Factors affecting the adoption to use digital banking of vietnam

Introduction

The rise of digital banking is a crucial development in the context of the fourth technological revolution, facilitating the growth of non-cash payment transactions both domestically and internationally Over the years, the banking industry has undergone significant transformations due to advancements in technology The journey of digital banking began with the introduction of ATMs in the 1960s, which allowed customers to access their funds without relying on bank tellers The implementation of personal identification numbers (PINs) in 1970 further enhanced security for ATM users By 1983, online banking emerged, paving the way for a broader range of banking services to be offered through internet platforms.

The influence of online banking in the United Kingdom has extended globally, impacting countries like the US, France, and various Asian nations including China and India Initially, the US was cautious about online banking due to a lack of trust, but Chemical Bank pioneered the service by allowing individuals and small businesses to manage electronic checkbooks and transfer funds Following this, major banks such as Citibank and Chase Bank adopted similar services In France, online banking was introduced in 1988 via the Minitel system, which provided free access to the public Japan saw its first online banking service from Sumitomo Bank in 1997, followed by India a year later, with most Japanese banks offering diverse online services by 2010 In China, Tencent launched its online banking platform, WeBank, in January 2015, which subsequently gained popularity and expanded to Vietnam.

Utilizing the PEST model provides a comprehensive understanding of the current payment tools landscape in Vietnam This analytical framework examines the external factors—political, economic, social, and technological—that significantly influence the payment ecosystem By applying the PEST model, we can gain clear insights into these critical performance areas within the Vietnamese context.

Political: Vietnamese government started to deploy non – cash payment in

In 2011, the State Bank of Vietnam issued Circular No 29/2011/TT-NHNN on January 29, establishing safety and confidentiality standards for internet banking services This regulation was reinforced by Decree No 101/2012/NĐ-CP, which outlined the SBV's responsibilities for managing non-cash payment activities, ensuring information security, and supervising mobile banking operating systems.

Since 2012, Vietnam has implemented decrees and resolutions to promote non-cash payment projects and advance fintech technology In 2020, the State Bank of Vietnam issued Decision No 711/QĐ-NHNN to foster the growth of digital technology enterprises, aiming to establish a supportive legal framework for digital banking development Additionally, Decision No 1238/QĐ-NHNN further emphasizes the government's commitment to enhancing the banking sector in alignment with the Fourth Industrial Revolution Overall, the Vietnamese government has consistently created favorable conditions for the banking industry to evolve and thrive.

Vietnam has experienced relatively stable economic growth, with GDP rising from 6.81% to 7.017% over three years Despite the serious global economic impact of the Covid-19 pandemic, the Vietnamese government effectively controlled the outbreak, allowing the economy to transition back to a new normal Although GDP growth fell by 2.91% in 2020, it remained stable overall Additionally, Vietnam's open-door policy encourages foreign investment, further supporting economic resilience.

The EU-Vietnam Free Trade Agreement, effective August 1, 2020, presents a significant opportunity for Vietnam to enhance its appeal as an investment destination for leading technology companies This strategic partnership is expected to foster economic growth and innovation within the region.

Figure 1.1: Grow rate of GDP in Vietnam from 2017 to Q1/2021

Source: Vietnam GSO, World Bank

In 2020, the General Statistics Office reported that Vietnam's population reached approximately 97.58 million, with around 53.59 million individuals actively participating in the labor force The country's youthful demographic facilitates the adoption of new technologies and trends, making it easier for Vietnamese citizens to integrate modern advancements into their daily lives.

Vietnamese culture strongly favors cash transactions, making it challenging to transition to non-cash payment methods According to Ms Le Thi Thuy Sen, Director of the Communications Department of the State Bank of Vietnam, changing consumer habits and perceptions is crucial for promoting digital payments Despite nearly 40% of the population having bank accounts, a staggering 80% of daily expenses are still paid in cash, with 98% of purchases under VND 100,000 made in cash and nearly 85% of ATM transactions being cash withdrawals.

In 2019, the percentage of ATM cash withdrawal transactions significantly declined, dropping from 62% in 2018 to 42% This reduction can be attributed to the advancement of non-cash payment policies that have encouraged consumers to adopt alternative payment methods.

2019 It can be seen that the consumption habits of people have begun to change when gradually shifting from cash transactions to using non-cash payment methods (Quang Tuan, 2020)

The outbreak of Covid-19 significantly accelerated the shift towards non-cash payments, as the government's social distancing directives prompted a surge in digital transactions To support this transition, over 50% of banks implemented fee reductions for online transactions, lowering fees from 7,000 VND to 0 VND during the pandemic Consequently, 65% of payment transactions benefited from fee exemptions or reductions, with 70% of payments under 2 million VND being conducted digitally (Quang Tuan, 2020).

The shift from cash to non-cash payment methods significantly alters consumer habits, a trend that is expected to accelerate with the implementation of digital banking policies in the upcoming year.

Technology plays a crucial role in developing modern products and services, offering numerous advantages to customers while enhancing overall quality of life It facilitates faster work completion and ensures high levels of authenticity Additionally, advancements in technology have opened doors for new and startup tech enterprises in Vietnam.

Vietnam's non-cash payment system is experiencing rapid growth, driven by significant investments in infrastructure and technology to meet both domestic and international payment demands Most banks and payment service providers utilize electronic money transfers through SWIFT for foreign currency transactions and international payments (Le Thi Thanh, 2020) Additionally, the development of mobile banking and internet banking services incorporates advanced technology, enabling efficient processing of high transaction volumes and timely service delivery.

The rapid advancement of digital technology is transforming banking operations, with innovations such as mPOS contactless payments and QR codes enhancing customer interactions Additionally, the implementation of electronic Know Your Customer (eKYC) processes significantly boosts security while streamlining customer registration These technological advancements not only improve the bank's management system but also elevate the overall customer experience, highlighting the positive impact of technology in the banking sector.

Literature review

Literature review about digital banking

The 4.0 technology revolution has permeated various aspects of daily life, including machines, home appliances, and smartphones, with the banking industry also embracing this shift Since 2018, the concept of digital banking has gained significant attention in Vietnam, reflecting the growing integration of technology in financial services.

Carmen Cuesta and partners (2015) highlight that while they did not provide a detailed definition of digital banking, they emphasize its focus on generating the supply, distribution, and sales of financial products and services through digital channels They assert that digital banking prioritizes customer demand, as customers are the direct users of these banking services.

Digital banking is transforming retail banking, influenced by various institutional circumstances This transformation occurs in three main phases: responding to competition, adopting technology, and strategic positioning According to Darryl Proctor (2019), digital banking refers to the digitization of traditional banking services previously accessible only in physical branches, encompassing activities such as deposits, withdrawals, transfers, and account management A Gartner report (2019) further emphasizes the essential elements that define digital banking.

“ongoing financial management” and “digital aided by people” meaning that there is no need for human intervention in the use of translation digital banking

Digital banking is crucial for enhancing customer loyalty in Vietnam, necessitating its adoption by banks (Nguyen Thi Oanh, 2020) It encompasses a broader range of services than traditional banking, including online, internet, virtual, and electronic banking Digital banking signifies the comprehensive integration of digital technologies into banking services, business operations, and customer interactions In contrast, other definitions only address specific aspects of digitalization, such as wire transfers and payments, without encompassing the full operational integration of banks (Pham Tien Dat and Luu Anh Nguyet).

Digital banking represents a transformative business model that goes beyond merely digitizing traditional banking services; it integrates all banking activities into a cohesive digital application This evolution requires a fresh perspective on value creation, moving away from simply indexing existing services to embracing innovative approaches that redefine the banking experience (Kinh Duong, 2018).

Many people mistakenly equate digital banking with electronic banking, although they share similarities in facilitating online transactions Electronic banking services, such as internet banking and mobile banking, emphasize features like electronic money transfers, online savings deposits, and account inquiries Customers' trust in banking systems drives the adoption of these services A survey of over 300 customers at major retail banks in South Africa, combined with the Technology Acceptance Model (TAM), highlights that customer confidence in e-banking is a crucial factor influencing the use of electronic banking services via the internet and mobile devices.

Digital banking encompasses the complete digitization of essential banking functions, including customer identification and account opening (SCN Education B.V., 2001) It represents a modern banking model that operates entirely on digital platforms, whereas e-banking serves as a complementary service to traditional banking (Thanh Phuong Nguyen et al., 2018) A 2018 survey by the State Bank revealed that 94% of joint stock commercial banks are pursuing digital transformation initiatives, leveraging technologies like artificial intelligence, OPBA robots, and digital branches (Nguyen Thu Thuy et al., 2020) Research by Nguyen Duy Thanh and colleagues identifies a new acceptance model for electronic banking services in Vietnam, demonstrating that 57% of the variations in e-banking adoption can be explained by this model Consequently, digital banks can effectively utilize digital technologies such as artificial intelligence and big data to enhance their core services efficiently and scientifically.

I concur with the views of researcher Kinh Duong and Thanh Phuong Nguyen et al that digital banking represents a modern evolution of traditional banking services It digitizes all conventional banking activities, allowing customers to access and utilize banking services just as they would at a regular bank, but with the added convenience and efficiency of digital technology.

Many people mistakenly believe that digital banking is simply a subset of electronic banking, often confusing services like TP Bank's live banking with true digital banking offerings I align with Gartner's perspective that digital banking products are those that are enhanced by human interaction, rather than solely relying on technology.

Literature review about factors affecting the customers’ adoption

The objective of my graduate thesis is to analyze the factors influencing customers' adoption of digital banking in Vietnam Research indicates that early adopters and frequent users of internet banking exhibit higher satisfaction levels Most studies utilize models related to customer adoption, primarily the Technology Acceptance Model (TAM) Developed from the Theory of Reasoned Action (TRA) by Davis and colleagues, TAM aims to trace the influence of external factors on internal beliefs, attitudes, and intentions It identifies key variables that determine perceived usefulness and ease of use, both of which shape user attitudes Positive attitudes towards digital banking ultimately lead to increased actual usage among customers.

User motivation to adopt new technology, particularly in digital banking, is influenced by several key factors, including perceived ease of use (PE), perceived usefulness (PU), perceived risk, trust, attitude towards use, and intention to use According to Waleed Mugaheed Al-Rahimi (2013), external variables significantly impact these constructs Additionally, research by Nuno Fortes and Paulo Rita highlights the importance of these external factors in shaping users' attitudes towards digital banking services This study aims to explore how these elements collectively affect customer acceptance of digital banking.

Actual usage Perceived ease of use

Figure 1.3: Research model framework for the customers adoption to use digital banking of

According to Fred D Davis (1989), perceived usefulness refers to the extent to which an individual believes that utilizing a specific system can enhance their work performance This concept emphasizes the practical benefits of a system, which can significantly improve efficiency I concur with this definition, as an effective system can lead to substantial increases in productivity, saving both time and costs compared to traditional banking methods Digital banking services, for instance, facilitate the management of large transaction volumes, such as employee salary payments and bulk purchases, streamlining processes and enhancing overall operational efficiency.

In addition, with 6 assumptions made, surveying more than 200 customers and applying linear regression model combined with TAM model, the end result gives the

The "perceived usefulness" factor is the most influential in encouraging customers to adopt digital banking To enhance this adoption, banks should develop effective policies and implement a comprehensive banking development strategy that prioritizes customer service (S Anada et al., 2020).

Customers' Attitude towards use and Intention to use

12 this service can be accessed account query like any previous transactions These features are all integrated by banks on their e-banking products to help customers use them more conveniently

The concept of "ease of use" refers to the simplicity and effortlessness of engaging with a system or application According to Davis, it reflects the extent to which individuals perceive a system as requiring minimal effort He suggests that applications perceived as easier to use are more likely to gain user acceptance Fortes emphasizes that ease of use involves a straightforward and comprehensible process I align with their perspectives, as they accurately capture the essence of "ease of use" as being free of effort and easy to manipulate This principle is evident in banking applications, which are designed with clear objectives, each represented by intuitive images for their respective features.

E-banking services offer users convenience and comfort, yet they also raise concerns about risk perception when utilizing online platforms Fortes highlights that this perception of risk is a significant barrier to the growth of the e-consumer market, positioning it as a key factor in competing with traditional services As e-commerce continues to evolve, allowing for seamless shopping experiences at any hour, the advancement of technology also increases opportunities for fraudsters to compromise personal information, making data security challenging Lim (2003) provides a fresh perspective on perceived risk by distinguishing it from traditional approaches that focus solely on the consequences of risk.

The perception of risk in digital banking can be categorized into four levels: perceived technological risk, vendor risk, consumer risk, and product risk I align with two of these levels—perceived technological risk, which encompasses potential losses due to internet security vulnerabilities, and consumer risk, which involves the unauthorized use of personal information Recognizing these perceived risks is essential for customers to safeguard themselves while using digital banking services.

Customers using online products and services often exhibit confidence, yet challenges arise from the inability to physically interact with these offerings Research by McKnight et al highlights that a lack of trust can cause consumers to hesitate in sharing personal information and making purchases online Therefore, trust in the applications is crucial for customer engagement with online services In the banking sector, customers who trust digital banking solutions tend to rely on reputable banks, influenced by factors such as brand credibility and service efficiency.

(5) Attitude towards use and Intention to use

Customer attitudes significantly influence their decision to adopt new services Adoption refers to the acceptance and initiation of using a new product or service Ana Sousa posits that the alignment between a product's user image and a consumer's self-concept impacts purchasing behavior In the context of digital banking, customers often develop a positive attitude due to its convenience, allowing them to conduct transactions anytime and anywhere without visiting a physical bank Additionally, online savings accounts frequently offer more attractive interest rates compared to traditional options Nguyen Thi Oanh's study investigates the intent to use digital banking in Vietnam, employing data analysis methods such as Cronbach's alpha, Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) based on 201 survey responses.

The findings from the questionnaire indicate that service attitudes and perceived usefulness significantly influence customers' intention to adopt digital banking Fishbein and Ajzen (1975) emphasize that intention is a crucial component of action theory, serving as a predictor of users' future behaviors Supporting this, Jenifer et al (2014) affirm that intention acts as a preparatory step before an individual engages in specific actions Consequently, intentions play a vital role in shaping user behavior, ultimately determining whether users choose to embrace this service.

In conclusion, the five key factors—perceived ease of use, perceived usefulness, perceived risk, perceived trust, and attitude towards use—play a significant role in understanding user intention and behavior in this research area.

Gap, research objectives and research questions

Gap of the previous researches

In the world, it had the study about reinforces confidence in the adoption and use of existing e-banking services for customers The research of Daniel Kofi Madu

A 2014 study highlighted that customer confidence is a crucial factor influencing the use of electronic banking services in South Africa However, it focused solely on electronic banking rather than the broader scope of digital banking Additionally, the research conducted by Daniel was limited to South Africa and did not consider other countries, such as Vietnam In contrast, another study explored the factors impacting the adoption of digital banking within Omani retail banks.

Research in Vietnam primarily focuses on the acceptance and intention to use e-banking services, with findings from Nguyen Duy Thanh indicating that existing models do not significantly outperform others This suggests a limited capacity to gauge customer acceptance of e-banking services (Nguyen Duy Thanh et al., 2011) Additionally, studies have not progressed to establishing a comprehensive model for the application and utilization of e-banking services, leaving a gap in understanding the broader usage of digital banking, as highlighted by Nguyen Thi Oanh's research.

Nguyen Thi Oanh's research highlights the importance of raising customer awareness regarding the benefits of digital banking in Vietnam through effective advertising and counseling While the study focuses on customer perceptions of digital banking's usefulness and its impact on usage intentions, it emphasizes the need for further enhancement of these perceptions in the current context, rather than merely accepting digital banking as part of everyday life (Nguyen Thi Oanh, 2020).

While foreign studies on digital banking services are more prevalent than those in Vietnam, local research primarily focuses on the acceptance of mobile banking, lacking comprehensive analysis of current digital banking usage Most studies emphasize two key factors: ease of use and usefulness, yet they overlook critical elements such as user trust and risk perception.

Researcher Oanh Nguyen Thi highlighted the intention to use digital banking rather than its acceptance, indicating a gap in existing studies Most research employs the Technology Acceptance Model (TAM), which I have also chosen for my analysis Given the existing gaps and the incompleteness of prior studies, I have selected the topic “Factors Affecting the Adoption of Digital Banking in Vietnam” to uncover new insights and positively influence the adoption of digital banking in the country.

Research objectives

This article aims to assist banks in understanding their customers' needs and identifying suitable digital banking solutions In the context of the 4.0 technology revolution, it explores how customers perceive digital banking services By gaining insights into customer experiences, banks can enhance their product and service quality to better meet customer demands Additionally, many customers struggle to differentiate between a bank's digital banking offerings and those provided through partnerships, which significantly influences their perceptions.

The research paper provides valuable insights into customer consumption behavior, enhancing their understanding of digital banking as a whole rather than just its individual components that may often be misunderstood.

Research questions

This research paper explores customer acceptance of digital banking services in Vietnam and identifies necessary improvements to enhance customer confidence compared to traditional banking By addressing these critical questions, bank leaders can better understand customer needs and trends, enabling them to develop effective solutions that align with the evolving digital banking landscape while meeting customer expectations.

In the opening chapter, the author contextualizes Vietnam within the fourth technological era using PEST analysis and reviews existing literature on digital banking from both Vietnamese and international studies The research identifies five key factors influencing the adoption of digital banking: perceived ease of use, perceived usefulness, perceived risk, trust, and attitude towards use By aligning with previous research on these factors, the author presents a framework model that illustrates their impact on adoption The study aims to enhance banks' understanding of citizen needs and acceptance of digital banking services in Hanoi, leading to tailored product offerings Ultimately, the selection of the topic "Factors Affecting the Adoption of Digital Banking in Vietnam" is justified by the research objectives and identified gaps in existing studies.

Research method

Research approach and design

This study employs quantitative research, contrasting with qualitative research, which influences the nature of the data collected While qualitative research emphasizes in-depth information (Bryman, 2012), it allows for the exploration, description, and explanation of relationships between existing or new data (Saunders et al., 2012) Analyzing qualitative data provides diverse perspectives on the research topic (Bryman, 2012).

In 2009, it was noted that qualitative data offers significant advantages in measurement, enabling researchers to generate reliable data efficiently (Bryman, 2012) This reliability makes qualitative methods particularly suitable for examining the factors influencing the adoption of digital banking through the Technology Acceptance Model (TAM).

Data source

There are two main types of data: primary data and secondary data Secondary data is gathered by other researchers for similar topics and objectives, which can save time and costs in the research process (Bryman, 2012) However, secondary data may be outdated and not consistently updated to reflect current conditions, leading to potential inaccuracies.

Most researchers utilizing qualitative data rely on primary data collected through methods such as surveys, questionnaires, face-to-face interviews, and observations (Bryman, 2012; Saunders et al., 2009) These scholars emphasize that the preparation and data collection process can be time-consuming and may lead to low response rates, which can adversely affect the quality of the data and the conclusions drawn (Bryman, 2012; Saunders et al.).

This research primarily utilizes primary data due to the limited availability of relevant articles on the topic in Vietnam, with most information found in foreign journals Incorporating secondary data will enhance the clarity and strength of the arguments presented.

Data collection method

The research utilized a questionnaire as the primary data collection method to engage a wide range of customers This questionnaire is structured into three main sections: General Information, In-Depth Survey, and Assessment The General Information section comprises nine questions aimed at gathering personal details, service usage frequency, and types of services utilized The In-Depth Survey examines key dependent variables, including perceived usefulness, perceived ease of use, perceived risk, trust, attitude towards use, and intention to use, alongside the independent variable of adoption to use The final Assessment section summarizes the findings and customer insights The questionnaire was developed based on existing models from previous research, and the survey process spanned approximately two weeks, with an overall preparation and completion period of about one month.

Form of questionnaire

The table is below showing the content of research’s questionnaire included concept, question, theory and measurement

PE1 Conditions and terms when using digital banking services are clear

PE2 Product description of digital banking service is easy to see and understand

PE3 Using guidelines are easy to read and understand

PU1 Using digital banking services to save large expense

PU2 Using digital banking services to save transaction time

PU3 Using digital banking services to easily handle a large transaction volume at a time

PU4 I use digital banking services anytime, anywhere

Davis (1993) 5 – point Likert scale PU5 I easily re-query my finances as needed

PR1 Personal information security is not high

PR2 Updating my card number on the digital banking services application is easy to get information stolen

PR3 Digital banking service often has system error when I am making transaction

PR4 Digital banking service does not guarantee the successful transfer and receipt of money

T1 I choose to use digital banking services in here because of the bank’s brand name

T2 Using digital banking services helps me control my finances better

T3 The digital banking services at this bank which I choose is very reliable

Attitude towards use and Intention to use

ATT1 I accept to use digital banking services in the long term

ATT2 I will introduce to everyone to use digital banking services

INT I will use digital banking services instead of traditional banking services

Actual use I accept to use digital banking services in Vietnam

To draw conclusions and results of the dependent variable

Actual use How long do you use digital banking services?

Chang (2004) Multiple choice questions Actual use How much digital banking services do you use? And for what?

To establish the link between the research and the respondent (doing the basis for the situation)

Demographic Please state you gender To establish the link between the research

22 and the respondent (doing the basis for the situation) question about the respondents’ gender

Demographic Please state your age (divide the age in different generations)

A closed – ended question, personal question about the respondents’ age

Demographic Please state your occupation

(classified by job title levels by age group above, from student to retired)

A closed – ended question, personal question about the respondents’ occupation

Demographic Please state the major in which you are working (classified by field in society)

A closed – ended question, personal question about the respondents’ majors

Demographic Please state your current income level (based on the average income of people in Hanoi)

A closed – ended question, personal question about the respondents’ income

Source: Student summarized and researched

Sample data

Descriptive data

According to Bryman (2012), a sample is defined as “the segment of the population that is selected for investigation” (p 187) In this study, the sample consists of individuals from various industries, including Banking and Finance, Sociology, and Information Technology, all of whom utilize digital banking services in Hanoi, Vietnam.

The research garnered 181 responses, slightly below expectations but still deemed acceptable After filtering out invalid votes and addressing mutation phenomena, 150 valid responses were retained These responses met the requirements and were evenly distributed among participants The majority of respondents were female, primarily from the Banking and Finance sector, with experience in Digital Banking ranging from 1 to over 3 years.

Figure 2.1 illustrates the gender distribution among respondents, revealing that females constitute approximately 74% of the total, while males make up 26% A small number of respondents identify as other genders, but this group is not significant The higher female representation is attributed to women's greater engagement in shopping and consumption activities, leading to a more extensive experience with checkout transactions compared to their male counterparts.

Figure 2.2: The respondents about age group

The pie chart illustrates the distribution of respondents by age group, revealing a relatively even spread among three categories: 18 to under 22, 22 to under 30, and 30 to under 50 Notably, individuals over 50 represent a minimal percentage The 30 to under 50 age group, which includes the X generation, constitutes 46% of the total respondents, highlighting their education and stable employment.

The age groups of 18 to under 22 and 22 to under 30 years old represent significant segments of digital banking users, accounting for 22% and 28% of the total, respectively The 22 to under 30 age group, comprised of millennials born in the late 1980s to early 1990s, is notably influenced by technology, although their access remains limited In contrast, the 18 to under 22 age group, representing Generation Z, has early access to technology and smart devices, facing pressures related to materialism and prestige This group, which includes students and job seekers, also makes up 22% of digital banking users Meanwhile, individuals over the age of 50, primarily retirees with less exposure to technology and a preference for safety, constitute a small minority at just 4% of the total respondents.

Age 18 - under 22Age 22 - under 30Age 30 - under 50Above age 50

2.2.1.3 Respondents’ occupation and fields of operation

Figure 2.3: Respondents’ occupation of research

In this research, four occupational groups were identified: Students/unemployed individuals/job seekers, Occupants, Freelancers/self-employed/business owners, and Retirees Notably, the Occupant group represents the largest segment, comprising approximately 69% of the total with around 103 individuals, attributed to their higher proficiency in utilizing digital banking compared to the other groups.

Figure 2.4: Respondents’ fields of operation

In the total number of respondents, there are 100 people or 67% which are studying and working in the Banking and Finance sector Immediately after that there

Freelance/ self-employed/ business owner

Students/ unemployment people/ job seekers

In a recent analysis, 27 individuals were categorized, with 18 (12%) employed in business fields, while others were engaged in sociology, information technology, education, accounting, auditing, and construction, representing 3%, 7%, and 11% of the workforce, respectively The prominence of the Banking and Finance sector is attributed to their expertise in digital banking and their early adoption of digital banking services compared to other sectors, making them a preferred group for targeted outreach and analysis.

Figure 2.5: Distribution of respondents’ income Unit: VND million

According to the Vietnamese General Statistics Office, the average salary for new employees is 4.2 million VND To enhance their income, many individuals seek additional compensation, leading to income benchmarks of 5 million, 20 million, and 50 million VND These figures represent various employment levels: 5 million VND for new hires, 20 million VND for regular employees, and 50 million VND for department heads and above The survey results indicate that most respondents earn between 5 million and under 20 million VND.

90 persons, relatively 60% of total This can understand that the people in this income group are employees, workers, etc The group of under 5 VND million follows

In a recent analysis, it was found that 28 individuals, representing 22% of the total, are engaged in part-time work, entry-level positions, or low-paying jobs Additionally, 20 people earn between 20 million VND and under 50 million VND, accounting for approximately 13%, while 7 individuals earn above 50 million VND, making up about 5%.

2.2.1.5 Actual usage of digital banking services time

Figure 2.6: Respondents’ time to use digital banking services Unit: Year

Figure 2.6 illustrates the distribution of users utilizing digital banking services Notably, all respondents have engaged with these services, with 78% (117 users) having used digital banking for over three years Additionally, 19% (29 users) have utilized these services for one to three years, while only 3% of respondents have been using digital banking for less than one year.

Time to use digital banking services

2.2.1.6 Number of digital banking services

Figure 2.7: Respondent's number of digital banking services

Vietnam's digital banking landscape offers various services, including Internet banking, mobile banking, ATMs, and cash deposit machines (CDMs) Among 150 surveyed users, over 90% utilize Internet Banking and Mobile Banking, with ATMs being the most favored service, used by 139 individuals (93%) E-wallets linked to banks, like Viettel Pay and VinID, account for 57% of users In contrast, CDMs and video banking services, such as TPBank's Livebank, have lower user rates at approximately 30% and 13%, respectively, largely due to the limited availability of CDM machines in Hanoi, with only a few banks like ACB, VPBank, and Agribank offering them.

(4 units), etc and deployed digital banking services via video so that it cannot have as many customers as other services.

Data analysis

This article employs a multivariate method for analyzing research data, utilizing Cronbach's Alpha for scale reliability analysis This approach assesses the reliability of variables that consist of three or more observed variables, with a focus on those exhibiting a Corrected Item-Total Correlation of ≥ 0.3, as established by Nunnally and Bernstein (1994).

E-Walet linked to bank Digital banking through video

CDM ATM Mobile banking Internet banking

Respondent's number of digital banking services

A satisfactory correlation coefficient and a Cronbach's Alpha value of 0.6 or higher indicate reliability (Hoang Trong, Chu Nguyen Mong Ngoc, 2008) However, during the testing phase, issues arose with variable pooling and insufficient observed variables To address this, additional factors were utilized for validation.

Exploratory factor analysis (EFA) is utilized to consolidate numerous observed variables into meaningful groups, facilitated by the Pattern Matrix Following this, the Pattern Matrix is incorporated into confirmatory factor analysis (CFA) Structural equation modeling (SEM) is employed to examine the interactions among factors influencing service use attitudes and usage intent, with a significance level of 5% deemed acceptable Additionally, various tests are conducted on the pooled variable group during the SEM analysis to enhance the reliability of the findings.

Research Hypotheses

Before formulating my hypotheses, it is essential to address the gaps in my research Fishbein and colleagues highlighted that "Behavioral intention" reflects an individual's subjective ability to perform a behavior and influences their attitude towards that behavior This implies that if customers are inclined to use a service, their usage frequency and variety will indicate their level of trust My research incorporates the concept of "perceived trust," which, along with perceived usefulness, significantly affects long-term acceptance of internet services (Jian Mou et al., 2015) Furthermore, trust can enhance the intention to use a product by influencing its perceived ease of use and usefulness (Yi-Hsuan La et al., 2013) Due to the absence of a structured questionnaire, I will merge the intermediate variables of "attitude towards use" and "intention to use" into a single construct.

Based on theoretical concepts and prior research, along with the explanation of the five variances outlined earlier, this section will establish the hypotheses for my research model.

With this variance, perceived ease of use effect on perceived usefulness The hypothesis is proposed as follow:

H1: Perceived ease of use has positive impact on the perceived usefulness when using digital banking service

The effectiveness and usefulness of a product or service for users are significantly influenced by their perception of risk Based on this understanding, we propose the following hypothesis regarding perceived risk.

H2: Perceived risk has a negative impact on perceived usefulness

Because perceived usefulness and trust are both impact on accept use internet service for long time (Jian Mou et al, 2015) With this variance, the hypothesis is proposed as follow:

H3: Perceived usefulness has a positive impact on trust when using digital banking service

With this variance, the hypothesis is proposed as follow:

H4: Trust has a positive impact on the attitude towards use and intention to use

(5) Attitude towards use and intention to use

H5: Attitude towards use and intention to use have a positive impact on the acceptance of use

The table below illustrates the anticipated effects of the hypotheses presented in the article This forecast is essential, as it enables the study to verify the accuracy of the predictions after the results are tested.

Table 2.2: Forecast effect of research hypotheses

H1 (PE) Perceived ease of use has positive impact on the perceived usefulness when using digital banking service

H2 (PR) Perceived risk has a negative impact on perceived usefulness

H3 (PU) Perceived usefulness has a positive impact on trust (+) Accepted

Figure 2.8: Research model and hypotheses

33 when using digital banking service H4 (T) Trust has a positive impact on the attitude towards use and intention to use

Attitude towards use and intention to use have a positive impact on the acceptance of use

In the second chapter, the author outlines the research methods and data collection sources informed by prior studies The chapter includes a detailed description of the questionnaire used and the data sample, which consists of 150 collected responses Based on this sample, the author proposes five research hypotheses that correspond to the influence of the five factors identified in the model.

Research results

Reliability

To effectively test a scientific theory, it is essential to ensure the reliability of the scale and analyze its value Utilizing Cronbach Alpha analysis allows for the assessment of the reliability of the scale by examining a set of variables that encompass various factors representing the main variable In this study, the final group includes a pooled variable set that combines Attitude towards Use and Intention to Use.

This research has 5 independent variances, so that we renamed these variances: +) Perceived Ease of use – PE

+) Attitude towards use and Intention to use – ATTINT

Table 3.1: Overview of Cronbach Alpha

Alpha Number of items Item remove

Source: Results of IBM SPSS Statistics

According to Nunnally (1994), measurement variables should have a corrected item-total correlation of at least 0.3 and a Cronbach’s Alpha value that remains the same or increases when an item is deleted Hoang Trong and colleagues suggest that a reliability score between 0.8 and 1 indicates excellent reliability, while scores of 0.6 and above are considered acceptable.

The test results indicate that all five variables meet the established criteria, with Cronbach's Alpha reliability exceeding 0.8 for each The PR variable exhibits the highest reliability at 0.897, while the T variable, at 0.816, remains above the acceptable threshold Additionally, all observed variables demonstrate a Corrected Item-Total Correlation of at least 0.3, and the Cronbach’s Alpha if the item is deleted does not exceed the overall Cronbach's Alpha Consequently, no observed variables from the five groups were excluded, allowing all variables to proceed to the next phase of model analysis.

Results of exploratory factor analysis (EFA)

Table 3.2: KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy

The KMO and Bartlett’s Test table serves as a crucial initial assessment for determining the suitability of conducting Exploratory Factor Analysis (EFA) The Kaiser-Meyer-Olkin (KMO) index indicates the appropriateness of factor analysis, with values between 0.5 and 1 deemed acceptable; a KMO value of 0.820 confirms the model's suitability for EFA Additionally, Bartlett’s Test of Sphericity assesses the significance of the correlation among observed variables, with a significance value below 0.05 indicating strong intercorrelations; in this case, a significance index of 0.00 further validates the appropriateness of proceeding with EFA.

In Exploratory Factor Analysis (EFA), the eigenvalue index is crucial for determining the number of factors to retain, with factors having an eigenvalue of 1 or greater being included in the analysis model The accompanying table illustrates the total variance explained by the model, categorizing factors into groups that correspond to the number of variances A suitable model is characterized by a total variance explained of 50% or more, indicating the proportion of variance accounted for by the factors and the extent of variance lost from the observed variables.

Rotation Sums of Squared Loadings a Total

With 18 factors, it is possible to load only 5 group factors with Eigenvalues greater than 1 and which is condensed into 5 groups with a total extracted variance of 65.570% ≥ 50% (suitable condition) These 5 groups are equivalent to the 5 variables being watched

In exploratory factor analysis (EFA), a model is deemed suitable when the total variance explained exceeds 50% The pattern matrix, generated using the promax rotation method, presents coefficients sorted by size while suppressing small coefficients with an absolute value below 0.5 This matrix reveals five group factors, each with a factor loading greater than 0.5 If any factor loadings fall below 0.5, those variances are excluded, and the analysis is rerun to ensure accurate results.

Extraction Method: Principal Axis Factoring

Rotation Method: Promax with Kaiser Normalization a Rotation converged in 7 iterations

The pattern matrix reveals distinct groups of factors that are effectively organized without any clutter, ensuring that each observed variable aligns with its respective group The factor loadings are robust, exceeding 0.5, with the PR group demonstrating the highest loadings ranging from 0.738 to 0.937 Following this, the PU, PE, T, and ATTINT groups show varying loadings, with ATT1 at 0.594 being the lowest among the five groups but still above the threshold of 0.5, indicating it should remain included In summary, the pattern matrix identifies five groups of factors corresponding to the variables PU, PR, PE, T, and ATTINT.

Result of Confirmatory factor analysis (CFA)

According to the Hair and partners (2010), the result of CFA can be acceptable which

+) CMIN/df ≤ 2: positive, CMIN/df ≤ 5: acceptable

+) CFI ≥ 0.9: positive, CFI ≥ 0.95: perfectly positive, CFI ≥ 0.8: acceptable +) GFI ≥ 0.9: positive, GFI ≥ 0.95: perfectly positive

The study's sample size is limited, making it challenging to achieve a GFI index threshold of 0.9 However, as noted by Baumgartner and Homburg (1995), a GFI index of 0.8 is considered acceptable in such cases.

The result of CFA showed that: CMIN/df = 1.920 < 5: acceptable, CFI = 0.925

In confirmatory factor analysis, ensuring convergent validity, discriminant validity, and reliability is crucial Without these validity and reliability factors, the analysis results may be biased, leading to numbers that do not accurately reflect the significance of the data and reality.

According to Hair and partners (2010), the measure of Reliability test and Validity test is defined that:

+) Standardized Loading Estimates ≥ 0.5: positive, perfectly positive is ≥ 0.7 +) Composite Reliability (CR) ≥ 0.7: positive

+) Average Variance Extracted (AVE) ≥ 0.5: positive

+) Maximum Shared Variance (MSV) < Average Variance Extracted (AVE) +) Square Root of AVE (SQRTAVE) > Inter – Construct Correlations

In Confirmatory Factor Analysis (CFA), the Standardized Loading Estimates serve as a key indicator for evaluating model fit The Standardized Regression Weights table includes these estimates, where observations with values above 0.5 are retained for analysis Conversely, any observations with Standardized Loading Estimates below 0.5 must be excluded, necessitating a rerun of the CFA to ensure accurate results.

The estimates for various parameters are as follows: PU3 is 0.797, PU2 is 0.733, PU1 is 0.681, PU4 is 0.811, and PU5 is 0.748 For the PR values, PR4 is 0.944, PR3 is 0.885, PR2 is 0.764, and PR1 is 0.704 The PE estimates show PE3 at 0.819, PE2 at 0.883, and PE1 at 0.791 Additionally, the INT value derived from ATTINT is 0.719, with ATT2 at 0.771 and ATT1 at 0.847.

Source: Results of IBM AMOS Graphics

Table 3.5 presents significant reliability results for all observed variances, with Standardized Loading Estimates exceeding 0.5 The reliability scores range from 0.680 to 0.944, indicating that all observed variances are significant and above the 0.5 threshold, with differences of 0.2 to 0.4 units Consequently, no observational variables were eliminated, and there is no need to re-run the model.

Table 3.6 presents the results of Composite Reliability, indicating that all variances fall within the acceptable range, with values ranging from 0.792 to 0.897, exceeding the standard threshold of 0.7 Thus, these findings confirm the adequacy of Composite Reliability.

The validity is determined through the Convergent test and Discriminant test About Convergent test, the Average Variance Extracted (AVE) represents the guaranteed convergence if it is greater than 0.5

The research findings indicate that the Average Variance Extracted (AVE) for all factors with a factor loading greater than 0.5 exceeds the 50% standard Notably, the AVE index for PR is the highest at approximately 0.692, or 69.2%, while the AVE for T is relatively low at around 0.591 Overall, the AVE results meet the required standards, ensuring the model's convergence.

The discriminant test evaluates two key factors: Maximum Shared Variance (MSV) and the Square Root of Average Variance Extracted (SQRTAVE) For the test to confirm the distinctiveness of factors, the condition that MSV must be less than AVE and SQRTAVE must be lower than the inter-construct correlations must be met Table 3.8 illustrates the comparison between Maximum Shared Variance and Average Variance Extracted.

Table 3.8 illustrates that all independent variables exhibit a Maximum Shared Variance (MSV) value lower than their Average Variance Extracted (AVE) values, with all AVE values exceeding 50% Additionally, the Square Root of AVE (SQRTAVE) for each factor surpasses its Inter-Construct Correlations, confirming that the scales meet the criteria for the discriminant validity test To accurately compute SQRTAVE, it is essential to adjust the last value in the Inter-Construct Correlations table to 1000, thereby eliminating any confusion during comparisons.

Table 3.9: Comparation of Square Root of AVE and Inter – Construct Correlations

Variances SQRTAVE MaxR(H) ATTINT PU PR PE T

Table 3.9 presents the results for the Square Root of Average Variance Extracted (SQRTAVE) and Inter-Construct Correlations, demonstrating that SQRTAVE significantly exceeds the Inter-Construct Correlations This indicates that the scales meet the criteria for discriminant validity Specifically, the Average Variance Extracted (AVE) is above 50%, the Maximum Shared Variance (MSV) is lower than the AVE, and the SQRTAVE for each factor surpasses its Inter-Construct Correlations, confirming that the measurement fully complies with the conditions of the discriminant test.

Result of Structural Equation Modeling

Figure 3.1: Research of Structural Equation Modeling framework

Source: Student researched, IPM AMOS Graphics

The results of the Structural Equation Modeling align closely with the Confirmatory Factor Analysis (CFA) model, demonstrating a CMIN/df value of 1.884, which is below the threshold of 5, a CFI of 0.925 exceeding the 0.9 benchmark, and a GFI of 0.845 surpassing the 0.8 standard (Appendix 3) This model enables the identification of factors that positively influence attitudes toward and intentions to use digital banking services.

In assessing the reliability and validity of the model, a significance level of 5% is established, where the p-value is compared to 0.05 If the p-value for any factor exceeds 0.05, the corresponding hypothesis will not be accepted or tested further.

Table 3.10: Regression Weights of SEM

At a 95% confidence level, the PR effect on PU shows a significance of 0.303, exceeding the 0.05 threshold, which leads to the conclusion that the hypothesis cannot be rejected due to insufficient statistical evidence In contrast, the remaining variables exhibit a significance level of 0.000, indicating meaningful relationships Consequently, both the relationship between PE and PU, as well as PU and T, demonstrate a positive impact, with T also maintaining a significant relationship with ATTINT.

Table 3.11: Standardized Regression Weights of SEM

The research will utilize the estimated regression coefficients from the Standardized Regression Weights table to analyze the impact of independent variables on dependent variables The influence of these interacting variables is ranked in descending order, with T, PU, PE, and PR showing varying levels of impact.

Table 3.12: Squared Multiple Correlations of SEM

The Squared Multiple Correlations table reveals the R-squared value, indicating the influence of independent variables on the dependent variable Specifically, the R-squared value for Perceived Usefulness (PU) is 0.485, demonstrating that the independent variables, Perceived Risk (PR) and Perceived Ease (PE), collectively account for 48.5% of the variance in PU.

The analysis reveals that perceived usefulness (PU) influences 23.8% of technology (T), as indicated by an R-squared value of 0.283 Additionally, the R-squared value for attitude toward using technology (ATTINT) is 0.591, suggesting that 59.1% of ATTINT can be attributed to changes in T In conclusion, the R-squared values for PU, T, and ATTINT highlight the significant interactions among these variables.

Result of Multivariate regression analysis

The SEM model successfully tested four out of five proposed hypotheses, with one remaining test to assess how attitude towards use and intention to use influence the acceptance of digital banking services (H5) Pearson correlation analysis indicates a significant relationship between ATTINT and ADT, with a significance value of 0.000, which is less than 0.05, confirming a correlation with the dependent variable.

This study identifies a representative variable for each factor group by calculating the mean of the observed variables, given the presence of multiple observed variables within each group To test hypothesis H5, the analysis focuses on the dependent variable.

“Acceptance to use - ADT” and independent variables “Attitude towards use and Intention to use - ATTINT” as the following formula below:

Table 3.13: Model summary and ANOVA of linear regression

Std Error of the Estimate

1 778 a 606 603 310 1.873 a Predictors: (Constant), ATTINT b Dependent Variable: ADT

Total 35.973 149 a Dependent Variable: ADT b Predictors: (Constant), ATTINT

Table 3.13 presents the findings for R-squared, Durbin-Watson, and significance values The R-squared value of 0.606 indicates that ATTINT accounts for 60.6% of the variance in the dependent variable ADT, leaving 39.4% attributable to external factors and random error Additionally, the Durbin-Watson statistic is 1.873, with lower and upper bounds of dL = 1.473 and dU = 1.783, respectively.

< 1.873 < 4 - dU = 2.217, this model does not have autocorrelation phenomenon Sig value = 0.00 < 0.05 which means that this variance is meaningful for independent variance – ADT

Standardiz ed Coefficien ts t Sig

B Std Error Beta Tolerance VIF

The results indicate that the significance value of the t-test is 0.00, which is below the 0.05 threshold, confirming that the ATTINT variable is significant to the model The beta coefficient of 0.778 suggests that attitude towards use and intention to use account for 77.8% of the acceptance of digital banking services Additionally, with a VIF of 1.000, there is no indication of multicollinearity in the model Therefore, it can be concluded that both attitude and intention to use positively influence the acceptance of digital banking services, leading to the acceptance of the final hypothesis.

Testing hypotheses

As initially, the research paper gives 5 hypotheses After testing the hypotheses through surveyed data, we have the following results:

Table 3.15: Result of Testing hypotheses

H3 (PU) Perceived usefulness has a positive impact on trust when using digital banking service

H4 (T) Trust has a positive impact on the attitude towards use and intention to use

Attitude towards use and intention to use have a

47 positive impact on the acceptance of use

In a study utilizing SEM model analysis and linear regression, four out of five hypotheses were accepted, specifically H1, H3, H4, and H5 H1 confirmed that perceived ease of use significantly influences perceived usefulness H3 revealed a positive relationship between perceived usefulness and trust in digital banking services H4 demonstrated that trust positively impacts both attitudes towards use and the intention to use digital banking Lastly, H5 established that attitudes towards use and intention to use significantly affect the acceptance of digital banking services The findings indicated a strong impact among the variables, with a p-value of 0.000 for the relationships between perceived ease of use and perceived usefulness, perceived usefulness and trust, as well as attitude and intention to use However, hypotheses with p-values greater than 0.05 were rejected.

Discussion

This study aims to explore the various factors influencing the adoption of digital banking services While previous research has utilized the Technology Acceptance Model (TAM) to examine the intention to use digital banking, this survey specifically investigates the determinants that affect customer acceptance of these services The novelty of this research lies in its findings, which often diverge from established theories regarding digital banking acceptance in Vietnam.

According to Davis and partners (1989), the Technology Acceptance Model (TAM) illustrates that perceived ease of use positively impacts perceived usefulness This research aligns with those findings, demonstrating that when a service is easy to understand and the terms and conditions are clearly presented, it significantly influences user attitudes, particularly among translators Consequently, the ease of use of an application directly enhances its perceived usefulness, highlighting the importance of user-friendly design in technology adoption.

Perceived usefulness significantly enhances customer trust in digital banking services, aligning with findings from Jian Mou et al (2015) To foster trust and improve customer experience, banks must prioritize the usefulness of their products, focusing on factors like reduced transaction costs, time savings, and the ability to handle high transaction volumes Despite these advantages, banks often face challenges with slow processing times, which can disrupt urgent transactions To sustain and enhance customer trust, it is crucial for banks to continually improve their service quality and product offerings.

Trust significantly influences users' attitudes and intentions toward service usage, independent of risk perception According to Oanh Nguyen Thi's research (2020), trust indirectly affects these attitudes by positively impacting risk perception High customer confidence in a bank correlates with a favorable usage attitude, often stemming from satisfaction with services or the bank's reputable brand name However, to foster this trust, banks must remain vigilant in product development, as customers' risk perceptions are elevated, necessitating careful attention to avoid disappointment.

The study focuses on customers aged 30 to under 50, specifically those born in the 1980s to early 1990s, who are knowledgeable professionals in the banking and finance sector This demographic is expected to adopt digital banking products more rapidly than individuals aged 50 and above Their consumption habits are shifting from cash transactions to utilizing various banking products and services Despite the relative novelty of digital banking services in Vietnam, there remains a significant portion of the population that has yet to fully embrace them.

Digital banking refers to the online platforms and services that allow users to manage their financial activities Research indicates that positive attitudes towards digital banking significantly influence individuals' intentions to adopt these services As more people become supportive of digital banking, the likelihood of widespread acceptance and usage increases.

Digital banking is gaining popularity in Vietnam, although the country is still in the early stages of digital transformation Many banks have yet to develop their own digital banking products and primarily rely on partnerships with fintech companies to market these services under their brand names Recently, joint stock commercial banks have begun conceptualizing and testing their own digital banking offerings, with some even establishing dedicated digital banking centers and hiring skilled staff for these initiatives This growing adoption of digital banking products and services presents a positive opportunity for banks to enhance their offerings, aligning with the survey results that reflect the current state of Vietnam's banking landscape.

In Chapter Three, the author presents the findings from a reliability analysis of 150 samples using Cronbach's Alpha, confirming the trustworthiness of all variables Following this, Exploratory Factor Analysis (EFA) identifies factor groups, serving as a foundation for the Confirmatory Factor Analysis (CFA) model, which demonstrates reliable variables through achieved Composite Reliability (CR), Average Variance Extracted (AVE), and Square Root of AVE (SQRTAVE) results, allowing for hypothesis testing Utilizing AMOS software, the author performs Structural Equation Modeling (SEM) to evaluate the proposed hypotheses, revealing that four out of five hypotheses can be tested, with three being accepted Due to limitations in observed variables, regression testing is conducted for the final hypothesis, yielding an R-squared value of 0.606 (60.6% > 50%) and a significance value of 0.00 (< 0.05), confirming hypothesis H5.

The results of this model indicate a reasonable acceptance of digital banking services in Vietnam, reflecting the country's ongoing digital transformation With a positive attitude, strong intention to use, and confidence in the products available, Vietnamese users are increasingly embracing digital banking solutions.

SITUATION AND RECOMMENDATION FOR VIETNAM

Situation in Vietnam

Legal Policy

Since 2011, the Vietnamese Government has recognized the importance of non-cash payments and initiated their implementation through various regulations, including Circular No 29/2011/TT - NHNN and Decree No 101/2012/ND - CP The Prime Minister's Decisions No 2545/QD-TTg and No 241/QD-TTg further endorsed the development of non-cash payment systems and the promotion of via-bank payments for public services These measures aim to reduce cash transactions, enhance the volume and value of non-cash payments, save on money printing costs, and improve the quality of life in a modern Vietnam Additionally, the government is gradually advancing policies to support the use of digital banking services, which are currently in the early stages of development and implementation.

Technology systems

The integration of information technology in banking has led to the development of modern products and services, enhancing customer experiences and providing numerous benefits (Dinh Van Chuc, 2020) This technological advancement not only streamlines transaction processes for commercial banks but also optimizes workload efficiency, ensuring speed, accuracy, and reliability with a high level of security Furthermore, the Vietnamese government has enacted various decrees and directives promoting technology adoption in banking services, prompting commercial banks to invest significantly in innovative technologies for their service offerings, operations, and management.

A recent survey by the State Bank Strategy Institute reveals that 96% of participating banks are formulating development strategies centered around 4.0 technologies Notably, 92% are focusing on Internet and Mobile services, while 48% are implementing automation strategies Additionally, a significant number of banks plan to enhance collaborations with Fintech companies to offer banking products and services in key areas, including Payment (92%), digital banking (76%), Big Data (68%), and Blockchain technology (16%) (Tran Linh, 2020).

Many banks in the country today such as TCB, ACB, TP Bank, etc have deployed the achievements of technology 4.0 into the banking operations (Tran Linh,

In 2020, banks increasingly adopted advanced technologies such as Advanced Analytics, Machine Learning, and Artificial Intelligence to enhance their operations For instance, TCB effectively utilized Advanced Analytics to analyze customer data, enabling the development of tailored product strategies Meanwhile, ACB Bank implemented Machine Learning to facilitate employee training through an Online Learning Center, allowing staff to access courses conveniently from their computers Additionally, the use of Chatbots has streamlined customer service by providing automated responses to inquiries, ensuring efficient support for users facing issues.

Many banks have embraced automated banking services, applications, and digital payments, with notable implementations like TPBank's Live Bank, Nam A Bank's digital branch ATM OPBA, and the chatbot services used by MB and South Asia banks This innovation enhances customer experience by providing a wider range of banking services while allowing banks to gain insights into customer preferences and usage habits through digital platforms, including the internet, smartphones, and social networks.

General situation of using non – cash payment in Vietnam

In the world, the trend of using digital banking is booming, typically Europe, Japan, … They have invested heavily in service technology using chain technology,

Vietnam is embracing the trend of artificial intelligence in data management, with commercial banks enhancing their services to attract more customers This shift is evidenced by a notable rise in the number of individual accounts for non-cash payments (Pham The Hung et al., 2021).

Between 2015 and 2019, the banking sector experienced significant growth, with approximately 89 million individual accounts and an average growth rate of 10.26%, leading to a total account balance increase of 25.41% Internet transaction volumes surged by 50.2% annually, while mobile banking payments saw even more dramatic increases, with transaction numbers growing by 84.8% and values by 158.5% (Dao Minh Phuc, 2020) The COVID-19 pandemic further accelerated non-cash payments, with e-commerce sales rising by 17% Domestic card payments accounted for 81% of this growth, despite a 16% decline in international card payments (VECOM, 2021) In early 2020, domestic card payments increased by 26.2% in quantity and 16.7% in value, while internet channel payments rose by 3.2% in quantity and 45.7% in value (Dao Minh Phuc, 2020) By mid-2020, Vietnam had issued 10.3 million new cards, bringing the total to 103.4 million Online payment transactions for local cards processed through the NAPAS system were projected to increase by 185% in quantity and 200% in transaction value by the end of 2020 (VECOM, 2021), indicating robust growth compared to 2019.

General situation of using digital banking in Vietnam

* Digital banking in Vietnam phase

Digital banking refers to the transformation of traditional banking services into a fully digital format This modern approach allows customers to access and utilize banking services through digital platforms, effectively replacing conventional banking methods with a streamlined, technology-driven experience.

54 addition, digital banking is also shown when applying technology platforms such as Advanced Analytics, Machine learning, Artificial Intelligence and Chatbot to facilitate for operations in the bank’s internal system

The evolution of digital banking encompasses three key phases: the Digitalization phase, the Digital Transformation phase, and the Digital Reproduction phase (Le Nhan Tam, 2018) Each stage marks a significant progression in how banking services are delivered and experienced by customers.

During the digitalization phase, banks enhance operational efficiency by leveraging technology to optimize data, resources, and individual processes This stage marks a transition from manual and traditional service methods to digital, online, and computerized processes, ultimately streamlining operations and improving service delivery.

Digital transformation in banking marks a pivotal shift where banks digitize their operations to enhance customer experience and meet evolving customer needs This phase involves the integration of digital processes to create a seamless and personalized banking experience for customers.

Digital reproduction in banking involves the integration of cutting-edge digital technologies and platforms to enhance revenue generation and deliver innovative products and experiences This transformation necessitates a fundamental redefinition of how banks engage with customers and stakeholders, fostering a more dynamic and interactive relationship.

The Vietnamese banking sector is undergoing a significant digital transformation, marking its initial transition from traditional to digital banking (Le Anh Vu, 2021) This process involves digitizing banking operations, particularly in customer-facing products and services, known as the front end Ultimately, digital banking represents the goal of this transformation, leading to a more proactive and efficient banking experience (Le Anh Vu, 2021).

In Vietnam's rapidly expanding internet landscape, banks are adapting by offering a range of e-banking services to enhance customer reach Key electronic banking options include ATM services, Mobile Banking, and Internet Banking, which are the most utilized by customers in recent surveys Additionally, banks provide CDMs—similar to ATMs but with deposit capabilities—as well as Digital Video Banking and E-Wallets, often integrated with intermediary payment platforms.

In Vietnam, digital banking services are not fully realized; they primarily involve a shift from traditional banking to mobile apps, allowing transactions to be completed in just one to two minutes For instance, Tien Phong Bank's Live Bank service enables customers to perform various banking activities at designated transaction offices without visiting a traditional counter However, these services still require staff presence and online guidance for customers, indicating that the transition to fully electronic banking is not yet complete.

According to the data presented in Figures 4.1 and 4.2, customers predominantly utilize traditional banking services, with Internet banking and mobile banking being the most frequently used options In comparison, other services such as ATMs, CDMs, digital banking through video, and e-wallets are used less frequently.

Figure 4.1: The banking features of the Internet banking service which customers use

Customers are increasingly engaging in Internet Banking activities, with 14% utilizing it for money transfer services, averaging 79% per user In Vietnam, a significant shift has occurred as most commercial banks now pay employees through accounts rather than cash, leading to 13% of users receiving salaries via Internet Banking, which represents 71% of those surveyed The COVID-19 pandemic has accelerated the transition from cash to online payments, with 9% of Internet Banking services used for consumer shopping, averaging 53% per user Additionally, electronic payment services and online money transfers have enhanced spending management, resulting in service registrations—such as balance alerts and OTP code receipts—comprising 11% of total services, or 65% per user This trend indicates a growing adaptation to Internet Banking, suggesting that digital banking will become the norm.

Frequency of doing Internet service

Transfer Saving money online Receiving salary Bill payment

Registration of services (balance fluctuations, OTP, )

Open/ Close cardTicket bookingConsumer shoppingPhone rechargeBank loan

Figure 4.2: The banking features of the Mobile banking service which customers use

Mobile banking services share similarities with internet banking, particularly in online money transfers and service registrations such as balance fluctuations and OTPs However, mobile banking tends to enhance customer satisfaction by providing a more comprehensive user experience Online money transfers represent the largest segment at 13% of total services, followed closely by registration services, phone recharges, and consumer shopping at 12%, while bill payments account for 11% Ultimately, customers continue to prefer the fundamental and established features of both internet and mobile banking over newer functionalities.

Frequency of using Mobile banking service

Transfer Saving money online Receiving salary Bill payment

Registration of services (balance fluctuations, OTP, )

Open/ Close cardTicket bookingConsumer shoppingPhone rechargeBank loan

Figure 4.3: Accessing the E – commerce platform in Q4/ 2020 of Vietnam

The number of hits on TIKI e – commerce platform was the highest with over

In Q4 2020, online platforms experienced a surge in traffic, with 22 million hits recorded, followed by Sendo with over 11 million hits This increase in visits to e-commerce sites contributed to a significant rise in online payment usage, notably in services like Zalopay and Momo, as well as a marked growth in mobile and internet banking.

Table 4.1: The decisive factor for customers to use digital banking services

Criteria Service Number of users Frequency

Ease of use Internet Banking 107 71%

Limitation the risk Internet Banking 96 64%

In surveys regarding digital banking services, customers prioritize factors such as ease of use, usefulness, limitations, risk, and trust The majority of respondents indicated that ease of use is the most significant factor influencing their choice to utilize digital banking services.

59 use” and “usefulness” for mobile banking and internet banking applications The

The "ease of use" factor is crucial for mobile banking products, accounting for 79% of customer preference, while internet banking holds a 71% share Additionally, the "usefulness" of mobile banking products contributes to 70% of overall customer satisfaction Other factors influencing customer decisions exceed 60% of total responses, highlighting the importance of user experience in banking services.

Surveys indicate that the ease of use significantly enhances the perceived usefulness of digital banking products This perceived usefulness fosters trust in digital banking services, which is crucial for customer confidence in these platforms Furthermore, positive customer attitudes and intentions towards digital banking play a vital role in promoting its acceptance among users in Vietnam.

Recommendation

For the Vietnamese government

I concur with Assoc Dr Dao Minh Phuc's viewpoint that the government must enhance the legal framework and establish mechanisms to foster non-cash payment development It is crucial to effectively execute the National Financial Strategy by 2025, with a vision extending to 2030, as outlined in Decision No 149/QD-TTg, issued on January 22, 2020 Furthermore, I believe the State Bank of Vietnam should play a pivotal role in this initiative.

* Raise the trust of customers and reputation for Vietnamese government

(1) Perfect the legal framework, creating a premise for SBV’s policy directions with commercial banks

+) Continue to implement a legal corridor to promote the development of digital technology enterprises in Vietnam according to Decision No 711 /

QD - NHNN issued by the Government,

+) Continue to effectively implement digital banking development policy in commercial banks on the basis of Decision No 1238 / QD - NHNN issued by the State Bank of Vietnam,

(2) Develop and improve the quality of money laundering prevention system, personal information security and safety,

The Vietnamese government is increasingly concerned about the unregulated transfer of money abroad via online services, fearing that it may facilitate illegal activities and hinder the verification of the source of funds To address these concerns, enhancing the effectiveness of 24/7 anti-money laundering measures is crucial Additionally, there is a growing apprehension among Vietnamese citizens regarding the security of their personal information, particularly when using e-commerce platforms that require linking bank cards for advance payments Therefore, it is imperative to focus on developing robust security measures to protect both government interests and citizen safety.

* Improve the usefulness for services through the framework of guideline

(3) Effectively ensure to get to know your customers by electronics (eKYC) and expanding development to the entire all banking system is applied and deployed

Because I personally agree with SBV when they believe that eKYC is

“gateway” to develop digital banking model Moreover, this will be ensured to get effectively implement the Financial Strategy policy national comprehensive to 2025, vison to 2030.

For the State Bank of Vietnam

The State Bank serves as the central authority for commercial banks and must persist in implementing policies that foster their growth, ensuring they keep pace with the advancements in electronic technology within the banking sector.

* Increase the confidence of customers and reputation for State Bank of Vietnam

(1) Complete the legal framework for digital banking

Digital banking policies encompass various aspects, including the identification of electronic customers through eKYC, the implementation of a payment center system, and the emphasis on information safety and confidentiality Additionally, there is a focus on professional training processes aimed at enhancing development orientation and effectively managing digital banking services.

(2) Improve the quality of management, professional knowledge of digital banking services of the staff of the State Bank

+) Each leader can clearly understand directions, policies and instructions with commercial banks to understand and implement,

Organize training sessions, seminars, and workshops featuring leaders from commercial banks and educators in the banking sector to enhance understanding of digital banking Focus on clearly distinguishing digital banking from electronic banking to prevent misinformation and ensure accurate knowledge dissemination.

(3) Promote communication to press agencies, universities, so that all people can understand what digital banking is, encourage people to use and adapt to

62 themselves new book, keeping up with the government's proposal of applying Digital Banking

* Make better services quality and limit risks when using service for users

(4) Support to improve the quality of electronic services of commercial banks

+) Coordinate the work of inviting leading overseas experts to train and advise banking managers relating to the development of strategies and projects for digital banking products and services,

Digital banking products and services should adhere to a standard framework that prioritizes an easy-to-use interface for customers By incorporating a variety of useful features, such as mobile recharge and cash withdrawal options, these services can significantly enhance the overall customer experience Additionally, it's essential to minimize the risks that customers may encounter while using digital banking, ensuring a secure and user-friendly environment.

+) Coordinate with the State’s Information Technology department with Commercial Banks to provide for customers with the best quality services, quickly and promptly process all transactions

(5) Actively supervise the system of digital banking services, non-cash payments at commercial banks to provide solutions if there is a risk.

For the commercial banks

Commercial banks serve as the primary point of contact for individuals, necessitating that their leaders thoroughly understand government directives and policies set by the State Bank This understanding enables them to effectively guide staff in executing these policies and assisting customers with their banking needs.

* Develop the banking system and reputation of bank

Every bank should create a dedicated digital banking center focused on researching and delivering digital banking products and services that align with its strategic goals and policies, while also staying attuned to global trends.

(2) Organize professional training sessions related to digital banking so that the employees in the bank can understand and implement properly,

(3) Assign foreign consultant experts to assist with employees at Vietnamese banks to come up with suitable digital banking solutions for the bank,

(4) Strengthen the bank's brand and reputation, helping to increase customers' trust in trusting, accompanying and experiencing using the bank's services,

* Improve the quality of digital banking products about ease of use, usefulness and limit risks to increase customers’ belief

(5) Actively increase customer experience when using digital banking, add appropriate features, associate with financial companies, e-wallets to bank digital banking products and services found more features,

Conducting research and surveying customers can help identify any difficulties they encounter while using the service, as well as areas of dissatisfaction related to product completion This feedback is essential for enhancing the overall usefulness of the products offered to customers.

(7) Treat all customer risks, and fastest recovery of risks so as not to affect customer experience

Chapter four highlights the current state of Vietnam's banking sector and offers solutions for the government, the State Bank of Vietnam (SBV), and commercial banks based on research findings Vietnam is currently in the initial phase of digital transformation, progressing towards a fully developed digital banking system As banking products and services increasingly incorporate digital technology, customers are gradually adopting digital banking solutions Data from e-commerce platforms and customer usage statistics indicate a shift from traditional banking to digital services This trend is driven by positive customer attitudes, emphasizing ease of use, perceived usefulness, and risk mitigation, which enhance customer trust and bolster the reputation of banks.

64 improve customer acceptance when using digital services and develop Vietnam’s economy more

Digital banking in Vietnam is still a relatively new concept for customers, but research indicates a growing acceptance and confidence in these services over traditional banking Trust plays a crucial role in shaping customer attitudes and intentions toward using digital banking Additionally, the perceived usefulness of digital banking products significantly influences customer beliefs about their chosen bank However, concerns about the risks associated with digital banking persist, highlighting the need for banks to enhance product features and ensure customer safety To develop effective digital banking solutions that meet customer needs, banks must gain a deep understanding of their customers' mindsets and preferences, ultimately improving their reputation and service quality.

To encourage customers to fully embrace digital banking services, it is essential for banks to integrate technology by collaborating with fintech companies and consulting with digital banking experts This approach aligns with Vietnam’s economic growth Based on research findings, banks should enhance their reputation, brand, and service quality to build customer trust Additionally, improving user-friendliness and functionality is crucial for increasing user adoption and service quality Furthermore, banks must prioritize personal information security and system reliability to prevent customer inconveniences while using their services.

1 Circular no 29/ 2011/ TT – NHNN of State Bank of Vietnam published on January 29 th 2011 about defining safety, confidentiality over provision for banking service on the internet;

2 Decision no 1238/ QĐ - NHNN by State Bank of Vietnam about developing digital banking not only in enterprises but also in the banking industry;

3 Decision no 711/ QĐ – NHNN about promoting the development of digital technology enterprises in Vietnam was issued by the State Bank of Vietnam with objective to create a favorable law environment to develop technology enterprises;

4 Decision No 1238 / QD - NHNN issued by the State Bank of Vietnam about digital banking development policy in commercial banks on the basis;

5 Decision No 149 / QD-TTg published on January 22, 2020;

6 Decision No 241 / QD-TTg on approving the Scheme on promoting via-bank payment for public services;

7 Decision No 2545 / QD-TTg issued by Prime Minister on approving the Development Project of Non-Cash Payment in the 2016-2020 period;

8 Decision No 711 / QD - NHNN issued by the Government about promoting the development of digital technology enterprises in Vietnam;

9 Decree no 101/2012/NĐ-CP published on 2012 about State Bank of Vietnam (SBV)’s managed responsibilities for non – cash payment activity, information report, information safety and security, supervision operating systems applied for mobile banking;

10 Prime Minister's Directive No 16 / CT-TTg dated March 31, 2020

11 “Transform customer experience in retail banking”, 2019, Gartner Inc

12 Amola Bhatt, Shahir Bhatt, “Factors affecting customers adoption of Mobile

Banking Services”, published by Journal of internet banking and commerce, read on April 17 th 2021, https://www.icommercecentral.com/open-

67 access/factors-affecting-customers-adoption-of-mobile-banking- services.php?aidp189

13 Dao Minh Phuc, Nguyen Trong Chung, 2020, “Phat trien Ngan hang so nham thuc day thanh toan khong dung tien mat o Vietnam”, National workshop proceedings in 2020, read on May 1 st 2021

14 Bryman, A., 2012, “Social Research Methods”, 4th ed Oxford: Oxford University Press, read on April 25 th 2021

15 Carmen Cuesta, Macarena Ruesta, David Tuesta and Pablo Urbiola, 2015,

“The digital transformation of the banking industry” , published on July 16 th

2015, Digital Economy Watch and BBVA research, read at April 13 rd 2021

16 Chang, P V., 2004, “The validity of an extended technology acceptance model

(TAM) for predicting intranet/portal usage”, Master thesis University of

North Carolina, Chapel Hill, NC

17 D Harrison McKnight, Vivek Choudhury, Charles Kacmar, 2002, “The impact of initial consumer trust on intentions to transact with a web site: a trust building model”, published by The Journal of Strategic Information

Systems Volume 11, Issues 3–4, pages 297-323, read on Apirl 20 th 2021

18 Daniel Kofi Madu, 2014, “Customers’ adoption and use of e-banking services: The South African perspective”, published on Banks and Bank systems, volume 9, Issue 2 read on Apirl 20 th 2021

19 Fishbein, M& Ajzen, I (1975), “Belief attitude, intention and behavior: An introduction to the theory and research”, Addition – Wesley, page 11 – 18, read on Apirl 23 rd 2021

20 Fred D Davis, 1989, “Perceived Usefulness, Perceived Ease of use and user acceptance of information technology”, MIS Quarterly, Vol 13, No.3, page

319-340, published by https://www.jstor.org/stable/249008?seq=1 read on April 17th 2021

21 Fred D Davis, Richard P Bagozzi and Paul R Warshaw, 1989, “User

Acceptance of Computer Technology: A comparision of Two Theoretical Model Authors”, Management Science, Vol 35, No 8, page 982 – 1003, read on Apirl 22 nd 2021

22 Hans Baumgartner & Christian Homburg, 1996, “Applications of structural equation modeling in marketing and consumer research: A review”,

International Journal of Research in Marketing, Volume 13, Issued 2, pages

23 Hanudin Amin, “Internet banking adoption young intellectuals”, published by Journal of Internet banking and commerce, reat on April 17 th 2021 https://www.icommercecentral.com/open-access/internet-banking-adoption- among-young-intellectuals.php?aid8527

24 Hoang Trong, Chu Nguyen Mong Ngoc, 2008, “Phan tich du lieu nghien cuu voi SPSS”, episode 2 nd , Hong Duc publication, page 24, read on Apirl 28 th

25 Jennifer Austermann, Birte Mertins, 2014, “Technology Acceptance Model Revised - An Investigation on the Managerial Attitudes towards Using Social Media in Innovation Processes”, Master Thesis, Linnaeus University

Sweeden, read on Apirl 24 th 2021

26 Jian Mou, Dong – Hee Shin, Jason Cohen, 2015, “Understanding trust and perceived usefulness in the consumer acceptance of an e-service: a longitudinal investigation”, Behaviour & Information Technology, Pages

125-139, published on July 22 nd 2016, Taylor Francis Online, read on May

27 Joseph F Hair Jr., William C Black, Barr y J Babin, Rolph E Anderson,

2010, “Multivariate Data Analysis: A global perspective”,7 th Edition, Pearson Education, read on Apirl 28 th 2021

28 Le Anh Dung, 2021, “Chuyen doi so tai cac Ngan hang Viet Nam”, Digital banking seminar articles, State Bank of Vietnam, read on May 1 st 2021

29 Le Nhan Tam, 2018, “Tai tao so, goc nhin cua IBM”, The report presents the Workshop of Digitalization of the Bank - a breakthrough opportunity, State Bank of Vietnam, November 2018, read on May 1 st 20201

30 Nena Lim, 2003, “Consumers’ perceived risk: sources versus consequences”, published by Electronic Commerce Research and application, volume 2, issue

3, page 216 – 228, read on Apirl 20 th 2021

31 Nguyen Dinh Tho, 2011, “Phuong phap nghien cuu khoa hoc trong kinh doanh”, Financial public house, 2 nd edition, page 364, read on Apirl 28 th 2021

32 Nguyen Duy Thanh, Cao Hao Thi, 2011, “De xuat mo hinh chap nhạn va su dung ngan hang dien tu o Vietnam”, published on Science and technology

Development Journal, volume 4, issue 2), read on Apirl 22 nd 2021

33 Nui Polatoglu, V and Ekin S, 2001, “An empirical investigation of the Turkish consumers’ acceptance of internet banking services”, International Journal of

Bank Marketing 19: 156-165, read on Apirl 15 th 2021

34 Nuno Fortes and Paulo Rita, 2016, “Privacy concerns and online purchasing behaviour: Towards an integrated model”, European research on management and business economics, volume 22, issue 3, pages 167 – 176, read on Apirl

35 Oanh Thi Nguyen, 2020, “Factors affecting the intention to use digital banking in Vietnam”, Journal of Asian Finance, Economics and Business Vol

36 Pham Tien Dung, 2020, “Phat trien thanh toan khong dung tien mat: Ket qua dat duoc, kho khan va thach thuc trong thoi gian toi”, National workshop proceedings in 2020, read on May 1 st 2021

37 S Anada, Sonal Devesh, Anis Moosa AI Lawati, 2020, “What factors drive the adoption of digital banking? An empirical study from the perspective of Omani retail banking”, published on Journal of Financial Services Marketing, read on Apirl 20 th 2021 < https://www.researchgate.net/publication/341709456_What_factors_drive_th

70 e_adoption_of_digital_banking_An_empirical_study_from_the_perspective_ of_Omani_retail_banking>

38 Saunders, M., Lewis, P and Thornhill, A., 2009, “Research methods for business students” Harlow, UK: Pearson Education Limited, read on April

39 SCN Education B.V, 2001, “Electronic Banking: The Ultimate Guide to Business and Technology of Online Banking”, Springer Science & Business

Media read on May 8 th 2021

40 Thanh Phuong Nguyen and Thi Lan Phuong Dang, 2018, “Digital Banking in

Vietnam Current Situation and Recommendations”, International Journal of

Innovation and Research in Educational Sciences Volume 5, Issue 4, ISSN (Online), page 418 – 420

41 Vietnam E – commerce Association (VECOM), 2021, “Report of Vietnam E- business index 2021, Sustainable growth”, Vietnam E- commerce Association

(VECOM), published on April 20 th 202, read on May 8 th 2021

42 Waleed Mugaheed Al-Rahimi, Mohd Shahizan Othman and Mahdi Alhaji Musa, 2013, “Using TAM model to measure the use of social media for collaborative learning”, International Journal of Engineering Trends and

Technology (IJETT) – Volume 5 number 2 – Nov 2013, read on Apirl 15 th

43 Yi-Hsuan Lai, Hsiu-Chin Huang, Ruey-Shan Lu, and Chia-Ming Chang, 2013,

“The Effects of Website Trust, Perceived Ease of Use, and Perceived

Usefulness on Consumers’ Online Booking Intention: Evidence from Taiwan B&B Sector”, Life Science Journal 2013; 10(2), published in 2013, read on

44 “Vietnam E – commerce map”, 2021, Iprice Insight, public by Iprice insight read on May 1 st 2021 https://iprice.vn/insights/mapofecommerce/

45 “A brief history of IT in the banking industry”, BNP Paribas, at April 8 th , 2021

< https://history.bnpparibas/dossier/a-brief-history-of-it-in-the-banking- industry/>

46 “A history of ATM innovation”, published on January 12, 2021, NCR

Company, read on Apirl 8 th , 2021 < https://www.ncr.com/blogs/banking/history-atm-innovation

47 Pham Tien Dat, Luu Anh Nguyet, 2019, “Ngan hang so – Trien Vong va phat trien trong tuong lai”, Banking Review, read on April 15 th 2021 http://tapchinganhang.gov.vn/ngan-hang-so-trien-vong-va-phat-trien-trong- tuong-lai.htm

48 Darryl Proctor, 2019, “What is Digital Banking?”, Temenos, read at April 14 th

2021, https://www.temenos.com/news/2019/12/19/what-is-digital-banking/

49 Dinh Van Chuc, 2020, “Ung dung cong nghe thong tin trong phat trien san pham dich vu ngan hang o Viet Nam”, Finance Review, read on May 1 st 2021, https://tapchitaichinh.vn/ngan-hang/ung-dung-cong-nghe-thong-tin-trong- phat-trien-san-pham-dich-vu-ngan-hang-o-viet-nam-330451.html

50 “GDP growth (annual %) – Vietnam”, 2019, World Bank, read at April 13rd

51 Jum Nunnally and Ira Bernstein, 1994, “Psychometric Theory”, 3 rd edition, New York: McGraw – Hill, xxiv + 752 pp, read on Apirl 28 th 2021 < https://journals.sagepub.com/doi/abs/10.1177/014662169501900308?journal Code=apma>

Reliability Statistics

Perceived ease of use

With this variance, perceived ease of use effect on perceived usefulness The hypothesis is proposed as follow:

H1: Perceived ease of use has positive impact on the perceived usefulness when using digital banking service

Understanding the effectiveness and utility of a product or service for users is heavily influenced by their perception of risk This leads to the hypothesis that perceived risk plays a crucial role in determining user satisfaction and product efficacy.

H2: Perceived risk has a negative impact on perceived usefulness

Because perceived usefulness and trust are both impact on accept use internet service for long time (Jian Mou et al, 2015) With this variance, the hypothesis is proposed as follow:

H3: Perceived usefulness has a positive impact on trust when using digital banking service

With this variance, the hypothesis is proposed as follow:

H4: Trust has a positive impact on the attitude towards use and intention to use

(5) Attitude towards use and intention to use

H5: Attitude towards use and intention to use have a positive impact on the acceptance of use

The table below outlines the anticipated effects of the hypotheses presented in this article This forecast is crucial as it allows the study to verify the accuracy of the predictions after testing the results.

Table 2.2: Forecast effect of research hypotheses

H3 (PU) Perceived usefulness has a positive impact on trust (+) Accepted

Figure 2.8: Research model and hypotheses

33 when using digital banking service H4 (T) Trust has a positive impact on the attitude towards use and intention to use

Attitude towards use and intention to use have a positive impact on the acceptance of use

In the second chapter, the author outlines the research methods and data collection sources derived from prior studies The chapter includes a detailed questionnaire format and describes the data sample, which consists of 150 collected responses Based on this data, the author proposes five research hypotheses that correspond to the influence of the five factors identified in the model.

This research addresses the challenges of obtaining valid primary data, particularly issues like repetitive answers and incomplete responses, by employing Q-Q plots to identify and eliminate outlier variables from a dataset of 150 responses Additionally, the study highlights a deficiency in explanatory variables within the questionnaire, leading to the merging of observed variables during model execution.

To effectively test a scientific theory, it is essential to ensure the reliability of the scale and evaluate its significance This involves employing Cronbach Alpha analysis to assess a comprehensive set of variables that encompass various factors representing the primary variable In this study, the final group of variables focuses on the combined aspects of Attitude towards Use and Intention to Use.

This research has 5 independent variances, so that we renamed these variances: +) Perceived Ease of use – PE

+) Attitude towards use and Intention to use – ATTINT

Table 3.1: Overview of Cronbach Alpha

Alpha Number of items Item remove

Nunnally (1994) established that measurement variables should have a corrected item-total correlation of at least 0.3 and a Cronbach’s Alpha if the item is deleted that is less than or equal to the overall Cronbach’s Alpha to ensure reliability Hoang Trong and colleagues further noted that a reliability score ranging from 0.8 to 1 indicates significantly good reliability, while a score of 0.6 and above is considered acceptable.

The analysis of the five tested variables indicates that they all meet the established criteria, with Cronbach's Alpha reliability scores exceeding 0.8 Among these, the PR variable demonstrates the highest reliability at 0.897, while the T variable, at 0.816, remains above the acceptable threshold Furthermore, each observed variable shows a Corrected Item-Total Correlation of at least 0.3, and the Cronbach’s Alpha if the item is deleted does not exceed the overall Cronbach’s Alpha, confirming that no observed variables are excluded from the five groups Consequently, all variables are deemed acceptable and will proceed to the next phase of model analysis.

3.1.2 Results of exploratory factor analysis (EFA)

Table 3.2: KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy

The KMO and Bartlett’s Test table serves as a preliminary assessment to determine the suitability of conducting Exploratory Factor Analysis (EFA) The Kaiser-Meyer-Olkin (KMO) index indicates the appropriateness of factor analysis, with values ranging from 0.5 to 1 deemed acceptable; in this case, a KMO value of 0.820 confirms the model's suitability for EFA Additionally, the significance of Bartlett’s Test of Sphericity is crucial; a significance level below 0.05 suggests that the observed variables are correlated, and with a significance index of 0.00, the conditions are ideal for performing EFA.

In Exploratory Factor Analysis (EFA), the eigenvalue index is crucial for determining the number of factors to retain, with factors having an eigenvalue of 1 or higher being included in the analysis model The accompanying table illustrates the total variance explained, categorizing factors into groups that correspond to the number of variances A suitable model is characterized by a total variance explained of 50% or more, indicating the proportion of variation accounted for by the factors and highlighting the percentage of observed variables that are not captured.

Rotation Sums of Squared Loadings a Total

With 18 factors, it is possible to load only 5 group factors with Eigenvalues greater than 1 and which is condensed into 5 groups with a total extracted variance of 65.570% ≥ 50% (suitable condition) These 5 groups are equivalent to the 5 variables being watched

In exploratory factor analysis (EFA), a model is deemed suitable when the total variance explained exceeds 50% The pattern matrix, generated using the promax rotation method, displays coefficients sorted by size, with small coefficients below an absolute value of 0.5 suppressed This matrix reveals five group factors, each with factor loadings greater than 0.5 If any factor loadings fall below 0.5, those variances are excluded, and the matrix is rerun for improved accuracy.

Extraction Method: Principal Axis Factoring

Rotation Method: Promax with Kaiser Normalization a Rotation converged in 7 iterations

The pattern matrix reveals distinct groups of factors formed by converging variables without any clutter, ensuring that each observed variable aligns with its corresponding group The factor loadings are notably high, exceeding 0.5, with the PR group demonstrating the strongest loadings, ranging from 0.738 to 0.937 Following this, the PU, PE, T, and ATTINT groups show decreasing factor loadings Although ATT1 has the lowest loading at 0.594 among the five groups, it remains above the 0.5 threshold, indicating it should not be excluded In conclusion, the pattern matrix identifies five factor groups corresponding to the variables PU, PR, PE, T, and ATTINT.

3.1.3 Result of Confirmatory factor analysis (CFA)

According to the Hair and partners (2010), the result of CFA can be acceptable which

+) CMIN/df ≤ 2: positive, CMIN/df ≤ 5: acceptable

+) CFI ≥ 0.9: positive, CFI ≥ 0.95: perfectly positive, CFI ≥ 0.8: acceptable +) GFI ≥ 0.9: positive, GFI ≥ 0.95: perfectly positive

The study's limited sample size makes achieving a GFI index threshold of 0.9 challenging; however, Baumgartner and Homburg (1995) suggest that a GFI index of at least 0.8 is considered acceptable.

The result of CFA showed that: CMIN/df = 1.920 < 5: acceptable, CFI = 0.925

In confirmatory factor analysis, ensuring convergent validity, discriminant validity, and reliability is crucial If these validity and reliability factors are not established, it can lead to biased results, rendering the obtained numbers unrepresentative of the actual data and its significance.

According to Hair and partners (2010), the measure of Reliability test and Validity test is defined that:

+) Standardized Loading Estimates ≥ 0.5: positive, perfectly positive is ≥ 0.7 +) Composite Reliability (CR) ≥ 0.7: positive

+) Average Variance Extracted (AVE) ≥ 0.5: positive

+) Maximum Shared Variance (MSV) < Average Variance Extracted (AVE) +) Square Root of AVE (SQRTAVE) > Inter – Construct Correlations

In Confirmatory Factor Analysis (CFA), Standardized Loading Estimates serve as a crucial indicator The Standardized Regression Weights table includes these estimates, with values above 0.5 being retained for analysis Conversely, observations with Standardized Loading Estimates below 0.5 should be excluded, necessitating a rerun of the CFA to ensure accurate results.

Perceived risk

E-banking services offer users convenience and comfort, but they also raise concerns about risk perception, which Fortes identifies as a significant barrier to the growth of the e-consumer market This perception poses a challenge for e-banking to compete with traditional services As e-commerce continues to thrive, allowing users to shop online at any hour, the advancement of technology also increases opportunities for fraudsters to compromise personal information, making security a critical issue Lim (2003) provides a fresh perspective on perceived risk by separating it from traditional methods that focus solely on the consequences of risk.

The perception of risk in digital banking can be categorized into four levels: perceived technological risk, vendor risk, consumer risk, and product risk I align with two of these categories: perceived technological risk, which encompasses potential losses due to security vulnerabilities in internet and technology infrastructure, and consumer risk, which pertains to the unauthorized use of personal information Understanding these perceived risks is essential for customers to safeguard themselves while using digital banking services.

Trust

Customers' confidence in online products and services is crucial for their usage, yet challenges persist, such as the inability to physically interact with items Research by McKnight et al indicates that a lack of trust can cause consumers to hesitate in engaging in online behaviors like sharing personal information or making purchases Consequently, customers are more likely to utilize online services when they feel assured about the applications they use In the banking sector, trust in digital banking services is often linked to the credibility of the bank's brand and the efficiency of its service processing.

Attitude towards use and intention to use

Consumer attitudes significantly influence their decisions to adopt new services, particularly in the context of digital banking Adoption refers to the acceptance and initiation of using innovative products According to Ana Sousa, a consumer's perception of a product must align with their self-image to affect purchasing behavior For banking services like digital banking, customers often develop a favorable attitude due to the convenience it offers, allowing transactions anytime and anywhere without the need to visit a physical bank Additionally, online services frequently provide more attractive interest rates compared to traditional savings methods A study by Nguyen Thi Oanh investigates the intent to use digital banking in Vietnam, employing data analysis techniques such as Cronbach's alpha, Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM), based on 201 responses.

The findings from the questionnaire indicate that service attitudes and perceived usefulness significantly influence customers' intentions to adopt digital banking According to Fishbein and Ajzen (1975), intention is a critical component of action theory, serving as a predictor for user behavior Supporting this view, Jenifer et al (2014) emphasize the role of intention in guiding future actions The author posits that intention acts as a preparatory step before an individual engages in specific behaviors, ultimately affecting their actions I concur with these perspectives, recognizing that intention plays a decisive role in user behavior and is a key factor in determining whether users choose to embrace digital banking services.

In conclusion, the five key factors—perceived ease of use, perceived usefulness, perceived risk, perceived trust, and attitude towards use—are essential for effectively researching this topic.

1.3 Gap, research objectives and research questions

1.3.1 Gap of the previous researches

In the world, it had the study about reinforces confidence in the adoption and use of existing e-banking services for customers The research of Daniel Kofi Madu

A 2014 study highlighted that customer confidence is a crucial factor in the adoption of electronic banking services in South Africa, but it did not extend its focus to digital banking Additionally, the research conducted by Daniel was limited to South Africa and did not consider insights from other countries, such as Vietnam In contrast, another study explored the factors influencing the adoption of digital banking specifically within Omani retail banks.

In Vietnam, research primarily focuses on the acceptance and intention to use e-banking services, with findings indicating that the existing models, such as those presented by Nguyen Duy Thanh and colleagues in 2011, do not significantly outperform others Consequently, the effectiveness of measuring customer acceptance of e-banking services remains limited Additionally, there is a lack of comprehensive studies that generalize the application and usage of digital banking services, as highlighted in the work of author Nguyen Thi Oanh.

Nguyen Thi Oanh's research highlights the importance of raising customer awareness regarding the benefits of digital banking in Vietnam through effective advertising and counseling While the study focuses on customer perceptions of digital banking's usefulness and its impact on usage intentions, it emphasizes the need for a proactive approach to enhance acceptance and integration of digital banking into everyday life, rather than merely acknowledging its existence.

Research on digital banking services is more prevalent internationally than in Vietnam, where studies primarily focus on the acceptance of mobile banking rather than the broader use of digital banking services Most existing research highlights two key factors: ease of use and usefulness However, there is a noticeable lack of studies addressing user trust and risk perception in the context of digital banking.

Researcher Oanh Nguyen Thi highlighted the intention to use digital banking rather than its actual acceptance Most studies utilize the Technology Acceptance Model (TAM), which I have also chosen for my research Given the existing gaps in previous studies and the lack of comprehensive papers, my topic, “Factors Affecting the Adoption of Digital Banking in Vietnam,” aims to address these deficiencies and uncover new insights that can positively influence the adoption of digital banking in the country.

This article aims to assist banks in understanding their customers' needs and identifying appropriate digital banking solutions tailored to each bank's clientele In the context of the ongoing 4.0 technology revolution, it is crucial to assess how customers perceive digital banking services By doing so, banks can enhance their product and service quality to better meet customer demands Additionally, many customers struggle to differentiate between a bank's digital banking offerings and those of affiliated digital banking products, which significantly affects their overall perception.

The research paper provides valuable insights into customer consumption behavior in digital banking, helping to clarify common misconceptions and enhance overall understanding of this financial sector.

This research paper addresses the critical questions of whether customers in Vietnam will accept digital banking services and what enhancements are necessary to instill greater confidence compared to traditional banking By exploring these key issues, bank leaders can gain valuable insights into customer needs and emerging trends, enabling them to develop effective solutions that align with the evolving digital banking landscape while catering to customer demands.

In the first chapter, the author sets the stage for Vietnam's context in the fourth technological era using a PEST analysis and reviews existing literature on digital banking from both Vietnamese and international studies The author identifies key factors influencing the adoption of digital banking, including perceived ease of use, perceived usefulness, perceived risk, trust, attitude towards use, and intention to use By aligning with previous research, the author presents a model framework to illustrate these adoption factors Additionally, the study highlights research gaps, objectives, and questions aimed at helping banks understand the needs and acceptance of digital banking services among citizens in Hanoi Ultimately, the research aims to inform banks in developing customer-centric digital banking products, justifying the selection of the topic "Factors Affecting the Adoption of Digital Banking in Vietnam."

This study employs quantitative research, distinguishing it from qualitative research, which impacts the nature of the data collected While qualitative research emphasizes in-depth information (Bryman, 2012), it facilitates the exploration, description, and explanation of relationships between existing or new data (Saunders et al., 2012) Analyzing qualitative data allows researchers to present diverse viewpoints, enriching the overall understanding of the research topic (Bryman, 2012).

Using qualitative data offers significant advantages in measurement, as it allows researchers to generate reliable information more easily (Bryman, 2012) Therefore, when applying the Technology Acceptance Model (TAM) to identify the factors influencing the adoption of digital banking, qualitative data proves to be an appropriate choice for this research.

Primary and secondary data are the two main sources of information for research Secondary data, collected by other researchers for similar topics, can save time and costs in the research process (Bryman, 2012) However, it is important to note that secondary data may be outdated and not regularly updated, which can affect its accuracy and relevance to current research needs.

CFA analysis

Model NPAR CMIN DF P CMIN/DF

Model RMR GFI AGFI PGFI

TLI rho2 CFI Default model 857 825 926 908 925

Structural Equation Modeling analysis

Model NPAR CMIN DF P CMIN/DF

Model RMR GFI AGFI PGFI

TLI rho2 CFI Default model 854 828 926 911 925

Pearson Correlations

ADT PR PU PE T ATTINT

** Correlation is significant at the 0.01 level (2-tailed)

The banking features of the service the customers use

Using for Service Number of users Frequency

Saving money online Internet banking 78 52%

Registration of changing in balance account

Open/ Close card Internet banking 74 49%

XÁC NHẬN CỦA ĐƠN VỊ THỰC TẬP

NHẬN XÉT CỦA GIẢNG VIÊN HƯỚNG DẪN

Đánh giá năng lực chuyên môn và nghiên cứu của sinh viên trong quá trình thực hiện khóa luận tốt nghiệp (KLTN) là rất quan trọng Việc này không chỉ phản ánh nỗ lực và hiệu quả công việc của sinh viên mà còn thể hiện sự thường xuyên liên lạc và hợp tác giữa sinh viên với giảng viên hướng dẫn (GVHD) Sự tương tác này góp phần nâng cao chất lượng nghiên cứu và phát triển kỹ năng chuyên môn cho sinh viên.

(Ký & ghi rõ họ tên)

Tiêu đề	Factors Affecting The Adoption To Use Digital Banking Of Vietnam
Tác giả	Bui Phuong Anh
Người hướng dẫn	Assoc. Prof. Dr. Dao Minh Phuc
Trường học	Banking Academy
Chuyên ngành	Banking
Thể loại	Graduation Thesis
Năm xuất bản	2021
Thành phố	Hanoi

Định dạng
Số trang	91
Dung lượng	1,04 MB