INTRODUCTION
Research background
In today's competitive market, retaining customers is crucial, as acquiring new ones can be up to ten times more expensive and may require up to 16 times the investment to achieve the same profitability level (Lindgreen et al., 2000) Consequently, companies are increasingly prioritizing customer retention strategies (Berry, 1983; Fornell, 1992) Research has highlighted that a key element of successful customer retention is relationship quality, which reflects customers' perceptions of how well their needs and expectations are met (Oliver, 1997; Jarvelin & Lehtinen, 1996) Factors influencing relationship quality include customer satisfaction (Hendrick, 1988), trust (Rempel, Holmes & Zanna, 1985), and commitment (Adams & Jones, 1997; Lund, 1985), all of which play a significant role in customers' decisions to maintain 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
Recent studies highlight the importance of switching barriers, defined by Jones et al (2000) as factors that complicate or increase the cost for customers to change suppliers Understanding these barriers is crucial for companies aiming to foster long-lasting customer relationships, as it helps explain why dissatisfied customers might choose to stay or switch By identifying the key dimensions influencing customer decisions, businesses can tailor their offerings to better meet customer needs, thereby enhancing customer retention and fostering brand loyalty To prevent switching and cultivate enduring relationships, suppliers are increasingly employing strategies to ensure customer satisfaction, build trust, and strengthen exit barriers This research aims to explore the interaction effects of relationship quality and switching barriers on customer awareness and decision-making.
In the context of Vietnam's banking sector, which has evolved significantly since joining the World Trade Organization (WTO) in 2007, the number of foreign-owned financial institutions has surged to 49 branches, primarily in Ho Chi Minh City and Hanoi This growth highlights the competitive landscape where foreign banks, equipped with superior organizational structures and extensive international networks, hold an advantage over local banks However, local banks leverage their widespread branches, familiarity with the Vietnamese market, and support from the State Bank As customer demands diversify, both foreign and local banks must innovate and implement effective strategies to attract and retain customers, intensifying competition in the marketplace Understanding the factors influencing customer retention is crucial for developing successful 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 customers at local and foreign banks in Ho Chi Minh City, focusing on individuals who regularly utilize banking services Young people under 18, lacking significant income and the ability to make independent financial decisions, are excluded from the research, limiting the sample's representation of Vietnam as a whole The investigation explores four key factors: customer 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, specifically targeting individuals who regularly utilize banking services It excludes young people under 18 years old, as they typically lack sufficient income and the ability to make independent financial decisions, which limits the sample's representation of the broader Vietnamese population 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 critical activity for selling organizations aimed at minimizing customer defection, as highlighted by Jones et al (2000) This process involves fostering repetitive behavior among customers, ultimately striving to achieve lasting customer loyalty, as noted by Liu and others.
Customer retention is a crucial aspect of relationship marketing, focusing on maintaining long-term relationships with customers (Wu, 2007; Gronroos, 1997) It serves as a key metric for measuring the continuity of these relationships and is recognized as an effective strategy for businesses to achieve 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 beneficial than acquiring new ones (Hidalgo et al., 2008) Customers have a life-cycle that includes acquisition, retention, and growth in value (Ang & Buttle, 2006) Effective retention starts with the initial contract and continues throughout the customer relationship, leading to increased purchases and positive word-of-mouth from satisfied long-term customers Research shows that the costs associated with customer retention are significantly lower than those of 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 mature, the cost to serve customers decreases due to learning effects, leading to improved income stability and reduced churn (Reichheld & Sasser, 1990; Turnbull, 1990) Therefore, developing an effective customer retention strategy is essential for managers aiming to thrive in today's competitive marketplace (Weinstein, 2002).
Key factors influencing a customer's choice of bank include service quality, rates, fees, and charges To thrive in the banking sector, it is crucial to excel in service delivery, meet client needs, and offer innovative products However, exceptional service alone is not enough to ensure long-term customer loyalty Relationship quality and switching barriers also play a vital role in customer retention Many commercial banks recognize the importance of building and maintaining strong customer relationships, understanding the benefits that come from high relationship quality and effective switching barriers.
In light of these findings, it is essential for service providers to enhance the quality of their customer relationships and implement stronger switching barriers to effectively retain their customers.
Over the past two decades, relationship quality has emerged as a crucial factor in customer relationship management and is increasingly recognized as a key indicator of successful business interactions Defined by Crosby et al (1990) as an evaluation of the strength and fulfillment of expectations within a relationship, relationship quality encompasses a multidimensional construct that reflects the dynamics between suppliers and consumers (Hennig-Thurau & Klee, 1997; Hennig-Thurau et al., 2002) It plays a vital role in 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) Key dimensions of relationship quality identified in consumer market research include trust and satisfaction (Bejou et al., 1996; Crosby et al., 1990; Lin & Ding, 2005), with commitment also recognized as an essential element (De Wulf et al., 2001; Hennig-Thurau, 2000; Moliner et al., 2007) Some studies suggest additional dimensions, such as affective conflict (Roberts et al., 2003) and social bonds (Lang & Colgate, 2003), further enriching the understanding of relationship quality.
In the retail environment, relationship quality is characterized by trust, commitment, and satisfaction, which collectively indicate a long-term orientation and connect consumer markets.
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; however, if it falls short, dissatisfaction arises This emotional response is shaped by the gap between expected and actual service performance, which customers assess through their interactions with the business's offerings (Salami, 2005) High-quality products and services can enhance customer loyalty, boost profitability, increase market share, and reduce turnover rates Conversely, dissatisfied customers are unlikely to maintain a positive relationship with the business (Roberts et al., 2003).
Trust is the willingness to rely on a partner, grounded in confidence and the belief that their promises are reliable (Moorman et al., 1993; Schurr & Ozanne, 1985) The strength of a relationship is directly linked to the level of trust; higher trust leads to stronger bonds Loyalty and trust in relationships are obligations given without expecting anything in return (Yau et al., 2000), and failing to uphold this can harm one's reputation and result in significant drawbacks Ultimately, a trustworthy partner is expected to produce positive outcomes, reinforcing the importance of integrity in relationships (Morgan & Hunt, 1994).
Commitment in relationships is fundamentally derived from trust, shared values, and the perception that finding equally valuable partners is challenging (Morgan & Hunt, 1994) This commitment fosters cooperation between parties, promoting the conservation of investments made in the relationship Research indicates that mutual commitment serves as a robust predictor of the voluntary decision to engage in a relationship (Ibrahim & Najjar).
Commitment is recognized as the fundamental element for both parties in a relationship to foster and sustain their connection A strong commitment creates an environment where individuals can achieve both personal and shared goals, free from the worry of opportunistic behavior.
Research has shown that the quality of relationships plays a crucial role in customer loyalty and retention While loyalty can still exist in situations with weak relationships, it is often influenced more by external factors, such as limited alternatives or significant switching barriers.
In the retail services industry, switching barriers encompass various factors such as search costs, transaction costs, learning costs, loyal customer discounts, and emotional costs (Va ´zquez-Carrasco & Foxall, 2006; Pass, 2006; Pont & McQuilken, 2005; Sengupta et al., 1997) These barriers are closely linked to the perceived risk experienced by customers, which refers to their apprehension regarding the uncertainties and potential negative outcomes associated with purchasing a product or service (Dowling & Staelin, 1994) Colgate and Lang (2001) categorize these barriers into relational benefits, switching costs, availability and attractiveness of alternatives, and service recovery Subsequent research by Va´zquez-Carrasco and Foxall (2006) further emphasized the significance of the first three categories of switching barriers.
3 Availability and attractiveness of alternatives.
Consumers are inclined to foster relationships with companies that offer significant relational benefits, such as social connections, trust, and preferential treatment (Liu, 2006; Gwinner et al., 1998; Va´zquez-Carrasco & Foxall, 2006) The fear of losing these benefits often leads dissatisfied customers to remain loyal, despite service shortcomings (Yanamandram & White, 2006) Research by Ranaweera and Prabhu (2003) indicates that service providers can retain even unhappy customers if they perceive high switching barriers However, in the long run, dissatisfied customers will seek solutions to their issues Therefore, companies should implement strategies that enhance customer satisfaction while maintaining switching barriers to ensure long-term loyalty.
Switching costs refer to the time, monetary, and psychological expenses involved in changing service providers (Jones et al., 2002; Dick & Basu, 1994; Sengupta et al., 1997) According to Panther and Farquhar (2004), customers often remain with their current services due to the hassle of finding and evaluating new providers, as well as the effort required to inform business partners about the change For instance, when switching banks, customers face delays in receiving essential items like checkbooks and ATM cards, and must navigate the complexities of canceling services such as internet banking and settling any existing loans or commitments 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 often maintain their current relationships when few or no alternatives exist within their industry Additionally, Patterson and Smith (2003) note that customers may overlook potential alternatives due to a lack of awareness or because they do not find these options more appealing than their existing supplier.
This section explores the model that connects relationship quality, switching barriers, and customer retention It examines how key dimensions of relationship quality, including customer satisfaction, trust, and commitment, impact customer retention Additionally, it analyzes the influence of various switching barrier factors on retaining customers.
2.2.1 Customer satisfaction and customer retention.
Customer satisfaction is defined as a pleasurable emotional state that arises 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 meets or exceeds 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 research highlights that customer satisfaction is essential for retaining clients, positioning it as a key element in relational marketing strategies A strong correlation exists between customer satisfaction and retention; higher satisfaction levels increase the likelihood of customers remaining loyal to a service Improved service quality enhances customer satisfaction, which in turn fosters stronger relationships between customers and businesses As relationships deepen, satisfaction plays a crucial role in differentiating a business from competitors offering similar benefits Conversely, customers who are dissatisfied with the services are unlikely to maintain a positive relationship with the firm or continue their patronage.
& 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 (2004) This perspective emphasizes that satisfaction is "backward looking," shaped by past performance and experiences up to the present (Gustafsson et al., 2005).
Customer satisfaction in the retail environment is defined as the post-consumption evaluation of how well a retailer meets or exceeds customer expectations, encompassing both products and services (Addition, Levy, and Weitz, 2009; Storbacka et al., 1994) In today's highly competitive market, banks must differentiate themselves by offering high-quality products and services to enhance customer satisfaction, which is essential for fostering long-term relationships Satisfied customers can also act as advocates, attracting new clients through positive word-of-mouth, serving as an effective marketing strategy Consequently, the significance of customer satisfaction in retention is recognized by major global economies as a predictor of 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 propose that relationships can be viewed as a sequence of transactions that enhance awareness of strong connections through trust and commitment A greater degree of trust is significantly linked to an increased 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 (Heskett et al., 1994; Schneider & Bowen, 1999) To foster long-term loyalty, businesses must focus on additional factors, such as trust (Hart & Johnson, 1999) Trust is a dynamic element that requires ongoing effort to build, earn, and renew In the retail context, it reflects a consumer's confidence in a retailer's reliability and integrity (De Wulf et al., 2001) According to Thomas (2009), trust involves the expectation of positive outcomes based on anticipated actions, while Gro¨nroos (2007) describes it as the belief that one party will act predictably in specific situations Ultimately, trust is cultivated through positive customer experiences that encourage continued relationships (Berry, 2000; Foster & Cadogan, 2000).
The marketing literature identifies two types of trust: credibility and benevolence Trust in a retailer's credibility means customers believe they can rely on the retailer's knowledge and effectiveness, while trust in benevolence reflects the customer's perception of the retailer's care for their welfare In the financial services sector, trust is fundamental, with customers expecting banks to manage their money responsibly, offer competitive interest 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 Building and nurturing customer trust and loyalty is essential for commercial success, as it significantly enhances sales growth through customer acquisition and retention.
H2.There is a positive impact of trust on customer retention.
Commitment is essential for fostering successful long-term relationships, as it encompasses the intentions and behaviors of both parties over time 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 identify with and appreciate, leading to a strong attachment This emotional bond encourages customers to willingly maintain their relationship with the firm On the other hand, calculative commitment arises from the recognition of potential losses and benefits tied to the relationship, prompting customers to continue their engagement to avoid adverse consequences.
In relationships, both parties may fear losing one another, leading to different types of commitment Calculative commitment is characterized by a rational, economic-based dependence, while emotional commitment arises from the level of reciprocity and personal involvement a customer has with a company (Gustafsson et al., 2005) Additionally, normative commitment reflects a moral obligation to maintain the relationship (Allen & Meyer, 1990).
Emotional, calculative, and normative commitments differ in their focus on the desire to stay, economic investments, and moral obligations Emotional commitment, driven by personal attachment, and normative commitment, rooted in ethical considerations, positively influence customer behavior and retention In contrast, calculative commitment, which is based on a rational assessment of costs and benefits, tends to have a negative correlation with customer behavior Nonetheless, calculative commitment can still positively impact retention by making it challenging for customers to switch suppliers In the banking sector, customers' attitudes vary, as they may choose to maintain their relationship with a bank based on emotional, calculative, or normative commitment, depending on their perceptions of which type of commitment offers greater benefits at different times.
Emotional commitment significantly enhances customer retention, fostering a deeper connection between the brand and its customers Similarly, calculative commitment plays a crucial role in keeping customers engaged, as it emphasizes the perceived benefits and costs associated with staying loyal to a brand Additionally, normative commitment contributes positively to customer retention by instilling a sense of obligation and loyalty, encouraging customers to remain with a brand due to shared values and social expectations.
2.2.4 Switching barriers and customer retention.
Switching barriers are factors that complicate or increase the costs for consumers when changing service providers These barriers can be understood as the consumers' evaluation of the resources and opportunities required to switch, as well as the constraints that hinder this process (Bansal & Taylor, 1999) Keaveney's (1995) research was pivotal in identifying switching barriers as a key influence on customer switching behavior Following this, Gremler and Brown (1996) developed a model through in-depth interviews, highlighting switching costs as essential for customer loyalty and retention They defined switching costs as the time, money, and effort that customers perceive as making it challenging to change providers, including factors such as habit, inertia, setup, 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 be viewed from both positive and negative perspectives According to Julander and Soderberg (2003), the positive aspect relates to the desire to maintain a relationship, while the negative aspect pertains to feeling compelled to stay in a relationship, as highlighted by Hirschman (1970).
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 factors influencing customer retention The research follows a structured procedure, as depicted in the accompanying figure.
Measurement scales
The scales for nine constructs within the model were developed based on established studies, tailored to the specific context of the banking industry in Vietnam A multiple-item approach was utilized, employing a five-point Likert scale 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),
The study by Gustafsson et al (2005), Kelly (2004), and Allen and Meyer (1990) builds on existing literature regarding switching barriers, incorporating scales for relational benefits, switching costs, availability, and attractiveness of alternatives (Burnham et al., 2003; Jones et al., 2000; Goitom and Nancy, 2011) Retention is defined as a customer's future likelihood of remaining with a service provider, measured using a three-item formative scale adapted from Morgan and Hunt (1994) This scale assesses the probability of customers leaving their banks over three time frames: six months, one year, and two years The overall retention score is calculated by summing the weighted responses, with the first item receiving the highest weight, followed by the second, and the third item remaining unweighted, yielding a scoring ratio of 2.5:1.5:1 on a scale of 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 valid 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 using the formula: n3*55 observations.
To achieve a sample size of 165, 350 questionnaires were distributed to participants aged 18 to 60 This age group typically demonstrates a greater demand for banking services and possesses the financial capacity to utilize them effectively The respondents come from diverse careers and have 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 from this research served as valuable input for designing the final questionnaire, enhancing its effectiveness in capturing customer perspectives.
• 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 conducted to test 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 and eliminate potential issues, enhance reliability, and ensure the suitability of data collection tools In this research, a pilot study was carried out by distributing the questionnaire to 10 randomly selected interviewees through face-to-face interactions The interview questions focused on customer satisfaction, exploring factors that influence satisfaction or dissatisfaction with banking services, trust in their current provider, and awareness of any 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.
The multi-item scales require thorough evaluation for reliability and validity, with Cronbach's Alpha being the most widely used method for assessing reliability A high Cronbach's Alpha indicates strong correlation among 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 to enhance the scale's effectiveness.
The current study employs exploratory factor analysis (EFA) using SPSS 16.5 as its primary assessment method EFA utilizes two main extraction techniques: common factor analysis and principal components factor analysis While principal component factor analysis focuses on item reduction and assessing test unidimensionality and reliability, common factor analysis is aimed at uncovering the latent dimensions within the original variables, as well as evaluating 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 In this study, Principal Components Factor Analysis was the method chosen for factor extraction, complemented by the varimax rotation technique To ensure the data's appropriateness for factor analysis, specific conditions must be satisfied, as outlined by 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.
After refining the data, correlation analysis was performed to assess the relationship between independent and dependent variables (Tabachnick & Fidell, 2001) This study utilized correlation analysis to explore the interrelationships among these variables Following this, regression analysis was conducted to deepen the understanding of the relationships and 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, several questionnaires were discarded due to incomplete responses, resulting in a final sample of 202 valid 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.
The study sample included 112 participants (55.45%) who typically conducted transactions with commercial or local banks, while 90 participants (44.55%) held accounts with foreign banks These findings indicate that there is no significant difference in the usage rates of commercial banks compared to foreign banks among the respondents.
A significant portion of banking service users possess higher education, with 56.9% holding bachelor's degrees, 34.2% having master's degrees, and 8.9% at the high school level This indicates that the majority of individuals utilizing banking services have attained a specific 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, employing Cronbach's Alpha to evaluate reliability, and second, conducting Exploratory Factor Analysis (EFA) to assess both convergent and discriminant validity During this analysis, items that did not meet the established criteria were removed The reliability criteria included a factor loading greater than 0.40, an 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, revealing values ranging from 0.6 to 0.9, with customer satisfaction achieving the highest score of 0.900 and normative commitment the lowest at 0.615 A Cronbach's Alpha above 0.6 is considered acceptable; however, some constructs exhibited overall alpha values lower than the alpha if items were deleted, indicating potential issues with item correlation Specifically, the corrected item-total correlations for certain items, including Trt7, Emc11, Noc18, Noc9, Swc26, and Aaa30, fell below the acceptable threshold of 0.4, suggesting that these items may not be effectively aligned with their respective constructs.
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.
After conducting factor analysis three times, the findings revealed that all remaining variables exhibited factor loadings exceeding 0.4, indicating a significant association with an acceptable factor.
The initial factor analysis revealed strong KMO values for all independent factors, exceeding 0.8, with Bartlett's test yielding a significance level of 0.000, which is less than 0.05 Six factors exhibited eigenvalues greater than 1; however, variables Emc9 and Emc10 were associated with two different factors, while Emc8 was linked to another group with a lower loading value, leading to their omission 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, all factors related to commitment were largely dismissed, leaving only "normative commitment" as the key representative for commitment in this study Consequently, "normative commitment" has been redefined simply as "commitment" for clarity and ease of understanding.
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 below 0.8, suggesting a relationship between the independent and dependent variables that meets the conditions for Exploratory Factor Analysis (EFA) Notably, customer satisfaction exhibits a strong correlation with various factors, while the correlation 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 threshold of 0.10, with Customer Satisfaction at 0.582, Trust at 0.654, Commitment at 0.610, Switching Costs at 0.814, Relational Benefits at 0.614, and Availability and Attractiveness of Alternatives at 0.869 This indicates no multicollinearity violations Furthermore, the VIF values for all independent variables remain below the cut-off of 2, with Customer Satisfaction at 1.718, Trust at 1.530, Commitment at 1.639, Switching Costs at 1.228, Relational Benefits at 1.628, and Availability and Attractiveness of Alternatives at 1.150.
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 variables related to the availability and attractiveness of alternatives negatively affect customer retention.
In multiple linear regression (MLR) analysis, a Variance Inflation Factor (VIF) greater than 10 indicates that an independent variable may not significantly explain 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 had VIF values greater than 1, suggesting that the issue of multicollinearity can be effectively addressed.
The standardized coefficient Beta for Customer Satisfaction (CS) was found to be 0.568, with a significance value of 000, indicating a strong positive relationship between Customer Satisfaction and Customer Retention (RT) at a 95% confidence level Therefore, the hypothesis H1, which posits that customer satisfaction positively impacts customer retention, is supported.
The analysis revealed that Trust (TR) had a standardized Beta of 0.31 with a significance value of 0.555, indicating that at a 95% confidence level, Trust did not significantly influence Customer Retention Consequently, the hypothesis “H2: There is a positive impact of trust on customer retention” was not supported.
The standardized coefficient Beta for Commitment was 0.54, with a significance value of 0.323, indicating a positive relationship between Commitment and Customer Retention However, at a 95% confidence level, the independent variable Commitment did not significantly predict the dependent variable Consequently, the hypothesis H3, which posited a positive impact of commitment on customer retention, was not supported.
Relational Benefits‟ standardized Beta was 0.178 and Sig Value was 0.01