VIETNAM NATIONAL UNIVERSITY HO CHI MINH CITY INTERNATIONAL UNIVERSITY
Topic: Factors Affecting Vietnamese People’s Intention to Use MOMO
BA080IU_1: Statistics for Business_S1_2023-24_G01
Lecturer: Dr. Nguyen Hoang Phu Ho Chi Minh City, 2024 Group Members No. Name Student ID Contribution 1 Nguyễn Quang Minh BABAIU22586 100% 2 Tống Trần Ngọc Minh BABAWE20067 0% 3 Nguyễn Minh Thanh Nga BAACIU20137 100% 4 Nguyễn Hoàng Bảo Ngọc FAFBIU22253 100% 5 Nguyễn Hồng Nhung FAFBIU22146 100% 6 Nguyễn Hoàng Oanh BABAWE18578 100% 7 Trần Gia Phúc BABAUH21043 100% 8 Ngô Quỳnh Trúc Phương FAFBIU22155 100% 9 Nguyễn Trần Thảo Quyên BAFNIU21556 100% 10 Lại Nữ Hạnh Tâm FAFBIU22166 100% 11 Nguyễn Đức Thịnh BABAIU22403 100% 12 Trần Huỳnh Thuận BABAIU22613 100% Thank you
To be able to complete this project “Research on Affective Factors on Vietnamese People's Intention to use
ewallet”, we would like to send our deep thanks to:
Dr. Nguyen Hoang Phu – lecturer of the subject “Statistics for Business”, has provided us with a lot of useful
knowledge about this subject so that we can make the most of what we have learned. Go into practice and complete
the survey. At the same time, the teacher enthusiastically guided, answered questions as well, and gave many
suggestions throughout the process to guide and help the group's project be more complete.
Thank you to all participants for taking the time to complete the survey so that the team has a rich and diverse
data source to serve the project.
The members of group 3 (Stat_Thu_456) have always tried, united, and cooperated from the beginning of the idea
until the project was completed. Hopefully, after the project, we will learn a lot of useful knowledge that, will
support us in future subjects and projects.
Due to limited knowledge and experience, our group still has many errors. We look forward to receiving your
feedback so that the group can have conditions to correct, supplement, and better complete projects. Sincerely, Table of Content
1 INTRODUCTION .................................................................................................................................................................................5
2 LITERATURE REVIEW .....................................................................................................................................................................5
2.1 TERMS AND GLOSSARY .....................................................................................................................................................................5
2.2 RESEARCH MODEL ............................................................................................................................................................................6
3 METHODOLOGY ................................................................................................................................................................................7
3.1 RESEARCH METHODOLOGY ..............................................................................................................................................................7
3.2 DATA COLLECTION PROCESS .............................................................................................................................................................7
4 DESCRIPTIVE STATISTICS ..............................................................................................................................................................8
4.1 GENDER ............................................................................................................................................................................................8
4.2 AGE ..................................................................................................................................................................................................8
4.3 WORKING STATUS .............................................................................................................................................................................8
4.4 CENTRAL TENDENCY MEASUREMENT ...............................................................................................................................................8
4.5 VARIATION MEASUREMENT ..............................................................................................................................................................9
4.6 SUMMARY.........................................................................................................................................................................................9
5 INFERENTIAL STATISTICS ..............................................................................................................................................................9
5.1 CONFIDENCE INTERVAL ....................................................................................................................................................................9
5.2 HYPOTHESIS TESTING .....................................................................................................................................................................10
5.3 ANOVA ANALYSIS ......................................................................................................................................................................... 11
5.4 REGRESSION ANALYSIS ................................................................................................................................................................... 11
6 CONCLUSION ....................................................................................................................................................................................12
7 REFERENCES ....................................................................................................................................................................................13 Abstract
There is a vast market for e-wallets in Vietnam. The Vietnamese people are rapidly embracing digitization, making
e-payment a vital part of their lives. Hence, e-wallet companies are increasingly popping up, and they're thriving in the
market. To increase their portion in the market, banks as well as emerging players are intensely competing to provide
better e-wallet services. The purpose of this research is to explore the various elements that may affect Vietnamese
people's decisions to use the MOMO digital payment system.
The sample size for the study is 146 MOMO e-wallet users. The research method that was employed in the study
was quantitative. The conceptual research framework is the theoretical model which is based on the Technology
Acceptance Model and the Unified Theory of Acceptance and Use of Technology on e-wallet. The factors are evaluated to
form a hypothesis. According to the study, the use of electronic payment through MOMO is influenced by three factors:
perceived usefulness (PU), social influence (SI) and mobility (MO). To improve the customer experience and speed up the
growth of electronic payments in Vietnam, the MOMO e-wallet has been analyzed in terms of its practical applications
and suggestions for improvement.
As per the study, the researchers give guidance on intermediary payments. It would be great if the government
collaborated with financial organizations to motivate people to use digital payments more often. Vietnam plays an
important part in moving its economy forward technologically. Key findings: e-wallet, electronic wallet, behavioural intention 1 Introduction
The digital revolution has redefined payment landscapes, with e-wallets emerging as potent challengers to traditional
methods. This burgeoning market, estimated to reach a staggering $567.2 billion by 2032, thrives on convenience, security,
and a fundamental shift in how we interact with money (Stars, 2023). In Vietnam, this digital wave has propelled MoMo to
prominence, boasting over 31 million users and dominating the e-wallet space (MoMo website, 2024). With their inherent
digital fluency and preference for mobile solutions, Gen Z has embraced e-wallets as a primary payment tool, reshaping
their buying behavior in a profound way.
In the field of digital finance, the Momo e-wallet has attracted much attention from experts, whose reviews contribute
to a deep understanding of how Momo develops an electronic payment system. Jeffrey Perlman - the Board of Directors
for the US-ASEAN Business Council, have mentioned that with the high internet penetration rate in Vietnam, a rapidly
growing middle-class population, and a strong push for a cashless economy, MoMo is believed to has the opportunity to
win the mobile payments market and replicate the growth story of the top mobile platforms in Asia (Warburg-Backed
Vietnam E-Wallet Raises $100 Million - BNN Bloomberg, 2021)
The primary focus of the project will revolve around examining how mobility, perceived usefulness and social
influence impact the intention to use Momo on the Vietnamese people. This comprehensive study aims to delve into the
intricacies of this issue by addressing key questions such as:
1. How does perceived usefulness influence intention to use Momo?
2. To what extent does social influence affect the adoption of this e-wallet?
3. How does mobility factor into the usage and influence of Momo within the Vietnamese community? 2 Literature review 2.1 Terms and glossary
To further clarify the issue that needs to be researched, we would like to propose some concepts that need to be clearly
stated during the data analysis process based on the documents the group found combined with the group's opinions. Term Definition References E-wallet • •
An E-wallet is a form of an electronic card that may be used for making Aji & Adawiyah
transactions online using a computer or a smartphone. (2021) •
It functions similarly to a credit or debit card. For transactions, an ewallet • Kumar et al (2019)
must be associated with a valid bank account
Highlighted the effect of factors: perceived ease of use (PEU) and perceived • Davis (1989) Technology
usefulness (PU) of technology, influencing attitudes towards • King & He, Acceptance the usage of technology. (2006). Model (TAM)
The original foundation of TAM is the psychology theory of reasoned Chhonker et al.
action, which explains the behavior. (2017)
TAM used the two predictors of perceived usefulness and perceived Yousafzai et al.
ease of use to make decisions. (2007) Behavioral
The intention is a factor used to evaluate the ability to perform a Ajzen, (1991) intention
behavior in the future. The intention is a motivating factor; it motivates
an individual to be willing to perform the behavior and is influenced by
it directly by attitudes, subjective norms, and perceived behavioral
control. Behavioral intention is assumed to be an intermediate
antecedent of behavior, and research on intention to use is a good predictor of usage behavior
Perceived usefulness is "the degree to which a person's belief in using Davis, (1989)
a particular system enhances their job performance". Perceived Venkatesh et al., usefulness (2003) Social influence Kotler & Brady,
Customers often consider the advice of their friends, family, coworkers, (2009)
and other members of their social networks (consumer groups, Venkatesh et al.,
professional organizations, and other relationships linked with their (2003)
life) when evaluating their alternatives and making a purchase decision.
Social influence is “the degree to which an individual thinks they should
use the new system - in this case, an electronic wallet”.
Mobility is defined as the ability to access service and complete Kalinic and Mobility
financial transactions at any time, in any location. Marinkovic (2015)
Table 1: Definition of terminilogy 2.2 Research model
By applying this theoretical model - the Technology Acceptance Model (TAM), a model that has been widely used
in research on technology acceptance; this report has applied and developed a new model as follow: with Perveiced
Usefulness (PU), Social Influence (SI), Mobility (MO) are the independent factors; while Decision to use (D) is the dependent factor. Figure 1: The research model 3 Methodology 3.1 Research methodology
Our team used quantitative research methods through an online questionnaire survey on factors affecting young
people's decision to use MOMO (e-wallets) in Ho Chi Minh City. It uses a numerical approach to measure and
classify features before turning data into useful statistics. The ability to gather a large amount of data and maintain
a balance between the goals and conclusion are two advantages of using this approach (Kotler and Keller, 2006;
Hallowell, 2011). A crucial aspect of quantitative methods is the use of probability models to assess statistical
hypotheses connected to research issues and surveys to collect data (Harwell, 2011). 3.2 Data collection process
The survey will be used as the method for gathering data in this study. The use of an online questionnaire helped
the researchers capture responses systematically in a standardized manner. It was therefore designed to be highly
customizable with well-organized recorded data that could also be interpreted in real time using the online survey
tool - Google Form. As it was a study that took place in Vietnam, the preliminary was written in both English and Vietnamese.
To develop the questionnaire, our team searched for relevant documents, selected, consulted, and built a set of
preliminary evaluation criteria, thereby establishing a survey questionnaire for the research article of our group.
Scale is needed to measure variables accurately, so different variables were selected with appropriate scales. The
variables are applied on a 5-level Likert scale as follows: 1 – Strongly dissatisfied 3 – Neutral
5 - Strongly satisfied 2 – Dissatisfied 4 – Satisfied
After implementation and editing, the group agreed and proposed a set of questions as described below: Factor Observed variables Content Perceived Usefulness PU
Using MOMO helps me make transactions easier than before. Social influence SI
I use MOMO because everyone around me uses it. Mobility MO
I can use MOMO easily, as long as I always carry my phone with me.
Table 2: Questions based on 5-point Likert scale
After 2 weeks, a total of 146 responses were received.
The observation was eliminated if: 1.
The respondent participated in the survey more than once. 2. Incomplete response.
As there are no responses that have any problems mentioned above, all 146 responses are taken into analysis. 4 Descriptive statistics 4.1 Gender
There is a difference in the ratio between male and Gender
female participating in the survey. 59% of survey
respondents were female, and 41% of survey respondents were male.
Figure 2: Quantitative chart based on gender 41 % 4.2 Age 59 %
In general, the majority of respondents participating Age
in the survey were between the ages of 18 and 21,
accounting for 57%. The next age group is between 60 % 57 %
26 and 29 years of age accounting for less than a
fifth and with the lowest representing groups greater 50%
than or equal to 36 which accounts for only 3%. Male Female 40 % 30 % 20 % 15 % 12 % 13 % 10 % % 3 0%
18 - 21 22-25 26 - 29 30 - 35 >=36
Figure 3: Quantitative chart based on age group 4.3 Working status
Of the total 146 survey participants, 77 were Working Status
employed and 69 were student/unemployed. Of
which, the percentage of employed people is 6%
higher than student/unemployed, specifically,
employed people account for 53% and
student/unemployed account for 47% of the total number of people surveyed. 47 % 53 % Employed Student/Unemployed
Figure 4: Quantitative chart based on employment status
4.4 Central tendency measurement Perceived usefulness (PU) Social Influence (SI) Mobility (MO) Mean 4,1 3,6 4,0 Median 4,0 4,0 4,0 Mode 5,0 3,0 5,0
Table 3: Table of Central tendency measurement
In general, the mean of SI being above 3 (neutral point on a 1-5 scale), PU and MO being above 4. Along with a
moderate mean, people intend to agreed more with PU and MO than SI. The mode of both 3 factors PU, SI, MO being
above 3 of 5 scale likert. Overall, Vietnamese people indicate a generally positive sentiment about the statement that the
perceived usefulness (PU), social influence (SI) and mobility (MO) affect Vietnamese people's decisions to use the MOMO digital payment system. 4.5 Variation measurement Perceived usefulness (PU) Social Influence (SI) Mobility (MO) Standard deviation 0,9 1,0 0,9
Table 4: Table of Variation measurement
Vietnamese users perceive perceived usefulness (PU), social influence (SI) and mobility (MO) indicated by their
standard deviations of 0.9 - 1.0. Of which reflects highly positively significant role of perceived usefulness (PU), social
influence (SI) and mobility (MO) factors influencing Vietnamese’people intention to use MOMO 4.6 Summary
E-wallet is a vast market that is defined as the golden field for companies to empower their dominance. And Momo,
an online payment platform with 20 million Vietnamese users (Long, 2023), is known as an indispensable candidate for the
throne. This report aimed to examine and generalize the vital role of three factors: perceived usefulness (PU), social
influence (SI), and mobility (MO) in affecting Vietnamese attitudes towards using MOMO. By analyzing 146 users, the
feedback is positive towards all three factors, with the means and medians exceeding 3 (a neutral point on a 5-point Likert
scale). However, slight differences in standard deviations reflect the differing opinions of MOMO’s users. These
independent factors were strategic: While perceived usefulness helps to create user satisfaction, social influence can deal
with community pressure and mobility shows the ease of mobile payments, which are the important factors associated with
influencing Vietnamese people's intentions to use MOMO. These interrelationships can empower MoMo to refine its
platform, tweak marketing strategies, and utilize its dominance in the Vietnamese digital payment revolution.
5 Inferential statistics 5.1 Confidence interval
With 95% confidence interval, confidence coefficient is (1 - α) = 0.95, so α = 0.05 -> α/2 = 0.025 Looking
up the Z table, we get Zα/2 = 1.96
Data from Data Analysis of Excel
Using MOMO helps me make transactions easier than before. (PU) Mean 4,12 Standard Deviation 0,88
Table 5: Factor analysis for Perceived Usefulness
- Interval estimate: 4.12 ± 1.96 x
= 4.12 ± 0.14 => [3.98; 4.26] •
Conclusion: With 95% Confidence interval, we get the confidence interval is between 3.98 pounds and 4.26 pounds. If
we randomly participants out of 146, there will be 95% fall into between range 3.98 and 4.26 tend by Perceived Usefulness.
I use MOMO because everyone around me uses it. (SI) Mean 3,62 Standard Deviation 1,04
Table 6: Factor analysis for Social Influence
- Interval estimate: 3.62 ± 1.96 x
= 3.62 ± 0.17 => [3.45; 3.79] •
Conclusion: With 95% Confidence interval, we get the confidence interval is between 3.45 pounds and 3.79 pounds. If
we randomly participants out of 146, there will be 95% fall into between range 3.45 and 3.79 tend by Social Influence.
I can use MOMO easily, as long as I always carry my phone with me. (MO) Mean 4,05 Standard Deviation 0,93
Table 7: Factor analysis for Mobility (MO)
- Interval estimate: 4.05 ± 1.96 x
= 4.05 ± 0.15 => [3.9; 4.2] •
Conclusion: With 95% Confidence interval, we get the confidence interval is between 3.9 pounds and 4.2 pounds. If
we randomly participants out of 146, there will be 95% fall into between range 3.9 and 4.2 tend by Mobility. 5.2 Hypothesis testing
We use a rating scale from 1 to 5 according to the rater's satisfaction level
1 – Strongly dissatisfied 3 – Neutral 5 - Strongly satisfied
2 – Dissatisfied 4 – Satisfied 5.2.1 For population mean
If participants choose 3 or more, it means Momo helps them make transactions easier (PU). Mean N SDV Confidence Z-statistic Z-critical interval 4.12 146 0.88 95% 15.2798 1.64
Table 8: Hypothesis testing for mean
- Null Hypothesis (H0): There is a significant difference that using Momo does not make it easier for people to trade before.
- Alternative Hypothesis (H1): There is a significant difference that using Momo helps them make transactions easier.
- Test: Use z-test to compare the convenience or inconvenience of using Momo. •
Based on the z-test results, we can make the following conclusions:
- Statistical Test (Two-Sample, Z-Test Assuming Unequal Variances): The z-statistic is approximately 15,2798,
and the P-value one tail: 5.4*10-53 • Decision:
- Since the one-tailed p-value (5.4*10-53 ) is less than α= 0.05, we have enough evidence to reject the null
hypothesis (H0) that using Momo does not make it easier for people to trade before. • Interpretation:
- There is not enough evidence to conclude that there is a significant difference in the mean of the topic. The data
does not provide sufficient support to reject the null hypothesis, suggesting that the observed difference in
means is likely due to random variability. •
Summary: Based on the provided z-test results, we do not find
significant evidence to support a difference in the average of using
Momo helps them make transactions easier. 5.2.2 For population proportion.
If participants choose 3 or more, that means everyone can use MOMO easily, as long as everyone has their phone with them at all times.
Topic: Assuming that 50% of people always have a phone, so using MOMO is simple for everyone. In sample 146, there were 80 people doing this. π N SDV Confidence Z-statistic Z-critical Level of interval significant 0.5 146 0.93 95% 1.208 1.64 0.05
Table 9: Hypothesis testing for proportions
- Null Hypothesis (H0): As long as everyone always has a phone with them, there is a substantial difference in
the amount of people who find it easy to utilize MOMO — less than 50%.
- Alternative Hypothesis (H1): There is a significant difference that more than 50% people can use MOMO easily,
as long as everyone has their phone with them at all times.
- Test: Use z-test to compare the decision to use of people. •
Based on the t-test results, we can make the following conclusions:
- Sample proportion: p=80/146=0.55.
- 95% CI => α = 0.05 - The critical value for confidence interval with one-tail testing is 1.64.
- Statistical Test (Two-Sample, Z-Test Assuming Unequal Variances): The z-statistic is approximately Z-test
(1.208) < Z-critical (1.64). • Decision:
- Since the Z-test (1.208) < Z-critical (1.64), we have enough evidence to accepted the null hypothesis (H0), and
the alternative hypothesis (H1) is rejected that more than 50% people can use MOMO easily, as long as everyone
has their phone with them at all times. • Interpretation:
- There is not enough evidence to conclude that there is a significant difference in the mean of the topic. The data
does not provide sufficient support to reject the null hypothesis, suggesting that the observed difference in
means is likely due to random variability. •
Summary: There is evidence to conclude that there is a significant
difference in mean values, and that this difference is not due to chance. 5.3 ANOVA analysis Source of variation SS df MS F P-value F crit Between Groups 17,7534 1 17,7534 18,977 0,0000184 3,8737 Within Groups 271,3014 290 0,9355 Total 289,0548 291
Table 10: ANOVA analysis 1 - The inspection results of Perceived Usefulness (PU) and Social influence (SI)
- In the first one-way ANOVA table that analyzes the two variables, “Perceived Usefulness” and “Social
Influence”, we observe that the “P-value” is less than 0.05. Upon considering the 'F' and 'Fcritical' values, we
find that F higher than Fcrit, indicating that these two variables are independent and unrelated. Source of variation SS df MS F P-value F crit Between Groups 0,3425 1 0,3425 0,4144 0,5203 3,8737 Within Groups 239,6849 290 0,8265 Total 240,0274 291
Table 11: ANOVA analysis 2 - The inspection results of Perceived Usefulness (PU) and Mobility (MO)
- Conversely, in the second ANOVA table, we notice that the value of F is less than Fcrit and P-value is more
than 0.05, confirming that these two variables are not independent and are related to each other. All of the above
suggests that "Mobility" and "Perceived Usefulness" are not different and should be disregarded.
Conclusion: “Perceived Usefulness” and “Social Influence” are two independent variables therefore these variables are
completely usable to run the regression in the linear regression model. 5.4 Regression analysis
A linear regression model can be used by building a regression model with Decision to use (D) as the dependent variable,
the opposite was true for Perceived Usefulness, Social Influence, Mobility as the independent variables. Here is the formula for the regression model:
D = β0 + β1Es + β2Fo + ɛ In which:
β0: intercept, represents the value of the dependent variable when all independent variables are zero. Es: Perceived
Usefulness (PU) Fo: Social Influence (SI) ɛ: error term, often called residuals, represent the difference between the actual
value of the dependent variable and the value predicted by the model. Multiple R 0.324851799 R Square 0.105528691 Adjusted R Square 0.093018603 Standard Error 0.13557119 Observations 146
Table 12: Regression statistics Coefficients Standard Error T Stat P-value Lower 95% Upper 95% Intercept 0.741 0.059 12.512 0.000 0.624 0.858 Perceived 0.026 0.011 2.346 0.02 0.004 0.047 Usefulness (PU) Social 0.036 0.012 2.953 0.004 0.012 0.06 Influence (SI)
Table 13: Regression analysis for Perceived Usefulness (PU) and Social Influence (SI) •
Based on the result from regression analysis: - P- value < 0.05
- Social Influence coefficient = 0.036 -
Perceived Usefulness coefficient = 0.026 In this regression model:
- Social influence (SI) represents the independent variable, which is assumed to have an impact on the user's
decision to use MOMO. The positive coefficient (0.036) with a low p-value (0.02) shows a statistically
significant positive relationship between FOMO and users' decision to use MOMO. Specifically, with each unit
increase in SI, users' decision to use MOMO is predicted to increase by 0.036. This supports that SI is related
to users' decision to use MOMO.
- Perceived usefulness (PU) represents the independent variable, which is assumed to have an impact on the user's
decision to use MOMO. The positive coefficient (0.026) with a low p-value (0.004) shows a statistically
significant positive relationship between PU and users' decision to use MOMO. Specifically, with each unit
increase in PU, users' decision to use MOMO is predicted to increase by 0.026. This supports that PU is related
to users' decision to use MOMO. •
Conclusion: Perceived usefulness (PU) helps MOMO save time for users when
paying for purchases. Customers do not need to bring cash and wallet when
shopping, they just need to carry their phone. Regarding Social Influence (SI), it
contributes to creating a community, making it easy for people to transact with each
other. This proves Perceived usefulness (PU) and Social Influence (SI) affects users' decisions to use MOMO. 6 Conclusion
In conclusion, the comprehensive analysis of the various elements that may affect Vietnamese people's decisions to
use the MOMO and the specific examination of 146 selected MOMO users reveal positive feedback toward three factors:
perceived usefulness (PU), social influence (SI), and mobility (MO). However, regarding to ANOVA analysis, the
Mobility (MO) and Perceived Usefulness (PU) are not different then need to be disregarded.
The detailed data analysis emphasizes the importance of perceived usefulness in creating user satisfaction, social
influence to deal with community to influent Vietnamese people's intentions to use MOMO. This insight helps MOMO
refine marketing, develop features, and potentially bridge demographic gaps to expand its reach.
As we conclude this report, it's crucial to recognize the indispensable role of two factors: perceived usefulness (PU)
and social influence (SI) in affecting Vietnamese attitudes towards using MOMO and the need for continuous research to
improve the customer experience and speed up the growth of electronic payments in Vietnam. 7 References
1. Aji, H. M., & Adawiyah, W. R. (2021). How E-wallets encourage excessive spending behavior among young adult
consumers? Journal of Asia Business Studies.
2. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes.
3. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly.
4. Chhonker, M. S., Verma, D., & Kar, A. K. (2017). Review of technology adoption frameworks in mobile commerce. Procedia Computer Science.
5. Kalinic, Z. & Marinkovic, V. (2015). Information System and e-Business Management.
6. King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management.
7. Kotler, P., & Brady, M. (2009). Marketing management. Pearson Education.
8. Kumar, R., Le, D.-N., Mishra, B. K., Chatterjee, J. M., & Khari, M. (2019). Cyber Security in Parallel and
Distributed Computing: Concepts, Techniques, Applications and Case Studies. John Wiley & Sons.
9. Long, L. V. (2023b, October 19). Ai là chủ sở hữu của “siêu ứng dụng” ví MoMo? Cộng Đồng Kinh Doanh Việt
Nam. https://vietnambusinessinsider.vn/ai-la-chu-so-huu-cua-sieu-ung-dung-vi-momo-a11705.html
10. Stars, D. (2023, December 28). A business analyst’s take on the E-Wallet expansion.
https://www.linkedin.com/pulse/business-analysts-take-e-wallet-expansion-django-stars-wmbwf/?trk=article-
ssrfrontend-pulse_more-articles_related-content-card
11. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology:
Toward a unified view. MIS Quarterly, 425 – 478.
12. Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2007). Technology acceptance: a meta analysis of the TAM: Part
1. Journal of Modelling in Management.