INTRODUCTION
Research background
The overview about credit card use in over the world and Vietnam is discussed in this section
Credit cards allow consumers to access funds in advance and make payments later, making them a popular choice for various purchases, from utility bills to major items like cars and homes As economic growth continues, the middle-income population and bank account ownership are rising, contributing to the increased adoption of credit cards Technological advancements have significantly transformed credit card services and their delivery, leading to a surge in electronic financial transactions Consequently, more individuals and businesses are utilizing credit cards, intensifying competition among providers to capture a larger market share.
Since their introduction in the 1950s, the credit card market in the USA has experienced significant growth, with an increasing number of consumers holding credit cards (Durkin, 2000; Devlin, Worthington & Gerrard, 2007) Unlike other payment methods, credit cards provide long-term credit without requiring collateral at the time of purchase (Stavins, 1996, cited by Chakravorti, 2003) Historically, banks restricted credit card access primarily to affluent individuals, but over time, they have gradually relaxed these policies to accommodate a broader customer base.
The rapid economic growth in Asian countries has significantly increased credit card opportunities, with the Asia Pacific region accounting for $1.3 trillion in credit card usage in 2007, representing 30% of global transactions Japan led this growth with $209 billion in transactions, followed closely by South Korea at $203 billion, and Australia at $140 billion The rise of credit card usage in emerging markets highlights the importance of understanding customer behavior in these regions Researchers point to the surge in middle-income consumers and advancements in technology as key factors attracting credit card providers to these markets.
There has been a rapid increase in credit card issuing in Vietnam recently
Between 2009 and 2011, the number of credit card issuing increases by 198 percent and 1.62 million credit cards are issued at the end of 2012 or 2.4 cards per 100 adults
(Lafferty, 2013) According to The State Bank (cited in Ocean Bank Annual Report,
As of October 2013, Vietnam had 52 payment card providers and approximately 64 million payment cards, with credit cards representing 3.6% of this total This marks a significant increase from just 1% in 2011, according to Nielsen Research The rise in credit card usage can be attributed to the government's Decision 291/QD-TTg in 2006, which initiated a plan for non-cash payments, initially set for 2006 to 2010 and later extended to 2020.
20/200/NHNN about the issuing, using and supplying services to support card payment These decisions play very important roles in promoting non-cash transactions in
Vietnam, by developing infrastructure for non-cash payments and providing incentives h
Recent research by Spire Research and Consulting indicates that Vietnam is progressing towards a cashless society, with significant advancements in its banking and credit card sectors over the past decade The study highlights a notable decline in cash transactions, which fell from 3.4% in 2009 to 2.7% in 2013, alongside a rise in card transactions from 1.5% during the same period This trend underscores the increasing adoption of advanced technologies in non-cash payment systems by financial institutions in Vietnam.
From 2009 to 2013, Vietnam's credit card market experienced a growth from 0.9% to 3.1% (Business Journal, 2014) According to Dang (2013), significant changes are anticipated in this market over the next decade Major global banks, including Citibank, ANZ, and HSBC, alongside local institutions like Vietcombank, Vietinbank, and Maritimebank, have launched various promotional initiatives to enhance customer awareness of credit cards in Vietnam.
The credit card market in Vietnam faces significant challenges due to a large unbanked population and the dominance of cash as the primary payment method for daily transactions Despite an urban population growth rate of approximately 3.5 percent in recent years, Vietnam remains one of the least urbanized countries in emerging Asia, with a substantial rural population engaged mainly in textiles, agriculture, and fisheries As of 2012, only 20 percent of the population had bank accounts, and merely half of these individuals actively utilized consumer banking services Furthermore, many consumers, despite owning credit or debit cards, still prefer cash for everyday purchases.
Vietnam is emerging as a prime destination for the credit card market, driven by its status as one of the fastest-growing economies in Asia The country's GDP per capita has seen significant growth, increasing from US$1,097.1 in 2009 to US$1,728.4, highlighting its economic potential and attractiveness for financial services.
The socio-economic developments in Vietnam since 2013 have significantly improved the quality of life for its citizens As noted by Lawrence (2003), credit cards serve as a convenient payment method, promote financial responsibility, provide emergency resources, help establish a good credit history, and enhance future credit access Consequently, the growing trend of credit card usage in Vietnam reflects these advancements in the country's socio-economic landscape.
Vietnam's young population, with a median age of 25 and an annual growth rate of approximately 1%, is projected to reach 94.5 million by 2016, presenting significant opportunities for short- to medium-term economic growth (Lafferty, 2013) Additionally, the shift in payment habits among Vietnamese consumers has created a favorable environment for the credit card market Since January 2011, following Vietnam's trade commitments to the WTO, foreign banks have been granted equal treatment with domestic banks regarding credit limits and guarantees, enabling them to establish wholly owned subsidiaries and branches This has led to increased competition, with overseas banks introducing advanced technologies and innovative marketing strategies, making credit cards more accessible than ever, particularly in major cities like Ho Chi Minh City and Hanoi.
Research motivation
Vietnam is emerging as an attractive market for international credit card providers, driven by its numerous advantages Despite the current limitations in credit card usage, primarily due to a lack of familiarity and understanding among many Vietnamese consumers, the potential for growth in this sector remains significant According to Dang (2013), the increasing awareness and adoption of credit cards in Vietnam present a promising opportunity for providers looking to expand their services in the region.
Vietnam's credit card market, despite being one of the least profitable globally with an average profit of $6 per card in 2011, shows significant potential for growth due to its young population, expanding middle class, and improving infrastructure To thrive in this competitive landscape, both international and local credit card issuers must implement effective marketing strategies and understand customer expectations Conducting in-depth research to identify the key factors influencing credit card usage is essential for providers to enhance their understanding of consumer behavior This knowledge is crucial for developing long-term strategies to capture a larger share of Vietnam's payment card market, motivating further exploration in this research.
Research on credit card usage in Vietnam is notably scarce compared to numerous studies conducted in other countries While many emerging market economies have seen limited exploration of this topic, various factors such as legal, structural, cultural, geographical, and socio-economic differences can significantly influence credit card adoption This study aims to identify the key factors affecting credit card use specifically in Ho Chi Minh City, Vietnam.
Research objective
This study aims to analyze the key factors influencing credit card usage among customers in Ho Chi Minh City Specifically, it seeks to address the following research questions.
RQ1: Is there a positive relation between bank policy and credit card use of customers in Ho Chi Minh City?
RQ2: Is there a positive relation between convenience and credit card use of customers in Ho Chi Minh City?
RQ3: Is there a positive relation between compatibility and credit card use of customers in Ho Chi Minh City?
RQ4: Is there a positive relation between risk barriers and credit card use of customers in Ho Chi Minh City?
Research methodology and research scope
This study employs a questionnaire to gather data, initially developed in English and translated into Vietnamese with expert assistance An in-depth interview phase refines the measurement scale, followed by a quantitative pilot study that includes face-to-face and online interviews to assess participants' comprehension of the questions and ensure the online survey functions correctly The finalized questionnaire is distributed via Google Survey and paper formats Data analysis is conducted using SPSS software, involving three key stages: testing the measurement scale's reliability with Cronbach’s Alpha, validating the scale through Exploratory Factor Analysis (EFA), and performing simple regression analysis.
7 multiple regressions are used as the main method for investigating the relationships among factors in the research model
This thesis examines credit card usage among residents of Ho Chi Minh City, chosen for its status as the largest city in Vietnam, characterized by a young, dynamic population with high income and technological proficiency The research aims to identify the key factors that influence credit card adoption and usage Participants in the study include individuals living in Ho Chi Minh City who are knowledgeable about credit cards.
Research contribution
This study provides valuable insights for credit card marketers in Ho Chi Minh City, addressing the challenges of slow market growth and intense competition among card providers in Vietnam The research findings equip credit card issuers with essential information to develop effective strategies tailored to their target consumers' preferences, as well as to enhance the credit card application and usage experience.
Research on credit card usage in Vietnam is scarce This study employs a multi-faceted framework to explore the impact of bank policies, convenience, compatibility, and risk barriers on Vietnamese consumers' credit card adoption It aims to enhance the existing literature on the factors influencing credit card use in Vietnam and to inspire similar research in emerging market economies to assess whether these findings are consistent or vary across different contexts.
Research structure
This study is organized into five chapters h
The introduction chapter outlines the research by providing essential background information, highlighting the motivation behind the study, and defining the research objectives Additionally, it details the research methodology and scope while emphasizing the contributions of the research.
Chapter two examines existing theories related to credit card usage, focusing on four key factors that influence customer behavior in Ho Chi Minh City: bank policies, convenience, compatibility, and risk barriers Additionally, this chapter proposes a research model with corresponding hypotheses to explore these influences further.
Chapter three introduces research methodology used to empirically test the research model
Chapter four presents the results of data analysis
The concluding chapter summarizes the key findings of the study, offers strategic recommendations for credit card issuers based on these insights, and highlights the limitations of the research.
LITERATURE REVIEW
Bank’s policies
This study examines bank policies related to the benefits offered to credit card holders and potential applicants These benefits include complimentary gifts, the opportunity to earn points for rewards, and cash rebates on purchases made with credit cards (Teoh et al., 2013).
Experts emphasize that policy plays a crucial role in helping banks attract new customers and retain the loyalty of existing ones According to Dowling and Uncles (1997), intense competition has led to the introduction of various customer loyalty programs To entice customers to apply for credit cards, many banks provide a range of incentives (Chakravorti, 2003) In response to the fierce competition in the credit card market, banks are continuously working to enhance their product offerings (Subramaniam & Marimuthu, 2010) Liu (2009) highlights the importance of effective communication by credit card marketers to engage potential customers.
To enhance customer awareness of reward points programs, it is crucial to effectively communicate the redemption procedures and benefits associated with these programs By broadening the advantages offered, easing the eligibility criteria for credit card applications, and implementing more flexible payment options, banks can significantly boost their credit cardholder numbers.
Customers view credit cards and banking services as a comprehensive package, often influenced by attractive incentives such as no annual fees for the first year, cash rebates, point rewards, airline miles, shopping discounts, and installment payment options (Akin et al., 2011) Recent trends show that banks are increasingly offering gifts upon credit card application to entice new customers (Liu, 2009) Additionally, credit card benefits may include coverage for lost cards, travel accidents, and support for cardholders facing unemployment or illness.
Zinman (2009) argues that the incentives provided to customers influence their decision to use credit cards as their primary payment method Additionally, to examine the impact of bank policies on credit card usage in Vietnam, a hypothesis has been formulated for testing.
Hypothesis 1: There is a positive impact of bank policy on credit card use.
Convenience
This study highlights the advantages of credit cards over cash, emphasizing their convenience and safety, especially when traveling abroad Credit cards eliminate the need to carry large amounts of cash and offer a more secure payment method compared to cash transactions (Khare et al., 2011).
Numerous studies have explored the convenience and inconvenience associated with varying levels of credit card usage Research by Khare et al (2013) highlights the regular use of credit cards, while Safakli (2007) identifies key attributes such as "convenience," "easiness," and "safety" as significant factors influencing consumer behavior.
To effectively pursue marketing strategies that meet the needs and desires of both existing and potential customers, it's crucial to consider 15 vital factors In the Greek credit card market, convenience stands out as the most significant factor influencing credit card usage, accounting for 37% of its utilization (Meidan & Davos).
Credit cards are increasingly popular among consumers, particularly women, due to their convenience and security features (Ahmed et al., 2009) They are commonly used for travel and entertainment, as well as serving as a status symbol (Khare, 2011) The rise in credit card usage can be attributed to the ease of not carrying cash and the availability of open-ended credit (Lee and Kwon, 2002) In Turkey, the primary motivations for credit card use include access to emergency funds, travel convenience, and shopping flexibility (Kaynak et al., 1995) Durkin (2000) highlights that credit cards facilitate millions of transactions, making purchases more convenient Ultimately, possessing and using credit cards enhances consumer comfort, particularly in travel and entertainment spending (Ahmed, 2010).
Above findings show the convenience of credit card use however Lafferty report
The growth of card payments in Vietnam is significantly hindered by low acceptance rates, with 60% of transactions at POS being international and primarily occurring in major cities where POS systems are predominantly found in shopping malls and high-end retailers Additionally, factors such as a strong cash habit and limited acceptance contribute to the inconvenience of credit cards in emerging markets Similarly, Laforet and Li (2005) identify the traditional cash-carry banking culture as a major barrier to the adoption of online banking among Chinese customers.
The limited acceptance of credit cards, particularly among inactive users, is viewed as a non-monetary cost (Khalid et al., 2013) Research by Chan (1997) in Hong Kong indicates that these users face challenges due to the unrestricted usage rates of their credit cards.
With above discussion, following hypothesis is developed
Hypothesis 2: There is a positive impact of convenience on credit card use 2.4 Compatibility
The definition of compatibility in this study follows to Chemingui and Lallouna
(2013) It refers to the match of credit card using with customers’ lifestyle, financial transaction style and the way doing jobs
Credit cards primarily appeal to young and affluent urban Vietnamese individuals who are drawn to a modern lifestyle According to Kucukemiroglu (1999), lifestyle encompasses people’s interests, how they allocate their time and resources, and their perceptions of themselves and others, distinguishing it from personality Additionally, Sjoberg & Engelberg (2005) highlight that the purchasing decisions of certain brands are influenced by lifestyle choices.
Research on the compatibility of credit cards with their usage is scarce However, compatibility is a key factor influencing behavioral intention, as noted by Rogers (2003) Users are more likely to adopt innovations that they perceive as compatible with their needs and preferences (Scott et al.).
Research indicates that the primary driver for customers' intention to use mobile banking services is their compatibility with user needs (Chemingui and Lallouna, 2013) Furthermore, compatibility significantly influences the likelihood of adopting mobile banking, as highlighted by Wessels and Drennan (2010) Lin (2011) also emphasizes that customers are more inclined to embrace mobile banking when they recognize its alignment with their requirements.
According to Ilie et al (2005), as cited by Lin (2011), achieving a higher compatibility between individual needs and technological innovations is advantageous, as it enables these innovations to be understood within a more familiar context.
Liang et al (2006) highlight the appeal of using credit cards, allowing consumers to enjoy immediate purchases while deferring payment According to Khare et al (2011), lifestyle significantly influences credit card ownership Devlin, Worthington, and Gerrard (2007) categorize credit cardholders into two groups: convenience users, who prioritize ease of use, and installment users, who rely on credit for structured payments Additionally, Mathew and Slocum reveal a correlation between social class and credit card usage, with higher social classes utilizing credit cards primarily for convenience, while lower social classes often depend on them for installment payments.
In 1969, research indicated that credit card users can be categorized into two groups: transactors and revolvers (Khalid, 2013; Worthington, Stewart & Lu, 2007) Transactor users prefer credit cards for payments over cash, highlighting the convenience they offer Additionally, individuals from low socio-economic classes often utilize credit cards for financing purposes (Gan, Mayrami & Koh, 2008) According to Bernthal, Crockett, and Rose (2005), credit cards not only represent a lifestyle but also play a significant role in shaping consumer lifestyles and values Ultimately, the use of credit cards enables users to attain their desired lifestyle.
This study investigates the impact of compatibility on credit card usage within the context of Vietnam, drawing insights from previous research on mobile financial services and the compatibility of credit cards.
Risk barriers
In this study, risk barriers is security concerning when using credit card
According to Chemingui and Lallouna (2013), risk barriers comprises the card stolen, unsecure of personal information providing, other people can access to account and credit card system is not secure
Many scholars in their researches define about the security Polatoglu and Ekin
Reliability, safety, and privacy are essential dimensions of security (2001) According to Dukin (2000), credit cards have become the main source of unsecured open-end revolving credit, replacing traditional installment-purchase plans that were crucial for retail sales in previous decades Ram and Sheth (1989) (as cited in Rammile & Nel, 2012) highlight that the risk barrier reflects the degree of risk linked to technological innovation Arthur and Dimitris (1994) define security as protection against credit card fraud and ensure that bills and balances are accurate, indicating that security is a critical factor for customers when selecting credit cards.
Perceived risk in financial services marketing significantly influences consumers' purchase decisions and poses challenges for service marketers (Goyal, 2008) Many online vendors primarily accept credit card payments, which can limit their customer base According to Park, Lee, and Ahn (2004), perceived risk in online transactions (PRT) refers to the potential risks consumers face when engaging in electronic commerce (p.12) Concerns about credit card information being exposed to hackers or unknown vendors remain a critical security issue (Sindhav & Balazs, 1999) Furthermore, Tan and Teo (2000) highlight that the rise of public networks has intensified security concerns, making it a key barrier to the adoption and use of online financial services.
19 internet banking As credit card is one of the modes of internet banking, this concept indirectly shows the effect of security perceived to credit card use
Numerous studies have examined the impact of security on credit card usage, revealing both positive and negative effects Khalid et al (2013) identified that protection against credit card fraud and the risk of loss or theft significantly influence credit card adoption Liao and Cheung (2002) highlighted confidentiality as a major concern that heightens perceived risks among consumers Ahmed et al (2009) found that security factors critically affect credit card usage in Pakistan A survey conducted in the USA indicated that security remains a primary barrier to internet banking (Consulting, 1996, cited by Narsi, 2007) Similarly, Narsi (2011) noted that perceived risk inhibits internet banking adoption Customers often avoid mobile banking due to fears of making errors and concerns over security, including the potential loss of funds and personal information (Laukkanen et al., 2007) Conversely, Rammile and Nel (2012) reported no significant impact of risk barriers on cell phone banking adoption, a finding echoed by Chemingui and Lallouna (2013) regarding mobile financial services.
According to data from the Vietnam State Bank, only 9 out of 41 card-issuing organizations in the country employ chip-based security technology (Lafferty, 2013) Additionally, the overall development of high technology in Vietnam remains limited As a result, many customers express concerns about risk barriers, leading to the proposal of the following hypothesis.
Hypothesis 4: There is a negative impact of risk barriers on credit card use h
Based on the review of some related literature and hypotheses developed, the following model is proposed (see Figure 2.1)
The conceptual model and hypotheses of the research
The conceptual framework illustrated in Figure 2.1 comprises four hypotheses, labeled H1 to H4, which include independent and quantitative variables that directly influence the dependent variable of credit card usage.
Following are four hypotheses which are proposed for this research:
H1: There is a positive impact of bank policy on credit card use
H2: There is a positive impact of convenience on credit card use
H3: There is a positive impact of compatibility on credit card use
H4: There is a negative impact of risk barriers on credit card use h
This chapter provides the theoretical foundation for the model, highlighting four key factors that influence credit card usage: bank policy, convenience, compatibility, and risk barriers These factors were chosen due to their established relationships with dependent variables closely related to credit card use, as evidenced by previous scholarly research The upcoming chapter will outline the methodology employed to analyze the data and test the research model's hypotheses.
RESEARCH METHODOLOGY
Research process
The research process included item generation step, pilot step and main study (Hair, Black, Babin, & Anderson, 2009) which was presented in Figure 3.1
Based on the literature review in Chapter 2, a draft questionnaire was created utilizing specific measurement scales (refer to Table 3.2) Subsequently, in-depth interviews were conducted to gather qualitative insights The initial survey questionnaire was developed in English and later translated into Vietnamese by the researcher, with assistance to ensure accuracy.
In the qualitative phase of the study, a Vietnamese version of the survey questionnaire was pre-tested through in-depth interviews conducted over two weeks with five English experts The purpose was to gather their insights on the questionnaire's accuracy, clarity, and understandability, as well as to assess the suitability of the chosen measurement scale for research in Ho Chi Minh City Feedback from the interviewees was compiled to refine the measurement scale accordingly.
The pilot survey aimed to evaluate the viability of the questionnaire rather than collect data Its primary focus was to identify any necessary modifications or improvements Following the pilot, the final questionnaire will be revised based on SPSS analysis and participant feedback.
Following the completion of the final questionnaire, a mass survey was conducted to gather data for testing the research hypotheses Participants filled out the survey independently, with most items measured using a five-point Likert scale, ranging from "strongly disagree" (1) to "neutral" (3).
The questionnaire utilized a scale ranging from "agree" (4) to "strongly agree" (5) and was distributed to respondents via the Google Survey tool and paper formats Participants received a link to the questionnaire through email and were given a two-week period to complete it A reminder email was sent two weeks after the initial invitation to encourage participation and express gratitude to those who had already completed the survey.
Following was the summary of whole process for this research
Deleted 1 item (in Use scale)
Questionnaire design
The questionnaire comprised three sections, as detailed in Appendix A The initial section assessed respondents' knowledge of credit cards, featuring a screening question designed to identify the target audience for the survey This screening question asked, "Do you know what a credit card is?" Respondents who answered "No" were deemed outside the target demographic and were instructed to discontinue their participation in the survey.
The second section examined the factors influencing credit card usage, utilizing measurement scales established by previous researchers To prevent biased responses, the names of all concepts were removed from the questionnaire, and all questions were organized in a single, continuous table.
Demographics information included income, gender, age and education of the respondents was mentioned in third section Such information was used to classify and compare groups of respondents h
Table 3.1 Summarize the reference sources of measurement scale used for each factors
I apply for credit card to get free gifts
I spend using credit card to earn points and exchange for gifts
I was attracted by the cash rebate system, thus I always spend using credit card
There are more advantages with credit card payments, than with cash
It is more convenient to use credit card payment, rather than cash
Using a credit card means that I do not have to worry about taking too much cash with me
It is necessary to have a credit card with me when I travel overseas
It is safer to use credit cards payment compared to cash payment
Using credit card would be compatible with my lifestyle
Selecting credit card matches the way I like to manage my financial transactions
Selecting credit card to perform financial transactions matches the way
I think my money could be stolen easily if I use credit card
I do not feel completely secure when providing personal information while using credit card
I am worried when using credit card because other people could access my account
Credit card system is not secure
I prefer to use a credit card regularly
I occasionally use a credit card for only specific purchases
I like to use a credit card and not prefer to make payment by cash
I am thinking of applying for a new credit card
Sample size and sampling method were determined in this step
A survey was conducted in Ho Chi Minh City, utilizing a convenience sampling technique for participant selection The target respondents were residents of Ho Chi Minh City.
For effective exploratory factor analysis (EFA), a sufficient sample size is crucial, with a minimum requirement of at least 100 participants or five times the number of variables being analyzed According to Hair et al (2009), this ensures the reliability and validity of the statistical results, emphasizing that the sample size must meet the condition n ≥ 100 and n ≥ 5k, where k represents the number of variables.
The model in this study consist 5 factors with 18 variables so that the necessary sample size should be: 19*5= 95 observations
For standard multiple regression analysis, Nguyen (2011) emphasized that the sample size must satisfy: n > 50 + 8m ( m: number of independent variables)
This research involved four independent variables, necessitating a minimum sample size of 82 observations for multiple regression analysis, calculated using the formula n > 50 + 8 * 4 This formula, as noted by Green (cited in Nguyen, 2011), is suitable for models with fewer than seven variables.
Summarily, with 15 dependent variables and 4 independent variables, this research needs 100 observations at least for running EFA and regression h
As mentioned above, the minimum sample size needed for data analysis is 100, hence, for this survey; more than 200 questionnaires were distributed directly via
A survey conducted by Google targeted students from the International School of Business and employees from Microsoft Company and Saigon Public Lighting Company (SPLC), along with additional participants A total of 40 paper questionnaires were distributed, resulting in 158 responses, which reflects a response rate of approximately 49.1 percent.
Table 3.2 Source of data collection
Source Distributed Collected Eliminated Valid
However, there only 118 responses were qualified for data analysis process Total
Out of the initial 40 responses, 14 questionnaires were discarded due to respondents' lack of knowledge about credit cards, while 26 were eliminated for being invalid, either by selecting the same option for all questions or providing implausible answers Ultimately, 118 valid questionnaires were utilized for this research, meeting the required minimum sample size for analysis.
Data analysis method
The data collected were analyzed using SPSS version 16, a statistical software package Initially, the validity and reliability of the scale instrument were assessed through Cronbach’s Alpha analysis and Exploratory Factor Analysis.
In the study, items that did not meet the reliability and validity criteria were excluded prior to conducting regression analysis Ultimately, multiple regression techniques were employed to assess the correlations and determine the impact of each independent variable on credit card usage.
In summary, this chapter described the choice and adaption of measurement scale construction, sample size, and research method employed to process the collected data
A comprehensive questionnaire was created and distributed both directly and via email for data collection The study was structured in three phases: the initial qualitative phase involved in-depth interviews, followed by a quantitative pilot phase, and concluding with a quantitative main survey The in-depth interviews aimed to refine the measurement scale, leading to slight adjustments in the questionnaire for enhanced clarity and accuracy The main survey was conducted after these revisions were implemented based on the pilot survey findings The subsequent chapter will present the data analysis results from the main survey.
DATA ANALYSIS
Respondents’ demographics
The results of the demographics analysis were summarized in table 4.1
Initial analysis of data indicated that gender was not equally between female and male Female was slight dominant with 55.93% of respondents and male was 44.07% of respondents
The study primarily involved young adults aged 26 to 35, comprising 69.49% of the total respondents Additionally, 12.71% of participants were between 19 and 25 years old, while 16.95% fell within the 36 to 45 age range, with only one respondent being older than 45.
Education was divided in 3 groups with post-graduated group occupied 52.54%, under-graduated group occupied 33.90% Moreover, the percentage of respondents in college group was just 13.56
Income per month of most of respondents was rather high 35.59% respondents revealed that their income ranged from 6 to 12 million VND 27.97% respondents’ had h
31 income from 12 to 18 million VND There were about 32.20% people earned more than
18 million VND every month, and the last portion with the lowest percentages 4.25% was the respondents with the income under 6 million VND per month
Table 4.1 Respondents' characteristic Demographic profile Category Frequency Percentage (%)
Income less than 6 5 4.24 from 6 to 12 42 35.59 from 12 to 18 33 27.97 more than 18tr 38 32.20
Reliability Analysis
The reliability test for each construct in the measurement scale was essential to ensure the instrument's dependability in this research A Cronbach’s Alpha test was conducted, requiring a value of at least 0.6 to confirm the reliability of each scale item (Nguyen, 2011) Additionally, the Corrected Item-Total Correlation was significant, indicating that an item is closely related to the overall scale if its correlation with the total of other items exceeds 0.3 This correlation suggests that the item contributes positively to the overall rating.
If the Corrected item-total correlation for any item is negative or falls below 0.3, it is essential to review the measurement scale for potential wording or conceptual issues (Leech et al., 2005) In such cases, modifications or deletions of the problematic items are necessary.
The study revealed a high internal reliability for most test item scales, including Bank Policy, Convenience, Compatibility, and Risk Barriers, with Cronbach’s Alpha values around 0.7 However, the Use scale exhibited a lower reliability with a Cronbach’s Alpha of 0.582 To enhance the reliability of this scale, Item Use 4 was removed due to its corrected Item-Total correlation of 0.141, which was below the acceptable threshold of 0.3 The subsequent tables present the results following the deletion of Item Use 4.
Table 4.2 Reliability Statistics Observed Variable Scale Mean if
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted Bank’s Policy: Cronbach's Alpha = 0.727
Exploratory Factor Analysis (EFA)
Exploratory factor analysis (EFA) was conducted to confirm construct validity and examine the relationships between variables, allowing for the identification of how a large set of items cluster together (Leech et al., 2005) In this study, EFA utilized Varimax rotation to eliminate items with low loadings on the construct Specifically, the convenience item was removed due to a loading factor of 0.34, adhering to the strict criterion of deleting factors with loadings below 0.5.
Table 4.3 KMO and Bartlett's Test of Independent Variables
Table 4.3: KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .756
The KMO value of 0.756, exceeding the threshold of 0.7 (Nguyen, 2011b), indicates that there are sufficient items to measure each construct Additionally, the significant Bartlett’s test (with a significance value of less than 5%) confirms that the variables are highly correlated, providing a solid foundation for factor analysis Overall, the diagnostic tests demonstrate that the data is appropriate for factor analysis.
Table 4.4: Rotated Component Matrix a for Independent Variable
The Rotated Component Matrix (refer to Table 4.4) displays the items and factor loadings after rotation, with all loadings exceeding 0.5 A total of 14 items representing four independent variables were organized into these four distinct components.
The analysis revealed that the items within each construct were clearly defined, as they grouped together in a single component with strong loadings after rotation, indicating effective conceptualization without mixing into other components.
In addition, the cumulative of the four factors accounted for 64.052 percent of variance (Table 4.5) It meant that more than a half of variance could be explained by four factors
Table 4.5: Total Variance Explained of Dependent Variables
KMO equal 0.637 was acceptable (Nguyen, 2011) In other words, there were enough items to measure each construct The Bartlett’s test was also significant
(significance value was less than 5%) showing that the variables were well correlated
Table 4.6: Table KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .637
As shown in the table 4.7 the total 3 items of dependent variable clustered into one component This showed that the items of this construct were very well conceptualized
Table 4.7: Rotated Component Matrix for Dependent Variable
Table 4.8 reveals that one factor accounts for 63.581% of the Total Variance Explained, indicating that this factor explains more than half of the variance in the data.
Table 4.8: Total Variance Explained of Independent Variables
Initial Eigenvalues Extraction Sums of Squared Loadings
Multiple Regression Analysis
A multiple regression analysis was performed to test hypotheses 1 to 4, with bank policies, convenience, compatibility, and risk barriers serving as independent variables and credit card use as the dependent variable Prior to executing the multiple regressions, it was essential to ensure that all necessary assumptions were met.
Leech et al (2005) claimed five main assumptions:
Assumption 1: No significant outliers or influential points
Assumption 2: The residuals were independent
Assumption 3: The linear relationship between independent variables and dependent variable occurred
Assumption 4: The residual was distributed normally
Assumption 5: No multicollinearity among independent variables h
Case Number Std Residual use Predicted
According to Table 4.9, case number 59 was outlier because its standard residual was equal -3.555 < -3 So, this case number would be removed.
The data was checked again to find out any cases with outliers After checking again, there were no more significant outliers So now this data could be processed Assumption 2
To evaluate the assumption of residual independence, the Durbin-Watson value was analyzed A Durbin-Watson value ranging from 0 to 4, with an optimal value near 2, indicates that the residuals are independent As shown in Table 4.10, the Durbin-Watson value was 2.242, confirming that the second assumption was met satisfactorily.
The overall regression plot shape is crucial for testing assumptions, as demonstrated in Figure B1 of Appendix B, where the residuals resemble two equal-sided bells centered around a mean of nearly zero Additionally, Figure B2 shows that most plots are linearly distributed, further supporting this assumption.
The validity of this assumption is supported by the residual scatterplot chart, which shows that the residuals are randomly distributed around zero This indicates that the data satisfies the requirement for normally distributed residuals As illustrated in Figure B3 of Appendix B, this assumption was upheld in the research conducted.
Before conducting multiple regressions, it is crucial to address the assumption of multicollinearity This issue arises when independent variables exhibit high inter-correlations, indicating overlapping information among predictors (Leech et al., 2005) To effectively assess multicollinearity, a correlation matrix serves as a valuable tool.
Con Bank com Risk use
** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed) c Listwise N7 h
The Pearson test results from the Correlations matrix indicated a value lower than 0.8, suggesting a low likelihood of multicollinearity However, the Correlation matrix occasionally fell short in detecting multicollinearity, making the variance inflation factor (VIF) a more reliable indicator for this issue Consequently, it is essential to focus on the VIF values presented in the Coefficients table (refer to Table 4.12) to draw the most accurate conclusions.
In summary, the data almost met all the required assumptions Therefore, all predictors were qualified enough for multiple regression analysis
Results of multiple regression analysis
This research used the enter method to compute multiple regression It meant all four predictors would be input simultaneously for considering their impact on dependent variable
Std Error of the Estimate
1 785 a 616 602 41492 2.242 a Predictors: (Constant), risk, con, bank, com
The Model Summary table 4.11 indicates a multiple correlation coefficient (R) of 0.785, with an R Square value of 0.616 and an adjusted R Square of 0.602 This suggests that 60.2% of the variance in credit card usage can be predicted by four independent variables, demonstrating a strong fit for the model used in this study.
The dependent variable could be predicted by four independent variables with the value of F was 43.266 and significance value was lower than 0.05 in Table 4.12
B Std Error Beta Tolerance VIF
(Constant) 232 382 606 546 bank 121 050 147 2.425 017 945 1.058 con 532 072 528 7.362 000 679 1.474 com 332 082 288 4.067 000 697 1.436 risk -.082 061 -.082 -1.352 179 957 1.045 a Dependent Variable: use
Squares df Mean Square F Sig
Total 55.455 117 a Dependent Variable: use b Predictors: (Constant), bank, com, risk, con h
Table 4.13 presents the coefficients of multiple regression, highlighting the variance inflation factors (VIF) that indicate multicollinearity among predictor variables According to Hair et al (2009), VIF values above 4 suggest potential issues, while those exceeding 10 indicate serious multicollinearity concerns In this analysis, all VIF values ranged from 1.049 to 1.464, indicating that multicollinearity did not pose a threat to the validity of the final results.
Hypothesis 1: There is a positive impact of bank policy on credit card use
The analysis revealed a Beta value of 0.124 and a Sig value of 0.042 for bank policy, indicating a significant positive relationship with credit card usage Supporting this finding, Teoh et al (2013) demonstrated that benefits provided by issuing banks significantly influence the spending behavior of Malaysian credit card holders Consequently, Hypothesis 1 is validated within the research model.
Hypothesis 2: There is a positive impact of convenience on credit card use
The analysis presented in Table 4.13 indicates that the Beta value for convenience is 0.539, with a significance value (Sig) of 0.00, which is below the 0.05 threshold This suggests that convenience positively influences the adoption and use of credit cards Supporting this finding, Khare et al (2011) identified convenience as a key predictor of credit usage The results of this study align closely with Khare et al.'s previous research, confirming a strong correlation between the two studies Consequently, Hypothesis 2 is upheld within the model.
Hypothesis 3: There is a positive impact of compatibility on credit card use h
This analysis reveals a significant relationship between perceived compatibility and credit card usage, indicating that increased income enhances customers' lifestyles and their desire for improved living standards Lee and Kwon (2002) identified lifestyle trends as a key factor influencing credit card adoption With a β value of 0.307 and a p-value of 0.00, the findings confirm hypothesis 3.
Hypothesis 4: There is a negative impact of risk barriers on credit card use
The analysis indicated that H4 was not supported by the data, as shown by the coefficients (p > 0.05) This finding aligns with Rammile and Nel's (2012) study, which concluded that risk barriers do not influence customers' intentions to use mobile finance services Additionally, during in-depth interviews with five respondents regarding four risk barrier measurement items, three participants expressed that risk barriers did not impact their use of credit cards They believed that credit card systems were reliable due to significant investments by banks in their IT infrastructure Supporting this, Dang (2013) noted that many banks in Vietnam have made substantial investments to modernize their banking systems.
Since 2007, the IT system and infrastructure have evolved significantly, contributing to consumer confidence in credit card usage According to the Lafferty report (2013), consumers perceive credit card transactions as low-risk, largely due to advanced technology and secure access codes provided by financial institutions Additionally, Vietnam's fraud rate stands at approximately 0.15% of total card transactions, considerably lower than the global average of 0.6% The survey indicates that most respondents are highly educated and familiar with advanced technology, leading them to view risks as minimal barriers to credit card use.
In conclusion, three out of the four determinant variables—bank policy, convenience, and compatibility—showed positive impacts on credit card usage Notably, the convenience factor had the strongest influence on customers in Ho Chi Minh City, with a Beta value of 0.539, indicating its significance in driving credit card adoption.
As not as expectation, risk barrier did not affect to credit card use of customers in
Ho Chi Minh City With significant higher than 0.05, so risk barrier was not the predictor of dependent factor
The results of testing all hypotheses in this research were summarized briefly in the below table
Table 4.13 Summary of hypotheses testing result
No Hypotheses Testing result Beta Sig
H1 Hypothesis 1: There is a positive impact of bank policy on credit card use Supported 0.124 0.042
H2 There is a positive impact of convenience on credit card use Supported 0.539 0.000
H3 There is a positive impact of compatibility on credit card use Supported 0.307 0.000
H4 There is a negative impact of risk barriers on credit card use Not supported -0.037 0.538
This chapter summarizes the data analysis results, focusing on measurement scales, the research model, and hypotheses It includes findings from reliability tests and exploratory factor analysis (EFA) to identify the most reliable measurement scales suitable for each hypothesis.
46 construct Multiple regression analysis result demonstrated that most of independent variables had tight relationships with dependent factor h
CONCLUSION, IMPLICATIONS, AND LIMITATIONS
Conclusion
This research investigates the relationship between credit card usage among customers in Ho Chi Minh City and key influencing factors, including bank policies, convenience, compatibility, and risk barriers These factors were identified through an extensive review of prior studies on credit card utilization and mobile financial services.
The previous chapter's findings reveal positive relationships between bank policies, convenience, and compatibility with credit card usage, while the risk barrier predictor was not confirmed in this research This aligns with Rammile & Nel (2012), which also found that risk barriers do not negatively impact mobile finance service usage Among the variables studied, perceived convenience emerged as the most significant factor influencing credit card use in Ho Chi Minh City, with a coefficient of β = 0.539, followed by perceived compatibility at β = 0.307 and bank-provided policies at β = 0.124.
This empirical research highlights the key factors influencing credit card usage in Ho Chi Minh City, providing valuable insights for marketers Additionally, it offers practical recommendations for credit card issuers to develop effective marketing strategies tailored to their business needs.
Managerial Implications
This study, although based on an analysis of just 118 credit card holders, reveals valuable insights The findings can benefit credit card providers seeking to better understand their customers' preferences and behaviors.
48 expectation to improve their product’s attributes and marketing plans as well This way, their products can best match with what customers are looking for
This study supports the relationship between bank policies and credit card usage, highlighting that benefits offered by banks significantly influence consumer behavior In a competitive market, credit card issuers provide various incentives to attract both potential and existing cardholders, which directly impacts their adoption and usage, as noted by Zinman (2009) Since bank policies are key factors in credit card adoption, consumers are more likely to favor banks with attractive offerings Additionally, Khare et al (2011) suggest that customers are inclined to spend more when incentivized by cash rebates or points systems Consequently, credit card providers in Vietnam should consider implementing more favorable policies and promotional programs to encourage both new and existing customers to apply for credit cards.
The use of credit cards in Ho Chi Minh City aligns with previous research, indicating that convenience perception significantly influences credit card usage This finding is consistent with the studies conducted by Khare et al (2011) and Maysami and Williams, highlighting the importance of convenience in consumer credit card behavior.
Despite Vietnam's cash-centric culture, many respondents view credit cards as a convenient and advantageous alternative In in-depth interviews, participants emphasized the necessity of having a credit card while traveling abroad, indicating that previous international travel experiences have heightened their appreciation for credit card utility This suggests that banks should consider promoting credit card usage to enhance customer convenience during travel.
49 non-banks may consider to deploy the advertising programs which increase the awareness about the convenience of credit card use to customers
Banks can enhance credit card usage by highlighting compatibility with consumers' jobs and lifestyles in their promotional communications Offering trial periods for credit card usage can help customers become familiar with the product, increasing their comfort level Additionally, credit card providers should focus on the emotional benefits in their marketing campaigns to showcase how credit cards can enhance customers' enjoyment in their daily lives.
This study offers valuable insights into the influence of banking policies, convenience, and compatibility on credit card usage among consumers in Ho Chi Minh City From an academic standpoint, it reinforces existing theories related to the credit card industry by identifying key factors that affect credit card adoption Additionally, the research provides actionable recommendations for credit card issuers, enabling them to develop effective marketing strategies tailored to their target audience.
Limitations and future research
Due to time and resource constraints, data were conveniently gathered from friends and colleagues of the author, primarily from the middle to upper class in Ho Chi Minh City, which limits its representativeness The small sample size raises concerns about generalizability, suggesting that future research should involve a larger, more diverse sample By including participants from various demographic groups, stronger conclusions regarding the relationships between the variables can be established.
Ho Chi Minh City presents a promising market for credit card issuers, but other regions in Vietnam also offer significant opportunities for banks to expand their services Future research should consider broadening the scope to encompass the entire country and analyze the variations in credit card usage across different areas.
Future research should focus on the implications of financial risks and transaction costs influenced by social trends, as emerging fashion trends may lower customers' perceived risk and enhance their acceptance of credit cards.
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Hoa Phan, a Master's student at the University of Economics Ho Chi Minh City, is conducting research on the factors influencing credit card usage among customers in Ho Chi Minh City To assist in this study, please complete a brief questionnaire about your credit card behavior, which will take no more than 10 minutes Your responses are vital to the research, and participation is completely voluntary.
Your personal information will remain confidential and will not be shared without your consent For any inquiries or concerns regarding this study, including scientific aspects or procedural guidance, please reach out via email at ptahoa@yahoo.com.vn or call +84 916920099.
This section of the questionnaire explores your knowledge regard to credit cards
1 Have you known credit card?
If your answer for question 1 is No, you can stop your work here Thank you for your co-operation in completing this questionnaire
If your answer for question 1 is Yes, please continue answering the questions in Section
This section explores your behavior to credit card use
To what extent do you agree with each of the following statements, please indicate h
60 your answer using the following 5-point scale where:
1 I apply for credit card to get free gifts 1 2 3 4 5
I spend using credit card to earn points and exchange for gifts 1 2 3 4 5
I was attracted by the cash rebate system, thus I always spend using credit card 1 2 3 4 5
There are more advantages with credit card payments, than with cash 1 2 3 4 5
It is more convenient to use credit card payment, rather than cash 1 2 3 4 5
Using a credit card means that I do not have to worry about taking too much cash with me
It is necessary to have a credit card with me when I travel overseas 1 2 3 4 5
It is safer to use credit cards payment compared to cash payment 1 2 3 4 5
Using credit card would be compatible with my lifestyle 1 2 3 4 5
Selecting credit card matches the way I like to manage my financial transactions 1 2 3 4 5 h
Selecting credit card to perform financial transactions matches the way I do my job 1 2 3 4 5
I think my money could be stolen easily if
I do not feel completely secure when providing personal information while using credit card
I am worried when using credit card because other people could access my account
15 Credit card system is not secure 1 2 3 4 5
16 I prefer to use a credit card regularly 1 2 3 4 5
I like to use a credit card for specific purchases 1 2 3 4 5
I like to use a credit card and not prefer to make payment by cash 1 2 3 4 5
I am thinking of applying for a new credit card 1 2 3 4 5
This section of the questionnaire refers to background or biographical information The information will allow me to classify and compare groups of respondents
4 Income per month (1,000,000vnd / month) from 12 to 18 han 18tr
Thank you for your co-operation in completing this questionnaire! h
Tôi tên Phan Thị Ái Hoa, hiện đang là học viên cao học của Trường Đại Học Kinh Tế
Tôi đang tiến hành nghiên cứu về hành vi sử dụng thẻ tín dụng của khách hàng tại TP Hồ Chí Minh và rất mong nhận được sự hỗ trợ từ Anh/Chị bằng cách dành khoảng 10 phút để hoàn thành Phiếu khảo sát này Mặc dù câu trả lời của Anh/Chị là rất quan trọng cho nghiên cứu của tôi, nhưng việc tham gia khảo sát hoàn toàn không bắt buộc.
Thông tin cá nhân của bạn sẽ được bảo mật hoàn toàn Nếu bạn có bất kỳ câu hỏi nào trong quá trình thực hiện khảo sát, xin vui lòng liên hệ với tôi qua email ptahoa@yahoo.com.vn hoặc số điện thoại 0916920099.
Xin trân trọng cảm ơn,
Phần này tìm hiểu về kiến thức của Anh/Chị về thẻ tín dụng
1 Bạn có từng biết các loại thẻ tín dụng không?
Nếu bạn trả lời "Không" cho câu hỏi đầu tiên, bạn có thể ngừng tham gia khảo sát tại đây Chúng tôi chân thành cảm ơn sự hỗ trợ của bạn.
Nếu câu trả lời của Anh/Chị cho câu 1 là Có, xin Anh/Chị vui lòng tiếp tục trả lời các câu hỏi ở phần B và phần C
Phần này khảo sát về hành vi sử dụng thè tín dụng
Xin vui lòng cho biết mức độ đồng ý của bạn đối với các phát biểu dưới đây bằng cách đánh dấu (X) vào ô tương ứng Ô số 1 thể hiện sự hoàn toàn không đồng ý, ô số 2 cho thấy bạn không đồng ý, và ô số 3 là trung dung.
64 Ô số 4: Đồng ý Ô số 5: Hoàn toàn đồng ý
Tôi đăng kí sử dụng thẻ tín dụng để nhận được quà tặng 1 2 3 4 5
Tôi thanh toán bằng thẻ tín dụng để tích lũy điểm để đổi quà 1 2 3 4 5
Tôi bị thu hút bởi hệ thống tích lũy điểm để được trả lại tiền mặt, vì vậy tôi luôn luôn thanh toán bằng thẻ tín dụng
Thanh toán bằng thẻ tín dụng có nhiều lợi ích hơn so với thanh toán tiền mặt 1 2 3 4 5
Thanh toán bằng thẻ tín dụng thuận tiện hơn so với thanh toán bằng tiền mặt 1 2 3 4 5
Sử dụng thẻ tín dụng giúp tôi giảm áp lực vì không phải đem theo nhiều tiền mặt 1 2 3 4 5
Tôi thấy thẻ tín dụng rất hữu ích khi đi nước ngoài 1 2 3 4 5
Sử dụng thẻ tín dụng an toàn hơn sử dụng tiền mặt 1 2 3 4 5
Sử dụng thẻ tín dụng phù hợp với phong cách sống của tôi 1 2 3 4 5
Sử dụng thẻ tín dụng phù hợp với cách thức quản lí tài chính của tôi 1 2 3 4 5
Sử dụng thẻ tín dụng để thanh toán phù hợp với công việc của tôi 1 2 3 4 5
Khi sử dụng thẻ tín dụng, tôi nghĩ tôi có thể bị mất tiền 1 2 3 4 5 h
Việc tiết lộ thông tin cá nhân khi thanh toán bằng thẻ tín dụng làm tôi cảm thấy bất an
Tôi thấy lo lắng khi sử dụng thẻ tín dụng vì người khác có thể truy cập vào tài khoản của tôi
Hệ thống thẻ tín dụng không đảm bảo an toàn 1 2 3 4 5
Tôi thích sử dụng thẻ tín dụng thường xuyên 1 2 3 4 5
Tôi thích sử dụng thẻ tín dụng để thanh toán cho những lần mua hàng đặc biệt 1 2 3 4 5
Tôi thích sử dụng thẻ tín dụng và không muốn thanh toán bằng tiền mặt 1 2 3 4 5
19 Tôi dự dịnh đăng kí thẻ tín dụng mới 1 2 3 4 5
III Phần C – Thông tin cá nhân
Đoạn này yêu cầu thông tin cá nhân từ Anh/Chị để phục vụ cho việc phân loại và so sánh các nhóm đối tượng trong khảo sát Xin vui lòng cung cấp một số thông tin cần thiết.
Phổ thông trung học Cao đẳng Đại học Sau đại học
4 Thu nhập hàng tháng (VNĐ/tháng) ít hơn 6 triệu từ 6 triệu đến 12 triệu từ 12 triệu đến 18 triệu nhiều hơn 18 triệu h
CẢM ƠN ANH CHỊ ĐÃ THAM GIA KHẢO SÁT - h
APPENDIX C: Histogram, Normal Regression & Scatter plot of Dependent
Figure B2: Normal Plot of Use h