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PREFACE
1. Urgency of the thesis topic
As communication technology has been developing increasing fast, Vietnamese
banks dare not only improving their traditional services but also expanding and
developing services that apply information technology. The application of internet
banking (e-banking) services is one of important solutions to Vietnamese commercial
banks in improving their competitiveness in the context of global integration.
Mobile banking means the customer carries out transactions with a bank via a
mobile phone or internet-enabled personal digital assistant (PDA). (Barnes and
Cobitt, 2003; Scomavacca and Barnes, 2004). Nowadays, the number of these
internet-enable devices is increasing (Laukkanen and Lauronen, 2005). Study of Nhu
Trang (2014) showed mobile banking will become popular and important
transactions when more than 20% of the population use smartphone. By 2017, there
were 4,8 million of broadband internet subscription and about 31 million internet
users (accounting for 34% of the total population) (Lan Anh, 2017). According to
International Data Corporation (IDC), Vietnam is in the top 3 of markets with the
highest growth of smartphone subscription ratio. It was expected that by 2018, the
ratio of smartphone application in Vietnam would increase by 70% and by 2021 the
number of smartphone subscription would increase by 3 times compared to 2015.
Mobile banking which includes the management of account through mobile
devices has created considerable changes in business operations of commercial
banks. It helps banks cut down cost and increase efficiency for customers. Mobile
devices, especially smartphones and PDAs are the most promising means to approach
customers thanks to their ability to provide services anywhere and anytime, high ratio
of market penetration and development potential (Meyer, 2007; Ondiege, 2010).
This will open more channels for financial corporations that are interested in
providing value-added services.
Despite the recent appearance of mobile banking, the demand of people is
increasing quite fast. Many banks develop mobile banking application for various
services to meet such demands as account management, transfer, service payment,
bill settlement and even for a number of special demands such as online saving,
security transaction, domestic financial transaction, online ticket booking...
Studies on mobile banking have been attracting special attention of local and
international researchers. Studies point out many different factors affecting use
intention and behavior of mobile banking. It was pointed out in many previous
studies (Luarn and Lin, 2005; Amin et al, 2008; Yang, 2009; Cruz, 2010; Yu, 2012)
that perceived risks, perceived transaction, ease of use, perceived credibility are
factors that considerably affect use intention of mobile banking services. However,
there are also studies that provide different impacting factor of use intention such as
perception of service advantages (Brown et al, 2003), conformity ability, customer
trust (Lee et al, 2003); social norms (Riquelme and Rios, 2010), demographic factor
(Laukkanen and Pasanen, 2008; Yu, 2012). In addition, there are studies that point
out perceived risk, cost and ease of use (Suoranta et al, 2005; Koening-Lewis et al,
2010), andperceived credibility factors (Alam, 2014) do not affect mobile banking
use intention. According to studies, in different contexts, there are different impacting
factors; on the other hand, demographic variable is considered as a control variable,
not as a moderating variable for each factor that affects mobile banking use intention.
Technology Acceptance Model (TAM) is one of main theoretical models about
technology acceptance studied based on such foundation theories as Theory of
Planned Behavior (TPB), Innovation Diffusion Theory (IDT). Several shortcomings
of these theories were pointed out by Venkatesh et al (2013), such as they did not
take into account the factor of social influence and each theory considered different
foundation factors.
This study inherits and develops the Unified Theory of Acceptance and Use of
Technology (UTAUT) with age and gender having moderating impact on mobile
banking use intention of individual customers. The application of this theory to study
the impact of factors on accepting and using mobile banking was studied in other
countries; however study results differed due to different economic development
levels and culture. Therefore, previous study results may not be suitable in the
context of Vietnam.
On that basis, the study of factors that influence the acceptance and use of
mobile banking in Vietnamese commercial banks is very important. Finding from this
study can help banks have suitable solutions for specific customer segments. For
these reasons, the author chooses the following topic: "Factors affecting individual
customers in accepting mobile banking services in Vietnam: a study from
Unified Theory of Acceptance and Use of Technology model (UTAUT)". In this,
the author applies the UTAUT model that is modified and added to match with the
context of Vietnam to answer study questions: what factors affect mobile banking use
intention and behavior, what are their levels of influence, do age and gender count in
these factors that affect use intention?.
2. Study objectives
Identifying factors affecting individual customers in adopting mobile banking
services; from that providing recommendations for commercial banks so that they can
attract individual customers in using mobile banking services in Vietnam
3. Study object and scope
- Study objects: influencing factors of acceptance and use of mobile banking
- Study scope:influencing factors of mobile banking use intention and behavior
in Vietnamese commercial banks, specifically:
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+ Study mobile banking in the form of mobile application (mobile banking
application that is installed on mobile phones)
+ Survey object: people who has not used and has been using mobile bankingas
representatives for the North, the South, and Center Region.
4. Study questions:
- What factors affect mobile banking use intention and behaviorof individual
customer?
- What is the level of influence of each factor on mobile banking use intention
of individual customers?
- Concerning factors affect mobile banking use intention, is there any
difference in age and gender?
- To how many percentages can mobile banking be explained from use
intention?
5. study methodology
The qualitative and quantitative research methods are combined.
-Qualitative research method: applied during the stages of developing the
questionnaire and discussion of study results.
- Quantitative research method: applied in preliminary survey, evaluation of
reliability of scale, official survey, analysis and verification of relationships between
variables in the model.
6. Study process
To achieve study objectives and answer study questions, the following steps are
carried out:
Step 1: Overview of study
After identifying study objectives, the author looks into study overview to find
our research gap and then build the theoretical framework.
Step 2: Qualitative research (in-depth interview)
After identifying the theoretical framework, the author carries out in-depth
interview with specialists and individual customer to determine and develop the
development model.
Step 3: Preliminary quantitative research
After proposing the study model, the author creates the preliminary
questionnaire and measurement scale. After that, the author tests questionnaire with
50 people to adjust it, discuss it and fix grammatical errors to have a suitable one for
the study.
Step 4: Official quantitative research
Collecting and analyzing data
Step 5: Discussion of study results and recommendations of solutions
Verifying the proposed study model, discussing results and proposing solutions
7. Contributions of the thesis
7.1 In terms of theory
The combination of factors in the second generation of the Unified Theory of
Acceptance and Use of Technology (UTAUT2) of Venkatest et al and the addition of
trust and perceived privacy factors in the field of mobile banking were mostly
overlooked in previous studies. In addition, in previous studies, the authors did not
consider the relation between the cultural factor with factors in UTAUT2 model. This
is the first study in Vietnam on accepting and using mobile banking that applies the
UTAUT2 model combined with trust and perceived privacy factors. In this study, the
new factor is named performance expectancy based on the combination of two factors
in the original model (performance expectancy and price value). The study also
points out the relation between the cultural factor and factors of perceived benefit,
effort expectancy and hedonic motivation.
7.2 New findings and recommendations from survey and study results
Firstly, the study points out perceived privacy has big influence on the
acceptance and use of mobile banking in Vietnam, followed by hedonic motivation,
social influence, trust, and performance expectancy. The factor of facilitating
conditions does not affect mobile banking users in Vietnam.
Secondly, age and gender create difference regarding each impacting factor.
Thirdly, the study provides a number of recommendations to increase the
number of customers using mobile banking.
8. Structure of the thesis
In addition to preface, conclusion, and list of reference material, the thesis has 5
chapters:
Chapter 1: Overview of study on mobile banking
Chapter 2: Study model and hypotheses
Chapter 3: Study methods
Chapter 4: Study results
Chapter 5: Discussion of study results and recommended solutions
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CHAPTER 1: OVERVIEW OF STUDY ON MOBILE BANKING
1.1 Overview of mobile banking services
1.1.1 Electronic banking (e-banking)
E-banking or internet banking) is understood as the use of electronic and
telecommunication networks by banks to deliver banking services to bank customers
(Aduda and Kingoo, 2012).
1.1.2 The concept of mobile banking
This study applies the concept of mobile banking according to Shaikh and
Karjaluoto (2015): Mobile banking is a product or service offered by a bank for
conducting financial and non-financial transactionsusing a mobile device, namely
a mobile phone, smartphone, or tablet.
In this study, mobile banking and mobile payment are considered two different
services. Mobile payment service is also done via the mobile phone but the bank does
not directly take part in it so it is not considered as a mobile banking service.
1.1.3Platforms of mobile banking
1.1.3.1 Wireless Application Protoco)
1.1.3.2 (Short Message Service)
1.1.3.3 Mobile banking with PDA (Personal Digital Assistant)
1.1.3.4 SIM-Toolkit and Mobile Client Applications
1.1.4Benefits of mobile banking services
* For the bank
The benefit of mobile banking from the bank’s perspective is shown as follows:
(i) Increasing customer satisfaction (Tiwari et al, 2006).
(ii) Cutting down cost and increasing revenue
(iii) Helping the bank become more proactive in delivering banking
information to customers
(iv) Intensifying competition in the banking sector(Tiwari et al, 2006)
(v) Adapting to requirements of core target groups (Tiwari et al, 2006).
(vi) Increasing the volume of products and services provided for customers
(Tiwari et al, 2006).
(vii) Reducing costof distribution(Tiwari et al, 2006).
(viii) Strengthening the bank’s reputation through enhanced image (Tiwari et
al, 2006).
*Đ For customers:
(i) Customers can make transfers and settle costs anywhere, anytime (Luarn
and Lin, 2004; Lee et al, 2003; Laukkanen et al, 2007; Yu, 2012).
(ii) Transactions can be done quickly and conveniently (Luarn and Lin, 2004;
Lee et al, 2003; Laukkanen et al, 2007; Yu, 2012).
(iii) Secured services are provided (Luarn and Lin, 2004; Lee et al, 2003;
Laukkanen et al, 2007; Yu, 2012).
1.2 Overview of models of acceptance and use of technology
Behavior theories used in studies on customer’s acceptance and use of
technology include Theory of Reasoned Action (TRA), Theory of Planned behavior
(TPB), Decomposed Theory of Planned Behavior (DTPB), Technology Acceptance
Model (TAM and TAM 2), Innovation Diffusion Theory (IDT), Model of Personal
Computer Utilization (MPCU), Social Cognitive Theory (SCT), Unified Theory of
Acceptance and Use of Technology (UTAUT).
Within the thesis’s scope , the author systemizes behavior theories about
accepting and applying technology as the foundation to build the theoretical
framework for the study.
1.2.1 Theory of Reasoned Action (TRA)
1.2.2 Theory of Planned Behavior (TPB)
1.2.3 Decomposed Theory of Planned Behavior (DTPB
1.2.4 Technology Acceptance Model (TAM)
1.2.5 Innovation Diffusion Theory (IDT)
1.2.6 Model of Personal Computer Utilization (MPCU)
1.2.7 Social Cognitive Theory (SCT)
1.2.8 Unified Theory of Acceptance and Use of Technology (UTAUT).
1.2.9Chosen theory as the foundation for study
The thesis applies UTAUT2 as the foundation theory for study because:
(i) UTAUT2 has certain advantages over other theories. It integrates essential
factors in previous technology acceptance and use , consideres the impact of
factors on use intention and behavior acceptance which differs by peripheral
factors (gender, level of competence, experience, voluntariness), and is verified
as being superior to other models(Venkatest et al, 2003; Park et al, 2007;
Venkatest & Zang, 2010)
(ii) UTAUT2 combines not only main relations in UTAUT but also other relations
that help increase application capabilities for users. Researchers created different
models and theories of technology acceptance and use; however, most initial
theoretical models were proposed in the corporate setting. Venkatesh et al
(2012) studied the UTAUT2 model in the individual setting. This thesis studies
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factors that form individual use intention and behavior in mobile banking,;
therefore, the author chooses this model as the foundation theory because it is
suitable to the study setting.
(iii) Venkatesh et al (2012) explained the behavioral intention (74%) in technology
use compared to the initial UTAUT model (56%) so the author applies
UTAUT2 as foundation for the study model.
1.3 Overview of factors affecting mobile banking
Table 1.3: A number of factors affecting mobile bankinguse intention from
previous studies
Factors
Author and result
Information
Rogers (2003); Cruz et al (2010) (+)
Observation ability
Lee et al (2003); Laforet and Xyaoyan (2005); Meuter et al
(2005); Rogers (2003) (+)
Complexity
Wan et al(2005) (+); Venkatesh and Davis (2000) (+);
Pikkarainen et al (2004) (+);
Hernandez and Mazzon (2006) (-); Lee et al (2003) (-);
Mattila et al (2003) (-)
Comparative
Brown et al (2003) (+);Suoranta (2003),Kim et al (2009),
advantage
Cruz et al (2010), Püschel et al (2010), Al-Jabri and Sohail
(2012) (+)
Perceived risk
Wan et al (2005) (-); Meuter et al (2005) (-);Brown et al
(2003) (-);Laforet and Li (2005) (-);Lee et al (2007) (-);
Pikkarainen et al (2004) (-); Lee et al (2007) (-) Brown et al.
(2003) (-)
Unsuitable device
Laukkanen and Lauronen (2005); Cruz et al (2009) (-)
Perceived cost
Luarn and Lin (2005); Yang (2009); KPMG International
(2009); Cruz et al (2010); Koenig-Lewis et al (2010); Yu
(2012); Alam (2014) (-)
Perceived credibility
Laforet and Li (2005); Amin et al (2008); Yang (2009);
KPMG International (2009); Koenig-Lewis et al (2010);
Dasgupta et al (2011); Yu (2012) (+)
Compatibility
Alam (2014)(+)
Perceived usefulness
Laukkanen and Lauronen (2005); Crabbe et al. (2009);
Riquelme and Rios (2010); Natarjan et al (2010); KoenigLewis et al (2010); Sripalawat et al (2011); Dasgupta et al
(2011); Mohammadi (2015); Mortimer et al (2015); Yuan et
al (2016)
Social influence
Zhou et al (2010); Yu (2012); Alam (2014); Mortimer et al
(2015) (+)
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Factors
Ease of use
Author and result
Brown et al (2003); Luarn and Lin (2005); Amin et al (2008);
Gu et al (2009); Dasgupta et al (2011); Yu (2012); Mortimer
et al (2015) (+)
Trust and initial faith
Lee et al (2007); Yang (2009); Kim et al (2009); Liu et al
(2009); Koenig-Lewis et al (2010), Bankole et al (2011);
Faria et al (2012); Oliveira et al (2014); Mahfuz et al (2016);
Baptista and Oliveira (2016); Afshan and Sharif (2016) (+)
Privacy
Laforet and Li (2005), Yang (2009) (+)
Cultural factor
Bankole et al (2011); Sriwindono and Yahya (2012);Baptista
and Oliveira (2015); Mahfuz et al (2016) (+)
Hedonic motivation
Baptista and Oliveira (2015)
Facilitating conditions Crabbe et al (2009); Püschel et al (2010); Faria (2012),
Mahfuz et al (2016) (+)
Cost value
Mahfuz et al (2016)
Performance
Gu et al (2009); Zhou et al (2010); Faria (2012); Alam (2014);
expectance
Baptista and Oliveira (2016) (+)
Effect expectancy
Alam (2014); Bankole et al (2011) (+)
Note: (+) positive impact; (-) negative impact
Source: collected from various authors
* Conclusion
(1) The demographic factor which serves as a control variable of relations
related to use intention of mobile banking is not a popular study topic.
(2) There are many factors mobile bankinguse intention; study results are
inconsistent in each research setting.
(3) The cultural factor was mentioned in only a small number of studies.
(4) The UTAUT2 model was applied in recent studies. In Vietnam, there is
hardly any study that applies UTAUT2.
CHAPTER2: STUDY MODEL AND HYPOTHESES
2.1 The relation between factors and mobile banking use intention
2.1.1 Impact of performance expectancy on use intention
In this study, performance expectancy indicates customer’s trust that using
mobile banking services will help them achieve better work performance (Venkatesh
et al, 2012).
H1: Performance expectancyhas positive impact on mobile banking use
intention
2.1.2 Impact of effort expectancyonuse intention
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In this study, effort expectancyis understood as expected effort related to the ease of
log-in and use of mobile banking service (Venkatesh et al, 2012)
In this study, individualism is understood as the extent to whichindividuals
emphasizetheir personal needs over collective needs and prefer individual actions
rather than bring as a group member (Srite, 2006)
H9.1: Individualists will have a positive perception of performance expectancy
when using mobile banking
H9.2: Individualists will have positive perception of effort expectancy when
using mobile banking
H9.3: Individualists will have positive perception of hedonic motivation when
using mobile banking
H9.4: Individualists will have positive perception of price value when using
mobile banking
2.2.2 Uncertainty avoidance
Uncertainty avoidance: is the degree to which the members of a culture feel
uncomfortable with uncertainty and ambiguity (Hofstede et al, 1980).
H10.1: Uncertainty avoidance has a positive relation withperception of
performance expectancy when using mobile banking
H10.2: Uncertainty avoidance has a positive relation with perception of trust
when using mobile banking.
H10.3: Uncertainty avoidance has a positive relation with perception of price
value when using mobile banking .
2.2.3 Masculinity
Masculinity is the extent evaluated as the focus, working goals, asseriveness,
efficiency and success contrary to a culture with lighter qualities (Hofstede et al,
1998).
H11.1: Masculinity has a positive relation withperception of performance
expectancy when using mobile banking
H11.2: Masculinity has a positive relation with perception of effort
expectancywhen using mobile banking
H11.3:Masculinity has a positive relation with hedonic motivation when using
mobile banking
H11.1: Masculinity has a positive relation withperception of price value when
using mobile banking
2.3 Age and gender
Test results show different impacts of age and gender on mobile banking use
intention. Age and gender all affect how people accept and adopt mobile banking.
Therefore, in the study, author tests age and gender according to the original model.
Hypothesesfor testing are:
H12.1 to H12.8: factors (in order according the model) having different
impacts on mobile banking use intention by gender ( male or female)
H2: Effort expectancyhas positive impact on mobile banking use intention
2.1.3 Impact of social influenceon use intention
In this study, social influenceis defined as the influence of other people to
personal perception which has big impact on mobile banking use(Venkatesh et al,
2012)
H3: Social influencehas positive impact on mobile banking use intention
2.1.4 Impact of facilitating conditions on use intentionand behavior
In this study, facilitating conditions are defined as the degree to which an
individual believes that organisational and technical infrastructure is available to
support the use (Venkatesh et al, 2012)
H4.1: Facilitating conditions has positive impact onmobile banking use intention
H4.2: Facilitating conditions has positive impact on mobile bankinguse behavior
2.1.5 Impact of hedonic motivation of use intention
In this study, hedonic motivation is defined as the pleasure of using mobile
banking and the perception of predicted usefulness (Venkatesh et al, 2012)
H5: Hedonic motivation has positive impact on mobile banking use intention
2.1.6 Impact of price value onuse intention
In this study, price value is considered the balance in customer perception
between the benefit brought about by mobile banking services and monetary cost to
use them(Venkatesh et al, 2012)
H6: Price value has positive impact on mobile banking use intention
2.1.7 Impact of trust on use intention
In this study, trust is understood as customer trust in banking transactions via
mobile banking (Ahamad et al, 2016).
H7: Trust has positive impact on mobile banking use intention
2.1.8 Impact of perceived privacy on trust and use intention
In this study, perceived privacy is understood as the degree of trust that an
organization will handle all transactions in a safe way and ensure personal privacy
(Roca et al, 2012).
H8.1: Perceived privacyhas positive impact on trust in mobile banking
H8.2: Perceived privacy has positive impact onmobile banking use intention
2.2 Cultural value
2.2.1 Individualism
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H13.1 to H13.8: factors (in order according the model) having different
impacts on mobile banking use intention by different group age .
2.4 Mobile banking use intention and behavior
Study hypothesis
H14: Use intention has positive impact on use behavior of mobile banking
4.2.2 Interview content
Via direct interview, the author summarizes main points and identifies factors
with the high rates of mention to consider putting them into the study model.
3.3 Preliminary quantitative study
3.3.1 Creating the questionnaire (developing the questionnaire)
After proposing the study model, the author identifies concepts, study
variables, and measurement scale of these variables. The measurement scale is
mainly based on original scales used in previous studies.
3.3.1.1 Identifying the measurement scale
3.3.1.2 Creating the preliminary questionnaire
3.4 Oofficial quantitative study
3.4.1Identifying study samples and survey method
* Sample size
* Survey objects
Survey objects are individuals who are using and who have not yet used mobile
banking. They use mobile phone and have transactions with commercial banks in
Vietnam.
The number of customers that have transactions in Vietnam is very large with
coverage in all cities and provinces nationwide. However, in this thesis, the author
focuses on studying individual customers as representatives for the North, the South,
and the Central region. Therefore, the survey sample includes 200 people living in the
North, 200 people living in the South, and 200 living in the Central region.
600 questionnaires are sent out. After the questionnaires are collected, the
author removes those that only choose 1 answer forall questions about perceived
level of factors in the model and those that do not have adequate data for analysis.
540 questionnaires are considered valid with 177 from the North, 170 from the South,
and 193 from the Central region.
* Data collection method
Questionnaires are sent directly to survey objects. The author sends
questionnaires to survey objects through family relatives and friends and also put
them at the banking transaction counter. Of all 160 questionnaires put at transaction
counters, 150 are valid. Of all 440 questionnaires that are directly surveyed at
residential areas (by a group of students), 390 are valid. 540 questionnaires are used
for analysis.
*Data collection period
From Oct 2017 to December 12/2017
3.4.2Data collection methods
After being collected, data are input into Excel to remove questionnaires that
lack data and only have 1 answer about perceived level of factors in the model . After
Figure 3.1: The study model proposed by the author
Source: the author’s proposal
CHAPTER 3: STUDY METHODOLOGY
3.1 Study procedures
The main method applied in the study is quantitative research method. It aims
to verify the model’s hypothesis; from that study results are evaluated and solutions
are recommended. However, before official quantitative study is carried out, the
author performs qualitative study to test the compatibility of the study model and
determine the official questionnaire for quantitative study.
Step 1: Identification of study issues
Step 2: Overview of study
Step 3: Preliminary study
Step 4: Official quantitative study
Step 5: Study results and recommendations
3.2In-depth interview
3.2.1 Objects and time of interview
Interview objects include 10 specialists in the banking sector, 10 customers
who are using mobile banking and 10 customers who have not yet used mobile
Time of interview: in July and August, 2017.
Interview method: Direct
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questionnaires are selected, the author uses SPSS software (version 20) to create the
database for analyzing factors, determining reliability level and for descriptive
statistics. The author also uses AMOS software (ver 20) exploratory factor analysis,
confirmatory factor analysis, and structural equation modelling.
• Exploratory Factor Analysis (EFA)
• Confirmatory Factor Analysis (CFA)
• Verification of the measurement scale’s reliability
• Structural Equation Modelling (SEM)
4.1.3 About legal basis
The current legal corridor for developing mobile banking service is still lacking
and incompatible the rapid with of digital banking. At present, there are a number of
documents in Vietnam, such as Decision No.35/2007/ND-CP on conduction banking
e-transactions., Circular dated Mar 08, 2007 of the governmenton banking etransactions, Circular No.31/2015/TT-NHNN about assurance of information systems
safety security in banking operations; Circular 35/2016/TT-NHNNon safety and
confidentiality over provision of banking services on the Internet, Law
86/2015/QH13 dated Nov 19, 2015 on Cyberinformation Security, Decree No.
35/2007/ND-CP of March 08, 2007 of the government on banking e-transaction,
Circular 35/2016/TT-NHNN on safety and confidentiality over provision of
banking services on the Internet, and draft decree on e-transaction in financial
activities is being discussed.
4.2 Research sample statistics
This part collects some results of data in the questionnaire with focus on
statistical description of information of survey participants.
CHAPTER4: STUDY RESULTS
4.1 Reality of mobile banking in Vietnam
4.1.1 History of establishment and development of mobile banking in Vietnam
Mobile banking was first carried out in Vietnam by Asia Commercial Joint
Stock Bank in 2003 in collaboration with VASC Software and Media company and
two mobile phone service providers MobiFone and VinaPhone ((Tran Thi Thanh
Phuong (2012) - abstract from the websitehttps://www.sbv.gov.vn). Banks in
Vietnam started to adopt this service from 2010. By now, most banks provide mobile
banking application (33 banks - table 4.1 - out of more than 40 commercial bank Việt
Nam (According to the websitehttps://www.sbv.gov.vn, as of June 30, 2018, the
systems of local joint stockcommercial bank, state-owned commercial bank and 100per cent foreign owned bank include 43 banks with 2710 branches and transaction
offices).
4.1.2 Reality of infrastructure and privacy
For applications that have been using in Vietnamese banks, attention is paid on
privacy issues. However, there are always risks for customers when using mobile
banking services, causing them to hesitate as follows:
- The operating system is outdated and has insecure connections.
- The anonymous feature allows criminals to steal accounts and use mobile
devices to access user accounts.
- Identifiable Information is stolen through transaction channels.
- Applications on mobile devices are attacked…
There is another issue occurs when running mobile banking applications in
Vietnam: the telecommunication network does not run smoothly. Network
congestion still happens a lot; many transactions are unsuccessful. When customers
access the software, the system displays error notice and failed transaction notice;
they perform transfer multiple times but get the same failed transaction notice.
Sometimes they cannot log into the system. There is delay in getting OTP messages
or getting notice of changes in account information…. Therefore, this is one of the
big hurdles for customers when they want to use mobile banking services.
37.0%
Chưa sử dụng mobile banking
63.0%
Đang sử dụng mobile banking
Figure: Ratio of customers using mobile banking
Source: Results of data analysis by the author
Table:Description of demographic characteristics
Frequency
Ratio (%)
Gender
Male
Female
Age
20 to 30
31 to 40
254
286
47
53
140
167
25,9
30,9
15
41 to 50
From 51 above
Educational evel
High school
College, university
Post-graduate
Other
Occupation
Student
Housewife
Free labor
Employee
Business
State officers
Teacher
Other
Living area
The North
The Central region
The South
Income
Under 5 million VND/month
5-10 million VND/month
10 to under 15 million/month
From 15 million/month
16
142
91
26,3
16,9
100.0%
87.4%
80.0%
68.2%
60.0%
120
247
161
12
22,2
45,7
29,8
2.2
51.5%
38.2%
35.6%
28.5%
40.0%
20.0%
14.4%
11.8%
8.5%
0.0%
29
5,4
95
75
86
88
64
56
47
17,6
13,9
15,9
16,3
11,9
10,4
8,7
32,8
193
170
35,7
31,5
50
9,3
170
31,5
196
36,3
124
23
Source: Synthesized by the author from survey data
4.3Customer perception of reason to use and not yet use mobile banking
2.4.1 Reason for using mobile banking
Tôi sử dụng mobile banking do người thân là cán bộ
ngân hàng vận động
Table 2.1: Reasons for using mobile banking of individual customer
Source: Synthezed by the author from survey data
2.4.2 Reasons why customers have not yet used mobile banking
100.0%
87.5%
Chưa hiểu rõ được tiện ích dịch vụ
Quy trình đăng ký phức tạp
80.0%
71.0%
Yêu thích sử dụng giao dịch truyền thống
60.0%
Sử dụng phức tạp (mật khẩu, mạng,…)
50.5%
46.0%
40.0%
Lo lắng lỗi kỷ thuật
32.5%
Lo lắng về bảo mật
18.0%
20.0%
177
Tôi sử dụng mobile banking vì có thể mua hàng trực
tuyến, thanh toán hóa đơn mua hàng
Tôi sử dụng mobile banking vì có thể nhận tiền kiều
hối từ nước ngoài
Tôi sử dụng mobile banking vì có thể thực hiện các
dịch vụ 24/7
Tôi sử dụng mobile banking vì được sử dụng nhiều
dịch vụ giá trị gia tăng của các nhà cung cấp
Tôi sử dụng mobile banking vì đơn vị trả lương có
thỏa thuận liên kết với ngân hàng
Tôi sử dụng mobile banking theo xu hướng, trào lưu
23.5%
18.0%
15.0%
0.0%
Chưa được ngân hàng giới thiệu
Không có nhu cầu sử dụng dịch vụ
Khác
Figure 2.3: Main reasons why customers have not yet used mobile banking
Source: Synthezed by the author from survey data
Through the reality of applying mobile banking, it is seen that privacy and trust
factors have significant impact on customer perception of mobile banking. This
shows not all factors in previous studies need to be considered in the context of
Vietnam.
4.4Analysis results of factors affecting mobile bankinguse intention and
behavior
4.4.1 Analysis ofreliability level of measurement scale with Cronbach’s
Alphacoefficient
After running Cronbach’s Alpha for the second time (and removing 7 ineligible
observation variables), it is shown that observation variables are eligible for further
analyses.
4.4.2Exploratory Factor Analysis (EFA)
Results of analyzing reliability shows HQKV3, GTCP3, NL1, SNT1, TKCC2,
NT3, CNCN4 variables are not eligible so they are not suitable for EFA and are
removed from the study model.
17
18
After performing EFA and initial evaluation of the measurement scale’s
reliability, the author edits and name factors as well as restate hypothesis as follows:
Factor 1: including observation variables HQKV1, HQKV2, HQKV4, GTCP1,
GTCP2. It reflects benefits that mobile banking users expect to receive both in terms
of work efficiency and finance. Therefore, this group of factors combines
performance expectancy and price value in the initial theoretical model into “benefit
expectancy” (LOIICH).
Factor 2:“Security and privacy” (BAOMAT) includes observation variables
BMRT1, BMRT2, BMRT3, BMRT4.
Factor 3: “Hhedonic motivation” (HEDONIC) includes observation variables
DLH1, DLH2, DLH3.
Factor 4: “Facilitating conditions” (THUANLOI) includes observation
variables DKTL1, DKTL2, DKTL3
Factor 5: “Usage intention” (YDSUDUNG)includes observation variables
ydinh1, ydinh 2, ydinh3
Factor 6: “Effort expectancy” (NOLUC)includes observation variables NL2,
NL3, NL4 and excludes observation variable NL1.
Factor 7: “Masculinity” (SUNAMTINH)includes observation variables SNT2,
SNT3, SNT4 and excludesobservation variable SNT1
Factor 8: “Social influence” (AHXAHOI)includes observation variables
AHXH1, AHXH2, AHXH3
Factor 9: “Uncertainty avoidance” (TRANHKCC)includes observation
variables TKCC1, TKCC3, TKCC4 and excludes observation variable TKCC2
Factor 10: “Trust” (NIEMTIN)includes observation variables NT1, NT2, NT4
and excludes observation variable NT3
Factor 11: “Individualism” (CNCANHAN)includes observation variables
CNCN1, CNCN2, CNCN3 and exludesobservation variable CNCN4
EFA shows that observation variablesensure convergent value and discriminant
value.
Due to changes compared to the original theoretical model, the author states
study hypothesis again.
The modified study model that is proposed in this thesis is:
Proposed study model after Exploratory Factor Analysis
4.4.3Confirmatory Factor Analysis (CFA)
Results of CFA show the study model is suitable with market information
(Figure 3.5). P-value of observation variables all have sig.=0,000; therefore it is
confirmed thatobservation variables perform wells for CFA .
*General compatible level
GFI, TLI, CFI values are all> 0,9; CMIN/df < 2, RMSEA < 0,05, indicating
that the model is condired very suitable with market data (Figure 4.9)
*Convergence value and unitary property
Standardized weights ( ) are all> 0,5 and unstandardized weights all have
statistical value .<0,000) so concepts achieve convergence value. This measurement
model is compatible with market data and there is no no relation among measurement
error so it achieve unitary properties.
*Discriminant value.
The correlation value of each pair of concept differs from 1 at reliability of
95% (P-Value =0,000); therefore concepts achieve discriminant value.
*Verification of the measurement scale’s reliability after CFA
Cronbach’s Alpha testing show the Cronbach’s Alpha coefficient of each factor
is>0,7, the general reliability and Average Variance Extracted of each factor are all >
0,5 (table 5.7). Therefore, factors in the model all ensure reliability.
Measurement results show the model achives consistency, reliability,
convergence value , and discriminant value; as a result it is entirely suitable for
Structural Equation Modelling.
4.4.4Structural Equation Modelling (SEM)
19
20
SEM analysis results show valuesTLI, GFI, CFI, RMSEA are all satisfactory
so the model is entirely compatible with market data and can be used test expected
relations mentioned in the hypothetical model.
Results of the model’s regression coefficient in the data table show a number of
factor with sig. > 0,05; therefore, these relations have no statistical significance.
Among factors affecting mobile banking use intention, “facilitating
conditions” has sig.= 0,084>0,5. On the other hand, the direct impact of
facilitating conditions has no statistical significance. As a result, this factor is
excludes from the model for testing SEM again.
In testing the impact of cultural factors, it is seen that “individualism” has no
impact on “hedonic motivation” (sig = 0.672)and “effort expectancy”.Therefore, the
author also excludes these impacts for testing SEM again.
Estimate*
HEDONIC
NOLUC
<--- SUNAMTINH
S.E.
C.R.
P
.208
.047
4.174
***
<--- SUNAMTINH
.114
.056
2.285
.022
YDINHSD
<---
LOIICH
.104
.030
2.589
.010
YDINHSD
<---
NOLUC
.152
.031
3.668
***
YDINHSD
<---
AHXAHOI
.255
.044
5.664
***
YDINHSD
<---
HEDONIC
.297
.038
6.981
***
YDINHSD
<---
NIEMTIN
.234
.054
4.784
***
YDINHSD
<---
BAOMAT
.343
.051
7.089
***
HVSUDUNG
<---
YDINHSD
1.000
.078
18.402
***
Estimate*: standardized Estimate
***: really have statistical significance
Figure 4.10Second test of Structural Equation Modelling
After removing relations with no statistical significance, results of SEM testing
show the remaining value all have sig. <0,05; therefore all relations have statistical
significance (Table4.11).
Table4.11: Regression model coefficient of second SEM test
Estimate*
NIEMTIN
<---
BAOMAT
S.E.
C.R.
P
.312
.053
5.549
***
.141
.057
2.906
.004
LOIICH
<--- TRANHKCC
LOIICH
<--- CNCANHAN
.109
.068
2.152
.031
LOIICH
<--- SUNAMTINH
.106
.055
2.189
.029
NIEMTIN
<--- TRANHKCC
.131
.040
2.516
.012
Source: Analysis of survey results
Test results show allstandardized weights are positive so relations in the model
have positive impacts. All sig values < 0,05 so they have statistical significance. This
matches with the proposed statistical hypothesis.
4.4.5Testing the impact of age and gender on impacting factors of mobile
banking use intention
4.4.5.1 Testing the age difference in impacting factors of mobile banking use
intention
Test results show that:
Regarding performance expectancy andeffort expectancy: people under 40
think that the better the performance expectancyandeffort expectancythey get, the
higher themobile banking use intention. However, people above 40 are not affected
by these factors.
Regardingeffort expectancy: young people (under 30) and those in the 41-50
range think the easier the use of mobile banking, the higher the mobile banking use
intention they have. Normally, they are people who start to access mobile banking
applications so they have expectations for this factor. Those in the range of 30-40 and
above 50 are not affected by this factor.
Regarding social influence: only people in the 40-50 range think that social
influencehas no impact on mobile banking use intention.
21
Regarding perceived privacy, hedonic motivation and social influence: there is
no difference in different age groups. People at any age understand the importance of
information privacy and hedonicmotivation formobile banking use intention.
4.4.5.2Testing the difference in gender for impacting factors of mobile banking
use intention
Test results show that gender only creates differences ineffort expectancy
andperformance expectancy. Male people think that the easier the use of mobile
banking, the higher the mobile banking use intentionbut female people are not
affected by this factor. Male people are not affected byperformance expectancybut
female people think the better the performance expectancy, the higher use intention
they have.
4.4.6Hypothesis conclusion
Here are the test results of hypotheses
Table4.14: the test results of hypotheses
No Hypothesis
Content
Result
Performance expectancyhas positive impact onmobile
Accepted
1
H1
banking use intention
Effort expectancyhas positive impact onmobile Accepted
2
H2
banking use intention
Social influencehas positive impact onmobile banking Accepted
3
H3
use intention
Facilitating conditionshas positive impact onmobile Rejected
4
H4.1
banking use intention
Facilitating conditionshas positive impact onuse Rejected
5
H4.2
behavior of mobile banking
Hedonic motivationhas positive impact onmobile Accepted
6
H5
banking use intention
Trusthas positive impact onmobile banking use Accepted
7
H6
intention
Perceived privacy has positive impact onon trust in Accepted
8
H7.1
mobile banking
Perceived privacyhas positive impact onmobile Accepted
9
H7.1
banking use intention
Individualists will have positive perception of Accepted
10
H8.1
performance expectancywhen using mobile banking
Individualists will have positive perception of effort Rejected
11
H8.2
expectancywhen using mobile banking
22
No Hypothesis
12
H8.3
13
H9.1
14
H9.2
15
H10.1
16
H10.2
17
H10.3
18
H11.1
19
H11.2
20
H11.3
21
H11.4
22
H11.5
23
H11.6
24
H11.7
25
H12.1
26
H12.2
27
H12.3
28
H12.4
Content
Individualists will have positive perception of Hedonic
motivationwhen using mobile banking
Uncertainty avoidance has a positive relation
withperception ofperformance expectancywhen using
mobile banking
Uncertainty avoidance has a positive relation
withperception oftrustwhen using mobile banking
Masculinityhas a positive relation with perception of
performance expectancywhen using mobile banking
Masculinityhas a positive relation with effort
expectancyof mobile banking
Masculinity has a positive relation with Hedonic
motivationof mobile banking
Performance expectancyaffecting mobile banking use
intention differs by age
Effort expectancyaffecting mobile banking use
intention differs by age
Social influenceaffecting mobile banking use intention
differs by age
Facilitating conditionsaffectingmobile banking use
intentiondiffers by age
Result
Rejected
Accepted
Accepted
Accepted
Accepted
Accepted
Accepted
Accepted
Rejected
Rejected
use
Rejected
Trustaffectingmobile banking use intentiondiffers by
age
Perceived privacyaffectingmobile banking use
intentiondiffers by age
Performance expectancyaffectingmobile banking use
intentiondiffers by gender
Effort expectancyaffectingmobile banking use
intentiondiffers by gender
Social
influenceaffectingmobile
banking
use
intentiondiffers by gender
Accepted
Facilitating conditionsaffectingmobile banking use
intentiondiffers by gender
Rejected
Hedonic motivationaffectingmobile
intentiondiffers by age
banking
Rejected
Accepted
Accepted
Rejected
23
No Hypothesis
29
H12.5
30
H12.6
31
H12.7
32
H13
Content
Hedonic
motivationaffectingmobile
useintentiondiffers by gender
24
banking
Trustaffectingmobile banking use intentiondiffers by
gender
Perceived privacyaffectingmobile banking use
intentiondiffers by gender
Result
Rejected
Rejected
Rejected
Mobile banking use intentionhas positive impact on Accepted
use behavior of mobile banking
Source: Study results of the author
CHAPTER 5: DISCUSION OF STUDY RESULTS AND
RECOMMENDATION OF SOLUTIONS
5.1 Discussion of study results
5.2 Suggestions to increase the number of customers using mobile banking
5.2.1 Increasing perceived privacy of customers
Study results show that perceived privacy is the factor with biggest impact on
mobile bankinguse intention. Survey results of reasons why customers have not yet
use mobile banking also indicate that worry about privacy issue is the main reason.
Information privacy related to mobile banking comes from three parties: the
banks, customers, and third party.
The banks need to implement a number of solutions, such as:
Firstly, increasing security methods
Secondly, enhancing woth ethics of banking officers
Thirdly, improving communication methods with customers who have not used
mobile banking about safety and privacy.
5.2.2Increasing the positive impact of social influence
Social influenceindicates the influence of people around the customers about
using mobile banking (relatives, friends...). Banks need to pay attention to this factor
to increase the number of potential users and increase the use level of existing
customers.
• Increasing communication methods
For customers who are using mobile banking., banks need to hold regular small
surveys about the actual benefit they perceive when using services.
Secondly, for people who have not yet used mobile banking, banks should
organize workshop to introduce mobile banking services.
• Enhancing service quality to gain better custom satisfaction
Banks need to create trust of existing customers by enhancing the quality of
mobile banking services. They should rarely let errors occur. In case of errors, bank
need to solve them in a timely and quick manner. Transactions need to be done
quickly anytime. When service quality is improved and customers are satisfied, when
will share will friends and relatives.
5.2.3 Building customer trust
5.2.4. Improving customer’seffort expectancy and hedonic motivation
5.2.5. Increasing performance expectancy
5.2.6 Having appropriate marketing strategies for target customer groups
CONCLUSION
This study systemizes the theoretical basis of factors affectingmobile banking
use intention. It inherits and further develops the Unified Theory of Acceptance and
Use of Technology(UTAUT) (which is considered superior to other theories on
behavioral intention). With the context of study in Vietnam, the study points out that
“facilitating conditions” (in UTAUT) have no impact onuse intentionand proves that
“perceived privacy” and “trust” affect mobile banking use intention. In addition, the
thesis evaluates the impact of the demographic factor (age, gender) on use
intentionfor each factor by SEM analysis. On the basis of identifying the impact level
of each factor and different impact of age and gender, the author suggests a number
of suitable solutions for commercial banks in Vietnam.
This study has limitations because survey is done in the urbanarea and select
representatives for the North, the South and Central region; study sample has not
have high representativeness. The author has yet studied factors with direct impact on
mobile banking use or considered the mobile banking market share of banks in
Vietnam. These will serve as directions for further studies.