FACTORS AFFECTING ADOPTION MOBILE BANKING OF INDIVIDUAL CUSTOMER AT SAI GON THUONG TIN COMMERCIAL JOINT STOCK BANK QUANG TRI BRANCHFACTORS AFFECTING ADOPTION MOBILE BANKING OF INDIVIDUAL CUSTOMER AT SAI GON THUONG TIN COMMERCIAL JOINT STOCK BANK QUANG TRI BRANCH
INTRODUCTION
REASONS FOR CHOOSING A RESEARCH TOPIC
In the first month of 2021, after more than a year the COVID epidemic appeared with a new variant domestically and internationally, which has affected domestic economic activities and resulted in a decline reduction of many economic professions Although now the world has invented and provided vaccines to prevent people, the dangers of virus strains can not be foreseen And up to now, people are forming a habit of avoiding contact, not gathering in public places, using technology and smart devices in their lives
The development of technology has made customers be increasingly interested in electronic banking Therefore, the competition between banks when providing e- banking services is more and more fierce Besides, the 4.0 technology revolution is having a strong impact on people's lives today The birth of a series smartphones with many models, diverse prices and many outstanding features suitable for all classes of people have created opportunities for Mobile banking to be established
To retain and increase the number of customers as well as increase revenue from services and help reduce dependence on traditional credit, on April 9th 2018 Sacombank officially launched a new version of the electronic banking system with many outstanding features on the platform of high-security technology The Sacombank’s Mobile banking is designed in a streamlined form on the homepage to display group transactions and icons for customers to choose from Smaller transaction steps and smoother display are suitable for mobile users In addition, new enhancements such as the ability to select, adding favorite transactions and installing featured images provide customers with interesting experiences about the personalization of banking services However, after 3 years of operating in the market, the number of individual customers registering to use Sacombank Mobile banking is currently quite low compared to the set expectation
Stemming from the above reality, with the desire to provide scientific foundations, the author studied “Factors affecting adoption Mobile banking of individual customer at Sai Gon Thuong Tin commercial joint stock bank - Quang Tri
Branch”, on that basis, good and bad sides will be recognized to give directions to attract attention and strongly develop Mobile banking for individual customers at Sacombank in particular as well as the Vietnamese banking system in general.
RESEARCH OBJECTIVES
Common objective: Evaluate the influence of factors on the decision to use
Mobile banking of individual customers at the bank, thereby proposing solutions to improve the quality of Mobile banking services at the bank in the near future
Clarifying groups of individual customers using Mobile banking: age, gender, occupation, income
Observing and collecting service usage habits of individual customers
❖ Purpose of using Mobile banking
❖ Frequency of using Mobile banking
Statisticizing, evaluating the influence of these factors on the decision to use of individual customers
Finally, recognizing the missing factors, which one needs to develop, properly assessing customers' needs, proposing solutions to help customers experience and use Mobile banking more easily and conveniently.
QUESTIONS RESEARCH
What are the determinants affecting the adoption of Mobile banking services? How do customers feel about the usefulness and ease of use of the application?
Is the security of information guaranteed by the bank for customers?
Which factors strongly influence the decision to use Mobile Banking?
Which factors have little impact on the decision to use Mobile banking?
SUBJECT AND SCOPE OF RESEARCH
Study subjects are factors affecting individual customers’ intention to use Mobile banking
- Scope of space: Survey of individual customers who have been and are
Joint Stock Bank - Quang Tri Branch, address 43 Tran Hung Dao, Ward 1, Dong Ha, Quang Tri
- Scope of time: The study was conducted in the period from date February 17 to May 5 2021
RESEARCH METHODS
First, review the theory and inherit the results from previous research models to use the influence factor evaluation scale, then use the discussion and research process to correct, adding observed variables to build evaluation and adjustment criteria for the quantitative research process
The author investigates by questionnaires through interviews to collect information from customers who have been and will use Sacombank Mobile banking applying judgemental sampling method with an expected sample size of 200 samples Questionnaires were sent directly to customers The obtained survey results will be verified reliability, validated for cronbach's alpha coefficients, average variance extracted, analyzing the discovery factor, measurement model, structural model through SmartPLS 3 software.
SIGNIFICANCE OF THE STUDY
In addition to the introduction, list of tables, acronyms and references, the study is divided into 5 chapters as follows:
Chapter 4: Data analysis and results
LITERATURE VIEW
OVERVIEW OF MOBILE BANKING
The commercial bank is a credit institution that is allowed to conduct all banking operations and other related business activities for profit purposes under the Law on Credit Institutions and other regulations (Decree No.59/2009/ND-CP of the Government on organization and operation of commercial banks)
According to the Law on State Bank: Banking operation is a monetary business and banking service with the regular content of receiving deposits and using this money to extend credit, provide services pay Thus, commercial banks are an important level of financial intermediaries to become the first class in the market economy Thanks to this institutional system, idle capital will be mobilized, creating large sources of credit for economic development loans From that can be said the nature of commercial banks can be displayed through the following points:
❖ A commercial bank is an economic organization
❖ Commercial banks do business in monetary credit and service banking
Exchanging foreign currency: This is the first banking service to be performed
In which the bank buys and sells one currency for another, the bank will collect a fee for this exchange
Commercial paper discount and commercial lending: Bank discount commercial paper, which is actually lending to businesses, by reselling debts to collect cash
Receiving deposits: Lending is a highly profitable activity, so banks find ways to mobilize loan money One of the important sources of capital is customer savings, bank offer low interest rates to attract this capital
Valuable object preservation: Banks usually have a storage room to store gold or valuables that customers deposit Bank-issued certificates to the customer can be
Financing of government operations: Banks are established on the condition that they buy government bonds at a certain percentage of the total deposits that the bank can raise
Supply of transaction accounts: The bank provides transaction accounts, allowing depositors to write checks to pay for the purchase of goods and services
Providing trust services: banks perform asset management and financial operations management for individuals and commercial enterprises Accordingly, banks will collect fees based on the value of the assets or the size of the management
Consumer loans: In the past, banks were not active with consumer lending services because they thought that this activity contained many risks, small scale and high costs However, today the bank has focused on the potential individual customer market Consumer loans are developing day by day and bringing significant profits to the bank
Financial consulting: today banks provide a wide range of financial advisory services, from tax preparation and financial planning for science and technology, to research on investment opportunities, on domestic market and for business customers
Electronic banking (E-banking) includes the systems that enable financial institution customers, individuals or businesses, to access accounts, transact business, or obtain information on financial products and services through a public or private network, including the internet (Sadaf Firdous and Rahela Farooqi, 2017)
E-banking is defined as the automatic provision of modern and traditional banking products and services directly to customers through electronic communication channels The definition of e-banking differs between studies partly because e-banking refers to a number of services through which the bank's customers can request information and perform most of the services through computers and smart phones (Daniel, 1999; Mols, 1998; Sathye, 1999)
In countries around the world, e-banking is a service that is provided to the market quite early In 1980, this service was provided by a bank in Scotland (Tait,
Fand Davis, 1989) However, this service was officially provided to the market by banks in 1990 (Daniel, 1998) and it’s increasingly expanding and developing
According to Burr (1996), electronic banking as an electronic connection between banks and customers to manage and control their financial transactions
Electronic banking includes systems that allow customers to be financial institutions, individuals or businesses, to access accounts, to transact business or to obtain information about financial products and services over the network public or private, including Internet or cell phones Customers access e-banking services using smart electronic devices, such as personal computers (PC), personal digital assistants (PDA), automatic teller machines (ATM), Kiosk
According to the Report of the Basel Committee on Banking Supervision
(1998), e-banking refers to the provision of small value and retail banking products and services through electronic channels Such products and services may include receiving deposits, lending, managing accounts, providing financial advice, paying e-invoices, and providing other electronic payment products and services like cryptocurrency
Internet Banking: A banking facility provided to the customers through which the customers are able to perform a number of monetary and non-monetary transactions, using the internet, through the bank’s website or application
Mobile Banking: An electronic banking service supported on smart mobile phone platforms, currently mainly supports on 2 operating systems iOs and Android
SMS Banking: Electronic banking service supported on SMS system (Short Message Services), automatic banking switchboard
Mobile Banking is a modern banking service that allows customers to use mobile phones to perform transactions with the bank This is a form of online payment via mobile phones (customers do not need to go to the bank to still have access to all services 24/7 and anywhere) This method is designed to solve the need to pay for small value transactions or automated services with no servants To become a member, customers need to provide: mobile phone number, personal account used in payment The customer will then be provided with an identification number (ID)
It helps to provide customer information during checkout quicker, accurately and simpler In addition, customers also receive a personal code (PIN) for customers to confirm the payment transaction when requested by the service provider (Vu Hong Thanh and Vu Duy Linh, 2017)
Mehrad & Mohammadi (2016) defined Mobile banking as a mobile commerce application that enables customers to bank at virtually any time and place
Mobile banking refers to the provision and utilization of banking and financial services with the help of mobile telecommunications devices The scope of services provided may include facilities to conduct bank transactions and securities market, account administration and access customized information (Tiwari and Buse, 2007)
Mobile banking can be defined as a channel whereby the customer interacts with a bank via a mobile device, such as a mobile phone or personal digital assistant (PDA) The emphasis is on data communication, and in its strictest form Mobile banking does not include telephone banking, either in its traditional form of voice dial-up or through the form of dial-up to a service based on touch-tone phones (Stuart
CONSUMER DECISION STAGES
Figure 2.1 Consumer Decision stages adopted by S Vázquez et al
S Vázquez et al (2014) provide information about how customers are distributed along the four stages of the consumer decision journey
*In the awareness, refers to the very first contact of the customer with the product or brand, with or without the desire of purchase Customers usually convey their interest through references or expressions about the advertising campaigns
*In the evaluation phase, the customer already knows the product or brand and evaluates it, frequently with respect to other similar products or brands In this step, buyers actively investigate the brand in comparison with its competitors (asking for opinions, formulating questions, consulting product reviews, etc.) and/or express their preference towards a specific brand or product
*In the purchase stage customers either explicitly convey their decision to buy the product or make comments referring to the transaction involved when buying the item
*The postpurchase experience phase refers to the moment when customers, having tried the product, criticize, recommend it or simply talk about their personal experience with it
THEORETICAL BACKGROUND
Originally developed from Fishbein and Ajzen’s Theory of Reasoned Action (TRA); Technology Acceptance Model (TAM) is the most commonly used framework to examine factors influencing the adoption of information systems In
1989, Davis proposed the TAM to explain the potential user’s behavioral intention to use technological innovation TAM examines the factors that influence user’s intentions to accept or reject information systems (Wu and Wang, 2005) TAM involved two primary predictors: Perceived Ease of Use (PEoU) and Perceived Usefulness (PU) and the Dependent Variable: Behavioral Intention (BI)
Based on literature relating to the theory of planned behavior (TPB) and the TAM, Luarn and Lin (2005) extends the applicability of the TAM in a mobile banking context, by adding one trust-based construct Perceived Credibility and two resource- based constructs: Perceived Self-efficacy and Perceived Financial Cost to the model, while paying careful attention to the placing of these constructs in the TAM's existing nomological structure Data collected from 180 users in Taiwan were tested against the extended TAM, using the structural equation modeling approach
Wu and Wang (2005) integrated TAM with IDT and two additional variables (Cost and Perceived Risk) to model for Mobile commerce acceptance Jeong & Yoon
(2013) explores factors influencing the adoption of mobile banking Based on the extended Technology Acceptance Model (TAM), they identified five factors that influence consumer’s behavioral intention to adopt mobile banking: Perceived Usefulness, Perceived Ease of Use, Perceived Credibility, Perceived Self-efficacy, and Perceived Financial Cost Data was collected from 165 respondents through a survey questionnaire in Singapore Their results indicate that all factors except for Perceived Financial Cost have a significant impact on behavioral intention towards mobile banking usage Perceived Usefulness is the most influential factor explaining the adoption intention
2.3.3.1 Le Chau Phu, Dao Duy Huan (2019)
The technology adoption model (TAM) is used by Le Chau Phu and Dao Duy Huan authors to explain and predict the adoption and use of a technology TAM is widely tested and accepted in the research of information technology This is considered as a good predictive model Expected efficiency is the factor that has the strongest impact on the individual customers' decisions to use e-banking services at the Bank Second comes the Risk factor in trading
Banking Brand Behavioral Intention to Adopt Mobile Banking
Figure 2.2 Research model of Le Chau Phu, Dao Duy Huan (2019)
Figure 2.3 Research model of Shi Yu (2009) This study identifies and investigates the factors which influence customers’ decision to use a specific form of Mobile banking in the context of New Zealand The research model includes the basic concepts of the Technology Acceptance Model (TAM), as well as some constructs derived through a focus group discussion The model is tested to determine its predictive power with respect to individual’s behaviour when considering the use of Mobile banking A survey questionnaire was developed and employed to collect data from 250 AUT university students in New Zealand The results of the data analysis contributes to the body of knowledge in the area by demonstrating that context specific factors such as service quality and service awareness are influencing user perceptions about the usefulness of SMS mobile banking which in turn affect intention to use and adoption The findings of this study revealed that perceived usefulness, perceived benefit and perceived credibility were the factors affecting users having intention to adopt mobile banking Meanwhile, the perceived ease of use and perceived financial cost were found to be insignificant in this study
2.3.3.3 Bong-Keun Jeong & Tom E Yoon (2012)
Based on extended Technology Acceptance Model (TAM), they identified five factors which influence consumers’ behavioral intention to adopt mobile banking: Perceived Usefulness, Perceived Ease of Use, Perceived Credibility, Perceived Self- efficacy, and Perceived financial cost Data was collected from 165 respondents through a survey questionnaire, and the regression was used to analyze the relationships Their results indicate that all factors except for perceived financial cost have a significant impact on behavioral intention towards mobile banking usage Figure 2.4 Research model of Bong-Keun Jeong & Tom E Yoon (2012)
2.3.3.4 Isaiah Lule; Tonny Kerage Omwansa and Timothy Mwololo Waema (2012)
This study applied Technology Acceptance Model to examine the factors that influence the adoption of Mobile banking in Kenya A survey was conducted to gather data which was coded in SPSS 16 Out of a total of 450 questionnaires distributed to M-Kesho users, 395 were returned and validated The analysis revealed that Perceived Ease of Use, Perceived Usefulness, Perceived Self -efficacy and Perceived Credibility significantly influenced customers’ attitude towards usage of Mobile banking The implications of the results form a good basis for providing practical recommendations to the banking industry, and directions for further work
Figure 2.5 Research model of Lule, Omwansa and Waema (2012)
2.3.3.5 Ching Mun Cheah, Aik Chuan Teo, Jia Jia Sim, Kam Hoe Oon and Boon In Tan (2011)
A self-administrated questionnaire had been developed and distributed in Malaysia Out of the 400 questionnaires, only 175 useable questionnaires were returned, yielding a response rate of 43.75% Factors such as Perceived Usefulness, Perceived Ease of Use, Relative Advantages and Personal Innovativeness were found positively related with the intention to adopt mobile banking services However, social norms were the only factor found insignificant Perceived Risk was negatively associated with the mobile banking adoption
Relative Advantages Behavioral Intention to Adopt Mobile Banking
Figure 2.6 Research model of Cheah, Sim, Oon and Tan (2011)
2.3.4 Selected literature on consumer acceptance of Mobile banking
Table 2.1 Selected Literature on Consumer Acceptance
Perceived Usefulness Perceived Ease of Use Perceived Risk Social Influence Transaction cost Branch Perceived Self-efficacy Trust Compatibility
RESEARCH FRAMEWORK AND RESEARCH HYPOTHESES
Based on the available research results on behavioral adopt Mobile banking and the actual situation in the research area, the author proposes to study 4 factors affecting the decision to use Mobile Banking services In which, the study inherits 2 traditional elements of TAM model: Perception Usefulness (PU), Perception Ease of Use (PEoU), At the same time, this study adds 2 new factors: Perception Risk (PR); Social Influence (SI) to consider the effect of variables on the dependent variable in which these constructs are believed to affect the behavioral intention to adopt Mobile banking
The proposed research framework is shown as in Figure 2.7 below
The behavioral intention to adopt Mobile banking in this study is understood as the decision to register an account using Mobile banking of an individual customer
2.4.2.1 Perceived Usefulness is the degree to which individuals believe that using a particular system will improve their performance
According to Visa research, in the period July 1, 2017 - May 31, 2018, the growth rate of contactless transactions in Vietnam reached 44% per month Contactless speed Visa card transactions increased by 43% per month over the same period With the “contactless” payment trend, customers are increasingly interested in services that fully respond to their requests Found the functions of the bank when providing Mobile banking
Based on results Arunagiri, Michael & Teoh (2014); Jeong & Yoon (2013); Lule, Omwansa & Waema (2012); Giao & Chau (2020) concludes that Perceived Usefulness has a positive impact on the individual customers adoption of Mobile banking
Hypothesis - H1: Perceived Usefulness has a positive effect on behavioral intention to adopt Mobile banking
2.4.2.2 Perceived Ease of Use is the level at which one believes using a particular system will take no effort (Davis 1985) Therefore, the perception of ease of use greatly affects the customer's decision to use the service, then the customer believes that the ability to perform tasks (payment) on smart devices is easy Depending on the interface design of the application, showing group and icon transactions, transaction steps are reduced, displayed smoothly
According to the studies of Phu, L.C & Huan, D H (2019); Arunagiri, Michael & Teoh (2014); Bong & Tom (2013); Lule, Omwansa & Waema (2012); Giao & Chau (2020) proves that Mobile Banking is provided in the market with many services that benefit customers, meeting their usage needs Rated as one of the main factors affecting adoption Mobile banking
Hypothesis - H2: Perceived ease of use has a positive effect on behavioral intention to adopt Mobile banking
2.4.2.3 Perceived Risk is defined as the negative perception of consumers that service providers will not fulfill their security requirements when transacting; Consequently, the consumer may incur a loss while participating in payment transactions on the app The risk perception factor is assessed through the criteria inherited from the study of Shaikh, Karjaluoto (2018); Phu, Huan (2019); Giao, Chau (2020) According to Tiwari, Buse, and Herstatt (2007), users' concerns are mainly about the insecurity of the application
Hypothesis H3: Perceived Risk has a negative effect on behavioral intention to adopt Mobile banking
2.4.2.4 Social Influence: Riquelme, H., and Rios, R E (2010) surveyed 681 consumers in Singapore and concluded that perceptions usefulness, social influence and risk are three important factors that influence the mobile banking application Similarly, research was done by Yu, 2012 in Taiwan; Kazi & Mannan, 2013 in Pakistan results that the most important factor in a customer's mobile banking decision making is social influence
Hypothesis - H4: Social Influence has a positive effect on behavioral intention to adopt Mobile banking
To validate our proposed model, we used a survey to test consumers’ behavioral intention to adopt m-banking The survey instruments were developed based on a broad literature review (Arunagiri, Michael & Teoh 2014; Abdul and Muhammad 2013; Jeong and Yoon 2013; Lule, Omwansa & Waema 2012; Hernan and Rosa 2010; Gu, Lee & Suh 2009; Wu and Wang 2005; Phu, Huan 2019; Riquelme and Rios 2010) to ensure content validity The survey questionnaire consisted of two parts The first part recorded the respondents’ demographic details The second part recorded respondents’ multi-item attitudes of each factor in the model using the seven-point Likert scale from (1) strongly disagree to (5) strongly agree When banking were being translated to local languages in order to achieve better accuracy in data collection
PU1 Using Mobile banking enables me to access banking services more quickly Behzad et al (2018)
PU2 Using Mobile banking makes it easier to access banking services Behzad et al (2018)
PU3 Using Mobile banking enhances the effectiveness of my banking activities/services Behzad et al., 2018)
PU4 Using Mobile banking would improve the quality of the banking transactions performed Behzad et al (2018)
PU5 I find Mobile banking to be useful for my banking needs Behzad et al (2018)
Perceived Ease of Use (PEoU)
PEoU1 Learning to use the Mobile banking is easy for me Tang et al (2004)
PEoU2 I find it easy to get Mobile banking to do what I what it to do Behzad et al (2018)
PEoU3 I would find the Mobile banking easy to use Tang et al (2004)
PR1 The decision of whether to use Mobile banking services is risky Shaikh et al (2018)
PR2 Using Mobile banking services puts my privacy at risk Shaikh et al (2018)
Compared with other banking channels, such as the internet, Mobile banking has more uncertainties
PR4 In general, I believe using a Mobile banking service is risky Shaikh et al (2018)
SI1 I use Mobile banking because people think I should use Mobile Banking Gu et al (2009)
SI2 I use Mobile banking because it is very famous Gu et al (2009)
SI3 I use Mobile Banking because many people use
Mobile banking Gu et al (2009)
BI1 I would use Mobile banking for my banking needs Shaikh et al (2018) BI2 Using Mobile banking for handling my banking transactions is something I would do Shaikh et al (2018)
RESEARCH METHODOLOGY
THE RESEARCH PROCESS
DESIGN OF RESEARCH
The collected data sample is screened and discarded for unsatisfactory data streams Next, the structure model is used to test the research hypothesis Unlike most previous studies using CB-SEM (e.g., AMOS), this study implements partial least square linear structure model (PLS-SEM) because this method is widely used In current studies (Hair et al., 2014; Ringle et al., 2012) as well as demonstrating some advantages compared to CB-SEM (Hair et al., 2016) PLS-SEM is used to simultaneously estimate the measurement model and the structural model of the proposed research model Tools used to perform analyzes are SPSS 20 software for descriptive statistics, and SmartPLS 3 software for both measurement models and structural models
Quantitative data is analyzed by using descriptive statistics Data collected from the survey is entered into the statistical package, SmartPLS 3 for analysis, discussion and presentation of the results in this research Plot for raw data was used to test the data distribution
For data collection the author distributed 200 questionnaires in the Sacombank Mobile banking at Quang Tri branch in accordance with the locality by applying judgmental sampling method The survey was conducted in local during the period of April 13, 2021 to April 28, 2021
The survey questionnaire consisted of two parts The first part recorded the respondents’ demographic details The second part recorded respondents’ multi-item attitudes of each factor in the model using the five-point Likert scale from 1 being Strongly Disagree to 5 being Strongly Agree When required, the questionnaire items for factors affecting intention to adopt mobile banking were being translated to local languages in order to achieve better accuracy in data collection
The total number of non-usable questionnaires (29) was omitted, and 171 completely filled questionnaires were used for analysis
Use SPSS 20 and SmartPLS 3 software to convert raw data into variables that can be used for analysis and results.
PREPARE DATA PROCESSING
The data sheet is encrypted and entered directly into SPSS, including 24 columns, 171 rows Items include data collected from 171 consumers, columns including general consumer information (7 columns), measures of factors (17 columns) The rows are data obtained from the tables of 171 consumers
Column Information Symbol Encode Scale
2: Between 19 and 25 3: Between 25 and 40 4: Above 40
2: Banker 3: Employed 4: Businessman 5: Real estate business 6: Teacher
5 Frequency of using tansuat 1: Everyday
6 Time using TGsudung 1: Below 1 month
2: 1-6 months 3: 6 months – 2 years 4: Above 2 years
7 Other account linking lienket 1: No
PU1 PU2 PU3 PU4 PU5
OVERVIEW OF SAI GON THUONG TIN COMMERCIAL JOINT STOCK BANK
Bank name in Vietnamese: Ngân hàng thương mại cổ phần Sài Gòn Thương Tín Bank name in foreign language: SAIGON THUONG TIN COMMERCIAL JOINT STOCK BANK
Address of Head office: 266 - 268 Nam Ky Khoi Nghia, Vo Thi Sau Ward, District 3,
Website: www.sacombank.com.vn
Establishment licenses: No 05GP-UB dated November 3, 1992 of the People's Committee of Ho Chi Minh City
Operation license: No 0006GP-NH dated December 5, 1991 of the State Bank of Vietnam
Account: No 453100804 at the State Bank branch in Ho Chi Minh City
Business registration certificate: No 059002 issued by the Department of Planning and Investment of Ho Chi Minh City on 11/13/1992, registered for the 24th change on April 10, 2006
Business lines: Mobilizing short-term, medium-term and long-term capital in the form of time deposit, demand deposit, certificate of deposit; Receive investment capital and develop domestic organizations borrowing capital from other credit institutions; Providing short, medium and long-term loans; Discount commercial law; Payment services between customers; Trading foreign currencies, gold and silver, making international payments; Raising capital from abroad and other services
3.4.1.1 Vision, mission and core values a, Vision: To be a national leader in modern retail banking b, Mission: Maximizing added-value to partners, investors and shareholders, and Committing to build social communities c, Core values
- Pioneering in paving the way and bravely facing challenges to continue the successes
- Providing innovative approaches for sustainable development
- Strengthening community and social responsibility
3.4.1.2 The process of formation and development
1991: Sacombank Is One of The First Commercial Banks Established In Ho Chi Minh city based on the consolidation from Go Vap Economic Development Bank and 3 credit cooperatives: Tan Binh, Lu Gia and Thanh Cong with charter capital of VND
1993: Open the first branch in Ha Noi
1997: Pioneering expanding its operation network (where there has no Sacombank branch located yet) to provide capital to rural areas, contributing to promoting business activities and improving the standard living of the farmers and preventing black market credit in the economy This is also the crucial foundation for establishing branches and developing effective business activities in the area later
2002: Initiating diversified financial services & products
2006: Sacombank was the first commercial joint stock bank of Vietnam to list on Ho
Chi Minh city stock exchange with stock code STB, and total capital as the listing date was VND 1,900 billion
2008: Launched operation in Laos, step by step conquered Indochina market
2015: Sacombank merged with Southern Bank and became one of the 5 biggest commercial banks in Vietnam in terms of total assets, chartered capital and operation network
2017: Restructuring This is the first year Sacombank officially carried out the Plan of Restructuring after the merger which was approved by the State Bank of Vietnam Also, Sacombank has completed building and applying a corporate governance model in conformity with a new development period
2018: Initiating many important projects: LOS, CRM, BASEL II and Establishing digital technology banking center, Sacombank continues to consolidate existing value systems and speed up the trend, capture the development opportunities
2019: March 11, 2019: Officially implement the Loan Origination System (LOS)
May 28, 2019: Sacombank is one of the first 7 banks in Vietnam to be eligible to issue domestic cards equipped with EMV chip which optimizing the card information and enables contactless payment
September 2019: Successfully upgraded core banking system T24 to the most modern version of R17
September 23, 2019: Signed a cooperation agreement with Alliex Vietnam Joint Stock Company to deploy Alliex's shared POS infrastructure to promote non- cash payment in Vietnam Sacombank is the pioneer bank to hand on this activity
3.4.2 Sacombank Quang Tri branch Introduction
3.4.2.1 The process of formation and development of branch
Bank name: SAI GON THUONG TIN COMMERCIAL JOINT STOCK BANK - QUANG TRI BRANCH
Address: 43 Tran Hung Dao, Ward 1, Dong Ha City, Quang Tri Province
Opening hours: Monday to Friday: 7:30 - 17:00
On April 19, 2005, in order to expand the network, develop the brand name and create conditions for the banking system to operate more smoothly, Saigon Thuong Tin Commercial Joint Stock Bank established a tier-2 branch in Quang Tri, under branch level 1 in Hue City, according to Decision No 72/2005/QD - HĐQT
On April 10, 2006, the Branch of Saigon Thuong Tin Quang Tri Commercial Joint Stock Bank officially separated from Hue Branch and has been operating until now
The branch has the main address at 43 Tran Hung Dao, Ward 5, Dong Ha City, Quang Tri Province and 5 subordinate transaction offices operating in key economic regions: Lao Bao, Khe Sanh, Vinh Linh, Quang Tri town, Dong Ha city In which, 13 ATMs are operating in the whole province The establishment of Sacombank branch in Quang Tri aims to become the most modern and versatile retail bank, using small marketing tools to reach and cover the market
With a staff of young, beautiful, dynamic, dedicated professional services, the ability to respond to quick and simple procedures that few banks have, Quag Tri branch has served 20,000 individual customers, 500 corporates; the market share of deposits and loans accounts for more than 10% of Quang Tri province and is always trusted and appreciated by customers Sacombank Quang Tri branch strives to become the leading multi-purpose retail bank in the area with the motto “Safety - Efficiency - Sustainability”
As a branch of Sacombank Commercial Joint Stock Bank in Quang Tri, the dependent accounting unit is bound by the obligations and interests of Sacombank Commercial Joint Stock Bank Business operations of a bank include:
- Capital mobilization activities: mobilizing short-term, medium-term and long-term capital from economic organizations and population classes in the form of term deposits, demand deposits, certificates of deposit, valuable papers,…
- Credit activities: to provide organizations and individuals with long, medium and short-term loans, discount commercial papers and valuable papers
- Other activities: payment services, gold and silver trading, foreign currencies, international payment, investment, investment consulting, investment trust receipt,
3.4.2.2 Organizational structure of Quang Tri branch
Source: Administration department of Quang Tri Branch
Include: 1 Branch manager and 3 Deputy branch directors
Branch manager: Directly manage the operations of the bank and is responsible for directing and operating the business tasks in general and credit operations in particular within the scope of authorization Is authorized to authorize its employees to sign and run the operations of the bank on their own, usually with the authorization of the deputy governor or department heads
Deputy branch director: Directly manage and supervise the operations of the departments in the bank, perform the tasks of mobilizing deposits, lending and providing appropriate services in accordance with the bank's regulations row
Figure 3.2 Organizational structure of Quang Tri branch
Branch manager Nguyen Tran Vinh
Manage and implement sales targets for each specific product
Marketing, customer relationship management: implementing sales, providing support services, customer care, in order to maintain and develop customer relationships in business, tracking, urge debt collection
SACOMBANK MOBILE BANKING
Pic 3-2 mBanking Login screen Pic 3-3 mBanking Dashboard screendd
Pic 3-4 mBanking Transfer and Payment screen
Individuals who are Vietnamese or foreigners (with residents) with full civil act capacity in accordance with current laws
A person with civil act capacity and from full fifteen to less than eighteen years old is accepted by his/her legal representative for the use of Mobile banking
3.5.2 Mobile banking services provided by Sacombank
Currently, to fully meet the needs of customers, Sacombank mBanking offers outstanding features, including:
- Send money to Visa/MasterCard
- Transfer Outside Sacombank (Inter Bank 24/7)
- Deposit to Stock Trade Account
- Payment of Port services fees
- Buy Non-Life Insurance Online
3.5.3 Registration process for Mobile banking service
Customers with a current account at a Sacombank can register to use Sacombank Mobile banking If customers do not have an account at Sacombank, they can open an account when registering for the service
Approach 1: Register Mobile Banking directly at the transaction counter
Customers only need to bring their ID card to the nearest Sacombank branch or transaction office to register for Mobile Banking After successful registration, customers will be provided with a login account and password
Approach 2: Online register for Mobile Banking through Internet Banking
In order to register for mBanking online through iBanking, you would like to follow these steps:
❖ Access the web page www.isacombank.com.vn
❖ Enter your user ID, password and verification code, then click on
Step 2: Select General Services/Register Mobile Banking
Note: Please select valid Authorization Mode It should be either Transaction Password or your eBanking Authorization Mode
You need to accept Terms and Conditions of Sacombank eBanking by check the box marked “I have read, understand and accept the Terms and Conditions of Sacombank eBanking”, then click on “Continue”
Step 3: At the confirmation screen, you need to re-check your registration information If everything is correct, you need to enter OTP and click on “Submit” to complete the transaction
Step 4: The system shows the screen of successful registration
With many attractive features, but the fee for using Mobile Banking when making transactions is very reasonable and competitive In addition, individual customers can also use many free services The fee schedule is as follows:
Table 3.3 The fee for Personal Mobile banking Service
(Tariff does not include VAT)
(No charge when customers use less than a month) 15,000 per month
OTP authentication fee through mSign Free of charge
OTP authentication fee through SMS Free of charge
OTP authentication fee through Token/Advanced token 200,000 per device
Update fee for authentication type (Token/
Advanced token or SMS or vice versa) (/time) 10,000 per time
Updating trading limit (/per time/per user) 10,000
Registering/updating high trading limit
From over 1 billion to under
From 5 billion to under 10 billion 300,000 per time
From 10 billion or more 500,000 per time
Same province/city Under 50m: Free of charge
From 10m and above: 8,000 Intra Bank Funds Transfer (Card to account) 8,000 per transaction
Intra Bank Funds Transfer to personal ID 0.024% of amount transfer
Cash on Mobile 8,000 per transaction
Send Money to Visa Card 15,000 per transaction
Inter Bank Funds transfer receiving with personal ID/in an account (CITAD system)
Same province/city 0.01% of amount transfer
Different province/city 0.03% of amount transfer;
Fast Inter Bank Funds transfer receiving by an account/a card (banknet system) (per transaction)
Buy virtual prepaid card 13,636 per transaction
Adjusting or reversing a transfer order within
Sacombank, to beneficiary who receives by personal ID
Adjusting or reversing a transfer order outside
Sacombank, to receive by account/personal ID 15,000 per transaction
Pay financial bill VIETCREDIT 5,000 per transaction
3.5.5 Mobile banking users in branch, 2018 to 2020
Table 3.4 The number of users in Quang Tri branch from 2018 to 2020
Source: Statistics of Sacombank Quang Tri branch
Through the situation of the number of accounts over the years 2018-2020, the number of registered accounts has steadily increased Compared to 2018, the number of accounts in 2019 increased by 110 accounts (corresponding to an increase of
16.40%) By 2020, the number of accounts increased by 160 accounts (i.e an increase of 20.5%) compared to 2019 That shows that the demand for using Mobile Banking is tending to increase as well as seeing the effects by Sacombank in extended
According to data shown at Table 3.4, most of the customer of branch from
2018 to 2020 are doing business 2018 are 26%; 2019 are 26% of all total, by 2020,
RESEARCH RESULTS
RESULT OF DESCRIPTIVE STATISTIC
Data used to test my research model were collected from a sample of respondents of Sacombank users within Quang Tri I distributed 200 questionnaires and obtained 171 completed The response rate of 85.5% was attributed to the eagerness of respondents in using this technology
Source: SPSS 20 results & compiled by author Frequency of user Mobile banking, the most group 2 - 4 each week (46.8%),
1 - 2 each month (19.9%), Everyday (17.5%), 3-4 each month (15.8%) Time used Mobile banking shows that 1 - 6 months (47.4%) is the most, Below 1 month (21.1%),
Figure 4.1 Distribution of respondents by Gender According to the Table 4.1 and Figure 4.1, there are 101 respondents approximating 59% are female while 70 respondents accounted for 41% were male This result implies that female more than male
Figure 4.2 Distribution of respondents by Age
Table 4.1 and Figure 4.2 shows the demographics of the respondents by ages that group 25 - 40 years had the most users 51.5%; 24.6% are ranged from the age of
19 to 25; 15.2% are ranged from the age of Above 40; 8.8% are ranged from the age of Below 18 This result indicated that Mobile banking seems to be fit the 25 to 40 rather than the other
Figure 4.3 Distribution of respondents by Income Table 4.1 and Figure 4.3 shows the monthly salary earned up to 7.000.000 – 10.000.000 per month comprised 46.8% of the total 171 respondents participated in the survey This is followed by group 5.000.000 – 7.000.000 with 29.8%; 13.5% are ranged from the monthly income of Above 10.000.000; 9.9% are ranged from the age
Figure 4.4 Distribution of respondents by Occupation Table 4.1 and Figure 4.3 shows that surveyed people worked in a variety of fields, the most of which were Businessman with 22.8%, followed by Student with 20.5%, Other, Real estate business, Banker, Employed, Teacher support is 17.0%, 11.7% and 11.1%, 6.4%, 5.8% and the least is Engineer with 6.4%
Student Banker Employed Business Real estate business
ASSESSMENT OF THE MEASUREMENT MODEL
Data are standardized automatically in SmartPLS, the loadings vary from 0 to
1 The loadings should be significant In general, the larger the loadings, the stronger and more reliable the measurement model Indicator reliability may be interpreted as the square of the measurement loading: thus, (0.708) 2 = 0.50 reliability (Hair et al.,
2014) Outer Loading should be > 0.7 (Hair et al., 2016) The author deleted the indicator PR4 that has outer loadings that is less than 0.7 as and rerun the analysis again This result is shown in Table 4.2 below:
Table 4.2 Result of Outer Loading
CONSTRUCT ITEM BI PEoU PR PU SI
Perceived Ease of Use PEoU1 0.862
Source: SmartPLS 3 results & compiled by author
4.2.1.2 Cronbach's Alpha, Composite reliability and Average Variance Extracted
The assessment of the reliability of the scale is done through two typical indicators, the Cronbach’s Alpha (CA) and Composite reliability (CR) index CR and
CA show that the variables on the scale converge to a single latent structure Normally, to check the reliability of the CA, if the result is above 0.7 then the result will be accepted The analytical results show that all the above factors satisfy the above condition 0.7 However, compared with CA, CR is considered to be a better measure of uniformity of reliability because it uses the standard load of the observed variables Fornell and Larcker (1981) In which CR is above 0.7 is satisfactory
After evaluating convergence values of potential variables based on the external load factor and the variance of the AVE extract If the external factor load factor of a variable > 0.7 is considered ideal, then the interval between 0.4 and 0.7 should be considered before deletion (Henseler et al., 2009) According to Fornell and Larcker (1981), the value of the sum of the AVE extracted variance must be equal to or higher than 0.5 to be satisfactory, which means that the latent variable can explain more than half of its variance with the mean jar If the AVE is less than 0.5, that latent factor or variable is generally considered to be excluded from the research model
Table 4.3 Cronbach's Alpha (CA), Composite reliability (CR) and Average Variance Extracted (AVE)
Perceived Ease of Use PEoU 0.854 0.911 0.774
Source: SmartPLS 3 results & compiled by author
Figure 4.7 Average Variance Extracted (AVE)
In the results of this study, all factors are satisfactory as presented in Table 4.3 and Figure 4.5, Figure 4.6 Figure 4.7 indicated that convergent validity of this study measurement model can be proved as the factor loading of same construct of all 5 constructs are higher than 0.7 Average Variance Extracted of all constructs are higher than 0.5 and Composite Reliability of all construct are all higher than 0.7
4.2.2.1 Discriminant Validity: Fornell and Larcker criterion
The discriminant validity was assessed using Fornell and Larcker (1971) by comparing the square root of each average extracted variance in the diagonal with the correlation coefficients (off-diagonal) for each construct in the relevant rows and columns The conditional region of Fornell and Larcker (1981), other concept is assessed discriminant validity when its AVE value is greater than the square of its correlation coefficient with the rest of the paradigm concept
Table 4.4 after type PU1, SI3 (Refer to Appendix) shows that the square root value of AVE of each concept is greater than the correlation coefficients among the corresponding variables so the 171 samples in the study obtained distinct validity All
Average Variance Extracted the square roots of AVE have coefficients higher than 0.5 (from 0.814 to 0.926) are satisfactory In each factor, the square root of AVE is higher than the correlation coefficient of other factors in the same column
CONSTRUCT ITEM BI PeoU PR PU SI
Perceived Ease of Use PeoU 0.806 0.880
Source: SmartPLS 3 results & compiled by author Note: The square root of the average variance extracted (AVE) in bold
The variance inflation factor (VIF) is used as an indicator of multicollinearity Computationally, it is defined as the reciprocal of tolerance: 1/(1-R 2 ) All other things equal, researchers desire lower levels of VIF, as higher levels of VIF are known to affect adversely the results associated with a multiple regression analysis In fact, the utility of VIF, as distinct from tolerance, is that VIF specifically indicates the magnitude of the inflation in the standard errors associated with a particular beta weight that is due to multicollinearity Various recommendations for acceptable levels of VIF have been published in the literature Perhaps most commonly, a value of 10 has recommended as the maximum level of VIF (e.g., Hair, Anderson, Tatham, & Black, 1995; Kennedy, 1992; Marquardt, 1970) The VIF recommendation of 10 corresponds to the tolerance recommendation of 0.10 (i.e., 1/0.10 = 10) However, a recommended maximum VIF value of 5 (e.g., Ringle et al., 2015; Rogerson, 2001) Table 4.5 shows that the VIF values for the indicators of the composite model range smaller than 5, suggesting that multicollinearity is not a problem in our data
The evaluation criteria for the quality of the PLS-SEM model as well as the hypothesis testing steps in this study are based on the evaluation suggestions of Hair et al (2016), Hair et al (2017) According to these authors, PLS-SEM does not have a suitable metric for the entire model; instead, the quality of the model is assessed through two values, the coefficient of determination (R 2 ) and blindfolding-based cross validated redundancy measure (Q 2 ) The values higher than 0.02, 0.15 and 0.35 depict small, medium and large f 2 effect sizes (Cohen, 1988) showing that the exogenous structure has small, medium and large predictive relevance for the respective endogenous latent variables R 2 and Q 2 refer to the evaluations of the interpretability and predictability of endogenous structures As Table 4.6 displays, R 2 adjusted were 0.689 accounted for the variances explained in behavioral intention Consequently, this study demonstrates the applicability of TAM to a Mobile banking, and the empirical results strongly support the extended TAM in predicting individual intentions and behaviors of Mobile banking adoption And the results R 2 = 0.696, therefore the independent variables, Perceived Ease of Use, Perceived Risk,
Perceived Usefulness, Social Influence for 69.6% of the variance in the Mobile banking usage This means that the independent variables in the TAM model predict 69.6% of the factors that determine the adoption and use of Mobile banking The results Q 2 = 0.585 > 0 shows that the structural model has good quality
Path Coefficients Standard Deviation T Statistics P Values
Behavioral Intention (PeoU -> BI) 0.507 0.081 6.274 0.000 Perceived Risk (H3) -> Behavioral
R 2 BI=0.696 f 2 PU -> BI = 0.070 f 2 PeoU -> BI = 0.273 f 2 PR -> BI = 0.001 f 2 SI -> BI = 0.014
Q 2 BI= 0.585 q 2 PU -> BI = 0.036 q 2 PeoU -> BI = 0.169 q 2 PR -> BI = - 0.007 q 2 SI -> BI = 0.005
From Table 4.6 shows 2/4 hypotheses (H1, H2) are accepted because they have P-value 0.05, so these two hypotheses are not accepted Thus, only two concepts in the theoretical model reach theoretical value
Table 4.7 Results of Mode fit
Source: SmartPLS 3 results & compiled by author According to Hulland and Bentler (1999), a value SRMR less than 0.10 or of 0.08 are considered a good fit Thus, with the value of SRMR = 0.062 < 0.10, the research model is concluded consistent with the study area at Sacombank, Quang Tri branch
Chin, Marcolin, and Newsted (1996) have clearly pointed out that researcher should not only indicate whether the relationship between variables is significant or not, but also report the effect size between these variables The study can use bootstrap confidence intervals to test if the construct reliability is significantly higher than the recommended minimum threshold (e.g., the lower bound of the 95 per cent)
A larger number of bootstrapping samples is advised when using confidence intervals, because the estimates of the confidence intervals are getting more robust and stable as the number of bootstrapping samples increases (Streukens and Leroi-Werelds, 2016) Hence, they usually advise people to use as many bootstrapping samples as possible If it is possible to calculate 5,000 than do that instead of just 500 Thus, Author decided to opt for the conservative strategy generating 5,000 samples (Original Sample =171) and these samples are used to compute the base original sample is significant with the mean of bootstrapping because all weights are within the 95% confidence interval Estimates in the model can be concluded to be reliable Table 4.8 Bootstrapping 5000 samples
*PU -> BI: Perceived Usefulness (H1) -> Behavioral Intention
PeoU -> BI: Perceived Ease of Use (H2) -> Behavioral Intention
PR -> BI: Perceived Risk (H3) -> Behavioral Intention
SI -> BI: Social Influence (H4) -> Behavioral Intention
4.2.4 Verifying the relationship between demographic and dependent variable
4.2.4.1 The impacts of gender on Behavioral Intention
Table 4.9 The impacts of gender on Behavioral Intention
Test of Homogeneity of Variances
Levene Statistic df1 df2 Sig
Sum of Squares df Mean Square F Sig
Conclusion: Because sig = 0.079 > 0.05, there is no difference between male and female in the intention to adopt Mobile banking
4.2.4.2 The impacts of age on Behavioral Intention
Table 4.10 The impacts of age on Behavioral Intention
Test of Homogeneity of Variances
Levene Statistic df1 df2 Sig
Sum of Squares df Mean Square F Sig
Conclusion: Because sig = 0.692 > 0.05, there is no difference in age in the intention to adopt Mobile banking of customer
4.2.4.3 The impacts of income on Behavioral Intention
Table 4.11 The impacts of income on Behavioral Intention
Test of Homogeneity of Variances income
Levene Statistic df1 df2 Sig
Sum of Squares df Mean Square F Sig
Conclusion: Because sig = 0.358 > 0.05, there is no difference in income in the intention to adopt Mobile banking of customer
4.2.4.4 The impacts of occupation on Behavioral Intention
Table 4.12 The impacts of occupation on Behavioral Intention
Test of Homogeneity of Variances occupation
Levene Statistic df1 df2 Sig
Sum of Squares df Mean Square F Sig
Conclusion: Because sig = 0.704 > 0.05, there is no difference in occupation in the intention to adopt Mobile banking of customer.
DISCUSSION AND RECOMMENDATION
DISCUSSION
This model has been tested and validated against data collected from 171 subjects survey Based on the extended TAM model, four factors were identified: Perceived Usefulness, Perceived Ease of Use, Perceived Risk and Social Influence The study revealed that the first hypothesis H1, Perceived Usefulness has a significant positive influence in examining the intention to adopt Mobile banking in Sacombank - Quang Tri branch (Path coefficient = 0.269, P-value = 0.001 < 0.05) This is consistent with the prior studied of Jeong & Yoon, 2013; Lule, Omwansa & Waema, 2012; Cheah, Teo, Sim, Oon and Tan, 2011; Chung and Kwon, 2009
The hypothesis H2, Perceived Ease of Use has a significant positive influence (Path coefficient = 0.507, P-value = 0.000 < 0.05) Similar results were demonstrated from previous studies by Bong & Tom 2013; Lule, Omwansa & Waema 2012; Laurn and Lin, 2005 This implies that if customers perceive that a Mobile banking system is easy to use, then they would use and adopt Mobile banking services and systems
The hypothesis H3, Perceived risk was found to have an insignificant impact on the customers’ intention to adopt Mobile banking in Sacombank - Quang Tri Branch (Path coefficient = 0.014, P-value = 0.828 > 0.05) Some studies found that security issues are not the main inhibitor in mobile banking adoption (Laukkanen, and Lauronen, 2005; Suoranta, 2003) This implies that customers perceived risk and certainty incurred in adopting Mobile banking Besides, prior studies strongly support perceived risk (Bhatnagar et al., 2000) as important factors influencing user’s behaviour A further study should retest and investigate these two issues
Finally in this study, the hypothesis H4, Social influence was found to have an insignificant impact on the customers’ intention to adopt Mobile banking in Sacombank - Quang Tri Branch (Path coefficient = 0.122, P-value = 0.122 > 0.05) This was in line with many past studies by Yu, 2012; Kazi & Mannan, 2013
Nowadays, the increasingly developing information society environment also the use of Mobile banking services is gradually becoming an important rival advantage, not only bringing benefits to customers but also bringing many benefits from customers Therefore, building and developing Mobile banking services is a long-term activity and requires a clear and specific expansion strategy
In the framework of the graduation thesis and the accumulated knowledge, the topic “Factors affecting adoption Mobile banking of individual customer at Sai Gon Thuong Tin commercial joint stock bank - Quang Tri Branch” errors and limitations of time and experience are inevitable Though, with useful theories and research gathered from practice The author hope this will be a valuable topic for producing Mobile banking services as well as build customer loyalty
Figure 5.1 Outer Loadings, Path coefficients and Cronbach's Alpha adjusted
Users’ intention is important for the success of Mobile banking service In this study, an extended version of the TAM was used to investigate customers’ intention to adopt Mobile banking in Sacombank - Quang Tri Branch This study was assumed that there are two direct impacts in the revised model The findings of this study showed that Perceived Ease of Use and Perceived Usefulness (P-Value