Chapter 3: Literature Review
3. Constructs of the model
3.1. Perceived usefulness
Perceived usefulness is known as performance expectancy when people think that based on advantages of innovation, information technology (IT) can help them enhance productivity and aid work performance (Davis, 1989; Davis, 2007).
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Liao and Cheung (2002) in their study about electronic banking measured perceived usefulness in a multi dimension with vast variables such as transaction speed, use-friendliness, user experience, accuracy, convenience, etc.
The importance of perceived usefulness has been widely recognized in technology adoption in past study. Jeyaraj et al. (2006) in their review of technology adoption studies from 1992-2003, found that of the 29 studies on technology adoptions, perceived usefulness was found to have significant influence on the user‟s intention to adopt and technology.
Perceived usefulness is also one of the common factors applied in existing electronic banking study. Guriting and Ndubisi, 2006; Laforet and Li, 2005; Liao and Cheung, 2002 have approved the significant effect of perceived usefulness on adoption intention, where perceived usefulness is known as advantage of innovation over existing banking channels. Pikkarainen et al, 2004, in their study of online banking in Finland, found that perceived usefulness is one of the most significant influence on the intention to use online banking among the consumers. Moreover, Polatoglu and Ekin, 2001 pointed out the greater the perceived usefulness of using electronic banking service, the more likely that electronic banking will be adopted. Evidently, Luarn and Lin (2005) examined that perceived usefulness has significant impact in the development of initial willingness to use mobile banking.
This study found that Davis‟s definition of perceived usefulness most applied where perceived usefulness means that the application is found available and helpful for customer at anytime and anyplace, allowing them to conduct their needed banking services more efficiently and encourage them to take part in more banking transactions.
22 3.2. Perceived ease of use
Perceived ease of use is defined as “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989). Innovative technology system that is perceived to be easier to use and less complex will have a higher likehood of being accepted, and used by potential user (Davis, 1989). Besides perceived usefulness, perceived ease of use has also been validated as important determinant in adoption of a lot of information technologies, such as intranet (Chang, 2004), WWW (Lederer, Maupin, Sena, & Zhuang, 2000), online banking (Wang, Wang, Lin, & Tang, 2003), and wireless internet (Lu, Yu, Liu, & Yao, 2003). Rogers, 1995 also pointed out that the complexity of one particular system will discourage the adoption of an innovation.
Consult (2002) noted that perceived ease of use refers to the ability of consumers to experiment with a new innovation and evaluate its benefits easily. He also affirmed that the drivers of growth in electronic banking are determined by the perceived ease of use which is a combination of convenience provided to those with easy internet access, the availability of secure, high standard electronic banking functionality, and the necessity of banking services.
In Vietnam, as (Hoang, 2003) pointed out, Vietnamese users have little experience in using the internet and therefore the ease of use of the online banking web site might influence their adoption decision. According to Thatcher & Perrewe, 2002, the ease of use of a new system is perceived differently among different level of knowledge and age of user where high education and young users are not hesitated to try a new IT system while low education or older users find IT systems complicated.
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This study define perceived ease of use as degree who people learn about using and come to utilize mobile banking in their daily life without paying too much effort. We will try to investigate the extent to which perceived ease of use determined user‟s intention and usage of mobile banking service. At the same time, we will also investigate the positive effect of perceived ease of use on perceived usefulness.
3.3. Perceived risks
Perceived risk‟s origin was back into 1960 when .Bauer firstly introduced the concept of perceived risks as a combination of uncertainty plus serious of outcome involved (R. Bauer, 1960). So far, perceived risk has been applied in many researched on consumer behavior and developed multi- dimension construct where risks are divided into financial, psychological, physical and social loss (Featherman & Pavlou, 2003;SM & B., 2003; J & L.B, 1972; Lu, Yu, Liu,
& Yao, 2003). However, the separation perceived risks into sub dimensions was agued to be lack of accuracy and perceived risk is over all difficult to capture because it‟s very individual subjective (Wang, Wang, Lin, & Tang, 2003).
However, none of study has refused the role of risk on consumer‟s decision to adopt a new technology. In more relevant research about internet banking, perceived risk has been approved as an important attitudinal factor that influences adoption behavior and mainly focuses on transaction security risk or privacy risk (Kim & Prabhakar, 2004; Laforet S, 2005; Polatogu &
Ekin, 2001). According to Yiu,, Grant, & Edgar, 2007, using e-payment customers always concern about the transaction process and perceived threats to privacy and personal information leak. Similar in mobile banking service, for each time using mobile banking, users has to depend of their trust on either banks or mobile network and other content providers. Therefore, we believe that perceived risk is very important variable which critically influences on consumer‟s
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adoption decision, while perceived risk will be measured from the perspective that includes two main concerns: transaction stability and personal information (Wang, Wang, Lin, & Tang, 2003;
Yiu, Grant, & Edgar, 2007).
In our study, referring to Pillarainen‟s research, four items measuring people‟s trust on transaction stability and the protection of personal information were designed.
3.4. Facilitating conditions
Facilitating conditions refer to how an individual believes an existing infrastructure would support his or her use of the information system (Venkatesh, Morris, Davis, & Davis, 2003).
Thompson, Higgins, and Howell (1991) proposed that facilitating conditions could be an important factor impacting technology acceptance and usage.
Previous study measured facilitating conditions in two main dimensions including technology support and government support. Goh , 1995 suggests that, as supporting technological infrastructures become easily and readily available, Internet commerce applications such as banking services will also become more feasible. Goh‟s study also suggested that the government can play an intervention and leadership role in the diffusion of innovation. The greater the extent of perceived government support for electronic commerce, the more likely that Internet banking will be adopted.(Tan & Teo, 2000).
In more recent research (Crabbe, Standing, & Standing, 2009) again supported that acilitating conditions and demographic factors also have obvious effects on mobile banking adoption in Ghana.
We do think that support from both technological infrastructure and government is critical for mobile banking adoption since it involved multi-players who are taking different roles in the
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game. Facilitating in our study will cover user‟s technology condition itself, the support from two main players which are banks and telecommunication companies and the legal support from government.
3.5. Personal innovativeness in information technology
Personal innovativeness was referred in Rogers‟ research (1983) as an important factor which decide why some individual are by their nature are more willing to take risk of trying innovation why others are suspicious of new idea and hesitant to change their current practice (Rogers, 1983). More recently studies segment potential adopters of innovation into innovators, early adopters, early and late majority adopters and laggards (Rao & Troshani, 2007; Yi & Park, 2006).
The segmentation in potential adoption is decided by demographical factors, social influence, personality and the involvement of media (Hoyer & Maclnnis, 2008).
Previous study added personal innovativeness in technology as a direct construct to TAM model which resulted in the conclusion that higher PIT higher positive intention to use new system (Lu, Hsu, & Hsu, 2005). However some other researches considered PIT as a moderator that can moderates the impact of perceived belief of use on technology usage (Agarwal & Prasad, 1998;
Ndubisi, 2005).
Since we view mobile banking as a disruptive technology innovation which fills in the niche that internet banking and physical bank service leave to deliver to customer the convenient connectivity and mobility, personal innovativeness logically will influence on user‟s adoption decision. In this study, responding to Agawal and Prasad‟s findings, we adopt personal innovativeness as a moderator and discuss the impact of demographic factors on PIT.
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Chapter 4. Research Design and Methodology
1. Conceptual model design
Literature review has shown the relationship between constructs where perceived usefulness, perceived ease of use, perceived risk and facilitating has direct influence on mobile banking use.
There are extensive research provides evidence of significant effect of usefulness on behavioral intention and usage (Davis F. , 1989; Hu, Chau, Sheng, & Tam, 1999; Jackson, Chow, & Leitch, 1997; Venkatesh & Morris, 2000). The ultimate reason people exploit mobile banking systems is that they find them useful.
Prior studies have also shown that there is a positive relationship between perceived ease of use and usage intention (Guriting & Ndubisi, 2006); (Luarn, P., & Lin, 2005; Wang, Wang, Lin, &
Tang, 2003; Kleijnen & Wetzels, 2004; Ramayah, Dahlan, Mohamad, & Ling, 2003). At the same time, perceive ease of use will increase degree of perceived usefulness.
Perceived risk has been historically found to have negative effect on users‟ intention to adopt a new technology (Suh & Han, 2002; Doney & Cannon, 1997). In a study of online banking (Aladwani, 2001) potential customers ranked internet security and customer‟s privacy as the most important future challenges that banks are facing. Similar hypothesis about negative influence of perceived risk on user‟s intention and usage is proposed here.
Regarding to facilitating condition which covers both technology conditions and government support, it is proposed to have positive effect on consumer‟s intention and usage.
The moderating effects of personal innovativeness in technology on relationship between constructs are also included in hypothesis tests.
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In summary, this research proposes the following hypotheses:
H1: Perceived ease of use has a positive impact on behavioral intention to use mobile banking
H2: Perceived usefulness has a positive impact on behavioral intention to use mobile banking H3: Perceived risk has a negative impact on behavioral intention to use mobile banking
H4: Facilitating conditions has a positive impact on behavioral intention to use mobile banking H5: Perceived ease of use has a positive impact on perceived usefulness
H6: Perceived risk has a negative impact on perceived usefulness
H7: Behavioral intention has positive effect on mobile banking use H8: Perceived ease of use has a positive impact on mobile banking usage
H9: Perceived usefulness has a positive impact on mobile banking usage H10: Perceived risk has a negative impact on mobile banking usage
H11: Facilitating conditions has a positive impact on mobile banking usage
H12a: Personal innovativeness has a moderation effect between perceived ease of use and mobile banking usage
H12b: Personal innovativeness has a moderation effect between perceived usefulness and mobile banking usage
H12c: Personal innovative has a moderation effect between perceived risks and mobile banking usage
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H12d: Personal innovativeness has a moderation effect between facilitating conditions and mobile banking usage
H12e: Personal innovativeness has a moderation effect between behavioral intention and mobile banking use
Figure 4: Conceptual model 2. Construct measurement
2.1. Questionnaire design
There seven constructs to be examined in this study: (1) Perceived usefulness (PU), (2) Perceived ease of use (PEU), (3) Perceived risk (PR), (4) Facilitating conditions (FC), (5) Personal innovativeness in technology (PIT), (6) Behavioral intention (BI) and (7) Mobile banking usage (USE). This study applied multiple items to measure those constructs. Seven point Likert was used to all question items of first five constructs, ranging from strongly disagree (1) through neutral (4) to strongly agree (7).
Perceived ease of use
Perceived usefulness
Perceived risk
Facilitating condition
Behavioral intention
Actual usage Personal innovativeness in technology
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Behavior intention and Mobile banking use are surveyed directly by asking which item of mobile banking service respondents intend to use or have been using.
Other sections of the questionnaire were designed to investigate respondent‟s banking behavior, their understanding status of mobile banking service providing currently in Vietnam and demographic information.
2.2. Pilot study
A pilot study was undertaken using an array of people that included two MBA students, two material science Ph.D students, a former bank employee, two free traders. Such a diverse group was chosen, as cell phone users are many and diverse. The main purpose of the pilot was to ensure the questionnaire adequately addressed the relevant issues, that it was easy to understand, the sequence of questions were reasonable, and that it had been professionally compiled. The participants were asked to fill in the questionnaire, and add any other comments on how the questionnaire could be improved.
After the pilot study, wording of the questionnaire and additional introduction about mobile banking at the beginning of the survey were revised and added.
3. Data processing
Google online survey provides detail time stream of respondents as well as a spreadsheet of all responses. The spreadsheet was later coded for easier analysis.
One point would be given for each item of service that respondent chosen indicating their behavioral intention of using mobile banking service. The range of measurement is from 1 to 8.
Mobile banking usage was coded depending respondent‟s chosen items under question 1 of section 3- Mobile banking.
30 None of item was chosen: non-user (coded as 0) 1 till 2 items were chosen: mild user (coded as 1)
3 till 4 items were chosen: medium user (coded as 2) 5 items and above were chosen: heavy user (coded as 3)
Data was processed by IBM SPSS statistic version 19.
4. Data analysis procedure
Figure 5: Data processing procedure Data coding
Characteristics of respondents
Discriptive statistics, Pearson Chi-Square test (confident level=95%)
Construct reliability (Cronbach's alpha=0.7)
Hypothesis test
Linear regression (confident level= 95%)
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Chapter 5. Data analysis and results
1. Data collection
The questionnaire items of this study were revised from previous researches and took 5 weeks to collect, starting from March 7th to April 15th of 2011. Questionnaires using double translating method were translated into Vietnamese to make it easier to respondents.
A web-based survey using Google form was created and sent through email, msn, yahoo messenger to researcher‟s 30 friends in Vietnam, mostly in Hanoi and Ho Chi Minh City. At the same time, said 30 friends were asked to distribute the questionnaire to their colleagues or classmates. The final number of response for this study up till April 15th was 159 with no missing data.
2. Characteristics of respondents
The attributes of respondents consist of five major control variables including (1) age, (2) gender, (3) education level, (4) job position and (5) income. The table bellow shows the profile of respondents:
Table 3: Characteristic of respondents and mobile banking users
Mild user Medium user Heavy user
Do not adopt mobile banking
Chi-Square sig.
Frequency Percentage Frequency Percentage Frequency Percentage Frequency Percentage
Gender
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The table does not show much different percentage between male and female respondents (52%
and 48%), with majority are between 18 to 30 years old, followed by those of thirty to forty years old. Seventy percent of the respondents have on in the process to get bachelor diploma while 29%
respondents has higher master or doctorate degree.
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Students occupied more than half of observations (54%), the rest are working as employee in a company (33%) and some are running their own business. Fifty seven people, equally to thirty six percent of the respondents have no income since they are still college or graduate students.
Half of the respondent has monthly income less than 500 USD, with 30% has more than 200 USD. More than ten percent of ten percent of the respondents (14%) has relative high income in Vietnam urban community (from 500 to 1000USD). More than half of the observations have been using mobile phone for over 5 years; the rest has at least 1 year using experience.
The characteristics of mobile banking users were identified by examining the relationship between the respondent‟s demographic profiles and whether they adopt mobile banking service.
Pearson Chi-Square with confident level of 95% was employed to test the variance of usage of population under demographic variables. It was found that there is no difference in mobile banking usage among population in term of gender, age and education level (p-values are higher than 0.05). However, employment position and income status indicated significant variance in population usage (p-value are lower than 0.05). Mobile banking is observed to be most popular among students and company employees, with monthly income lower than 500USD. The possible explanation is that students and company employees are also target group of internet transaction (www. Saigonmoney.com)
1. Mobile banking usage status
1.1. Rate of adoption
The survey enquired whether the respondents have used mobile banking and how often they use it to obtain the current rate of adoption of mobile banking. The result showed relative higher adoption rate (44.02%) than previous report from media (13%). It could be biased by the sampling group who are mainly young people (91% of respondents are younger than 30).
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However this penetration rate is still much lower than in other developing countries as China, Philippines, India…
1.2. Types of banking services performed through mobile phone
Table 4: Types of mobile banking service Types of mobile banking services Usage rate
Account inquiry 34%
Enquiry information about interest rate, exchange rate, stock market…
16%
Money transfer 15%
Recharge for prepaid mobile subscribers 31%
Telephone, internet bills payment 8%
E-commerce transaction payment 10%
Check transaction details 18%
The table listed 2 types of mobile banking transaction being performed by mobile banking users.
Account balance inquiry and recharge for prepaid mobile subscribers are the most commonly used banking services on mobile with more than 30% user having performed this kind of transaction. Other commonly used services include financial information inquiry, transaction detail inquiry and money transfer which are also most popularly performed through internet banking or ATM.
1.3. Advantages and disadvantages of mobile banking
Respondents were requested to point out advantages and disadvantages of mobile banking transaction. The results showed that the possibility of performing banking service anywhere, anytime, saving time and travel cost are the most important advantages that respondents see in mobile banking. In contrast, more than 50% of respondents think that the security concerns,
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instability of mobile network and “Not everybody‟s phone is facilitated to use mobile banking”
are the main inhibitors of adoption of mobile banking in Vietnam.
2. Constructs reliability
Reliability test was applied to observe and verify the internal consistency analysis, following the main criterion of the rule of thumb developed by Hair et al., (2006).
Table 5: Cronbach's Alpha results
TAM research construct Number of items Cronbach's Alpha
Perceived Ease of Use (PE) 5 0.914
Perceived Usefulness (PU) 4 0.922
Perceived Risk (PR) 4 0.842
Facilitating Condition (FC) 4 0.929
Personal Innovativeness in Technology (PIT) 3 0.79
Questionnaire items to measure perceived ease of use (PE) were retrieved from Davis, 1996;
Venkantesh, 2000; Wang, 3003. Davis, 1996 and Karahanna, 2006 are the main reference for questionnaire measuring perceived usefulness. Questionnaire about perceived risks were referred from Pikkaraimen, 2004. Reference paper for facilitating conditions is Crable et al, 2009.
Personal innovativeness in technology is measured by questionnaire learnt from Agawar, 1998 and lu et al., 2005.
Cronbach's alpha is well known as an internal consistency estimate of reliability of test scores.
Because intercorrelations among test items are maximized when all items measure the same construct, Cronbach's alpha is widely believed to indirectly indicate the degree to which a set of items measures a single unidimensional latent construct.
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According to Hair et al., (2006) and other researches, Cronbach‟s alpha is recommended to be at least 0.70, indicating high reliability. The reliability test results above show very high Cronbach‟s alpha (from 0.79 to 0.922), representing strong internal consistency between five different identified constructs. All five constructs will be kept for further analysis.
3. Hypothesis tests
3.1. Relationship between TAM constructs
3.1.1. Direct effect of TAM constructs on Behavioral Intention
Linear regression test with confident level of 95% took place in examining the linear relationship
Linear regression test with confident level of 95% took place in examining the linear relationship