INTRODUCTION
Research background
In today's competitive landscape, retaining customers is crucial, as it can be ten times more expensive to attract new ones than to keep existing clients, with the cost of making new customers profitable potentially reaching up to 16 times that of lost customers (Lindgreen et al., 2000) Consequently, businesses are increasingly prioritizing customer retention strategies (Berry, 1983; Fornell, 1992) Research highlights that relationship quality is a vital element in these retention efforts, defined as customers' perceptions of how well their expectations and demands are met (Jarvelin & Lehtinen, 1996) Key components of relationship quality include customer satisfaction (Hendrick, 1988), trust (Rempel, Holmes & Zanna, 1985), and commitment (Adams & Jones, 1997; Lund, 1985), all of which influence customers' decisions to continue or terminate their relationships with suppliers.
However, for the purpose of keeping customer staying with business longer, the management need to consider other factors helping them to achieve that
Switching barriers play a crucial role in customer retention, as they encompass factors that make it challenging or costly for customers to change suppliers (Jones et al., 2000) Understanding the reasons behind customer dissatisfaction and their likelihood to switch is essential for companies aiming to build lasting relationships (Yanamandram & White, 2006) By identifying the key dimensions influencing customers' switching decisions, businesses can tailor their offerings to better meet customer needs, thereby enhancing retention and fostering brand loyalty To prevent customer switching and strengthen long-term relationships, suppliers are increasingly implementing strategies to ensure customer satisfaction, reinforce trust, and create exit barriers This research aims to explore the interaction between relationship quality and switching barriers in shaping customer awareness and decision-making.
In the competitive landscape of Vietnam's banking sector, which has seen a significant increase in foreign-owned financial institutions since the country joined the World Trade Organization (WTO) in 2007, foreign banks hold an advantage due to their superior organizational structures, professional services, and international networks As of now, there are 49 foreign bank branches primarily located in Ho Chi Minh City and Hanoi, compared to just five in 2007 However, local banks possess unique strengths, such as widespread branch networks, familiarity with the Vietnamese market, and support from the State Bank With the growing diversification of customer demands, both local and foreign banks must innovate and implement effective strategies to attract and retain customers, intensifying competition within the marketplace Researching these factors and their impact on customer retention is crucial for developing effective banking strategies.
1.2 Research question and research objective
The objective of this study isto identify the effect of relationship quality and switching barriers on customer retention Particularly:
- How many factors constituting relationship quality? How does each of them affect customer retention?
- How many factors constituting switching barriers? How does each of them affect customer retention?
- Which factor will influence customer retention most?
This study examines retail banking customers at local and foreign banks in Ho Chi Minh City, focusing on individuals who regularly utilize banking services It excludes respondents under 18 years old due to their limited income and inability to make independent financial decisions, which means the sample may not reflect the broader population of Vietnam The research investigates four key factors: satisfaction, trust, commitment, and switching barriers.
This thesis is organized as follows:
- Chapter 1 introduces the background view, research problems, research objectives, research question, research delimitation and thesis structure.
- Chapter 2 introduces research model and its hypotheses as well as its literature review.
- Chapter 3 illustrates the methodology conducted in this paper.
- Chapter 4 presents research results is based on data collected.
- Chapter 5 summarizes the research result, provide the findings, limitation and recommendations.
Research delimitation
This study examines retail customers of local and foreign banks in Ho Chi Minh City, focusing on individuals who regularly use banking services It excludes young people under 18 years old due to their limited income and inability to make independent financial decisions, which means the sample may not represent the entire population of Vietnam The research explores four key factors: customer satisfaction, trust, commitment, and switching barriers.
Thesis Structure
This thesis is organized as follows:
- Chapter 1 introduces the background view, research problems, research objectives, research question, research delimitation and thesis structure.
- Chapter 2 introduces research model and its hypotheses as well as its literature review.
- Chapter 3 illustrates the methodology conducted in this paper.
- Chapter 4 presents research results is based on data collected.
- Chapter 5 summarizes the research result, provide the findings, limitation and recommendations.
LITERATURE REVIEW
Theoretical review
Customer retention is a strategic effort by selling organizations aimed at minimizing customer defection, as highlighted by Jones et al (2000) This process involves fostering repetitive behaviors that ultimately lead to enhanced customer loyalty, as noted by Liu and others.
Customer retention is a crucial aspect of relationship marketing, focusing on the long-term maintenance of customer relationships (Wu, 2007; Gronroos, 1997) It serves as a key metric for measuring the continuity of these relationships and is an effective strategy for businesses seeking to gain a competitive edge in today’s challenging marketplace (Thomas, 2001; Clayton-Smith, 1996; Dawkins & Reichheld, 1996).
Customer retention is crucial for enhancing firm value, as studies indicate that retaining existing customers is often more important than acquiring new ones (Hidalgo et al., 2008) Customers have a life cycle that includes acquisition, retention, and value growth (Ang & Buttle, 2006), with successful retention starting from the initial contract and continuing throughout the relationship Long-term customers tend to spend more and can provide valuable word-of-mouth promotion when satisfied Additionally, the costs associated with customer retention are significantly lower than those for acquiring new customers, with estimates suggesting it can be five to ten times more expensive to attract new clients (Rust & Zahorik, 1993; Lindgreen, 2000) As relationships deepen, serving existing customers becomes less costly due to learning effects, which also reduces replacement costs and enhances income stability (Reichheld & Sasser, 1990; Turnbull, 1990) Therefore, developing an effective customer retention strategy is essential for managers aiming to thrive in today’s competitive market (Weinstein, 2002).
Key factors influencing a customer's choice of bank include service quality, rates, fees, and charges (Abratt & Russell, 1999) To thrive in the banking sector, it is crucial to deliver exceptional service, meet client demands, and offer innovative products However, superior service alone is not enough to ensure long-term customer loyalty; relationship quality and switching barriers also play a vital role Many commercial banks recognize the importance of fostering and maintaining strong customer relationships, understanding the benefits that relationship quality and switching barriers bring (Colgate et al.).
In light of these findings, service providers must enhance the quality of their customer relationships and implement more switching barriers to effectively retain their customers.
Over the past two decades, relationship quality has emerged as a crucial element in customer relationship management and a key indicator of successful business interactions Defined by Crosby et al (1990) as the overall assessment of relationship strength and the fulfillment of expectations based on past cooperative experiences, relationship quality encompasses a multidimensional construct that captures the essence of supplier-consumer relationships (Hennig-Thurau & Klee, 1997; Hennig-Thurau et al., 2002) It is essential for fostering long-term relationships and enhancing customer retention (Bejou et al., 1996; Crosby et al., 1990; Hennig-Thurau, 2002; Hennig-Thurau & Klee, 1997; Moliner et al., 2007) Research consistently highlights trust and satisfaction as core dimensions of relationship quality (Bejou et al., 1996; Crosby et al., 1990; Lin & Ding, 2005), with commitment also recognized as a significant factor (De Wulf et al., 2001; Hennig-Thurau, 2000; Moliner et al., 2007) Some studies even introduce additional dimensions, such as affective conflict (Roberts et al., 2003) and social bonds (Lang & Colgate, 2003).
In the retail environment, relationship quality is characterized by three key components: trust, commitment, and satisfaction These elements indicate a long-term orientation and are essential for connecting consumer markets effectively.
Customer satisfaction is defined as the extent to which a business's product or service performance aligns with customer expectations (Roberts-Lombard, 2009) When performance meets or exceeds these expectations, customers feel satisfied; conversely, if performance falls short, dissatisfaction arises According to Salami (2005), this emotional response stems from the comparison between expected service and actual performance, which is shaped by direct interactions with the products and services High-quality service and products can enhance customer loyalty, profitability, market share, and reduce turnover rates In contrast, unsatisfied customers are unlikely to maintain a positive relationship with the business (Roberts et al., 2003).
Trust is the willingness to rely on a partner, rooted in confidence and belief in their reliability (Moorman et al., 1993; Schurr and Ozanne, 1985) The strength and quality of relationships are directly proportional to the level of trust; higher trust leads to stronger bonds Loyalty and trust in relationships are obligations that should be given without expecting anything in return (Yau et al., 2000) Failing to uphold this obligation can harm one's reputation and create significant disadvantages Ultimately, a reliable partner is expected to yield positive outcomes (Morgan & Hunt, 1994).
Commitment in relationships, as highlighted by Morgan and Hunt (1994), stems from trust, shared values, and the understanding that finding equally valuable partners is challenging This commitment fosters cooperation between parties, promoting the conservation of investments in the relationship Furthermore, research by Ibrahim and Najjar indicates that the level of commitment is the most significant predictor of the voluntary decision to engage in a relationship.
In a relationship, commitment is recognized as the essential factor for fostering and sustaining a strong bond When both parties exhibit a high level of commitment, it creates an environment where they can pursue their individual and shared goals without the worry of opportunistic behavior.
Research highlights that the quality of relationships plays a crucial role in understanding customer loyalty and retention While loyalty can exist even with weak relationship ties, the chances of continued service engagement are more influenced by external factors, such as limited alternatives or significant switching barriers.
Switching barriers in the retail services industry encompass various factors such as search costs, transaction costs, learning costs, loyal customer discounts, and emotional costs (Vázquez-Carrasco & Foxall, 2006; Pass, 2006; Pont & McQuilken, 2005; Sengupta et al., 1997) These barriers are closely tied to the perceived risk customers face, which involves their apprehension regarding the uncertainty and potential negative outcomes associated with purchasing a product or service (Dowling & Staelin, 1994) Colgate and Lang (2001) categorize switching barriers into relational benefits, switching costs, availability and attractiveness of alternatives, and service recovery In subsequent research, Vázquez-Carrasco and Foxall (2006) focused on the first three types of switching barriers.
3 Availability and attractiveness of alternatives.
Consumers are inclined to build and maintain relationships with companies that offer valuable benefits, such as social, confidence, and special treatment benefits (Liu, 2006; Gwinner et al., 1998; Va´zquez-Carrasco & Foxall, 2006) The fear of losing these relational benefits often keeps dissatisfied customers from switching to competitors (Yanamandram & White, 2006) Research by Ranaweera and Prabhu (2003) suggests that service providers can retain even dissatisfied customers when they perceive high switching barriers However, over time, these unsatisfied customers may seek alternatives Therefore, businesses should implement strategies that enhance customer satisfaction while leveraging switching barriers to improve retention.
Switching costs refer to the various expenses associated with changing service providers, which can be categorized into time, monetary, and psychological factors (Jones et al., 2002; Dick & Basu, 1994; Sengupta et al., 1997) According to Panther and Farquhar (2004), customers often hesitate to switch due to the inconvenience of evaluating new options and the time required for the transition Additionally, customers face the challenge of informing business partners about the change, and in the case of switching banks, they must navigate issues such as delays in receiving new checkbooks and ATM cards, as well as cancelling existing services like internet banking and managing any outstanding loans with their previous bank.
Hypotheses Development
2.1.3.3 Availability and attractiveness of alternatives
The availability and attractiveness of alternatives significantly influence customers' perceptions of competing options in the marketplace Bendapudi and Berry (1997) suggest that customers may remain loyal to their current supplier if there are limited alternatives available, a situation often dictated by industry characteristics Furthermore, Patterson and Smith (2003) highlight that customers might overlook potential alternatives because they are not top of mind or do not appear more appealing than their existing relationships.
This section explores the model that illustrates the interplay between relationship quality, switching barriers, and customer retention It examines how key dimensions of relationship quality—specifically customer satisfaction, trust, and commitment—impact customer retention rates Additionally, it analyzes the influence of various switching barriers on retaining customers, highlighting the significance of these factors in fostering long-term loyalty.
2.2.1 Customer satisfaction and customer retention.
Customer satisfaction is defined as a pleasurable emotional state resulting from the evaluation of a service, as noted by Magesh (2010) and Cronin et al (2000) It reflects the extent to which the quality of services aligns with customer expectations.
Customer satisfaction has been long recognized in marketing theories and practices as a core concept in business activities (Anderson & Weitz, 1992; Fornell,
1992) Marketers treat customer satisfaction as an important determinant of positive word of mouth, consumer loyalty and repeat purchase intention (Kotler, Armstrong
Recent studies highlight the critical role of customer satisfaction in retaining clients, positioning it as a cornerstone of relational marketing strategies A strong correlation exists between customer satisfaction and retention; the more satisfied customers are, the more likely they are to continue using a service, which is vital for fostering long-term business relationships Enhanced service quality directly contributes to increased customer satisfaction, which in turn strengthens customer relationships As relationships deepen, satisfaction becomes increasingly important in differentiating a business from its competitors Conversely, customers who are dissatisfied with the services provided are unlikely to maintain a positive relationship with the company or remain loyal over time.
& Lindestad, 1998; Garbarino & Johnson, 1999; Guenzi & Pelloni, 2004; Lam et al.,
Customer satisfaction should be viewed as a cumulative factor, reflecting a consumer's overall experience with a retailer rather than isolated evaluations at specific moments This perspective emphasizes that satisfaction is influenced by the retailer's past performance, making it a "backward-looking" measure that encompasses all prior interactions up to the present (Gustafsson et al., 2005).
Customer satisfaction in retail, as defined by Addition, Levy, and Weitz (2009) and Storbacka et al (1994), is the evaluation of how well a retailer meets or exceeds customer expectations through its products and services In today's competitive market, banks must differentiate themselves by providing high-quality offerings to enhance customer satisfaction, which is crucial for fostering long-term relationships Satisfied customers can also serve as effective marketers by sharing positive experiences, thereby attracting new clients Recognizing the significance of customer satisfaction for retention is essential for major economies worldwide to accurately predict customer behavior and future financial performance (Fornell, 1992).
H1 There is a positive impact of customer satisfaction on customer retention
Building on Morgan and Hunt's (1994) research, we view relationships as a series of transactions that enhance awareness of strong connections through trust and commitment Increased trust is directly linked to a higher likelihood of customer retention.
Recent studies indicate that customer satisfaction alone is insufficient to prevent customers from switching service providers, even when they are satisfied To foster long-term loyalty, it is essential to focus on factors like trust, which must be continually built and renewed In a retail context, trust reflects a consumer's confidence in a retailer's reliability and integrity Trust is defined as the expectation of positive outcomes based on anticipated actions, and it involves the belief that one party will behave predictably in specific situations Ultimately, trust is cultivated through positive customer experiences, encouraging them to maintain their relationships with businesses.
Marketing literature identifies two types of trust: credibility and benevolence Trust in a retailer's credibility involves customers believing in the retailer's expertise and reliability, while benevolence refers to customers' perceptions of how much the retailer cares for their welfare In the financial services sector, trust is considered a fundamental customer need, encompassing the belief that banks will manage funds responsibly, offer competitive rates, and conduct transactions accurately and promptly If banks fail to meet these expectations, they risk damaging their reputation, leading to customer attrition and loss of market share Consequently, building and maintaining customer trust and loyalty is essential for commerce-based businesses, as it significantly impacts sales growth through customer acquisition and retention.
H2.There is a positive impact of trust on customer retention.
Commitment is essential for the success of long-term relationships, encompassing both parties' intentions and behaviors (Anderson & Weitz, 1992; Farelly & Quester, 2005) It is a multidimensional construct that includes emotional, calculative, and normative commitment Emotional commitment reflects a customer's desire to engage with a business they resonate with, often stemming from a strong identification and affinity for the firm (Allen & Meyer, 1990; Fullerton, 2005) This attachment signifies a voluntary choice to maintain the relationship In contrast, calculative commitment is driven by the perceived necessity of sustaining the relationship due to the potential loss of benefits if it were to end (Allen & Meyer, 1990; Geyskens et al.).
In the realm of customer relationships, commitment can be categorized into three types: calculative, emotional, and normative Calculative commitment is characterized by a rational, economic-based dependence, while emotional commitment stems from the level of reciprocity and personal involvement a customer feels towards a company Additionally, normative commitment represents a moral obligation to maintain the relationship Understanding these dimensions of commitment is essential for businesses aiming to foster lasting customer loyalty.
Emotional, calculative, and normative commitments differ in their motivations for customer retention, with emotional commitment driven by a desire to stay, normative commitment rooted in moral obligations, and calculative commitment based on economic considerations Research indicates that emotional and normative commitments positively influence customer behavior and retention, while calculative commitment may negatively impact behavior due to its focus on rational trade-offs Nonetheless, calculative commitment can still enhance retention by creating barriers to changing suppliers In the banking sector, customers exhibit diverse attitudes, choosing to maintain relationships based on the type of commitment that they perceive as most beneficial, which may vary over time depending on their circumstances.
Emotional commitment significantly enhances customer retention, fostering a strong connection between the brand and its customers Similarly, calculative commitment also plays a crucial role in retaining customers, as it encourages individuals to weigh the benefits of staying loyal to the brand Additionally, normative commitment contributes positively to customer retention by instilling a sense of obligation and loyalty, ensuring that customers remain engaged and invested in the brand.
2.2.4 Switching barriers and customer retention.
Switching barriers are factors that complicate or increase the cost for consumers when changing providers, reflecting their assessment of the resources and opportunities required for such a transition (Bansal & Taylor, 1999) Keaveney (1995) identified these barriers as crucial in influencing customer switching behavior Building on this, Gremler and Brown (1996) conducted in-depth interviews to create a model highlighting switching costs as essential for customer loyalty and retention They defined switching costs as the time, money, and effort perceived by customers to make switching more challenging, citing examples such as habit, inertia, set-up, search, learning, contractual, and continuity costs.
Switching barriers in the banking industry include search cost, transaction costs, learning cost, loyal customer discounts and emotion costs (Vazques-Carrasco
Switching barriers can have both positive and negative implications, as noted by Julander and Soderberg (2003) According to Hirschman (1970), the positive side of these barriers relates to the desire to maintain a relationship, while the negative side pertains to the feeling of being compelled to stay in a relationship.
Research Model
Availability and attractive of alternativesH8-
H1 There is a positive impact of customer satisfaction on customer retention.
H2 There is a positive impact of trust on customer retention.
H3 There is a positive impact of emotional commitment on customer retention.
H4 There is a positive impact of calculative commitment on customer retention.
H5 There is a positive impact of normative commitment on customer retention. H6 There is a positive impact of relational benefits on customer retention.
H7 There is a positive impact of switching cost on customer retention.
H8 There is a negative impact of availability and attractiveness of alternatives on customer retention.
METHODOLOGY
Research design
This study employs a quantitative research method to investigate eight key factors influencing customer retention The research follows a structured procedure, as illustrated in the accompanying figure.
Measurement scales
The scales for nine constructs in the model were developed based on prior research, tailored specifically to the context of the banking industry in Vietnam Utilizing multiple item scales, a five-point Likert type format was employed for measurement.
Scales for customer satisfaction, trust, emotional commitment, calculative commitment, normative commitment were adapted from previous research of Cronin et al (2000), Coote, Forest and Tam (2003), Ball, Celho and Machas (2004),
In the study conducted by Gustafsson et al (2005), Kelly (2004), and Allen and Meyer (1990), various scales related to relational benefits, switching costs, availability, and attractiveness of alternatives were adapted from existing literature on switching barriers (Burnham et al., 2003; Jones et al., 2000; Goitom and Nancy, 2011) Retention is defined as a customer's future propensity to remain with a service provider, measured using a three-item formative scale based on Morgan and Hunt's (1994) "propensity to leave" framework This scale assesses the likelihood of respondents leaving their banks over three timeframes: six months, one year, and two years The overall retention score is calculated as the sum of these weighted items, with the first item receiving the highest weight, followed by the second, while the third is unweighted, resulting in a scoring ratio of 2.5:1.5:1 on a scale from 1 to 5.
The participants were asked to respond to survey questions by using five point Likert scale ranging from 1 to 5:
Table 3.1: Summary of scales for 9 constructs in the model.
Cus1 1 Overall, I am happy with my bank
Cus2 2 My bank meets my expectations.
Cus3 3 I think I did the right thing when I joined this bank
Trt4 1 I have great confidence in my banking services Items 1, 2 are adapted from Coote, Forest and Tam
(2003) Items 3,4 are adapted from Ball, Celho and Machas (2004)
Trt5 2 Promises made by my bank are reliable.
Trt6 3 My bank is capable in providing banking service to me.
Trt7 4 My bank treats me in an honest way in every transaction.
Emc8 1 I take pleasure in being a customer of bank X
Emc9 2 Bank X is the operator that takes the best care of their customers.
Emc10 3 There is a presence of reciprocity in my relationship with bank X.
Emc11 4 I have feelings of trust toward bank X
Cam12 1 It would be too costly for me to leave
Cam13 2 One of the major reasons I continue to bank with Bank is that leaving would require considerable personal sacrifice.
Cam14 3 I stay with Bank because the costs of changing exceed the benefits.
Noc15 1 Our attachment to bank X is mainly based on the similarity of our values Items 1,2,3 are adapted from Kelly (2004), whist item 4,5 are adapted from
Noc16 2 The reason I refer bank X to others is because of what it stands for, its value.
Noc17 3 What bank X stands for is important to us.
Noc18 4 I do feel an obligation to remain with bank.
Allen and Meyer (1994) Noc19 5 I owe a great deal to bank
Reb20 1 Staying allows me to get discounts and special deals Burnham,
Reb21 2 Staying saves me money.
Reb22 3 Staying allows me to get extra service benefits.
Swc23 1 In general it would be a hassle changing banks
Swc24 2 It would take a lot of time and effort changing banks.
Swc25 3.For me, the costs in time, money, and effort to switching banks are high Swc26 4 If I switch to another bank, I am concerned about negative financial outcomes.
Availability and attractiveness of alternatives
Aaa28 1 All banks are the same.
Aaa27 2 I am not sure if other banks offer better services.
Aaa29 3 Other banks do not offer better services.
Aaa30 4 I know other banks offer better services but I prefer to stay with my present main bank
How likely is that you continue your relationship with bank?
Ret31 1 Within the next six months?
Ret32 2 Within the next one year?
Ret33 3 Within the next two years?
Method of data collection
In Ho Chi Minh City, a convenience sampling approach was utilized due to time constraints, employing a self-administered survey that included 9 factors and 33 variables According to Hair et al (1995), the minimum sample size for reliable statistical analysis should be at least five times the number of independent variables, with a minimum of 100 observations Consequently, the required sample size was calculated to be n3*55 observations.
To achieve a sample size of 165, 350 questionnaires were distributed to participants aged between 18 and 60 years This age group typically has the financial means and demand for banking services, making them ideal respondents The participants come from diverse career backgrounds and possess sufficient income to engage in regular banking transactions.
All the respondents selected usually have transactions with commercial banks, or foreign banks or both.
A qualitative study was conducted to gather insights from customers of commercial banks in Ho Chi Minh City The findings served as valuable input for the development of a final questionnaire aimed at enhancing customer understanding.
• Draft questionnaire: using the outcomes of qualitative study, the measures and measurements scale of the conceptual model were decided and the questionnaire was formed.
A pilot survey is essential for testing a questionnaire on a small sample of respondents, typically ranging from 10 to 30 participants, as noted by Malhotra (2004) This preliminary study aims to identify potential issues, enhance reliability, and ensure the suitability of data collection tools In this research, a pilot study was conducted by distributing the questionnaire to 10 randomly selected interviewees through face-to-face interviews The questions focused on customer satisfaction, exploring factors that contribute to satisfaction or dissatisfaction with banking services, trust in current providers, and awareness of service barriers The insights gained from this pilot survey were instrumental in refining the questionnaire design.
After pilot study, some confused questions were refined cause of the equivocal Vietnamese meaning.
• Data collection process: 350 questionnaires were delivered via email, colleagues, and sent directly to customers who come to bank.
Data analysis method
We use descriptive and inferential statistics (Cronbach‟s Alpha, EFA, Correlation, Multiple regression analysis) with SPSS software package The analysis process is carried out as follow:
3.4.1 Assessment of measurement of scale.
To ensure the reliability and validity of the developed multi-item scales, it is essential to evaluate them using Cronbach's Alpha, a widely recognized method for testing reliability A high Cronbach's Alpha indicates strong correlation among the scale items Consequently, items with a Cronbach's Alpha of 0.60 or lower and item-to-total correlation coefficients of 0.4 or less were removed from the scale.
The current study employs exploratory factor analysis (EFA) using SPSS 16.5 as the primary assessment method EFA utilizes two key extraction techniques: common factor analysis and principal components factor analysis While principal components analysis focuses on item reduction and ensuring test unidimensionality, common factor analysis is aimed at uncovering the latent dimensions within the original variables, thereby testing convergent and discriminant validity (Conway & Huffcutt, 2003).
The analysis process was implemented through these respective steps:
Exploratory Factor Analysis (EFA) was utilized to investigate the relationships among various variables and to determine the underlying factors This study employed Principal Components Factor Analysis for factor extraction, along with varimax rotation for optimal results To ensure the data's appropriateness for factor analysis, specific conditions must be satisfied (Pallant, 2005).
- The sample size should be appropriate: the sample size should be at least 165 as the above foundation.
- The factorability of the data would be appropriate if:
• The Kaiser-Meyer-Olk in value (KMO) should be 0.5 or above.
• The Bartlett‟s test of sphericity should be statistically significant
- The number of factors were determined when:
• The components have eigenvalue of 1 or more.
• The total variance explained by these components should be above 50%
• Factor loading criteria should be 0.4 or more to ensure a practical significance.
Following the refinement process, correlation analysis was conducted to assess the relationship between independent and dependent variables, as outlined by Tabachnick and Fidell (2001) This study employed correlation analysis to explore the interrelationships among these variables Subsequently, regression analysis was performed to gain deeper insights into the dynamics between the dependent and independent variables, as well as to test the relevant hypotheses.
DATA ANALYSIS AND RESULT
Sample characteristics
In the previous chapter, data was gathered from 350 questionnaires distributed via email and directly to random customers of various banks in Ho Chi Minh City, achieving a response rate of 57.7% After filtering out incomplete responses, the final analysis was based on a sample of 202 completed questionnaires The subsequent sections will outline the key characteristics of this sample.
The sample consisted of 85 (equivalent to 42.1%) males and 117 (equivalent to 57.9%) female The majority of respondents in the sample were around of 18 to
50 years old Among the 202 cases, 11.4% or 23 respondents which were from 18 to
22 years old, 42.6% or 86 respondents were between 23 to 29 years old, 30.2% or 61 respondents were between 30 to 39 years old, and 15.8% or 32 people were more than 40 years old.
In the study, 112 participants (55.45%) reported regularly transacting with commercial or local banks, while 90 participants (44.55%) had accounts with foreign banks The findings indicate that there is no significant difference in the usage rates between commercial banks and foreign banks among the respondents.
A significant portion of banking service users possess varying levels of education, with 8.9% holding high school diplomas, 56.9% having bachelor's degrees, and 34.2% attaining master's degrees This indicates that the majority of individuals utilizing banking services have achieved at least a bachelor's level of education.
Assessment of measurement scales
The assessment and refinement of measurement scales were conducted using SPSS 16.5, following the procedures outlined in Chapter 3 This process involved two key steps: first, evaluating reliability through Cronbach's Alpha, and second, performing Exploratory Factor Analysis (EFA) to assess both convergent and discriminant validity During this evaluation, items that did not meet established criteria were removed The criteria for reliability and measurement included a factor loading greater than 0.40, item-total correlation exceeding 0.40, a Cronbach Alpha above 0.60, and a percentage of variance greater than 60% (Hair et al., 1998).
Table 4.2 presents the Cronbach's Alpha results for each scale during the initial analysis, with values ranging from 0.6 to 0.9 The highest alpha value was 0.900 for customer satisfaction, while the lowest was 0.615 for normative commitment, indicating that a Cronbach's Alpha above 0.6 is generally acceptable However, some constructs exhibited overall alpha values lower than the alpha if the item was deleted, and certain items had corrected item-total correlations below 0.4, suggesting a lack of correlation with other items Specifically, items Trt7, Emc11, Noc18, Noc9, Swc26, and Aaa30 fell into this category.
After eliminating uncorrelated items, the Cronbach‟s Alpha of that constructs became better in the second time running We could refer to table 4.3 for the new figures.
Availability and attractiveness of alternatives
All the independent and dependent factors were separately run through the Principal component analysis, using the varimax rotation method.
4.2.2.1 EFA result for measurement scales of independent factors.
Following three iterations of factor analysis, the results revealed that all retained variables exhibited high factor loadings exceeding 0.4, with significant loadings on a single acceptable factor, thereby validating the robustness of the analysis.
The initial factor analysis revealed strong KMO values for all independent factors, exceeding 0.8, and a significant Bartlett's test result (p < 0.05) Six factors were identified, each with eigenvalues greater than 1 However, variables Emc9 and Emc10 were associated with two different factors, while Emc8 showed a lower loading in another group, leading to their exclusion from the analysis.
In the second time running, the variable Cam13 had no value Cam 12 was loading into 2 factors Cam 14 was loading into another group (see Appendix 2). Therefore, they were omitted.
For the third consecutive time, all independent factors met the criteria with a KMO value exceeding 0.8, a significant Bartlett’s test result of 0.000 (p < 0.05), and a cumulative total variance of 74.527% (refer to Appendix 3) Six independent factors were successfully extracted, with rotation converging after six iterations.
The generated factors, the attributes of 6 factor loadings (customer satisfaction, trust, normative commitment, switching cost, relational benefits and availability and attractiveness of alternatives) were presented in Table 4.4.
Table 4.4: EFA result for independent factors
Following extensive analysis, it was found that nearly all factors associated with commitment were eliminated, leaving only "normative commitment" as a key representative Consequently, the term "normative commitment" has been simplified to "commitment" for clarity and ease of understanding in this study.
4.2.2.2EFA result for measurement scales of dependent factors.
The dependent variables of Customer Retention was assessed by principle component analysis using none rotation method as well The results below showed that these three scales are valid.
Table 4.5: EFA result for dependent factor
All factors above were satisfied with conditions KMO>0.5, Test andCumulative % total variance: 70.400 (see Appendix 4) The Bartlett‟s TestSignificance of 000 < 0.05 and therefore met the conditions required by EFA method.
Hypothesis testing
4.3.1Testing relationship of independent factors and dependent factor.
Before running regression step, we should test how the variables correlate with each other The results were shown in Table 4.6 below.
Table 4.6 Result of Pearson Correlation.
TR CM SW RE AA
CS: average value of Cus1, Cus2, Cus3
TR: average value of Trt4, Trt5, Trt6
CM: average value of Noc15, Noc16, Noc17
RE: average value of Reb20, Reb21, Reb22
SW: average value of Swc23, Swc24, Swc25
AA: average value of Aaa27, Aaa28, Aaa29
RT: average value of Ret31, Ret32, Ret33
The Pearson Correlation results indicate a value of less than 0.8, suggesting a relationship between independent and dependent variables that meets the conditions for Exploratory Factor Analysis (EFA) Notably, customer satisfaction exhibits a strong correlation with other factors, while the relationship between trust and commitment with retention is relatively weak.
Through the results from EFA and Cronbach Alpha Reliability Analysis, the measurement scales were tested and confirmed valid and reliable.
Chapter 2 presented eight research hypotheses After observing the results of the EFA analysis step scale of nine variables, we found that the hypothesis-related variables need some adjustments New research model would consist of six independent variables and one dependent variable as follow: customer satisfaction,trust, commitment, switching costs, relational benefits, availability and attractiveness of alternatives and customer retention Hypotheses related to these variables now are:
Availability and attractive of alternativesH6-
H1 There is a positive impact of customer satisfaction on customer retention.
H2 There is a positive impact of trust on customer retention.
H3 There is a positive impact of commitment on customer retention.
H4 There is a positive impact of relational benefits on customer retention.
H5 There is a positive impact of switching costs on customer retention.
H6 There is a negative impact of availability and attractiveness of alternatives on customer retention.
4.3.2 Testing Assumption of multiple Regressions
According to Pallant (2005), the standard cut-off points for identifying multicollinearity among independent variables are a Tolerance Value of 0.1 and a Variance Inflation Factor (VIF) of 2.0 As shown in Table 4.7, all independent variables exhibit tolerance values exceeding the 0.10 threshold (Customer satisfaction: 0.582, Trust: 0.654, Commitment: 0.610, Switching costs: 0.814, Relational benefits: 0.614, Availability and attractiveness of alternatives: 0.869), indicating no multicollinearity issues Furthermore, the VIF values for all independent variables remain below the critical value of 2 (Customer satisfaction: 1.718, Trust: 1.530, Commitment: 1.639, Switching costs: 1.228, Relational benefits: 1.628, Availability and attractiveness of alternatives: 1.150), further confirming the absence of multicollinearity.
As all the assumptions of Standard Multiple Regression were met, a further analysis on regression results were proceeded to test the research hypotheses and this research.
The findings from Table 4.7 indicate that all five independent variables—customer satisfaction, trust, commitment, switching costs, and relational benefits—positively influence customer retention In contrast, the availability and attractiveness of alternatives negatively affect retention rates.
In multiple linear regression (MLR) analysis, a Variance Inflation Factor (VIF) greater than 10 indicates that an independent variable is unlikely to contribute meaningfully to explaining the variability of the dependent variable However, caution is advised when interpreting regression weights if the VIF exceeds 2 As shown in Table 4.7, all variables have a VIF greater than 1, suggesting that the issue of multicollinearity can be effectively addressed.
The standardized coefficient Beta for Customer Satisfaction (CS) is 0.568, with a significance value of 000, indicating a statistically significant positive relationship with Customer Retention (RT) at a 95% confidence level Therefore, the hypothesis H1, which states that "there is a positive impact of customer satisfaction on customer retention," is supported.
The standardized Beta for Trust (TR) was found to be 0.31, with a significance value of 0.555, which exceeds the 0.05 threshold This indicates that, at a 95% confidence level, Trust does not significantly influence Customer Retention Consequently, the hypothesis “H2: There is a positive impact of trust on customer retention” is not supported.
The standardized coefficient Beta for Commitment, as shown in table 4.6, was 0.54, with a significance value of 323, indicating a positive relationship between Commitment and Customer Retention However, at the 95% confidence level, the independent variable Commitment did not significantly contribute to predicting the dependent variable Consequently, the hypothesis H3, stating that "there is a positive impact of commitment on customer retention," was not supported.
Relational Benefits‟ standardized Beta was 0.178 and Sig Value was 0.01