be categorized into two main types: economic and psychological Economic switching costs are considered sunk costs incurred when a customer changes brands On the other hand, psychological costs arise from established social bonds, such as relationships between staff and customers, and the uncertainty associated with trying a new brand Customers often perceive significant risk when considering a brand they have not previously used, particularly in the service industry where the quality cannot be assessed prior to purchase This risk is heightened when customers contemplate switching to a rival service provider.
In the internet services industry, high switching costs lead customers to remain with their current providers, as the risks associated with changing services can deter them from making a switch.
Learning costs are a significant factor when switching suppliers, as new stock brokers must familiarize themselves with different routines and contractual rules This process of adapting to new regulations can be viewed as an essential component of switching costs.
In internet market in Hong Kong, switching cost has a significant influence on customer loyalty (Cheng et al., 2008) Therefore, we have the second hypothesis:
H2: There is a positive relationship between switching cost and customer loyalty
Corporate image is the overall impression of a firm formed in people's minds, encompassing various physical and behavioral attributes such as business name, logo, products, and company culture (Barich and Kotler, 1991; Nguyen and Leblanc, 2001) It consists of both functional components, which refer to tangible characteristics, and emotional components, which relate to customers' feelings and attitudes towards the company (Kennedy, 1977) The formation of corporate image is a cumulative process where customers draw from their past experiences and information from diverse sources, including advertising and word of mouth (MacInnis and Price, 1987; Yuille and Catchpole, 1977) Factors influencing corporate image include advertising, public relations, physical appearance, and direct customer experiences (Normann, 1991) Ultimately, a positive corporate image fosters customer loyalty, particularly in sectors such as telecommunications, retailing, and education (Nguyen and Leblanc, 2001; Johnson et al., 2001).
H3: There is a positive relationship between corporate image and customer loyalty
Price perception, as defined by Zeithaml (1988), is viewed from the consumer's standpoint, where price represents the sacrifice made to acquire a product This notion aligns with the findings of various researchers who conceptualize price as a form of sacrifice (Chapman, 1986; Mazumdar, 1986; Monroe and Krishnan, 1985) Furthermore, Jacoby and Olson (1977) differentiate between objective price, which is the actual cost of a product, and perceived price, which reflects how consumers interpret that cost (cited in Zeithaml, 1988).
To enhance customer retention and deliver superior customer value, companies should adapt their strategies, as customer value encompasses both the costs and benefits associated with remaining loyal to a brand (Slater, 1997; Gale, 1994) Research highlights the relationship between pricing factors and perceived value (Grewal, Monroe, & Krishnan, 1998), as well as the connection between price and customer loyalty (Voss, Parasuraman, & Grewal, 1998) Furthermore, marketing literature indicates that pricing influences customer price perceptions, which play a crucial role in fostering customer loyalty (Reichheld, 1996) The concept of equity emphasizes customers' assessment of fairness regarding the perceived cost of a product or service (Bolton & Lemon).
Customer perceived value is a crucial factor in driving customer retention, with limited research exploring the link between price perception and loyalty Studies indicate a direct relationship between price perception and customer loyalty, particularly in the telecommunications sector, where poor price perceptions often lead to service switching In a survey, over half of the respondents reported changing services due to unfavorable pricing, highlighting that 30% of customers across various industries switched providers due to pricing issues Thus, price significantly influences customer decisions and loyalty towards products or services A positive perception of value from a service provider encourages repeat patronage, reinforcing the connection between perceived value and customer loyalty In the context of Hong Kong's internet market, price perception notably affects customer loyalty, suggesting that similar dynamics may exist in Ho Chi Minh City due to their comparable commercial characteristics and youthful populations This leads us to propose the fourth hypothesis regarding the relationship between price perception and customer loyalty.
H4: There is a positive relationship between price perception and customer loyalty
Research model
This article proposes a research model aimed at testing and verifying the factors that influence customer loyalty among internet service users in the Ho Chi Minh City market.
H1 : There is a positive relationship between customer satisfaction and customer loyalty
H2 : There is a positive relationship between switching cost and customer loyalty
H3 : There is a positive relationship between corporate image and customer loyalty
H4 : There is a positive relationship between price perception and customer loyalty h
RESEARCH METHODOLOGY
Research design
The research was performed through two phases: (1) an exploratory study,
The exploratory study aims to identify and refine relevant items for developing a comprehensive questionnaire Additionally, it encompasses discussions on data collection methods, the analysis of the gathered data, and the measurement of the proposed model.
Quantitative and qualitative research methodologies serve as essential frameworks in research According to Bryman and Bell (2003), these methodologies represent two distinct clusters of research strategies, highlighting the importance of the relationship between theory and research, as well as epistemological and ontological considerations.
Figure 3.1 Fundamental differences between quantitative and qualitative research strategies
Fundamental differences between quantitative and qualitative research strategies
Principal orientation to the role of theory in relation to research
Epistemological orientation Natural science model, in
Onto togical Orientation Objectivism Constructionism
The research employs a quantitative method for the main survey to collect data aimed at testing the proposed hypotheses, while an exploratory study utilizes a qualitative approach.
In the exploratory study, we used first questionnaires designed mostly based on the previous studies for the in-depth interviews which were conducted with
A study involving 15 participants, including 5 full-time students from Ho Chi Minh City University of Technology, 5 individuals who are both studying and working, and 5 professionals employed in Ho Chi Minh City, was conducted to gather feedback and insights The findings confirmed the conceptual model and hypotheses, leading to adjustments in the questionnaire for clarity in translation from English to Vietnamese To ensure the revised questionnaire was comprehensible and to assess the reliability of the measurement scales, a pilot test was carried out with a sample of 20 individuals, comprising 5 full-time students, 5 studying and working participants, and 10 working professionals in Ho Chi Minh City.
In Ho Chi Minh, hard copies of questionnaires were distributed to gather responses from participants A key question asked whether respondents had the ability to choose or change their Internet Service Provider (ISP), serving as a filter for data collection Only those who answered "yes" to this question were included in the data analysis.
A comprehensive survey was carried out in Ho Chi Minh City using convenient sampling methods The final questionnaires targeted both part-time and full-time students from local universities, including Ho Chi Minh City University of Social Sciences and Humanities, Ho Chi Minh City University of Technology, and Banking University of Ho Chi Minh City, as well as working professionals in the area.
An adequate sample size is essential for achieving both accuracy and precision, ensuring that systematic bias and acceptable sampling error are minimized (Donald & Pamela, 2003) Hair et al (1998) emphasized the necessity of collecting a minimum of five samples to accurately observe variance in Factor Analysis Furthermore, in Multiple Linear Regression Analysis, it is crucial to adhere to specific formulas to determine an appropriate sample size (Tabachnick & Fidell, 1996).
M: the number of independent variable of model
Therefore to meet the sampling size requirement, we should have valid data from at least 194 respondents
Many scholars, including Saunders et al (2000) and Cooper and Schindler (2006), emphasize that survey strategies primarily utilize self-administered or interviewer-administered structured or unstructured interviews, as well as questionnaires or a combination of both They agree that questionnaires are suitable for both descriptive and explanatory studies, provided they are well-designed with clear, relevant, and non-offensive questions, logically arranged items, and the ability to encourage respondents' willingness to answer Consequently, a questionnaire was employed for this study.
This study utilized a self-administered, structured questionnaire to gather data from respondents (see Appendix 1) The questionnaire was developed and distributed in hard copy to individuals directly and indirectly connected to the author, covering a wide age range This method facilitated rapid data collection, allowing for quick responses.
In March 2012, a total of 250 questionnaires were distributed, yielding 225 responses, of which 11 were deemed invalid This resulted in 214 valid responses, achieving a response rate of 85.6%, which is considered satisfactory for further analysis Additionally, this number exceeded the minimum required sample size of 194, ensuring robust data for the study.
The research process was demonstrated in figure 3.2 as below: h
Measurement
The study analyzed five key constructs: Customer Loyalty, Customer Satisfaction, Switching Cost, Corporate Image, and Price Perception, utilizing slightly modified scales derived from previous reliable research Each variable in the hypotheses was evaluated using multi-item scales based on a five-point Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree) as detailed in Appendix 1.
Customer satisfaction was assessed using a modified version of the scale proposed by Julander and Sửderlund (2003) The initial three items aimed to gauge overall satisfaction, while an additional fourth question was included to determine respondents' confidence in their decision regarding their Internet service providers, reflecting insights gathered from in-depth interviews.
Table 3.1: Scale of Customer Satisfaction
I am satisfied with the ISP CS1
The ISP meets all the requirements that I see reasonable CS2
The ISP satisfies my need CS3
I believe that I did the right thing when I chose this ISP CS4
ISP shorted for Internet Service Provider
Switching costs comprise five key variables derived from research by Jones, Mothersbaugh, and Beatty (2000) and Julander and Sửderlund (2003) These variables include search cost, transaction cost, learning cost, hassle to change, and the time and effort involved, all of which serve as indirect measures of switching costs The exception is the perception of being "locked to" a supplier, which directly assesses the feeling of being unable to change suppliers.
Table 3.2: Scale of Switching Cost
It takes me a great deal of time and effort to search for and SC1 h to get used to a new ISP
It costs me too much to switch to another ISP SC2
In general it would be a hassle switching to another ISP SC3
The Corporate Image factor was assessed using Nguyen and LeBlanc’s measurement scale (2001), focusing on key aspects such as creating a positive impression, establishing a favorable image in customers' minds, and maintaining a superior image compared to competitors.
Table 3.3: Scale of Corporate Image
I have always had a good impression of my ISP CI1
In my opinion, my ISP has a good image in the minds of customers
I believe that my ISP has a better image than its competitors
Price perception was assessed using the framework established by Cheng et al (2008), incorporating a question about the "reasonableness of price" from Ranaweera and Neely's (2003) research Additionally, it included a query regarding the relative pricing position of a service provider based on Varki and Colgate's (2001) findings This study enhanced the measurement scale's reliability by introducing an additional question focused on pricing strategies aimed at retaining customers.
ISP by cheaper price comparing with other ISPs The scales and their meaning in terms of translation were finalized after the pilot test
Table 3.4: Scale of Price Perception
The prices charged by my ISP are reasonable PP1
My ISP’s services are value-for-money PP2
I f the price is cheaper, that is an important reason to stay with the service
Customer loyalty was assessed using five key indicators developed by Zeithaml et al (1996) These indicators include: (1) the preference for the ISP as the primary choice for purchasing services, (2) the intention to engage in more business with the ISP within the next twelve months, (3) the likelihood of speaking positively about the ISP, (4) the willingness to recommend the ISP to others seeking advice, and (5) the encouragement of friends and family to utilize the ISP's services Notably, we modified the timeframe in the second indicator from "next few years" to "next twelve months" based on feedback from respondents during in-depth interviews, allowing for a more precise and actionable timeframe for their plans.
Table 3.5: Scale of Customer Loyalty
I consider the ISP as my first choice for internet service CL1 h
I will patronize the ISP more in the next 12 months CL2
I have said positive things about the ISP to other colleagues CL3
I have recommended the ISP to colleagues who seek my advice
I have encouraged others to patronize the ISP CL5
Data analysis method
The measurement models were validated using Cronbach alpha Reliablity Analysis and exploratory factor analysis (EFA)
Standard multiple regression by SPSS software was adopted to test the conceptual model and hypotheses.
Summary
This chapter outlines the research methods, data collection processes, and proposed analysis and measurement scales for the dissertation By utilizing questionnaires and in-depth interviews with part-time and full-time students, as well as working individuals in Ho Chi Minh City, both qualitative and quantitative primary data were gathered The effective combination of qualitative and quantitative analysis facilitated the handling of this collected data for subsequent research results.
DATA ANALYSIS AND RESULTS
Descriptive data analysis
A total of 250 questionnaires were distributed, yielding 225 responses from participants After excluding 11 invalid responses, we were left with 214 valid questionnaires, resulting in an impressive response rate of 85.6%.
The rest of 214 respondents were analyzed, and the characteristics of the survey sample were presented as below
The frequency analysis revealed that male respondents slightly outnumbered female respondents, with males comprising 54.7% of the total and females making up 45.3%.
According to the survey statistics, VNPT emerged as the leading Internet Service Provider (ISP) with a significant market share of 46.3% Following VNPT, Viettel and FPT accounted for 34.1% and 15.9% of the sample usage, respectively.
Other using ISP names as SCTV and SPT made up total 3.7% of the research sample collectively.
Testing factors of research model
The research model outlined in chapter 3 encompasses four key concepts measured by independent variables: Customer Satisfaction, Switching Cost, Corporate Image, and Price Perception These components were assessed using Cronbach Alpha reliability coefficients and Exploratory Factor Analysis to ensure robust evaluation.
We utilize Cronbach Alpha to assess the reliability of each observed variable Upon evaluation, all observed variables with a Cronbach Alpha exceeding 0.6 meet the reliability criteria and are subsequently analyzed using Exploratory Factor Analysis (EFA).
According to Nunnally & Burnstein (1994), the observed variables which were item – total correlation coeffiency over 0.3 and the Cronbach alpha over 0.6 would be accepted
Table 4.2 Cronbach Alpha of observed variables
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
After checking, we found all observed variables met the study’s criteria Thus, all observed variables would be continuously analyzed in EFA h
We followed the following criteria for exploring factor analysis:
• KMO (Kaiser – Meyer – Olkin) coefficient should be more than 0.5, significant rate of Bartlett should be less than 0.05
• Factor loading coefficient should be equal or more than 0.5 If any observed variable has factor loading coefficient less than 0.5, it should be eliminated
• Total variance explained criterion have to be more than 0.5 (>50%)
• Eigenvalue index have to be equal or more than 1 following Kaiser’s standard (Gerbing & Anderson, 1988)
• Differentiation of factor loading of a observed variable with factors should be more than 0.3 (Jabnoun & Al – Tamimi, 2003)
Principal components analysis with varimax rotated method was used together with the above mentioned criteria in this study
4.2.2.1 EFA results of independent variables
ALL 13 items of four independent variables were run through EFA with Principal Component Analysis and Varimax rotation method The analysis results indicated that there were four factors being created Result of total Variance Explained index was 62.999% It meant that these created four factors could explain 62.999% of the varying data Moreover, KMO coefficient also got the research criteria with 0.763 (>0.5), and the factor loading of the observed variables were meet the research requirement (>0.5) (Appendix 2) h
Therefore, the four factors would be continuously analyzed in Regression Analysis
Table 4.3: EFA for independent variables
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 5 iterations
◘ Factor 1 consisted of PP1, PP2, PP3 that was named Price Perception, and it was abbreviated to PP
◘ Factor 2 comprised SC1, SC2, SC3, which was named Switching Cost, and it was SC for short
◘ Factor 3 comprises CS1, CS2, CS3, CS4 which was named Customer Satisfaction, and it was abbreviated to CS h
◘ Factor 4 included CI1, CI2, CI3 that was named Corporate Image, and it was abbreviated to CI for short
4.2.2.2 EFA results of dependent variable
The assessment of the Customer Loyalty variable involved Exploratory Factor Analysis (EFA) using Principal Component Analysis and the Varimax rotation method The findings revealed a single extracted factor, accounting for a total variance explained of 69.107%, with a KMO index of 0.842 (see Appendix 3).
Dependent variable was included CL1, CL2, CL3, CL4, CL5 which was named Customer Loyalty, and it was abbreviated CL for short
Hypotheses testing
4.3.1 Testing Assumptions of Multiple Regression
All the assumptions of multiple regression were tested to make sure that the data did not make any violation
The sample size applied for the research was 214 which met required minimum sample size according to Tabachnick and Fidell (1996) as mentioned in part 3.1.3.1 above
The analysis in Table 4.3 (refer to Appendix 4) indicates significant correlations between Customer Satisfaction, Switching Cost, Corporate Image, and Price Perception with Customer Loyalty, with respective correlation coefficients of 338, 192, 253, and 289 Additionally, the low correlation among the independent variables (all values < 0.4) suggests that multicollinearity is not an issue.
Normality, Linearity, Homoscedasticity, Independence of Residuals
The shape of the histogram of Customer Loyalty as the dependent variable in Figure 4.4 (See Appendix 5) showed a normal distribution
This was also reflected in the normal probability plot that most points lied in a straight diagonal line from bottom left to top right
In the scatterplot of the standardized residuals, the residuals were distributed with most of the scores concentrated around +/- 2
Results from the testing indicated that no assumption was violated
4.3.2 Testing hypotheses between Independent Variables and Customer Loyalty
After refining the scales and testing all assumptions, a multiple regression analysis was conducted using SPSS software to examine the relationship between independent factors such as Customer Satisfaction, Switching Cost, Corporate Image, and Price Perception, and their impact on the dependent factor of Customer Loyalty.
The MRL analysis revealed an adjusted R square of 0.511, indicating that the regression model explained 51.1% of the variance in customer loyalty Additionally, the ANOVA results showed an F value of 56.561 with a significance level of 0.000, leading to the rejection of the null hypotheses and confirming that the model fits 95% of the data Consequently, all four hypotheses were accepted, as detailed in the attached MLR (Appendix 6).
H1 : There is a positive relationship between customer satisfaction and customer loyalty
H2 : There is a positive relationship between switching cost and customer loyalty h
H3 : There is a positive relationship between corporate image and customer loyalty
H4 : There is a positive relationship between price perception and customer loyalty
Table 4.4: Multiple regression between independent variables and dependent variable
Std Error of the Estimate
1 721 a 520 511 50170 a Predictors: (Constant), SC, CI, CS, PP b Dependent Variable: CL
Table 4.5: Anova between independent variables and dependent variable
Model Sum of Squares df Mean Square F Sig
Total 109.550 213 a Predictors: (Constant), SC, CI, CS, PP b Dependent Variable: CL
In conclusion, all hypotheses proved significant, indicating that the four factors positively influenced customer loyalty among internet users The impact of these factors on customer loyalty can be summarized by the following formula.
CL = 0.338CS + 0.289PP + 0.253CI + 0.192SC (Table 4.6) h
Table 4.6: Coefficients between independent variables and dependent variable
B Std Error Beta Tolerance VIF
The standardized coefficients for Customer Satisfaction (0.338), Price Perception (0.289), Corporate Image (0.253), and Switching Cost (0.192) serve as a foundation for assessing their impact on Customer Loyalty A higher coefficient indicates a greater influence on Customer Loyalty, highlighting the significance of these independent factors.
Customer Satisfaction is the most significant factor influencing Customer Loyalty, as highlighted in the literature review, emphasizing its crucial role in fostering lasting customer relationships.
The study revealed a positive relationship among Customer Satisfaction, Switching Cost, Corporate Image, Price Perception, and Customer Loyalty, indicating that these factors collectively contribute significantly to fostering Customer Loyalty Therefore, it is crucial for managers to consider all these elements rather than concentrating on just one or two.
The study revealed a strong relationship between Customer Satisfaction and Customer Loyalty, consistent with Cheng et al (2008) and Chiou (2003) in their respective markets Notably, the Beta of the standardized coefficient for Customer Satisfaction was the highest among all factors analyzed Additionally, the findings indicated a significant correlation between Price Perception and Customer Loyalty, aligning with Chiou’s (2003) research, but showing a stronger effect compared to Cheng et al (2008), likely due to market differences Furthermore, the influence of Price Perception and Corporate Image on Customer Loyalty was pronounced Although the relationship between Switching Cost and Customer Loyalty matched Cheng et al.'s (2008) findings, the Beta for Switching Cost was relatively low (0.192) due to the low switching costs associated with internet services in Ho Chi Minh City, where promotional programs often eliminate setup fees Lastly, the correlation between Corporate Image and Customer Loyalty supported the conclusions of Nguyen and LeBlanc (2001).
Testing the relationship among qualitative factors and quantitative
4.4.1 Testing the relationship between gender and Customer Loyalty
We applied Independent t-test to test the relationship between gender and SEV factor, with two values of gender (1: female, 2: male) The results were showed in table 4.7 as below h
Table 4.7 - Independent samples t-test results of gender factor and CL
Test for Equality of Variances t-test for Equality of Means
95% Confidence Interval of the Difference
Recent studies indicate that there is no significant difference in customer loyalty between males and females This trend reflects the modern landscape, where the distinctions between genders are diminishing, particularly in areas such as internet usage and the demand for internet services.
4.4.2 Testing the different influence levels of career on Customer Loyalty
A study on customer loyalty revealed significant differences among various career groups, with a p-value of 0.000 indicating statistical significance at the 95% confidence level The analysis highlighted a clear distinction between the loyalty of working individuals and those who are studying, with the former exhibiting the highest levels of loyalty towards their Internet Service Providers (ISPs) This suggests that busy professionals are less inclined to switch ISPs, likely due to time constraints and a lack of motivation to seek alternatives unless they experience significant dissatisfaction In Ho Chi Minh City, working individuals demonstrated greater loyalty compared to their studying counterparts, emphasizing the impact of career demands on customer loyalty in the internet market.
Table 4.8 The analysis results of the different influence levels of career factor on Customer Loyalty
Upper Bound h studying 63 3.0349 71078 08955 2.8559 3.2139 1.80 5.00 working 78 3.4590 58829 06661 3.3263 3.5916 1.20 5.00 studying and working 73 3.4630 77737 09098 3.2816 3.6444 1.60 5.00
Squares df Mean Square F Sig
LSD studying working -.42405 * 11747 000 -.6556 -.1925 studying and working -.42809 * 11926 000 -.6632 -.1930 working studying 42405 * 11747 000 1925 6556 studying and working -.00404 11294 972 -.2267 2186 studying and working studying 42809 * 11926 000 1930 6632 working 00404 11294 972 -.2186 2267 h
Tamhan e studying working -.42405 * 11161 001 -.6943 -.1538 studying and working -.42809 * 12766 003 -.7368 -.1194 working studying 42405 * 11161 001 1538 6943 studying and working -.00404 11276 1.000 -.2767 2686 studying and working studying 42809 * 12766 003 1194 7368 working 00404 11276 1.000 -.2686 2767
* The mean difference is significant at the 0.05 level.
Customer’s evaluation on Customer Loyalty following using ISP
Table 4.9 - Mean of each using ISP on Customer Loyalty
Used ISP name Mean of Customer Loyalty
The study revealed that FPT emerged as the ISP with the highest customer loyalty, while VNPT recorded the lowest SCTV and SPT were excluded from the analysis due to their minimal user base Overall, FPT customers expressed greater satisfaction compared to other ISPs However, the differences in customer loyalty among the examined ISPs—FPT, VNPT, and Viettel—were relatively minor These findings provide managers with valuable insights into customer loyalty within the Ho Chi Minh market, enabling them to better understand their competitive positioning and develop effective strategies.
Figure 4.5 Mean of each used ISP name on Customer Loyalty
Summary
This chapter presents the survey findings derived from questionnaires and interviews, addressing the research questions and hypotheses outlined in Chapter 2 Initially, the analysis results of the scales and models are discussed, followed by an examination of the relationship between qualitative and quantitative variables Notably, some unexpected results emerged, providing an objective overview of a small sample of internet users in the Ho Chi Minh City market.
Mean of CL following each ISP name
CONCLUSIONS
Conclusion
The primary purpose of this research is to find out the relationship between each of independent factors (customer satisfaction, switching cost, corporate image and price perception) and customer loyalty
This study utilized the model established by Cheng et al (2008) alongside measurement scales from various researchers, including Julander & Sửderlund (2003), Jones et al (2000), Nguyen & LeBlanc (2001), Zeithaml et al (1996), and Lam et al (2004) Through data collection and theoretical analysis, we demonstrated that the proposed model is applicable to the internet market in Ho Chi Minh City As a result, we confirmed several key findings.
Customer satisfaction is still the key direct antecedent to customer loyalty
Price perception significantly influences customer loyalty, making it a crucial factor for businesses Additionally, a positive corporate image and high switching costs further enhance customer loyalty, as demonstrated in this thesis.
We also find the different level of Customer Loyalty among different three career groups The studying group has less loyalty level than the working /working and studying people group.
Managerial Implication
From the findings of the thesis, the following points can be taken note by managers:
Customer satisfaction is essential for increasing market share and fostering customer loyalty among internet service providers in Ho Chi Minh City To retain customers, these providers must implement effective strategies that ensure a satisfactory experience In a competitive landscape, retaining existing customers often proves more beneficial than acquiring new ones, as profits from loyal customers tend to grow stronger over time Ultimately, customer loyalty serves as a key driver of long-term profitability in both B2B and B2C relationships, underscoring its importance in the internet market.
In today's competitive market, businesses face significant challenges in maintaining market share due to globalization and technological advancements, which provide consumers with more choices and reduce brand loyalty Consequently, customer perceived value has become essential for competitiveness Focusing solely on price can harm profits and is a short-sighted strategy, as price is the most easily adjustable element of the marketing mix Therefore, it is crucial for Internet Service Providers (ISPs) to regularly assess consumers' perceived value of their services to ensure that their pricing remains reasonable and acceptable.
A strong corporate image is crucial for fostering customer loyalty, as supported by Nguyen & LeBlanc’s 2001 research Consequently, service firms, particularly internet service providers, should prioritize substantial investments in enhancing their corporate images to effectively retain their customer base.
Switching costs have a positive but weak correlation with customer loyalty, suggesting that while they can be a backup strategy for retaining customers, they are not a standalone solution In Vietnam's internet market, where switching costs are generally low, service providers must implement a balanced strategy This involves reducing costs to attract new customers through promotional programs while simultaneously increasing costs to retain existing subscribers If switching costs are excessively high, providers may retain customers but struggle to foster true loyalty, as overall satisfaction could decline.
Customer loyalty varies significantly across three career groups: students, working individuals, and those who balance both work and study Research indicates that students exhibit lower loyalty levels compared to their working counterparts and those who juggle both responsibilities Understanding these differences enables managers to develop targeted strategies to effectively retain customers within each career group.
Implication for theory and future research
ISPs are increasingly focusing on competitive loyalty programs to enhance customer retention, with customer satisfaction being a crucial factor in fostering loyalty By segmenting customers into subgroups, managers can better understand the specific drivers of loyalty within each group, enabling the design of targeted retention strategies While customer satisfaction is essential for attracting business, evaluating service quality is equally important for its impact on loyalty Future research could benefit from directly asking customers whether they remain with a provider out of necessity or preference, which would shed light on the influence of switching costs on loyalty.
The study utilized a convenience sampling method, a form of non-random sampling, involving respondents aged 18 to 25 living in Ho Chi Minh City, who have direct or indirect relationships with the researcher Although the sample size of 214 valid respondents was adequate, the convenience sampling method limited the representation of the target population, specifically internet service users in Vietnam Future research should consider employing a random sampling technique, supported by additional time, manpower, and financial resources, to enhance the model's validity.
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Questionnaire in Vietnamese
BẢNG KHẢO SÁT LÒNG TRUNG THÀNH CỦA KHÁCH HÀNG
SỬ DỤNG DỊCH VỤ INTERNET PHẦN I:
Anh/chị vui lòng cho biết một số thông tin cá nhân sau bằng cách đánh dấu
Bạn có sử dụng internet tại nhà không? Bạn có quyền quyết định thay đổi hoặc lựa chọn nhà cung cấp dịch vụ internet mà bạn đang sử dụng hay không?
Nếu bạn trả lời câu hỏi số 1 là “Có”, xin vui lòng tiếp tục trả lời các câu hỏi dưới đây Nếu câu trả lời là “Không”, xin vui lòng dừng lại và cảm ơn sự hợp tác của bạn.
1 Phổ thông trung học cao đẳng
5) Anh/chị đang sử dụng dịch vụ internet của nhà cung cấp nào tại nhà các Anh/Chị?
Dưới đây là một số nhận định về dịch vụ internet từ nhà cung cấp mà bạn đang sử dụng Xin vui lòng đánh giá mức độ phù hợp cho từng nhận định theo thang điểm từ 1 đến 5.
Rất không đồng ý Không đồng ý Bình thường Đồng ý Rất đồng ý
Câu nhận định Mức độ đánh giá
Rất không đồng ý Không đồng ý Bình th ường Đồng ý đồng ý Rất
1 Theo Anh/Chị, dịch vụ internet của nhà cung cấp hiện tại đáng giá đồng tiền 1 2 3 4 5
2 Theo Anh/Chị, chi phí trả cho dịch vụ internet của nhà cung cấp hiện tại thì hợp lí
3 Nếu giá rẻ hơn , đó là một lý do quan trọng để Anh/Chị tiếp tục sử dụng dịch vụ internet của nhà cung cấp hiện tại
Sự thỏa mãn khách hàng
4 Anh/Chị hài lòng với nhà cung cấp dịch vụ internet hiện tại 1 2 3 4 5
5 Nhà cung cấp dịch vụ internet hiện tại đáp ứng tất cả các đòi hỏi thiết yếu của
6 Nhà cung cấp dịch vụ internet hiện tại làm Anh/Chị thỏa mãn 1 2 3 4 5
7 Anh/Chị tin rằng Anh/Chị đã quyết định đúng khi chọn nhà cung cấp dịch vụ h internet hiện tại
8 Theo Anh/Chị, nhà cung cấp hiện tại luôn luôn có ấn tượng tốt
9 Theo ý Anh/Chị, nhà cung cấp có hình ảnh tốt trong tâm trí của khách hàng 1 2 3 4 5
10 Anh/Chị tin rằng nhà cung cấp hiện tại có hình ảnh tốt hơn so với các đối thủ cạnh tranh khác
11 Anh/Chị sẽ cảm thấy rất tốn kém nếu chuyển sang nhà cung cấp dịch vụ internet khác
12 Anh/Chị cảm thấy rắc rối khi chuyển sang nhà cung cấp dịchvụ internet khác 1 2 3 4 5
13 Tôi cảm thấy bị ràng buộc với nhà cung cấp hiện tại 1 2 3 4 5
Lòng trung thành khách hàng
14 Khi muốn chọn lựa nhà cung cấp dịch vụ internet thì Anh/Chị chọn nhà cung cấp hiện tại trước nhất
15 Anh/Chị sẽ tiếp tục sử dụng dịch vụ của nhà cung cấp hiện tại trong vòng 12 tháng tới
16 Anh/Chị nói tốt về nhà cung cấp dịch vụ internet hiện tại với những người khác 1 2 3 4 5
17 Nếu có ai hỏi Anh/Chị thì Anh/Chị sẽ giới thiệu nhà cung cấp dịch vụ internet hiện tại cho họ
18 Anh/Chị khuyến khích những người khác sử dụng dịch vụ internet của nhà cung cấp hiện tại
Xin chân thành cảm ơn sự hợp tác của Anh/Chị! h
Questionnaire in English
SURVEY OF INTERNET USERS’ CUSTOMER LOYALTY PART 1:
Please answer the following questions by ticking into the MOST
1) Are you using internet service at your home, And can you make decision to change or to choose ISP?
If you answer the above question number 1 is “Yes”, pls continue to answer the next questions Otherwise, if you answer “No”, please stop and thanks for your cooperation
1 College, high school or less
5) Which ISP are you using at your home?
1 Studying at school or University
Following is your evaluation to the internet ISP which you are using at your home Please give your appropriate evaluation by giving point from 1 to 5
Disagree Neutral Agree Strongly agree
Statements Please select one option
Disagree Neutral Agree Strongly agree
1.The prices charged by my ISP are reasonable
2.My ISP’s services are value-for- money
3.I f the price is cheaper, that is an important reason to stay with the service
4 I am satisfied with the ISP 1 2 3 4 5
5 The ISP meets all the requirements that I see reasonable
6 The ISP satisfies my need 1 2 3 4 5 h
7 I believe that I did the right thing when I chose this ISP
8 I have always had a good impression of my ISP
9 In my opinion, my ISP has a good image in the minds of customers
10 I believe that my ISP has a better image than its competitors
11 It takes me a great deal of time and effort to search for and to get used to a new ISP
12 It costs me too much to switch to another ISP
13 In general it would be a hassle switching to another ISP
14 I consider the ISP as my first choice for internet service
15 I will patronize the ISP more in the next 12 months
16 I have said positive things about the ISP to other Colleagues
17 I have recommended the ISP to colleagues who seek my advice
18 I have encouraged others to patronize the ISP
Thank you for your assistance to this survey! h
Reliability results of measurement scales – Pilot test
Total 20 100.0 a Listwise deletion based on all variables in the procedure
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
EFA results of independent variables – Main survey
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
Bartlett's Test of Sphericity Approx Chi-Square
Extraction Method: Principal Component Analysis h
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 5 iterations h
Appendix 4: EFA results of dependent variable – Main survey
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .842
Bartlett's Test of Sphericity Approx Chi-Square 626.194 df 10.000
Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total
Extraction Method: Principal Component Analysis
Extraction Method: Principal Component Analysis a 1 components extracted h
Appendix 5: Testing Assumptions of Multiple Regression
Table 4.3: Correlations between CS, PP, CI, SC and CL
CS PP CI SC CL
** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed) h
Testing assumptions of multiple regression
Table 4.3: Correlations between CS, PP, CI, SC and CL
CS PP CI SC CL
** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed) h
Figure 4.4 Histogram, Normal P – P plot and Scatter plot of Dependent Variable - CL h
Normal P-P Plot of Regression Standardized Residual h h
Model Variables Entered Variables Removed Method
1 SC, CI, CS, PP a Enter a All requested variables entered b Dependent Variable: CL
Model R R Square Adjusted R Square Std Error of the Estimate
1 721 a 520 511 50170 a Predictors: (Constant), SC, CI, CS, PP b Dependent Variable: CL
Total 109.550 213 a Predictors: (Constant), SC, CI, CS, PP b Dependent Variable: CL h
Multiple Regression Line results
Model Variables Entered Variables Removed Method
1 SC, CI, CS, PP a Enter a All requested variables entered b Dependent Variable: CL
Model R R Square Adjusted R Square Std Error of the Estimate
1 721 a 520 511 50170 a Predictors: (Constant), SC, CI, CS, PP b Dependent Variable: CL
Total 109.550 213 a Predictors: (Constant), SC, CI, CS, PP b Dependent Variable: CL h