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A study on customer satisfaction on debit cards: The case of Vietnam

A study on customer satisfaction on debit cards: The case of Vietnam
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This research is conducted to examine the determinants of customer satisfaction in using debit cards issued by the Vietnam commercial banks (CB).

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  1. Uncertain Supply Chain Management 8 (2020) 241–254

    Contents lists available at GrowingScience

    Uncertain Supply Chain Management
    homepage: www.GrowingScience.com/uscm

    A study on customer satisfaction on debit cards: The case of Vietnam

    Thi Hoai Linh Truonga, Hong Mai Phana and Manh Dung Trana*

    National Economics University, Vietnam

    Article history: This research is conducted to examine the determinants of customer satisfaction in using debit
    Received October 26, 2019 cards issued by the Vietnam commercial banks (CB). By applying the exploratory factor
    Received in revised format analysis (EFA), logistic regression and linear regression on a dataset of 428 customers, we find
    December 27, 2019
    that the features and price of products were the key determinants influencing the frequency of
    Accepted January 20 2020
    Available online using debit cards. However, the impact of each determinant is heterogeneous among different
    January 20 2020 groups of customers. Product price and features are more likely to influence the users using
    Keywords: debit cards to purchase goods or services in stores or online than customers working for the
    Payment services via debit public agencies or frequently using non-cash payment for high-valued transaction.
    Commercial banks
    Vietnam © 2020 by the authors; license Growing Science, Canada.

    1. Introduction

    This study is conducted to meet two theoretical and practical needs. First, despite the rapid growth of
    payment services via debit cards offered by Vietnamese commercial banks, the quality of these services
    does not meet the clients’ expectation. Recently, the number of complaints and inconvenience to
    customers about debit card services tend to increase. This has resulted in breaking customer loyalty and
    then switch service providers. Customer dissatisfaction may arise from the shortage and uneven
    allocation of point of sales (POS), high fee, inadequate and unprofessional customer services (Truong
    & Phan, 2017; Oliver, 1980). In fact, debit cards are mainly utilized for money withdrawal rather than
    online, POS or ATM payments. According to the World Bank, Vietnam has the lowest rate of non-cash
    transactions in the region at 4.9% in comparison with 26.1%, 59.7% and 89.0% in China, Thailand and
    Malaysia, respectively. Furthermore, customer dissatisfaction and frequent switch on card providers
    lead to a large number of inactive cards and low card payment turnover. A report by Ernst & Young in
    2014 showed that 65% of Vietnamese customers were willing to change financial service providers.
    Although ATMs have accounted for more than 90% of total bank-issued cards, there have been only
    77 million active cards, along with 55 million unused cards. This situation makes bank hardly increase
    their card payment turnover and suffer more costs to keep track and maintain cash transactions at
    * Corresponding author
    E-mail address: manhdung@ktpt.edu.vn (M. D. Tran)

    © 2020 by the authors; licensee Growing Science.
    doi: 10.5267/j.uscm.2020.1.003

  2. 242

    ATMs. Due to the significant importance of non-interest revenue to bank efficiency (Nguyen, 2017),
    Vietnamese commercial banks must continue to aim to increase the popularity of card payment and
    limit cash transaction in the economy.
    Second, previous studies have demonstrated the positive relationship between service quality and
    customer satisfaction (for example Tran & Bui 2013, Tran & Pham 2013, Chu 2014). Generally, earlier
    studies have considered quality in banking services as “how well the service delivered meets customers’
    needs”. To measure customer satisfaction as well as the linking quality, satisfaction and loyalty in
    banking services, they either applied the original models of service quality or adjusted some of
    dimensions of those models in the context of Vietnam. Yet, their findings have contributed to rather
    than providing implications for banks to make final service decision because data concerning
    customer’s assessment was not completely mined by those researches.
    This research focuses on answering the following questions: (i) What are the drivers behind the
    customer satisfaction and dissatisfaction with debit card services? (ii) How do these determinants affect
    the choice and usage of debit card holders among different groups? In order to address the questions,
    we apply another scale to measure service quality which was more familiar with banking services than
    other scales. We rely on the primary data that was collected from interviewing a survey sample of 428
    customers residing in Hanoi-the capital of Vietnam. Thus, findings discovered from analysis are more
    thorough than that of other researches.
    2. Literature review
    Service quality has been defined obviously by different authors. For example, Olivier (1993), Zeitham
    (1988) define service quality as a global judgment relating to the superiority of the service provided
    over customer expectations. Specifically, service quality is referred to as the difference between
    customer expectations of “what they want” and their perceptions of “what they get” (Brown & Swartz,
    1989; Parasuraman et al., 1985, 1988; Teas, 1993). Based on varied conceptualizations, alternative
    scales have been proposed for service quality measurement. For instance, Lehtinen & Lehtinen (1982)
    highlight that the quality of service as perceived by customers has two dimensions including (i) process
    of service act (i.e., the manner in which service is delivered) and (ii) the outcome of service act (i.e.,
    what the customers receive from the service).
    On the other hand, service providers should demonstrate the ability to deliver and exceed customer
    expectations not only with how they deliver the services (functional quality), but also with what they
    deliver (technical quality) and these quality categories may influence customers’ image of the service
    providers (Gronroos, 1984, 2001). Parasuraman (1985, 1988) emphasize that there are five dimensions
    used to evaluate service quality, including (i) Tangibles (representing physical facilities, equipment,
    and appearance of personnel), (ii) Reliability (representing ability to perform the promised service
    dependably and accurately), (iii) Responsiveness (representing the willingness to help customers and
    provide prompt service, (iv) Assurance (representing the knowledge and courtesy of employees and
    they ability to inspire trust and confidence, and (v) Empathy (representing caring, individualized
    attention the firm provide its customers).
    For measuring the quality of electronic payment service conducted by banks, Humphrey et al. (1996)
    used four dimensions including output price, infrastructure, safety and financial strength of banks.
    Using research simple of banks in 14 developing countries, the authors find that banks should be
    interested in price policies (including fee and interest rates), infrastructure investment (in POS,
    ATM, etc.) in order to improve their electronic payment services. In later years, Boeschoten (1998),
    Humphrey et al. (2001) add dimensions of Transaction features, including transaction process,
    transaction time length and the interaction between bank officers and their customers, particularly
    in dealing with customer’s complaints about banking services. A study on electronic banking by
    Baskar & Ramesh (2010) in India finds that the online customer service quality, online information
    system quality and banking service product quality significantly and positively influence the customer

  3. T. H. L. Truong et al. /Uncertain Supply Chain Management 8 (2020) 243

    satisfaction. Parasuraman et al. (1994) illustrate the need of customer expectation as measured by a
    comparative standard to evaluate service quality. The aim of increasing service quality is to enhance
    customer’s perceptions in line with their expectations, then eventually to strengthen customer
    satisfaction. Moreover, this was approved to promote customers repeat patronage (Dick & Basu, 1994).
    They describe loyalty as the strength of the relationship between a customer’s relative attitude and
    repeat patronage and found out four following categories of loyalty due to above relationship. Service
    providers should pay attention to the group of spurious – loyalty customers who are less likely to rebuy
    the service in the case of their willingness to seek better services that exceed their inertia (Gounaris &
    Stathakopoulos, 2004). Thus, it is necessary to meet most of customer expectations rather than their
    current perceptions in order to make them to consistently repeat their repurchasing behaviors
    (Parasuraman et al., 1994).
    3. Research methodology
    3.1. Research design
    Following Parasuraman et al. (1994), the research structure consists of two stages as below:
    Stage 1:

    Determinants that Determinants that Determinants impact
    customers likely to customers actually on customer’s
    expect/care as making EFA expect/care as making Logistic loyalty/disloyalty
    decision involved in decision involved in regression decision involved in
    debit card services debit card services debit card services

    Stage 2:

    Differences in each
    Determinants impact
    custome group’s needs
    Customers’ on customer’s
    of each determinant on
    demographic loyalty/disloyalty
    Linear regression


    characteristics decision involved in
    involved in debit card
    debit card services

    Note: This exhibit indicates steps to solve research questions
    Fig. 1. Research Structure
    In stage 1, we identify customer expectations and determinants of customer satisfaction in debit card
    services provided by CBs. According to SERVQUAL model raised by Parasuraman et al. (1985, 1988),
    determinants that customers are likely to expect or care are chosen and then modified due to approach
    of Fornell (1992). Thus, determinants that are initially considered to make debit card holding decision
    consist of Service features, Price, Brand Image and Interaction. Each factor is selected from previous
    researches. Al-Eisa and Alhemoud (2009), Jamal and Naser (2002) highlight that customers care
    for procedures (referred to as progression of service delivery), time of service delivery, product
    diversification, the distance between service providers and customers and service price. Matzler et al.
    (2006), Varki and Colgate (2001), Seyedaliakbara et al. (2016) illustrate the vital effect of price on

  4. 244

    customer perceptions. Levesque et al. (1996) divide prices of banking service into three categories such
    as nominal interest rate written on the contract, negotiated interest rate except from nominal interest
    rate or fees and penalty interest rate as breaching the agreement. Besides, firm’s brand image was found
    to directly influence service quality according to customers (Nguyen & LeBlanc, 1998). Bank’s brand
    image that is widely known and loved is likely to positively affect customer perceptions toward its
    services (Che-Ha & Hashim, 2007). Last but not least, the fourth factor is the interaction between bank
    officers and its customers, which represents equipment and facilities (Barber & Scarcelli, 2010), the
    appearance of officers (Reimer & Kuehn, 2005), attitude and advisory capacity (Jamal & Naser, 2002).
    After providing services, customer care services such as expressing bank’s deep gratitude to existing
    customers, sending emails to customers regularly with useful information, etc. are proved to promote
    customer sympathy (Ennew & Binks, 1999).
    In stage 2, data of customer demographics (expressed on the top of the questionnaire) is coded. Then,
    we use a linear regression model to analyze the relationship between the mentioned coded demographic
    variables and significant determinants found in the first stage to examine the differences between each
    customer group’s need and each feature involved in loyalty or disloyalty decision in debit card services.
    The purpose of this stage is to learn more about different groups of customers, then recognize the target
    customer group and propose appropriate plans to take care of them (Şchiopu, 2010; Nguyen, 2019).
    Many demographic variables such as gender, age, education level, marital status, income were showed
    the impact on customer behavior (Farokhi et al., 2016; Negeri, 2017).
    3.2. Research sample
    This paper uses a random sample encompassing 428 customers whose debit cards are issued by CBs
    located in Hanoi, Vietnam. This sample size is adequate for conducting EFA and multiple regression
    (Tabachnick & Fidell, 2007).
    457 written survey questionnaires for gathering information were filled out directly by customers over
    the period from December 2016 to June 2017. There were 428 responses meeting the requirement. The
    survey questionnaire included 3 main parts: (i) customer information, (ii) Assessment the level of
    importance of 23 determinants in making decision of using debit cards and (iii) customer’s future
    decision of using debit cards. The second part uses the Likert scale with five-point scale that allows the
    respondents to express how important they assess each factor.
    3.3. Processing techniques
    We analyze data through the descriptive statistics, exploratory factor analysis (EFA), and binary
    logistic regression with SPSS 22. This study employs the Kaiser – Meyer – Olkin, the Bartlett’s test,
    the Total variance Explained, Loading Factor (in Rotated Component Matrix), and Cronbach Alpha to
    measure the adequacy and reliability of scales shown in Table 1. After that, we acquire FAC as
    independent variable in Logistic Regression.
    The Binary Logistic Regression model is given as below:
    Log (p/1−p) =  + β1X1 + β2X2 +…. + βnXn (1)
    where: p denotes the probability of the event that customers increase their frequency of using debit
    card. X1, X2… Xn represent FACs found after EFA. In order to assess the Logistic model fit, we test -2
    Log likelihood indicator, sig. in Hosmer and Lemeshow Test. The Linear Regression model is given as
    Yi =  + β1X1 + β2X2 +…. + βnXn + ei (2)
    where: Yi refers to as a significant FACi found through Logistic model. X1, X2… Xn represent variables
    described in Table 2. ei refers to as a random error. In order to assess the model reliability, the value of
    R square and the value of Durbin Watson were used.

  5. T. H. L. Truong et al. /Uncertain Supply Chain Management 8 (2020) 245

    Stage 1: The dependent variable is Loyalty that takes the value of 1 if customers increase their
    frequency of using debit card and 0 otherwise. The underlying factor includes 23 determinants that
    customers may appreciate as making debit card using decision.
    Table 1
    Underlying determinants in research model in stage 1
    Scales Items Definition
    Products The diversity of debit card products
    Procedures Procedures the customers have to fulfill to active debit card
    Balance Bank’s requirement of minimum balance on debit card account
    Process The ease of payment transactions
    Convenience The varied convenience provided by bank
    Service features Money safety The security of money on the account
    Money availability The availability of money in the ATM
    Privacy security The security of card holder’s personal information
    Account security The security of card holder’s account
    Network The point – of – sale network
    Promotion The diversify and attraction of promotion programs
    Brand image Reputation Bank has acquired high reputation
    Fame Many customers have known bank’s brand image
    Opening fees Banks charge fees to open card
    Price Transaction fees Banks charge fees to make transactions
    Interest rate Interest rate that card holder earns on deposit balance account
    Product advice Bank officer’s advice on using products
    Opening card advice Bank officer’s advice and assistance on opening card
    Attitude Bank officer’s attitude in solving card problems
    Interaction Solving time Time spent on solving card problems
    Care The bank’s policy of caring customers
    ATM ATM appearance and position
    Branches Bank branch appearance and position
    Note: This table describes underlying variables that are likely to be concerned by customers as they make debit card using decision. These variables were
    collected from previous researches.

    Stage 2: The dependent variables are those correlated with Customer Loyalty explored in stage 1. The
    independent variables stem from 17 demographic characteristics of customer, then form 44 dummy
    variables expressed as below:
    Table 2
    Demographic variables employed in stage 2
    Variables Value
    Gender Dummy (D) = 1 if customers are male; D = 0 if customers are female.
    Occupation D = 1 if customers are students, running business, doing the housework, public servants; D = 0 otherwise.
    Income D = 1 if monthly income stands “less than 5 million VND”, “from 5 to less than 10 million VND”; D = 0 otherwise
    Age D = 1 if the age of customers is under 30 years old; D = 0 otherwise
    Education D = 1 if customers hold a bachelor or master or doctoral degree; D = 0 otherwise
    Technology preference D = 1 if “technology preference”; D = 0 if vice versa
    Bank D = 1 if “BIDV”; “Vietinbank”; “Agribank”; “Vietcombank”, “DongAbank”; D = 0 otherwise
    Time D = 1 if “under 1 year”, “from 1 to 3 years”; D = 0 otherwise
    Purpose D = 1 if “cash withdrawal”, “pay for goods and services at stores”, “online shopping”, “check real time balance”; D
    = 0 otherwise
    Frequency D = 1 if “pay for goods and services with card more than that in cash”, D = 0 if vice versa
    Payment value D = 1 if “the total payment value with card more than that in cash”; D = 0 if vice versa
    Card preference D = 1 if “prefer card to cash”; D = 0 if vice versa
    Provider change D = 1 if “readily change provider aiming at paying with card instead of paying in cash”; D = 0 if vice versa
    Reasons to choose bank D = 1 if “family members’ bank”, “good reputation”, “spreading point of sale network”, “efficient customer service”,
    “a wide variety of promotion programs”, “competitive price policy”; D = 0 otherwise
    Channels to know bank card D = 1 if “traditional mass media such as television, newspaper, etc.”, “modern mass media such as social networks,
    electronic media, etc.”, “advertisement/leaflets”, “acquaintances, friends”, “being bank’s existing customer”; D = 0
    Viewpoint of card D = 1 if “safe place for money”, “comfortable place for money”, “easy for payments”, “style of person having high
    technology preference”; D = 0 otherwise
    Awareness of card D = 1 if card refers to as “level”, “personality”, “unimportance”; D = 0 otherwise
    Note: This table describes the ways we used to code demographic variables of survey sample. These variables are expected to correlate with determinants
    that influence on customer loyalty in debit card services.

  6. 246

    4. Results and Discussion
    4.1. Findings in stage 1
    Descriptive statistics
    The descriptive statistics of the importance score of underlying determinants are shown in Table 3.
    Determinants which customers pay more attention than others carry the value of mean greater than 4.2
    including Privacy Security, Account Security, Money Safety, and Money Availability. Due to the fact
    that account fraud has rapidly increased in recent years in both big and small Vietnamese banks,
    customers concern about the service security.
    Table 3
    Mean of underlying determinants
    Items Mean Variance Items Mean Variance
    Product 3.251 0.8884 Reputation 3.932 0.8378
    Procedures 3.557 0.8549 Fame 3.756 0.7942
    Balance 3.405 0.8033 Opening fees 3.782 0.8541
    Process 3.822 0.7544 Transaction fees 3.956 0.9040
    Convenience 3.913 0.8219 Interest rate 3.679 0.9605
    Money safety 4.321 0.8434 Product advice 3.632 0.8437
    Money availability 4.253 0.8916 Opening card advice 3.656 0.7878
    Privacy security 4.492 0.7853 Attitude 3.937 0.7526
    Account security 4.525 0.7545 Problem solving time 4.061 0.7544
    Network 4.143 0.7604 Care 3.803 0.7498
    Promotion 3.426 0.8370 ATM 3.698 0.7752
    Branches 3.604 0.7723
    Note: This table expresses the descriptive statistics of each question in the questionnaire. Due to 5 – point Likert scale, the value of mean in 2.61 – 3.4
    represents the respondents do not reveal their opinions about issue received (also called neutral). The value in 4.21-5 represents the maximum respect
    (strongly important).

    Validity and reliability tests of scales
    Conducting EFA of 23 items projected respected by customers as making debit card using decision, we
    found out that sample sufficiency index KMO is 0.838 (greater than 0.5). Sig. value in Bartlett test is
    0.000 (smaller than 0.05) for Approx. Consequently, factor analysis is reasonable and variables are
    correlated in the overall (shown in Appendix No. 1).
    Total variance explained is 65.845% (greater than 50%), which indicates that the new five determinants
    together account for 65.845% of the total variance. The result from the matrix of the rotated factor
    loadings shows that 22 items of 23 original items are grouped into new 5 groups and all items having
    factor loadings greater than 0.5. This ensures that these items are practical significance (see Appendix
    No. 1). The “Promotion” item is removed because its factor loading is below 0.5, which is consistent
    with the context of Vietnam. Debit card promotions that have been conducted by Vietnamese banks
    mainly focus on paying no fee as open card firstly and receiving discount rates for taking card
    payments. The popularity of the free charge for first time users makes this benefit to be considered
    customer’s apparent right. Many of discount promotions are thanks to with the partnership between
    card providers and businesses such as shops, restaurants, hotels, beauty salons, resorts, etc. Cardholders
    also receive many types of vouchers in the events of bank’s birthday, customer’s birthday, opening
    ceremony, etc. Cardholders only get this benefit in the case of they buy other goods or services supplied
    by bank’s partners in the alliance. Thus, this promotion program sometimes is not attractive to
    customers. Hence, they might not consider Promotion item as important item when they make decision
    to hold debit card.
    Looking at the table labeled Rotated Component Matrix, from 23 underlying items, after deleting
    Promotion item, the rest of 22 items is grouped into 5 categories (named FAC 1, FAC 2, FAC 3, FAC
    4 and FAC 5 respectively). For a measure of scale reliability with Cronbach’s alpha for 5 above FAC,
    the results are 0,875; 0,866; 0,732; 0,645 and 0,823 respectively (see Appendix No. 1). Having alpha
    coefficient below 0.7, FAC 4, composed of Products, Balance and Procedures, is unacceptable (Kline,

  7. T. H. L. Truong et al. /Uncertain Supply Chain Management 8 (2020) 247

    1998). This finding is consistent with the context of Vietnam. According to our previous research, debit
    cardholders recently have generally accepted Vietnamese banks’ regulation of the minimum balances
    in the deposit account, steps need to complete for holding card and the diversify of card products.
    Cardholders score these items at 3.44; 3.56 and 3.37 respectively (Truong & Phan, 2017). The relative
    similarly in those items among Vietnamese banks results in having no impact on provider choice of
    customers. After EFA, there are 19 determinants (in 4 groups) showing that cardholders pay attention
    to as making debit card using decision (shown in Table 4).
    Table 4
    Lists of determinants that cardholders pay attention to as making decisions on using debit cards offered
    by banks
    Factor Items Factor Factor Items Factor loading
    groups loading groups
    Opening card advice 0.870 Money safety 0.852
    Attitude 0.861 Privacy security 0.849
    Care 0.810 Account security 0.822
    FAC 1 Product advice 0.806 FAC 2 Money availability 0.693
    Problem solving time 0.801 Process 0.610
    ATM 0.677 Network 0.598
    Branches 0.650 Convenience 0.592
    Fame 0.824 Transaction fees 0.784
    FAC 3
    Reputation 0.800 FAC 5 Interest rate 0.746
    Opening fees 0.511
    Note: This table summarizes factor groups that have influence customer’s decision on making payments by debit cards after EFA and conducting the
    validity and reliability tests of scales.

    Results from Logistic regression analysis
    Applying Logistic regression technique to 4 factor groups found above and Overall Customer Loyalty,
    the value of -2 Log likelihood is 270.200 indicating the close relation among variables in the model.
    The value of sig. in Hosmer and Lemeshow Test is 0.007 (< 0.05) showing the model fit well the data
    (see in Appendix No. 2). Table 5 shows the Logistic regression results.
    Table 5
    The relationship between Determinants Groups and Customer Loyalty Involved in Using Debit Cards
    Independent variables Estimates
    FAC 1
    FAC 2
    FAC 3
    FAC 5
    Standard errors are in parentheses.
    Dependent variable is Overall Customer Loyalty.
    Number of observations: 428.
    ***, ** and * indicate significance at 1%, 5%, and 10% level respectively.
    Note: This table shows the estimates of independent variables in the model.

    This finding of the correlation analysis shows positive and significant relationships between two factor
    groups (FAC 2 and FAC 5) and the Overall Customer Loyalty. This implies that customers who regard
    the Service Features and Price as the important matters are more likely to repeat patronage in the case
    of holding debit card. This outcome is in line with the fact in Vietnam. Cardholders in Vietnam expect

  8. 248

    debit cards to have many of similar features to cash such as the convenience in making payments for
    goods and services (representing the availability of cash in ATM, the spreading of payment points and
    the easiness in payment processing). Also, customers reveal their expectation of using debit card make
    them avoid many limitations of holding cash (such as easily acquiring counterfeit money, being lost or
    stolen, inconvenience and lack of security as holding a large amount of money, etc.). Besides, card
    holders desire to earn interest rate on account balance greater than transaction fees paid to banks.
    Because customers pay attention to service features and price as deciding whether they should continue
    to use debit cards or not, it is necessary for Vietnamese banks to improve their service features and
    price policies in order to meet customer needs as well bank’s profitability expectation.
    4.2. Findings in stage 2
    In this stage, we examine the impact of demographic variables on factor groups having significant
    correlation with the Overall customer Loyalty (named FAC 2 and FAC 5 found in stage 1). Running
    the linear regression to check the relationship between Independent variables in Table 1 and FAC 2,
    the results are expressed in Table 6. The adjusted R –Squared is 31.9% showing that independent
    variables explain 32.9% the variation of the dependent variable. The Durbin Watson test statistic value
    is 1.706 (lies between 1 and 3). Thus, there is no autocorrelation in the model (see Appendix No. 3).
    Table 6
    The impact of demographic variable on FAC 2
    Independent variables Estimates
    Male -0.073* (0.085)
    Being student -0.211*** (0.161)
    Doing the housework -0.086** (0.333)
    Being a public servant -0.192*** (0.091)
    Under the age of 30 0.140*** (0.89)
    Bachelor -0.093** (0.084)
    Pay for goods and services at stores 0.137*** (0.101)
    Online shopping 0.114*** (0.090)
    Check real time balance 0.200*** (0.098)
    The total payment value with card more than in cash -0.157*** (0.101)
    Spreading point of sale network 0.128*** (0.097)
    Efficient customer service 0.203*** (0.094)
    Modern mass media such as social network, e-media… -0.327*** (0.096)
    Advertisement/leaflets -0.104** (0.123)
    Being bank’s existing customer -0.101** (0.093)
    Safe place for money 0.085** (0.088)
    Style of person having high technology preference -0.087** (0.104)
    Personality 0.074* (0.115)
    Constant -0.198 (0.153)
    Note: This table indicates the correlation between demographic variables and FAC2. Standard errors are in parentheses. The number of observations is
    428. ***, **, and * indicate significance at 1%, 5% and 10% levels respectively.

    Results in Table 6 show that there are 18 out of 44 demographic variables being correlated with FAC
    2. For eight variables that are positively correlated with FAC 2, we note that a certain portion of
    customers have a higher demand for Service Features than others. They are under the age of 30, using
    debit cards to pay for goods and services in stores or online shopping, using debit card to check real
    time balance. For them, debit cards are considered to be safe to store money and express their
    personality. This cardholder group selects debit card providers because of the spreading point of sale
    network and efficient customer service. Thus, if a bank targets the customer segment with above
    characteristics, the bank should improve all items in FAC 2 in order to retain customer loyalty. For 10
    variables having a negative correlation with FAC 2, we find that a specific portion of customers requires
    less than others about Service Features. They are men, being students or doing housework or being
    public servants. Importantly, this group includes customers who graduated universities or colleges and
    having been paying for goods and services with debit cards greater than in cash. This consumer group
    gets to know about debit cards via e-media, social networks, advertisements or leaflets or through using
    other banking services. For them, bank card in general and debit cards in particular express the style of
    high-tech preference. Thus, if a bank targets the customer segment with these features, it should remain
    all items in FAC 2 as the present level and give priority to other sides of debit card services. To explain

  9. T. H. L. Truong et al. /Uncertain Supply Chain Management 8 (2020) 249

    the relationship between Independent variables in Table 2 and FAC 5, we continued to run the linear
    regression, acquired results expressed in Table 7. The adjusted R –squared is 16.7% indicating that
    independent variables explain 16.7% the variation in the dependent variable. The Durbin Watson test
    statistic value is 2.101 (lies between 1 and 3). Thus, there is no autocorrelation in the model (see
    Appendix No. 4).
    Table 7
    The impact of demographic variables on FAC 5
    Independent variables Estimates
    Running business -0.206*** (0.117)
    Being a public servant -0.146*** (0.110)
    Technology preference 0.102** (0.135)
    Vietinbank -0.077* (0.112)
    Pay for goods and services at stores 0.167*** (0.106)
    Online shopping 0.114** (0.101)
    Pay for goods and services with card more than that in cash 0.137** (0.145)
    The total payment value with card more than in cash -0.167*** (0.145)
    Readily change provider aiming at paying with card instead of paying in cash -0.152*** (0.099)
    Good reputation -0.133*** (0.108)
    Efficient customer service 0.206*** (0.101)
    Modern mass media such as social network, e-media… 0.100** (0.095)
    Safe place for money -0.120** (0.095)
    Personality -0.095** (0.127)
    Constant -0.071 (0.167)
    Note: This table indicates the correlation between demographic variables and FAC 5. Standard error is written in parentheses. Number of observations is
    428. ***, **, and * indicate significance at 1%, 5% and 10% level respectively.

    The outcome, shown in Table 7, indicates the relationship between demographic variables and FAC 5.
    There are 14 out of 44 demographic variables having a correlation with FAC 5, including six positively
    correlated variables and eight negatively correlated variables. For six variables having positive
    correlation, we highlight that a specific portion of cardholders highly demand for Price more than
    others. This customer group consists of consumers who prefer high technology, get to know bank card
    through e-media, social networks. They use debit card for making payments at stores or e-shopping
    and also pay for goods and services with debit cards more than in cash. The reason for them to select
    card provider is good customer service. Thus, price policy is what banks need to concern about if they
    target to these consumer segments. For 8 variables having a negative correlation, these results indicate
    that a certain portion of customers pays less attention to Price than others. The common feature of this
    group is cardholders who are running businesses or public servants. They are Vietinbank’s customers.
    They use debit cards for making payments with larger amount than paying in cash and thus they are
    willing to change card provider for paying with debit card if the current provider cannot meet their
    expectations. Due to their preference for payments in cards, they choose card providers with high
    reputation in the hope of acquiring a safe place for their money. This consumer group also desires bank
    card to show their personality. This outcome suggests that banks should keep their current price policy
    and give priority to other matters involved in debit card services if they are willing to offer debit card
    services to above customer group.
    Moreover, we add two important findings as below:
    Customers who are more interested in both Service Features and Price determinants than others
    (expressed by positively correlated with both FAC 2 and FAC 5) are cardholders using debit cards for
    making payments in stores or online shopping. This group also chooses debit card providers with good
    customer services. His customer segment would prefer and have a habit of making payments for goods
    and services by debit card through POS or carrying electronic transfers. In other words, they often use
    debit card for the purpose of payments rather than cash withdrawals. For countries like Vietnam that
    cardholders mainly have used their card for cash withdrawals (accounts for 86.6% of total cardholders
    according to report of Vietnam bank card Association in 2016), banks should explore and target this
    segment of customers in order to widen their customer base in line with increasing their revenues from
    debit card services. This segment of customer has high expectation on account security and privacy,
    payment process, advantages and POS networks involved in debit cards. Furthermore, this customer

  10. 250

    group also concerns about banks’ price policy including interest rates on deposit accounts and fees paid
    for payment services more than others. They rarely or sometimes take money out of their demand
    account for using cash, so that they ask for earning proper interest rate on the account balance and being
    charged reasonable fees. The more customers make payments with debit cards, the better customer
    services they desire in the hope of being rapidly and efficiently solved all problems involved in debit
    cards transactions. To improve the convenience and security for all debit card services, it is inevitable
    for banks to customize services to meet the need of different customer groups with above
    characteristics. For price policy, it is difficult for banks to increase interest rates on demand deposit
    accounts for many reasons such as the right of depositors to withdraw cash or make payments as
    needed, the large amount of investment on maintaining and upgrading payment systems, etc. Thus, to
    attract the above customer segment, banks should strengthen their relationship with other goods and
    service providers in order to increase benefits for customers instead of the decline in fees and rise in
    interest rates.
    On the other hand, there is a certain portion of customers who are less interested in Service Features
    and Price determinants than others (represents a negative correlation with both FAC 2 and FAC 5).
    They are public servants or consumers whose value paid by card is greater than paid in cash. According
    to the Directive No. 20/2007/CT-TTg on the increase in noncash payment signed by the Vietnam’s
    Prime Minister in 2007, staffs who work in state agencies have to register to receive salaries and wages
    via their bank accounts from the date 1/1/2008. Thus, up to the beginning of 2017, this customer group
    has experienced long time for finding and using bank cards. The rapid development in payment services
    especially in paying for utilities in combination with their lack of time spending for daily purchases
    make them get used to making payments by many of bank cards and easily compare services offered
    by different banks. Up to now, services involved in debit card provided by most of Vietnamese banks
    have been relatively even. Customers have already chosen suitable banks they expect to be served long-
    lasting. Due to above explanation, the customer group has less concern about FAC 2 and FAC 5 because
    they deeply understand about services involved in debit cards issued by Vietnamese banks. Thus, if
    banks target this segment, they should keep their recent service features and price policy plus providing
    related or complementary products with debit card services (also called cross-selling) to existing
    In short, through applying EFA, Logistic regression and Linear regression techniques to a dataset of
    428 cardholders in Hanoi, we found out that Service Features and Price affect the loyalty of customers
    holding debit cards offered by Vietnamese banks. Moreover, customers in different groups of
    demographic characteristics express different concerns about these two determinants. Clearly,
    cardholders who usually pay for goods and services at stores or online shopping, choose banks with
    good customer care reveal higher demand for these two determinants than others. Conversely,
    cardholders who are public servants or make payments with card greater than in cash in value reveal
    their less concern about these two determinants. These findings suggest banks should conduct different
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    Appendix No. 1: Validity and reliability tests of scales in stage 1

    KMO and Bartlett’s test in stage 1
    Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.838
    Bartlett’s Test of Sphericity Approx. Chi-Square 5614.542
    Df 253
    Sig. 0.000

    Initial Eigenvalues Rotation Sums of Squared Loadings
    Component Total % of Variance Cumulative % Total % of Variance Cumulative %
    1 6.892 29.966 29.966 5.124 22.277 22.277
    2 4.022 17.485 47.451 3.857 16.768 39.045
    3 1.566 6.809 54.261 2.094 9.104 48.149
    4 1.430 6.217 60.478 2.056 8.938 57.087
    5 1.235 5.368 65.845 2.014 8.759 65.845
    6 0.889 3.866 69.711
    7 0.855 3.719 73.430
    8 0.706 3.070 76.499
    9 0.672 2.923 79.423
    10 0.606 2.637 82.060
    11 0.560 2.435 84.494
    12 0.507 2.206 86.700
    13 0.462 2.008 88.708
    14 0.418 1.818 90.526
    15 0.378 1.642 92.168
    16 0.334 1.451 93.619
    17 0.324 1.411 95.030
    18 0.274 1.191 96.221
    19 0.235 1.020 97.240
    20 0.198 0.860 98.101
    21 0.176 0.764 98.865
    22 0.151 0.657 99.521
    23 0.110 0.479 100.000
    Extraction Method: Principal Component Analysis.

    1 2 3 4 5
    Opening card advice 0.870
    Attitude 0.861
    Care 0.810
    Product advice 0.806
    Problem solving time 0.801
    ATM 0.677
    Branches 0.650
    Money safety 0.852
    Privacy security 0.849
    Account security 0.822
    Money availability 0.693
    Process 0.610
    Network 0.598
    Conveniences 0.592
    Fame 0.824
    Reputation 0.800
    Transaction fees 0.784
    Interest rate 0.746
    Opening fees 0.511
    Balance 0.767
    Procedures 0.698
    Products 0.685
    Extraction Method: Principal Component Analysis.
    Rotation Method: Varimax with Kaiser Normalization.
    a. Rotation converged in 6 iterations.

  13. T. H. L. Truong et al. /Uncertain Supply Chain Management 8 (2020) 253

    Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items
    0.875 0.875 7

    Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items
    0.866 0.868 7

    Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items
    0.732 0.733 2

    Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items
    0.645 0.644 3

    Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items
    0.823 0.825 3

    Appendix No. 2
    Validity and reliability tests of logistic model in stage 1
    Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square
    1 270.200a 0.049 0.100
    a. Estimation terminated at iteration number 5 because parameter estimates changed by less than 0.001
    Step Chi-square df Sig.
    1 21.093 8 0.007

    Appendix No. 3
    Validity and reliability tests of linear regression
    Model examined the impact of demographic variables on FAC 2
    Change Statistics
    Adjusted R Std. Error of the R Square Durbin-
    Model R R Square Square Estimate Change F Change df1 df2 Sig. F Change Watson
    1 0.612 0.375 0.292 0.84061009 0.375 4.517 50 377 0.000
    2 0.612 0.375 0.294 0.83949774 0.000 0.000 1 377 0.987
    3 0.612 0.375 0.295 0.83839003 0.000 0.000 1 378 0.983
    4 0.612 0.375 0.297 0.83728715 0.000 0.001 1 379 0.976
    5 0.612 0.375 0.299 0.83618860 0.000 0.001 1 380 0.976
    6 0.612 0.375 0.301 0.83510001 0.000 0.006 1 381 0.938
    7 0.612 0.375 0.303 0.83402208 0.000 0.012 1 382 0.913
    8 0.612 0.375 0.305 0.83295293 0.000 0.016 1 383 0.899
    9 0.612 0.375 0.306 0.83190217 0.000 0.029 1 384 0.864
    10 0.612 0.374 0.308 0.83086946 0.000 0.042 1 385 0.837
    11 0.612 0.374 0.310 0.82996259 0.000 0.156 1 386 0.693
    12 0.611 0.374 0.311 0.82909808 0.000 0.192 1 387 0.661
    13 0.611 0.374 0.312 0.82821594 0.000 0.173 1 388 0.678
    14 0.611 0.373 0.314 0.82745627 0.000 0.285 1 389 0.594
    15 0.611 0.373 0.315 0.82666135 0.000 0.249 1 390 0.618
    16 0.610 0.372 0.316 0.82589834 0.000 0.277 1 391 0.599
    17 0.610 0.372 0.318 0.82510766 0.000 0.248 1 392 0.619
    18 0.609 0.371 0.319 0.82436345 0.000 0.290 1 393 0.591
    19 0.609 0.371 0.320 0.82379009 -0.001 0.451 1 394 0.502
    20 0.608 0.370 0.321 0.82328499 -0.001 0.515 1 395 0.474
    21 0.607 0.369 0.321 0.82284153 -0.001 0.572 1 396 0.450
    22 0.607 0.368 0.322 0.82242110 -0.001 0.593 1 397 0.442
    23 0.606 0.367 0.323 0.82202507 -0.001 0.616 1 398 0.433
    24 0.605 0.366 0.324 0.82153037 -0.001 0.519 1 399 0.472
    25 0.604 0.365 0.324 0.82143639 -0.001 0.908 1 400 0.341
    26 0.603 0.363 0.323 0.82156820 -0.002 1.129 1 401 0.289
    27 0.601 0.361 0.323 0.82178734 -0.002 1.215 1 402 0.271
    28 0.599 0.359 0.323 0.82192816 -0.002 1.138 1 403 0.287
    29 0.598 0.357 0.322 0.82227915 -0.002 1.346 1 404 0.247
    30 0.595 0.354 0.321 0.82314359 -0.003 1.854 1 405 0.174
    31 0.592 0.351 0.319 0.82423675 -0.003 2.082 1 406 0.150 1.706

  14. 254

    Appendix No. 4: Validity and reliability tests of linear regression
    Model examined the impact of demographic variables on FAC 5
    Change Statistics
    Adjusted R Std. Error of R Square Durbin-
    Model R R Square Square the Estimate Change F Change df1 df2 Sig. F Change Watson
    1 0.501 0.251 0.152 .92003466 0.251 2.525 50 377 0.000
    2 0.501 0.251 0.154 .91881849 0.000 .001 1 377 0.971
    3 0.501 0.251 0.156 .91763156 0.000 .021 1 378 0.884
    4 0.501 0.251 0.158 .91645690 0.000 .028 1 379 0.868
    5 0.501 0.251 0.160 .91529909 0.000 .038 1 380 0.846
    6 0.501 0.251 0.162 .91413916 0.000 .032 1 381 0.857
    7 0.501 0.251 0.164 .91300166 0.000 .047 1 382 0.828
    8 0.500 0.250 0.167 .91187557 0.000 .053 1 383 0.817
    9 0.500 0.250 0.169 .91078379 0.000 .079 1 384 0.779
    10 0.500 0.250 0.170 .90975459 0.000 .128 1 385 0.721
    11 0.500 0.250 0.172 .90874875 0.000 .145 1 386 0.704
    12 0.499 0.249 0.174 .90788040 -0.001 .259 1 387 0.611
    13 0.499 0.249 0.175 .90707743 -0.001 .312 1 388 0.577
    14 0.498 0.248 0.177 .90624867 -0.001 .288 1 389 0.592
    15 0.497 0.247 0.178 .90552530 -0.001 .376 1 390 0.540
    16 0.497 0.247 0.179 .90479237 -0.001 .366 1 391 0.546
    17 0.496 0.246 0.181 .90403473 -0.001 .342 1 392 0.559
    18 0.495 0.245 0.182 .90331321 -0.001 .371 1 393 0.543
    19 0.494 0.244 0.183 .90288275 -0.001 .624 1 394 0.430
    20 0.493 0.243 0.184 .90247591 -0.001 .643 1 395 0.423
    21 0.492 0.242 0.184 .90200815 -0.001 .589 1 396 0.443
    22 0.490 0.240 0.185 .90177236 -0.002 .792 1 397 0.374
    23 0.488 0.239 0.185 .90166672 -0.002 .907 1 398 0.342
    24 0.486 0.236 0.185 .90185708 -0.002 1.169 1 399 0.280
    25 0.484 0.234 0.185 .90196593 -0.002 1.097 1 400 0.296
    26 0.482 0.232 0.184 .90214296 -0.002 1.158 1 401 0.283
    27 0.479 0.229 0.183 .90266320 -0.003 1.465 1 402 0.227
    28 0.476 0.227 0.183 .90302404 -0.003 1.323 1 403 0.251
    29 0.473 0.224 0.182 .90335173 -0.002 1.294 1 404 0.256
    30 0.469 0.220 0.180 .90449832 -0.004 2.031 1 405 0.155
    31 0.465 0.216 0.178 .90559381 -0.004 1.986 1 406 0.159
    32 0.462 0.213 0.177 .90627099 -0.003 1.610 1 407 0.205
    33 0.457 0.209 0.174 .90763923 -0.004 2.236 1 408 0.136
    34 0.452 0.205 0.172 .90907750 -0.004 2.300 1 409 0.130
    35 0.448 0.201 0.170 .91024846 -0.004 2.059 1 410 0.152
    36 0.443 0.197 0.167 .91143537 -0.004 2.075 1 411 0.150 2.101

    © 2020 by the authors; licensee Growing Science, Canada. This is an open access
    article distributed under the terms and conditions of the Creative Commons Attribution
    (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

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