## 4 Analysis of Results
### Discriminant Validity  
The square of the coefficient of the covariation relationship constructed by the two constructs is compared with the variance extraction amount (AVE) of the two constructs. All the squares are less than the variance extraction amount, indicating discriminant validity; if not, there may be no difference.  
As seen in Table 8, the comparison of perceived ease of use for perceived usefulness, usage attitude, behavioral willingness, and transaction security shows that perceived ease of use is different from others; perceived usefulness is related to usage attitude, behavioral willingness, transaction security, the results show that the perceived usefulness is different from others; the use attitude is different from behavioral willingness and transaction security, the results show that the use attitude is different from others. Finally, behavioral willingness is compared to transaction security, the results show that there is a  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Construct** & **Factor** & **Chronbach’s \(\alpha\)** \\ \hline PEOU 1 think it is easy to learn how to use proximity mobile payment. & \\ PEOU 2 I think it is easy to use proximity mobile payment to complete my tasks. & \\ PEOU 3 To me, proximity mobile payment is easy to understand. & 0.939 \\ PEOU 4 I think proximity mobile payment is flexible to use. & \\ PEOU 5 It is easy for me to become familiar with using proximity mobile payment. & \\ PU1 The use of proximity mobile payment can improve the convenience of my life and work. & \\ PU2 By using proximity mobile payment, I can complete payments faster. & \\ PU & PU3 Proximity mobile payment improves my efficiency when making payments. & 0.939 \\ PU4 Proximity mobile payment makes payments easier. & \\ PU5 Proximity mobile payment can improve the quality of my life and work. & \\ ATT I think it is a good idea to use proximity mobile payment. & \\ ATT2 I think proximity mobile payment is a good payment tool. & \\ ATT3 I think proximity mobile payment is an intelligent idea. & \\ ATT4 I think proximity mobile payment is an advanced idea. & 0.949 \\ ATT5 I think proximity mobile payment is valuable to me. & \\ ATT6 Overall, I’m willing to use proximity mobile payment. & \\ BI1 In the future, I will use proximity mobile payment instead of other payment methods. & \\ BI2 In the future, I will use proximity mobile payment often. & \\ BI & BI3 In the future, proximity mobile payment will become part of my daily life. & 0.959 \\ BI4 In the future, I will recommend others to use proximity mobile payment. & \\ BI5 In the future, I will encourage friends and family to use proximity mobile payment. & \\ TS I think customer data can securely transfer through proximity mobile payment. & \\ TS2 I think proximity mobile payment has a good reputation for security. & \\ TS3 I think proximity mobile payment has a good design for payment security protocols. & \\ TS4 I think proximity mobile payment contains state-of-the-art technologies available to & 0.977 \\ protect transactions. & \\ TS5 I think proximity mobile payment provides security protection in the shopping process. & \\ TS6 I think proximity mobile payment contains appropriate encryption and privacy & \\ protections are in place to ensure successful transactions. & \\ \hline \hline \end{tabular}
\end{table}
Table 6: CFA of perceived usefulness.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Construct** & **Combined Reliability** & **Average Variance Extraction** \\ \hline PEOU & 0.9397 & 0.7578 \\ PU & 0.9410 & 0.7623 \\ ATT & 0.9492 & 0.7579 \\ BI & 0.9598 & 0.8270 \\ TS & 0.9590 & 0.7579 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Combined reliability and average extraction of variance values for each dimension.  
difference between behavioral intention and transaction security, so this study meets the criteria of discriminant validity, and through the AVE comparison, it is determined that the measurement models have discriminant validity.