Analysis Results 1/ Efa Analysis Results


APPENDIX


APPENDIX 1: SURVEY FORM


Dear Sir/Madam.

I am: NGUYEN THI NGOC DIEM, a PhD student at the University of Commerce. Currently, I am implementing my thesis topic " State management of non-cash payment services in domestic payments of Vietnamese commercial banks ". To accurately and objectively assess the current situation, thereby researching and proposing solutions to improve state management of non-cash payment services in domestic payments of Vietnamese commercial banks, I look forward to receiving your opinions on these issues by answering the questions in the survey.

I assure you that the information in the survey will be kept confidential and used for research purposes only.

Thank you very much!


A. RESPONDENT INFORMATION:

INFORMATION RECORDED ON THE INVESTIGATION FORM IS COMMITTED TO BE KEEP CONFIDENTIAL

Full name of the informant: ………………………………………………………………… Address:………………………….………………………………………………. ………… District:……………… …………… City/Province………………………………………… Phone:……………………………………. Email……………………………………… Please fill in the appropriate box about the information below:

Occupation: Not yet employed Civil servant, public employee Worker, employee Self-employed Other

Age: Under 20 21-30 31-40 41-50 Over 50

Gender: Male Female

Graduated: Junior high school College/University Postgraduate Average monthly income:

Under 5 million VND From 5-10 million From 10-20 million From 20-40 million Over 40 million VND

Maybe you are interested!

Analysis Results 1/ Efa Analysis Results


B. SURVEY INFORMATION:

Question 1: Which of the following non-cash payment methods (KDTM) have you ever used for payment activities?

1. Check


5. Mobile Banking/SMS Banking


2. Payment authorization


6. Internet Banking


3. Collection authorization


7. E-wallet


4. Card


8. No/not used yet (only answer question 4)



For questions about level of agreement, please choose by circling 1 appropriate level (With level 5 being Completely agree and level 1 being Completely disagree)


Question 2: Please let us know your opinion when using KDTM payment methods via bank:

Main reasons why you use MLM payments

Level of agreement

Save time when shopping, spending, paying

5

4

3

2

1

Pay service fees quickly, conveniently, anytime, anywhere

5

4

3

2

1

No need to worry about running out of cash or small change when paying for goods and services

5

4

3

2

1

It's safer to not have to carry a lot of cash on you.

5

4

3

2

1

The State has a policy to encourage e-commerce payment when using public services.

5

4

3

2

1

The State has preferential policies on taxes and fees to encourage e-commerce payments.

5

4

3

2

1

The State is constantly improving the legal framework for e-commerce payments.

5

4

3

2

1

The State has a policy of investing in technological infrastructure for the development of e-commerce payments.

5

4

3

2

1

Higher payment discount than using cash

5

4

3

2

1

More shopping promotions than using cash

5

4

3

2

1

Easy access to promotional information from major, reputable brands

5

4

3

2

1

Easily accumulate points and enjoy incentives for traditional customers

5

4

3

2

1

Widespread ATM system, fast, convenient and stable operation

5

4

3

2

1

Websites that accept online payments are diverse, convenient, and safe.

5

4

3

2

1

Devices supporting safety in e-commerce payments are increasingly diverse and convenient.

5

4

3

2

1

Mobile payment applications are diverse, abundant, and work well.

5

4

3

2

1

The facilities of commercial banks serving e-commerce are modern, well-functioning and stable.

5

4

3

2

1

The team of commercial bank staff supporting KDTM payment is reliable, dedicated and thoughtful.

5

4

3

2

1

Diverse online banking applications, stable operation

5

4

3

2

1

The customer support system for KDTM payment of commercial banks operates well and stably.

5

4

3

2

1


Question 3: Please let us know your opinion after using the following payment methods for MLM via bank:

Satisfaction, willingness to use MLM payments in the future

Level of agreement

Always ready to use MLM payment services when shopping and spending

5

4

3

2

1

Really satisfied with using KDTM payment services

5

4

3

2

1

Will definitely continue to use e-commerce payment services of commercial banks and enterprises.

5

4

3

2

1

Question 4: Please give your opinion on the factors that hinder the development of e-commerce payment services in domestic payments through commercial banks:

Major concerns when making MLM payments

Level of agreement

Issues regarding personal information security, property and income safety

5

4

3

2

1

Issues regarding the authenticity of buyers, sellers, goods and services

5

4

3

2

1

Issues of complaints and legal disputes

5

4

3

2

1

Technological and technical issues delay payment operations.

5

4

3

2

1

Thanks again for your help!


APPENDIX 2: RESEARCH MODELS

(1) Theory of Reasoned Action (TRA)

The Theory of Reasoned Action (TRA) was developed in 1967 and revised and expanded over time from the early 1970s by Ajzen and Fishbein (1980). The TRA model shows that consumer propensity is the best predictor of consumer behavior. To pay more attention to the factors contributing to purchase propensity, consider two factors: customer attitude and subjective norm. In the TRA model, attitude is measured by perception of product attributes. Consumers will pay attention to attributes that provide necessary benefits and have different levels of importance. If the weight of those attributes is known, it is possible to predict the consumer's choice results.

Subjective norms can be measured through people related to the consumer (such as family, friends, colleagues, etc.); these people like or dislike the consumer's purchase. The level of impact of subjective norms on the consumer's purchase tendency depends on: (1) the level of support/disapproval for the consumer's purchase and (2) the consumer's motivation to follow the wishes of the influential people. The degree of influence of related people on consumer behavioral trends and the motivation for consumers to follow related people are two basic factors for evaluating subjective standards. The stronger the degree of intimacy of related people to consumers, the greater the influence on their purchase decisions. The greater the consumer's trust in the relevant people, the greater the influence on their purchasing tendency. Consumers' purchasing intention will be affected by these people with different levels of influence.

Behavioral trends

Subjective standard

TRA theory is modeled as follows:


Belief in product attributes

Attitude

Measuring beliefs about product attributes

Real behavior


Beliefs about what influencers think I should or shouldn't buy the product


Measuring beliefs about product attributes

Source: Fishbein and Ajzeп, 1975


Figure 1: TRA Theory


In the theory of reasoned action model, each individual consumer's belief about a product or brand will influence the attitude towards behavior, and the attitude towards behavior will influence the tendency to buy but not directly influence the behavior. Therefore, attitude will explain the reason leading to the consumer's shopping tendency, and the tendency is the best factor to explain the consumer's behavioral tendency.

Advantages: The TRA model is similar to the three-component attitude model, but this model combines the three components: cognitive, affective, and dispositional components, which are arranged in a different order than the three-component attitude model. The way attitudes are measured in the TRA model is also similar to the multi-attribute attitude model. However, the TRA model explains more details than the multi-attribute model because it adds the subjective norm component.

Disadvantages: The Theory of Reasoned Action is limited in predicting the performance of consumer behaviors over which they have no control because the model ignores the importance of social factors which in fact may be a determinant of individual behavior (Grandon & Peter P. Mykytyn 2004; Werner 2004).

Social factors mean all the influences of the environment surrounding individuals that can influence individual behavior (Ajzen 1991); factors of attitudes toward behavior and subjective norms are not enough to explain consumer actions.

(2) Theory of Planned Behavior (TPB)

The theory of planned behavior (TPB) (Ajzeп, 1991), developed from the theory of reasoned action (TRA; Ajzeп& Fishbeinп, 1975), assumes that a behavior can be predicted or explained by behavioral tendencies to perform that behavior. Behavioral tendencies are assumed to include motivational factors that influence the behavior, and are defined as the level of effort that people exert to perform that behavior (Ajzeп, 1991). Behavioral tendencies are a function of three factors. First, attitudes are conceptualized as positive or negative evaluations of the behavior to be performed. The second factor is social influence which refers to the perceived social pressure to perform or not to perform the behavior. Finally, the Theory of Planned Behavior (TPB) was developed by Ajzen by adding the factor of perceived behavioral control to the TRA model. The perceived behavioral control component reflects the ease or difficulty of performing the behavior; this depends on the availability of resources and opportunities to perform the behavior.


vi. Ajzeп proposed that behavioral control factors directly influence the tendency to perform a behavior, and if the subject is accurate in his or her perception of his or her level of control, then behavioral control also predicts behavior.

TPB theory is modeled as follows:



Behavioral trends

Attitude

Standard owner

Real behavior

Controlling emotional behavior

Source: (Ajzen, 1991),

Figure 2: TPB Theory

Advantages: The TPB model is considered to be more optimal than the TRA model in predicting and explaining consumer behavior in the same research content and context. Because the TPB model overcomes the disadvantages of the TRA model by adding the element of perceived behavioral control.

Disadvantages: The TPB model has some limitations in predicting behavior (Werner, 2004). The first limitation is that the determinants of intention are not limited to attitudes, subjective norms, perceived behavioral control (Ajzen 1991). There may be other factors that influence behavior. Based on empirical research, it is found that only 40% of the variation in behavior can be explained by using the TPB (Ajzen 1991; Werner 2004). The second limitation is that there may be a significant time gap between the assessment of behavioral intentions and the actual behavior being assessed (Werner 2004). Over time, an individual's intentions may change. The third limitation is that the TPB is a predictive model that predicts an individual's actions based on certain criteria. However, individuals do not always behave as predicted by the criteria (Werner 2004).

(3) Technology Acceptance Model (TAM)

The emergence of new technologies and utilities related to cashless payments in recent years has become increasingly popular. One of the useful tools in explaining the intention to accept new cashless payment technology products and services is the technology acceptance model (TAM). The TAM model successfully predicted about 40% of the adoption of a new system.


APPENDIX 3: ANALYSIS RESULTS 1/ EFA ANALYSIS RESULTS

Rotated Component Matrix a


Component


1

2

3

4

5

6

7

8

9

Issues of complaints and legal disputes

,875









Issues regarding the authenticity of buyers, sellers, goods and services

,819









Technological and technical issues are holding up payment operations.


,807









Issues regarding personal information security, property and income safety


,766









Websites that accept online payments are diverse, convenient, and safe.



,901








Widespread ATM and POS system, fast, convenient and stable operation


,880








The State has a policy of investing in technological infrastructure for the development of e-commerce payments.



,540








Save time when shopping, spending, paying



,932







No need to worry about running out of cash or small change when paying for goods and services




,928







Devices supporting secure payment in e-commerce are increasingly diverse and convenient.





,784






Mobile payment applications are diverse, rich, and work well.





,637






HTM staff support KDTM payment reliably, dedicatedly, thoughtfully





,583






The State has preferential policies on taxes and fees to encourage e-commerce payments.






,769





The State is constantly improving the legal corridor for e-commerce payments.






,717





More shopping promotions than using cash







,700




Higher payment discounts than using cash






,647





Rotated Component Matrix a


Component


1

2

3

4

5

6

7

8

9

It's safer not to have to carry a lot of cash on you.






,578




The facilities of the e-commerce service center are modern, well-functioning and stable.








,736



Easily accumulate points, enjoy incentives for traditional customers








,703



Easy access to promotional information from major, reputable brands








,498



Diverse online banking applications, stable operation








,862


PKTM's customer payment support system is working well and stably.









,609


The State has a policy to encourage e-commerce payment when using public services.










,759

Pay service fees quickly and conveniently anytime, anywhere










,483


2/RESULTS OF TEST ON RELIABILITY OF FACTORS

F1 test: Cronbach's alpha = 0.853 > 0.6 so the scale meets the standard.

Reliability Statistics

Cronbach's Alpha


П of Items

,853

4

Item-Total Statistics



Scale Mean if Item Deleted


Scale Variance if Item Deleted

Corrected Item-Total Correlatioп

Croпbach's Alpha if Item Deleted

Issues regarding personal information security, property and income safety


6.66


8,568


,624


,841

Issues regarding the authenticity of buyers, sellers, goods and services


7.14


8,348


,683


,817

Issues of complaints and legal disputes

6.94

7,575

,783

,773

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