INTRODUCTION
Research background
The overview about credit card use in over the world and Vietnam is discussed in this section
Credit cards are defined as a form of available money that allows users to make purchases now and pay later (Mitchell & Mickel, 1999) Globally, consumers prefer credit cards for various transactions, ranging from utility bills to shopping and major purchases like cars and homes The rise of the middle-income population and increased access to bank accounts have fueled this trend Additionally, advancements in technology have significantly transformed credit card services and their delivery (Suoranta, Mattila & Munnukka, 2005) As a result, more individuals and businesses are adopting credit cards for electronic financial transactions, leading to a surge in their popularity This growing demand has intensified competition among credit card providers striving for a larger market share.
The credit card market has experienced substantial growth since the introduction of credit cards in the 1950s in the USA, with a rising number of customers now holding credit cards Unlike other payment methods, credit cards offer long-term credit without requiring collateral at the time of purchase Initially, banks restricted credit card access to wealthy individuals, but over time, they have relaxed their qualifications, allowing more customers to apply The rapid economic growth in Asian countries has further expanded opportunities for credit card adoption, with the Asia Pacific region accounting for $1.3 trillion in credit card usage in 2007, representing 30% of global transactions Japan, South Korea, and Australia lead the region in total credit card transactions Given the significant increase in credit card usage in emerging markets, understanding customer behavior in these regions is crucial Researchers attribute this growth to the rise of new middle-income consumers and advancements in technology, making these markets increasingly attractive to global credit card providers.
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 an estimated 64 million payment cards, with credit card usage reaching 3.6% This marks a significant increase from the 1% reported by Nielsen Research in 2011, highlighting the rapid growth of credit card adoption in the country The widespread use of credit cards has been further supported by the government's Decision 291/QD-TTg in 2006, which established a plan for promoting non-cash payments from 2006 to 2010, 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 is making significant strides towards becoming a cashless society by enhancing infrastructure for non-cash payments and encouraging financial institutions to adopt advanced technologies A study by Spire Research and Consulting highlights that the banking and credit card sectors in Vietnam have experienced rapid growth over the past decade Notably, the share of cash transactions in the overall card payments channel has declined from 3.4% in 2009 to 2.7% in 2013, while card transactions have risen from 1.5% during the same period.
The Vietnam credit card market is projected to undergo significant transformations over the next decade, with growth from 3.1% in 2013, as noted by Dang (2013) Major global banks like Citibank, ANZ, and HSBC, along with local institutions such as Vietcombank, Vietinbank, and Maritimebank, are actively launching various promotional programs to enhance customer awareness and adoption of credit cards in Vietnam.
Vietnam's credit card market faces significant challenges due to a large unbanked population and a strong reliance on cash for daily transactions Despite an urban population growth rate of approximately 3.5% in recent years, Vietnam remains one of the least urbanized countries in emerging Asia, with many residents living in rural areas engaged in textiles, agriculture, and fisheries As of 2012, only 20% of the population had bank accounts, and among these, only half utilized consumer banking services actively Even those who possess credit or debit cards often prefer cash for their everyday payments.
Vietnam is emerging as a prime destination for the credit card market due to several key advantages As one of the fastest-growing economies in Asia, the country's GDP per capita has seen a significant increase, rising from US$1,097.1 in 2009 to US$1,728.4 during the review period.
The socio-economic developments in Vietnam since 2013 have significantly improved the quality of life for its citizens (Business Journal, 2014) According to Lawrence (2003), credit cards offer numerous benefits, including convenience in payments, a tool for cultivating financial responsibility, a resource for emergencies, and a means to build a solid credit history, ultimately leading to greater access to credit in the future (p 5) As a result of these advantages, credit cards have become increasingly popular in Vietnam, reflecting the country's ongoing socio-economic progress.
Vietnam's young population, with a median age of 25 and projected to reach 94.5 million by 2016, presents significant opportunities for short- to medium-term economic growth The evolving payment habits in Vietnam further enhance the potential of the credit card market Since January 2011, foreign bank branches have been treated on par with domestic banks due to Vietnam's WTO commitments, allowing them to establish wholly owned subsidiaries and branches This has led to increased competition, with overseas banks introducing advanced technologies and innovative marketing strategies Consequently, credit card ownership has become more accessible, and usage is rising, particularly in major cities like Ho Chi Minh City and Hanoi.
Research motivation
Vietnam is emerging as a promising market for international credit card providers, driven by its young population, expanding middle class, and significant economic growth potential Despite challenges such as limited credit card usage and a lack of consumer familiarity, the country presents opportunities for growth, particularly as network infrastructure improves However, success in this competitive landscape requires more than just recognizing these advantages; credit card issuers must implement effective marketing strategies and deeply understand customer needs Conducting thorough research to identify the key factors influencing credit card usage is essential for providers to enhance their understanding of consumer behavior, which is crucial for developing long-term strategies to capture market share in Vietnam's payment card industry This necessity motivates the author to pursue further research in this area.
Research on credit card usage in Vietnam is scarce compared to numerous studies conducted in other countries This lack of research in emerging market economies, including Vietnam, highlights the need for a deeper understanding of the factors influencing credit card adoption Given the unique legal, structural, cultural, geographical, and socio-economic differences, various factors may affect credit card usage This study aims to explore the predominant factors influencing credit card use specifically in Ho Chi Minh City, Vietnam.
Research objective
This study aims to investigate the key factors influencing credit card usage among customers in Ho Chi Minh City, focusing on specific research questions to provide a comprehensive understanding of the subject.
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 is conducted to refine the measurement scale, followed by a quantitative pilot study involving face-to-face and online surveys to ensure clarity and functionality The finalized questionnaire is distributed to respondents via Google Survey and paper formats Data analysis is performed using SPSS software, encompassing three key stages: assessing the measurement scale's reliability with Cronbach’s Alpha, validating it through Exploratory Factor Analysis (EFA), and employing simple and multiple regression analyses to explore the relationships among the research model's factors.
This thesis examines credit card usage among residents of Ho Chi Minh City, the largest city in Vietnam, known for its youthful and tech-savvy population with high income levels The research aims to uncover the key factors that influence credit card adoption and usage among these consumers Participants in the study include individuals living in Ho Chi Minh City who possess knowledge 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 providers in Vietnam The research findings offer crucial information that enables credit card issuers to develop and implement effective strategies tailored to their target consumers' preferences, as well as their application and usage behaviors.
Research on credit card usage in Vietnam is scarce, highlighting a gap in understanding the factors influencing this behavior This study employs a multi-faceted framework to examine the impact of bank policies, convenience, compatibility, and risk barriers on Vietnamese consumers' credit card use By contributing to the existing literature, it aims to inspire further research in emerging market economies to explore whether the findings are consistent or vary across different contexts.
Research structure
This study is organized into five chapters
The introduction chapter outlines the research by providing essential background information, articulating the motivation behind the study, and defining the research objectives Additionally, it discusses the research methodology, scope, and highlights the contributions of the research.
Chapter two examines existing theories related to credit card usage, focusing on four key factors influencing customer behavior in Ho Chi Minh City: bank policies, convenience, compatibility, and perceived risk barriers Additionally, this chapter proposes a research model with specific 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 redeemable rewards, and cash rebates on purchases made with credit cards (Teoh et al., 2013).
Experts emphasize that effective policy is crucial for banks to attract new customers and maintain the loyalty of existing ones Dowling and Uncles (1997) identify competition as a driving force behind the implementation of various customer loyalty programs To entice customers to apply for credit cards, many banks offer diverse incentives (Chakravorti, 2003) The intense competition in the credit card market has prompted banks to enhance their product offerings (Subramaniam & Marimuthu, 2010) Liu (2009) suggests that credit card marketers should effectively communicate the details of reward points programs, including redemption procedures and benefits, to raise awareness among current and potential customers By broadening the benefits, easing application qualifications, adopting more flexible payment policies, and implementing unique strategies, banks can significantly boost their number of credit card holders (Teoh et al.).
Customers perceive credit cards and banking services as a bundled offering, which includes incentives such as no annual fees for the first year, cash rebates, point rewards, airline miles, and shopping discounts (Akin et al., 2011) A recent trend in the industry is the provision of gifts upon applying for a credit card, which serves as an effective motivator for customers to obtain new cards (Liu, 2009) Additionally, benefits such as coverage for lost credit cards, travel accident protection, and support for cardholders facing unemployment or illness further enhance the appeal of these financial products.
Zinman (2009) argues that the incentives offered to customers significantly influence their choice to use credit cards as their primary payment method Furthermore, to examine the impact of bank policies on credit card usage in Vietnam, the following hypothesis has been formulated.
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, especially when traveling abroad Credit cards are easier to use than carrying large amounts of cash and offer a safer payment option compared to cash transactions (Khare et al., 2011).
Numerous studies have explored the convenience and inconvenience associated with credit card usage Research by Khare et al (2013) and Safakli (2007) highlights that "convenience," along with "easiness and safety," are crucial elements for developing effective marketing strategies to meet the needs of both current and potential customers In the Greek credit card market, convenience stands out as the most significant factor influencing credit card usage, contributing to 37 percent of overall use (Meidan & Davos).
Credit cards are increasingly popular among women due to their convenience and security, as highlighted by Ahmed, Amanullah, and Hamid (2009) In China, they are primarily used for travel and entertainment (2007), while Khare (2011) notes that credit card usage is linked to convenience, local acceptance, and status The rise in credit card popularity is attributed to the ease of not carrying cash and their role as readily available credit sources (Lee and Kwon, 2002) A study by Kaynak, Kucukemiroglu, and Ozmen (1995) in Turkey identifies emergency funds, travel convenience, and shopping cash availability as key reasons for credit card use Durkin (2000) emphasizes that credit cards have become essential for routine purchases and transactions that may be inconvenient without them Furthermore, holding 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 faces significant challenges, primarily due to low acceptance rates, with 60% of POS transactions being international and domestic use concentrated in major cities where POS systems are predominantly found in shopping malls and high-end retailers Scholars highlight factors like entrenched cash habits and limited acceptance, making credit cards less convenient in emerging markets Laforet and Li (2005) identify the traditional cash-based banking culture as a key barrier to online banking adoption among Chinese consumers Furthermore, Khalid et al (2013) suggest that the low acceptability of credit cards represents a non-monetary cost that should be acknowledged In Hong Kong, Chan (1997) found that inactive credit card users face limited acceptance due to the unrestricted usage rates of their 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, affluent urban Vietnamese individuals drawn to a modern lifestyle, which encompasses their interests, resource allocation, and self-perceptions (Kucukemiroglu, 1999) This lifestyle distinction highlights that it differs from personality traits Additionally, the purchasing decisions of certain brands are influenced by lifestyle choices, as noted by Sjoberg & Engelberg (2005).
Research on the compatibility of credit cards with user behavior is scarce However, compatibility is a key factor influencing behavioral intention, as noted by Rogers (2003) When users perceive a credit card as compatible with their needs, they are more likely to adopt it (Scott et al., 2014).
Research indicates that the primary factor driving the adoption of mobile banking services is their compatibility with customer needs (Chemingui and Lallouna, 2013) A strong direct relationship exists between compatibility and the intention to use mobile banking (Wessels and Drennan, 2010) Furthermore, customers are more inclined to embrace mobile banking when they perceive it as aligning with their lifestyles and preferences (Lin, 2011) As highlighted by Ilie et al (2005), greater compatibility between individual needs and technological innovations enhances the likelihood of adoption, allowing users to understand and integrate these innovations within a familiar context.
Liang et al (2006) highlight the appeal of using credit cards, allowing consumers to enjoy immediate purchases while deferring payment Khare et al (2011) emphasize the significant influence of lifestyle on credit card ownership According to Devlin, Worthington, and Gerrard (2007), credit cardholders can be categorized into two groups: convenience users, who primarily use credit cards for ease of transactions, and installment users, who rely on them for structured payments Furthermore, Mathew and Slocum reveal a correlation between social class and credit card usage, noting that individuals from higher social classes tend to use credit cards as a convenient financial tool, whereas those from lower social classes often use them for installment payments.
In 1969, Khalid noted the division of credit card users into two groups: transactors and revolvers (Worthington, Stewart & Lu, 2007) Transactor users prefer credit cards over cash for convenience, while individuals from low socio-economic backgrounds often rely on credit cards for financing (Gan, Mayrami & Koh, 2008) According to Bernthal, Crockett, and Rose (2005), credit cards symbolize a lifestyle and significantly influence customer behavior, reflecting specific values and lifestyle patterns The ability to use credit cards enables customers to attain their desired lifestyle, highlighting the integral role these financial tools play in shaping personal identity.
This study investigates the impact of compatibility on credit card usage in Vietnam, building on previous research regarding the effects of compatibility in mobile financial services and further examining the specific 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
According to research by Dukin (2000), credit cards have largely replaced traditional installment-purchase plans, becoming the main source of unsecured open-end revolving credit Security, which encompasses reliability, safety, and privacy, is crucial in protecting against credit card fraud and ensuring accurate billing, as highlighted by Arthur and Dimitris (1994) Additionally, Ram and Sheth (1989) (as cited in Rammile & Nel, 2012) emphasize that the risk barrier reflects the degree of risk associated with technological innovations This study underscores that security is a key factor for customers when choosing credit cards.
Perceived risk in financial services marketing significantly influences consumers' purchase decisions and is a critical concern for service marketers (Goyal, 2008) The prevalence of credit card payments among online vendors can limit consumer participation Park, Lee, and Ahn (2004) define perceived risk in online transactions (PRT) as the potential risks consumers face when engaging in electronic commerce Security concerns, such as the exposure of credit card information to hackers or unfamiliar vendors, remain a major issue (Sindhav & Balazs, 1999) Additionally, Tan and Teo (2000) highlight that the rise of public networks has made security concerns the primary barrier to the adoption of internet banking, indirectly linking the perceived security of credit card usage to consumer trust in online financial transactions.
Numerous studies have explored 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 risks associated with lost or stolen cards significantly influence credit card adoption Liao and Cheung (2002) highlighted confidentiality concerns as a major risk factor for customers Ahmed et al (2009) found that security plays a crucial role in credit card use within Pakistan's banking sector A survey cited by Narsi (2007) indicated that security is a primary barrier to internet banking in the U.S Similarly, Narsi (2011) noted that perceived risks hinder internet banking adoption Customers often avoid mobile banking due to fears of making errors and concerns over security, as reported by Laukkanen et al (2007), who also noted worries about losing money and personal information Conversely, Rammile and Nel (2012) and Chemingui and Lallouna (2013) found no significant impact of risk barriers on the adoption of cell phone banking and mobile financial services, respectively.
According to data from the Vietnam State Bank, only 9 out of 41 card-issuing organizations in the country have adopted chip-based security technology (Lafferty, 2013) Additionally, the overall development of high technology in Vietnam remains limited As a result, many customers are concerned about risk barriers, leading to the following hypothesis:
Hypothesis 4: There is a negative impact of risk barriers on credit card use
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
Figure 2.1 illustrates the conceptual framework, which includes four hypotheses labeled H1 to H4 These hypotheses encompass independent and quantitative variables that directly influence the dependent variable, which is 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
This chapter provides a theoretical foundation for the model, highlighting four key factors influencing credit card usage: bank policy, convenience, compatibility, and risk barriers These factors were selected 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) This was succeeded by in-depth interviews to gather qualitative insights Initially crafted in English, the survey questionnaire was subsequently translated into Vietnamese by the researcher, with assistance to ensure accuracy.
In a qualitative phase of research, the Vietnamese version of the survey questionnaire was pre-tested through in-depth interviews with five English experts over two weeks The objective was to gather their insights on the accuracy, clarity, and understandability of the questionnaire Additionally, the author sought to determine the appropriateness of the chosen measurement scale for conducting research in Ho Chi Minh City All feedback from the interviewees was collected to refine the measurement scale effectively.
The pilot survey aimed to evaluate the viability of the questionnaire rather than collect data It focused on identifying necessary modifications and improvements Following this preliminary assessment, the final questionnaire will be revised based on the pilot SPSS analysis and participant feedback.
Following the development of the final questionnaire, a large-scale survey was conducted to gather data for testing the research hypotheses Participants completed the survey independently, with most items assessed using a five-point Likert scale, ranging from "strongly disagree" (1) to "neutral" (3).
The questionnaire, utilizing a five-point scale with options ranging from "agree" (4) to "strongly agree" (5), was distributed to respondents via Google Survey and paper formats Participants received a link to the survey 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 submitted their responses.
Following was the summary of whole process for this research
Deleted 1 item (in Use scale)
Questionnaire design
The questionnaire consisted of three sections, as detailed in Appendix A The first section assessed respondents' knowledge of credit cards and included a screening question to identify the appropriate target audience The screening question asked, "Do you know what a credit card is?" Respondents who answered "No" were deemed unsuitable for the survey and were instructed to discontinue their participation.
The second section examined the factors influencing credit card usage, utilizing a model where all variables were assessed using scales created 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 table for clarity.
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
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 nonprobability convenience sampling technique to select participants The target respondents for this survey were residents of Ho Chi Minh City.
For effective exploratory factor analysis (EFA), the sample size must be sufficiently large for reliable statistical evaluation According to Hair et al (2009), the minimum sample size should be at least 100 participants, or five times the number of variables being analyzed (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 is deemed suitable for models with fewer than seven variables, as noted by Green (cited in Nguyen, 2011).
Summarily, with 15 dependent variables and 4 independent variables, this research needs 100 observations at least for running EFA and regression
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 Google survey was conducted among students from the International School of Business and employees of Microsoft Company and Saigon Public Lighting Company (SPLC), along with responses from some friends of the researcher A total of 40 paper questionnaires were distributed, resulting in 158 collected 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 40 responses deleted, 14 questionnaires revealed that respondents lacked knowledge about credit cards, while 26 were invalid due to inconsistent answers or selecting the same option for all questions Ultimately, 118 valid questionnaires were utilized for this research, meeting the minimum sample size requirements.
Data analysis method
The data collected were analyzed using SPSS version 16, focusing on the validity and reliability of the measurement instrument This was achieved through Cronbach’s Alpha analysis and Exploratory Factor Analysis to ensure robust statistical results.
Before conducting the regression analysis, items that did not meet the reliability and validity criteria were removed Subsequently, multiple regression techniques were employed to assess the correlation and quantify 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 for data collection and distributed both directly and via email to participants The study was structured into three distinct 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 improved clarity and accuracy After these revisions, the main survey was conducted based on the feedback from the pilot survey The subsequent chapter will present the results of the data analysis 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 individuals aged 26 to 35, who comprised 69.49% of the total sample Additionally, 12.71% of respondents were aged 19 to 25, while those aged 36 to 45 made up 16.95% Notably, there was only one participant over the age of 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
The majority of respondents reported a relatively high monthly income, with 35.59% earning between 6 to 12 million VND and 27.97% earning from 12 to 18 million VND Additionally, approximately 32.20% of participants indicated that their income exceeded 18 million VND.
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 is essential to ensure the developed instrument's dependability To achieve this, a Cronbach’s Alpha test was performed, requiring a value of at least 0.6 to confirm the reliability of each measurement item (Nguyen, 2011) Additionally, the Corrected Item-Total Correlation is crucial, as an item is considered closely correlated to others if its correlation with the total of the other items exceeds 0.3, indicating its suitability for inclusion in the overall rating scale.
If the corrected item-total correlation for any item is negative or below 0.3, it is essential to review the measurement scale for potential wording or conceptual issues (Leech et al., 2005) In such cases, items should be modified or removed to enhance the scale's effectiveness.
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 following tables present the results after the removal 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, revealing how a large set of items cluster together (Leech et al., 2005) In this study, EFA utilized Varimax rotation to identify items on the same scale with low loadings, leading to the deletion of the convenience item with a loading factor of 0.34, as factors with loadings below 0.5 were strictly excluded.
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, as presented in Table 4.3, exceeds the threshold of 0.7, indicating that there are sufficient items to effectively measure each construct (Nguyen, 2011b) Additionally, the significant Bartlett’s test, with a significance value below 5%, confirms that the variables are highly correlated, making them a strong foundation for factor analysis Overall, the diagnostic tests suggest that the data is appropriate for factor analysis.
Table 4.4: Rotated Component Matrix a for Independent Variable
The Rotated Component Matrix (Table 4.4) displays factor loadings exceeding 0.5 for all items, indicating a strong relationship between the variables The analysis revealed 14 items across four independent variables, which were distinctly grouped into their respective components based on high loadings Furthermore, items within the same construct clustered together in a single component without mixing with others, demonstrating that each construct is well-defined and clearly conceptualized.
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 single factor explains over 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, focusing on bank policies, convenience, compatibility, and risk barriers as independent variables, while credit card usage was treated as the dependent variable Prior to executing the multiple regression, it was essential to ensure that key 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
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 statistic was examined A Durbin-Watson value ranging from 0 to 4, with an ideal 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 useful for testing assumptions, as seen in Figure B1 in 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 distributed along a line, further supporting the validity of this assumption.
The validity of the assumption regarding the normal distribution of residuals can be confirmed by analyzing the residual scatterplot chart A random distribution of residuals around the zero value indicates that the data meets the criteria for normality As shown in Figure B3 in Appendix B, this assumption holds true in this research.
Multicollinearity is a critical assumption that must be met before conducting multiple regression analyses It occurs when independent variables exhibit high inter-correlation, indicating overlapping information among predictors (Leech et al., 2005) To assess the presence of multicollinearity, a correlation matrix serves as an effective tool for analysis.
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
The Pearson test results from the Correlations matrix showed a value below 0.8, indicating a low likelihood of multicollinearity However, the Correlation matrix was not always reliable in detecting multicollinearity issues, making the variance inflation factor (VIF) a more stringent measure for this problem Consequently, it is essential to focus on the VIF values presented in the Coefficients table (refer to Table 4.12) to draw 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 reveals 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 indicates 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
Table 4.13 presents the coefficients of multiple regression, highlighting the variance inflation factor (VIF) as an indicator of multicollinearity among predictor variables According to Hair et al (2009), VIF values above 4 warrant further investigation, while those exceeding 10 indicate serious multicollinearity In this analysis, all VIF values ranged from 1.049 to 1.464, suggesting that multicollinearity did not pose a significant threat to 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 positive relationship with credit card usage This finding aligns with Teoh et al (2013), who identified a significant correlation between the benefits provided by issuing banks and the spending behavior of credit card holders in Malaysia Consequently, Hypothesis 1 is supported 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 a Beta value of 0.539 and a Sig value of 0.00 for the convenience factor, demonstrating its significant positive impact on the adoption and use of credit cards Supporting previous research by Khare et al (2011), which identified convenience as a key predictor of credit use, this study reaffirms the strong correlation between convenience and credit card adoption Consequently, Hypothesis 2 is validated within the model.
Hypothesis 3: There is a positive impact of compatibility on credit card use
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 According to Lee and Kwon (2002), evolving lifestyle trends significantly influence 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 of the coefficients revealed that H4 was not supported, as indicated by a p-value greater than 0.05 This finding aligns with Rammile and Nel's (2012) research, which concluded that risk barriers do not influence customers' intentions to use mobile finance services Additionally, in-depth interviews with five participants highlighted that three of them believed risk barriers did not impact their credit card usage, citing confidence in the robust IT investments made by banks Supporting this perspective, Dang (2013) noted that many banks in Vietnam have significantly invested in modernizing their banking systems.
Since 2007, the development of IT systems and infrastructure has significantly enhanced consumer confidence in credit card usage, as noted in the Lafferty report (2013) This report indicates that consumers perceive credit card transactions as low-risk, largely due to the advanced technology and secure access codes provided by financial institutions Additionally, Vietnam's fraud rate stands at approximately 0.15 percent of the total card billed amount, which is notably lower than the global average of 0.6 percent The survey respondents, primarily highly educated individuals familiar with advanced technology, tend to view risks as minimal barriers to their credit card usage.
In conclusion, three out of four determinant variables—bank policy, convenience, and compatibility—positively influenced credit card usage Notably, the convenience factor exhibited the strongest impact on customers in Ho Chi Minh City, with a Beta value of 0.539, highlighting 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 presented the results of data analysis, focusing on measurement scales, the research model, and hypotheses The reliability and exploratory factor analysis (EFA) tests identified the most reliable measurement scales for each construct Additionally, the multiple regression analysis revealed that most independent variables exhibited strong relationships with the dependent factor.
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 such as 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 research reveals a positive correlation between bank policies, convenience, and compatibility with credit card usage, while the influence of risk barriers remains unconfirmed 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 affecting credit card use in Ho Chi Minh City, with a coefficient of β = 0.539 Following this, perceived compatibility had a coefficient of β = 0.307, and bank-provided policies had a coefficient of β = 0.124.
This empirical research highlights the key factors influencing credit card usage in Ho Chi Minh City, offering valuable insights for understanding consumer behavior Additionally, the study provides actionable recommendations for credit card issuers, enabling marketers to develop effective marketing strategies tailored to their business needs.
Managerial Implications
This study, based on an analysis of 118 credit card holders, reveals valuable insights for credit card providers seeking to enhance their products and marketing strategies By understanding customer expectations, providers can align their offerings more closely with what consumers desire, ultimately improving customer satisfaction and product effectiveness.
This study confirms the significant relationship between bank policies and credit card usage, highlighting that the benefits offered by banks greatly influence consumer adoption In a competitive market, both banks and non-banks provide various incentives to attract potential and existing credit card holders, directly impacting their usage, as noted by Zinman (2009) Given that bank policies are objective factors affecting credit card adoption, it’s unsurprising that consumers gravitate towards banks with favorable offerings Khare et al (2011) further suggest that customers are likely to spend more when incentivized by cash rebates or reward points Therefore, credit card providers in Vietnam should consider implementing more attractive 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 behavior regarding credit cards.
Despite Vietnam's cash-centric culture, many respondents in a 2002 study view credit cards as advantageous and more convenient than cash Participants emphasized the necessity of having a credit card while traveling abroad, indicating that their previous international experiences have heightened their appreciation for credit card utility This insight suggests that banks and financial institutions should consider implementing advertising campaigns to enhance customer awareness of the benefits associated with credit card usage.
Banks can leverage findings on compatibility to enhance credit card usage by emphasizing how their services align with consumers' jobs and lifestyles in promotional materials To succeed in this initial phase, credit card providers should offer trial opportunities for customers to familiarize themselves with credit cards Additionally, focusing on the emotional benefits in marketing campaigns can help promote customer enjoyment and enhance their overall experience with credit cards.
This study provides valuable insights into the influence of bank policies, convenience, and compatibility on credit card usage among consumers in Ho Chi Minh City It enhances existing theories in the credit card industry by identifying key factors affecting credit card adoption Additionally, the research offers practical recommendations for credit card marketers, enabling them to develop effective marketing strategies tailored to their target audience.
Limitations and future research
Due to time and resource constraints, the data for this study 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 of the broader population Furthermore, the small sample size raises concerns about the generalizability of the findings Future research should aim for a larger sample size that includes diverse demographic groups to facilitate more robust conclusions regarding the relationships between the variables involved.
While Ho Chi Minh City presents a promising market for credit card issuers, other regions in Vietnam also offer unique advantages for banks to expand their operations Future research should consider broadening the scope to include the entire country and explore the variations in credit card usage across different areas.
Future research should focus on the impact of financial risks and transaction costs influenced by social factors, as emerging fashion trends may enhance customers' perception of risk and boost their acceptance of credit card usage.
Akin, G.G., Aysan, A.F., Kara, G.I & Yildiran, L (2010) Non-price competition in the
Turkish credit card market Contemporary Economic Policy, 29(4), 1-12
Ahmed, A., Amunullah, A & Hamid, M (2009) Consumer Perception and Attitude towards Credit Card Usage: A Study of Pakistani Consumers Journal of
Ahmed, Z., Ismail, I., Sohail, M., Tabsh, I & Alias, H (2010) Malaysian consumers’ credit card usage behavior Asia Pacific Journal of Marketing and Logistics,
Arthur, M., & Dimitris, D (1994) Credit and Charge Cards Selection Criteria in
Greece International Journal of Bank Marketing, 12(2), 36 – 44
Austin, M J., & Phillips, M.R (2001) Educating students: an ethics responsibility of credit card company Journal of Services Marketing, 15(7) 516-528
Bernthal, M.J., Crockett, D and Rose, R.L (2005) Credit cards as lifestyle facilitators
Business Journal (2014, July 14) Vietnam's Cards and Payments Industry: Emerging
Opportunities, Trends, Size, Drivers, Strategies, Products and Competitive Landscape Retrieved from http://www.bizjournals.com/prnewswire/press_releases/2014/07/07/BR63687
Chan, R Y.-K (1997) Demographic and attitudinal differences between active and inactive credit cardholders - the case of Hong Kong International Journal of
Chakravorti, S (2003) Theory of credit card networks: a survey of the literature,
Chemingui, H., & Lallouna, H (2013) Resistance, motivations, trust and intention to use mobile financial services International Journal of Bank Marketing, 31(7), 574-592
Dang, H (2013, September 20) Stable development of card’s payment services in
Vietnam Retrieved at http://www.tapchitaichinh.vn/Trao-doi-Binh-luan/Phat- trien-ben-vung-dich-vu-the-thanh-toan-o-Viet-Nam/32149.tctc
Delener, N., & Katzenstein, H (1994), Credit card possession and other payment systems International Journal of Bank Marketing, 12 (4), 13-24
Devlin, J F., Worthington, S., & Gerrard, P (2007) An Analysis of Main and
Subsidiary Credit Card Holding and Spending, International Journal of Bank
Dowling, G.R., & Uncles, M (1997) Do customer loyalty programs really work? Sloan
Durkin, T.A (2000) Credit cards: use and consumer attitudes, 1970-2000 Federal
Farrell, D., Gersch, U.A & Stephenson, E (2006) The value of China’s emerging middle class The McKinsey Quarterly, (Special Edition: Serving the new
Gan, L L., Mayrami, R G., & Koh, H G (2008) Singapore credit cardholders: ownership, usage patterns, and perception Journal of Services Marketing, 22(4), 267-279
Goyal, A (2008) Managing perceived risk for credit card purchase through supplementary services Journal of Financial Services Marketing, 12(4), 331-46
Hair, J F., Black , W C., Babin, B J., & Anderson, R E (2009) Multivariate data analysis (7th ed.) Prentice Hall
Kaynak, E., Kucukemiroglu, O., & Ozmen, A (1995) Correlates of credit card acceptance and usage in an advanced developing Middle Eastern country
Kaynak, E and Harcar, T (2001) Consumers’ Attitudes and Intentions Towards Credit
Card Usage in an Advanced Developing Country Journal of Financial Services
Khalid, J., Safdarbutt, H., Murtaza, M., & Khizar, U (2013) Perceived Barriers in the
Adoption & Usage of Credit Cards in Pakistan Banking Industry International
Review of Management and Business Research, 2(1), 104-116
Khare, A., Khare, A and Singh, S (2011) Factors affecting credit card use in India,
Asia Pacific Journal of Marketing and Logistics, 24(2), 236-256
KPMG (2009) Card Payments in Asia Pacific Region: The State of Nation Retrieved from:http://www.kpmg.com.hk/en/virtual_library/Financial_services/Card_Paym ents.pdf
Kucukemiroglu, O (1999) Market segmentation by using consumer lifestyle dimensions and ethnocentrism: an empirical study European Journal of
Kurtulu, K., & Nasır, S (2006, October 15-17) Consumer Behavior of Credit card
Users in an Emerging Market 6th Global Conference on Business & Economics Gutman Conference Center, USA
Laforet, S & Li, X (2005) Consumers’ attitudes towards online and mobile banking in China International Journal of Bank Marketing, 23(5), 362 – 380
LAFFERTY (2013) World Cards Intelligence: Vietnam Available at http://www.worldcardsintelligence.com/journals/Markets/Vietnam_20080714/Lo aded/attachments/WCI%20Vietnam%202013.pdf
Lawrence, F C., Christofferson, R C., Nester, S E., Moser, E B., Tucker, J A &
Lyons A C (2003,September) Credit Card Usage of College Students:
The study conducted by Louisiana State University explores the credit card usage patterns among college students It highlights the financial behaviors, spending habits, and potential impacts of credit card debt on students' financial health The findings emphasize the importance of financial literacy and responsible credit management for students navigating their educational and financial journeys For more detailed insights, refer to the original publication.
Laukkanen, T., Sinkkonen, S., Kivijarvi M., & Laukkanen, P (2007) Innovation resistance among mature Consumers Journal of Consumer Marketing, 24(7):419
Lee, J., & Hogarth, Jeanne M (1999) Returns to information search: Consumer credit card shopping decision Financial Counseling and Planning, 10(2), 23-34
Lee, J., & Kwon, K (2002), Consumers’ use of credit cards: Store credit card usage as an alternative payment and financing medium The journal of Consumer Affairs,
Leech, N C., Barrett, K C., & Morgan, G A (2005) Spss for intermediate statistics:
Use and interpretation (2nd ed.) Mahwah, NJ: Lawrence Erlbaum Associates
Liao, Z., & Cheung, MT (2002) Internet-based e-banking and Consumer attitudes: An empirical study Information & Management, 39(4): 283 -295
Liang, H., Lu, D., & Tu, L (2006) The perceived risk and consumer decision-making process A study on Credit Card Holders Kristianstad University
Lin, H (2011) An empirical investigation of mobile banking adoption: the effect of innovation attributes and knowledge-based trust International Journal of
Liu, M.K (2009) Do credit card redemption reward programs work in China? An empirical study Journal of Consumer Marketing, 26(6), 404-13
Lu, X (2004) Segmentation of the credit cardholders in the urban areas of China
Working paper Chinese Marketing Research Centre of Fudan University
Luarn, P & Lin, H.H (2005) Toward an understanding of the behavioral intention to use mobile banking Computers in Human Behavior, 21(6), 873-891
Meidan, A., & Davos, D (1994) Credit and charge card selection criteria in Greece,
International Journal of Bank Marketing, 12(2), 36-44
Mitchell, T.R., & Mickel, A.E (1999) The meaning of money: an individual-difference perspective Academy of Management Review, 24(3), 568-78
Nasri, W (2011) Factors Influencing the Adoption of Internet Banking in Tunisia
International Journal of Business and Management, 6(8), 143-160
Nguyễn Đình Thọ (2011) Phương pháp nghiên cứu khoa học trong kinh doanh
TPHCM: NXB Lao Động Xã Hội
Ocean Bank Annual Report, (2014), available at http://oceanbank.vn/data/upload/Annualreport2013_Vn_papers_resize-
Park, H.-J., & Burns, L.D (2005) Fashion orientation, credit card use, and compulsive buying Journal of Consumer Marketing, 22(3), 135-41
Park, J., Lee, D., & Ahn, J (2004), Risk-Focused e-Commerce Adoption Model - A
Cross-Country Study Journal of Global Information Technology Management, 7(20), 6-30
Phau, I., & Woo, C (2008) Understanding compulsive buying tendencies among young
Australians: the roles of money attitude and credit card usage Journal of
Polatoglu, V.N., and Ekin, S (2001) An empirical investigation of the Turkish consumers' acceptance of internet banking services International Journal of
Rammile, N., & Nel, J (2012) Understanding resistance to cell phone banking adoption through the application of the technology acceptance model (TAM) African
Roberts, J.A., & Jones, E (2001) Money attitudes, credit card use, and compulsive buying among American college students The Journal of Consumer Affairs,
Rogers, E.M (2003) Diffusion of Innovations (5th ed.) Free Press, New York, NY
Safakli, O.V (2007).Motivating factors of credit card usage and ownership: Evidence from Northern Cyprus Investment Management and Financial Innovations, 4(4), 133-143
Vietnam's banking and credit card industry is experiencing significant growth, marking a transformative period in its financial landscape The sector, although still developing, shows promising signs of expansion and modernization Key players are emerging, and innovations in banking technology are enhancing customer experiences This evolution is crucial for the overall economic development of Vietnam, as it aligns with global financial trends The increasing adoption of credit cards is indicative of changing consumer behaviors and a move towards a more cashless society.
Scott, S., Plotnikoff, R., Karunamuni, N., Bize, R and Rodgers,W (2008) Factors influencing the adoption of an innovation: an examination of the uptake of the Canadian Heart Health Kit (HHK) Implementation Science, 3(1),1-8
Siddiqui, K., & Anjum, M (2013) Perceptions towards Credit Card Usage: Factor
Analytic Finding from Pakistan International Journal of Economics Business and Management Studies, 2(3), 128-135
Sindhav, B., & A L Balazs (1999) A Model of Factors Affecting the Growth of
Retailing on the Internet Journal of Market Focused Management, 4(4), 319-
Sjoberg, L and Engelberg, E (2005), “Lifestyles, and risk perception consumer behavior”, International Review of Sociology, Vol 15 No 2, pp 327-62
Subramaniam, R., & Marimuthu, M (2010) Bank credit card and the selection criteria: an exploratory study African Journal of Business Management, 4(16), 3463-
Suoranta, M., Mattila, M., & Munnukka, J (2005) Technology-based services: a study on the drivers and inhibitors of mobile banking International Journal of
Tabachnick, B G., & Fidell, L S (1991) Using Multivariate Statistics (4th ed.) NW:
Tan, M., & Teo, T.S.H (2000) Factors influencing the adoption of Internet banking
Journal of the Association for information Systems, 1(5), 1-42
Teoh, W., Chong, S., & Yong, A (2013) Exploring the factors influencing credit card spending behavior among Malaysians International Journal of Bank Marketing,
Varaprasad, G., Chandran, K S., Sridharan, R & Unnithan, A B (2013) An Empirical
Investigation on Credit Card Adoption in India International Journal of Service
Science, Management, Engineering, and Technology, 4 (1), 13-29
Watkins, J.P (2000) The corporate power and the evolution of consumer credit
Wessels, L & Drennan, J (2010) An investigation of consumer acceptance of M- banking in Australia International Journal of Bank Marketing, 28(7), 47-568
Worthington, S., Stewart, D & Lu, X (2007) The adoption and usage of credit cards by urban-affluent consumers in China, International Journal of Bank Marketing,
Wickramasinghe, V., & Gurugamage, A (2009) Consumer credit card ownership and usage practices: empirical evidence from Sri Lanka International Journal of
Zinman, J (2009) Debit or credit? Journal of Banking and Finance, 33(2), 358-366
My name is Hoa Phan, a Master's student at the University of Economics Ho Chi Minh City I am conducting research on the factors influencing credit card usage among customers in Ho Chi Minh City I kindly ask you to complete a brief questionnaire about your credit card behavior, which will take no more than 10 minutes Your responses are crucial to my research, and participation is entirely voluntary.
Your personal information will remain confidential and will not be shared without your consent If you have any questions or concerns regarding the study, including scientific inquiries or procedural guidance, please feel free to reach out via email at ptahoa@yahoo.com.vn or by phone at +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 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
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!
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 Rất mong quý vị dành khoảng 10 phút để hoàn thành phiếu khảo sát này Mặc dù các câu trả lời của quý vị rất quan trọng cho nghiên cứu của tôi, nhưng việc tham gia khảo sát hoàn toàn là tự nguyện.
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 câu 1 là Không, bạn có thể ngừng trả lời phiếu 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 sau bằng cách đánh dấu (X) vào ô tương ứng, với các mức độ từ 1 đến 5: Ô số 1 là "Hoàn toàn không đồng ý", Ô số 2 là "Không đồng ý", Ô số 3 là "Trung dung", Ô số 4 là "Đồng ý", và Ô số 5 là "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
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
Phần này yêu cầu thông tin cá nhân để phân loại và so sánh các nhóm đối tượng khảo sát Xin Anh/Chị 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
CẢM ƠN ANH CHỊ ĐÃ THAM GIA KHẢO SÁT -
APPENDIX C: Histogram, Normal Regression & Scatter plot of Dependent
Figure B2: Normal Plot of Use