Student e-wallet usage intention questionnaire (TAM)

Intention to use e-wallets (MoMo, ZaloPay, ShopeePay...) is one of the most common thesis topics at business schools. This template uses the technology acceptance model (TAM), compact enough for an undergraduate thesis and easy to extend with variables such as trust or perceived risk.

Research model

Model based on TAM (Davis, 1989): perceived ease of use affects perceived usefulness, and both lead to intention to use.

• Perceived Ease of Use → Perceived Usefulness (positive)
• Perceived Usefulness → Behavioral Intention to Use (positive)
• Perceived Ease of Use → Behavioral Intention to Use (positive)

Questionnaire items

Original English wording. Answered on a 5-point Likert scale (1 = Strongly disagree … 5 = Strongly agree) unless the scale page says otherwise; (R) marks a reverse-coded item.

Perceived Ease of Use (PEOU) · Technology Acceptance Model (TAM) scale

Code	Item
PEOU1	Learning to operate [system] would be easy for me.
PEOU2	I would find it easy to get [system] to do what I want it to do.
PEOU3	My interaction with [system] would be clear and understandable.
PEOU4	I would find [system] to be flexible to interact with.
PEOU5	It would be easy for me to become skillful at using [system].
PEOU6	I would find [system] easy to use.

Source: Davis (1989). See Technology Acceptance Model (TAM) scale.

Perceived Usefulness (PU) · Technology Acceptance Model (TAM) scale

Code	Item
PU1	Using [system] in my job would enable me to accomplish tasks more quickly.
PU2	Using [system] would improve my job performance.
PU3	Using [system] in my job would increase my productivity.
PU4	Using [system] would enhance my effectiveness on the job.
PU5	Using [system] would make it easier to do my job.
PU6	I would find [system] useful in my job.

Source: Davis (1989). See Technology Acceptance Model (TAM) scale.

Behavioral Intention to Use (BI) · Technology Acceptance Model (TAM) scale

Code	Item
BI1	Assuming I have access to the system, I intend to use it.
BI2	Given that I have access to the system, I predict that I would use it.

Source: Venkatesh & Davis (2000). See Technology Acceptance Model (TAM) scale.

Tips

• The Intention to use construct has only 2 items; committees often ask about reliability, so consider adding items from Venkatesh et al. (2003) and cite the source.
• The six original PU items refer to 'job'; this template rewrites them for payments and spending and keeps the original items for comparison. State the adaptation in Chapter 3.
• Most students already use e-wallets, so the 'If I had access...' wording suits them less. For existing users, consider replacing BI with continuance intention (CI) from the ECM model in the library.
• The meta-analysis by King and He (2006) shows that perceived usefulness usually predicts intention more strongly than perceived ease of use; this is a good basis for your hypotheses in Chapter 2.

Work out the minimum sample size for this model; once the data are in, clean the responses and run the survey data analysis for your results chapter.

Studies that used this model

• To and Trinh (2021). Understanding behavioral intention to use mobile wallets in Vietnam: Extending the TAM model with trust and enjoyment. Cogent Business & Management, 8(1), 1891661. Sample: 332 e-wallet users (37.3% students); TAM plus trust and enjoyment. Reliability: α 0.841-0.904; CR 0.844-0.906 (Table 2).
• Nguyen and Nguyen (2023). An investigation of students' intention to use E-payment service in Mobile Wallet in Ho Chi Minh City. Tạp chí Nghiên cứu Tài chính – Marketing, 14(6), 96–106. Sample: 310 students in Ho Chi Minh City; TAM plus trust and convenience; SmartPLS. Reliability: .
• Nguyen, Cao, Dang and Nguyen (2016). Predicting Consumer Intention to Use Mobile Payment Services: Empirical Evidence from Vietnam. International Journal of Marketing Studies, 8(1), 117. Sample: 489 consumers in Hanoi; combined TAM and TPB; regression. Reliability: α 0.752-0.912 (Table 1).

Collecting responses

If your own network cannot reach the target respondents, you can pay for verified responses through Genius Data (referral link, we may earn a commission), paying only for approved responses.