Continuance Usage Intention toward E-Payment during the COVID-19 Pandemic from the Financial Sustainable Development Perspective Using Perceived Usefulness and Electronic Word of Mouth as Mediators
Abstract
:1. Introduction
2. Literature Review and Hypotheses Development
2.1. Technology Acceptance Model
2.2. Health Belief Model
2.3. Security and Perceived Usefulness
2.4. Perceived Seriousness, Perceived Usefulness, and Continuance Usage Intention
2.5. Perceived Seriousness and Electronic Word of Mouth
2.6. Perceived Usefulness and Electronic Word of Mouth
2.7. Security, Electronic Word of Mouth, and Continuance Usage Intention
2.8. Perceived Usefulness and Continuance Usage Intention
2.9. Electronic Word of Mouth and Continuance Usage Intention
3. Research Method
3.1. Questionnaire Design
3.2. Sample Characteristics
3.3. Reliability and Validity Analysis
4. Research Results
4.1. Structural Equation Modeling
4.2. Verification of the Hypothesis Results
4.3. Mediation Effect Analysis
5. Conclusions
5.1. Theoretical and Practical Implications
5.2. Managerial Implications
6. Limitations and Future Research Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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N | % | |
---|---|---|
Gender | ||
Male | 214 | 55.3 |
Female | 173 | 44.7 |
Total | 387 | 100.0 |
Age | ||
18–24 y | 48 | 12.4 |
25–34 y | 44 | 11.4 |
35–44 y | 95 | 24.5 |
45–54 y | 108 | 27.9 |
55–64 y | 87 | 22.5 |
Over 65 y | 5 | 1.3 |
Total | 387 | 100.0 |
Education | ||
General and vocational high school or below | 13 | 3.4 |
Bachelor | 195 | 50.4 |
Master | 162 | 41.9 |
PhD | 17 | 4.4 |
Total | 387 | 100.0 |
Occupation | ||
Student | 42 | 10.9 |
Professionals | 58 | 15.0 |
Business services | 168 | 43.4 |
Soldiers, civil servants, and teachers | 70 | 18.1 |
Manufacturing | 35 | 9.0 |
Administrative associate | 14 | 3.6 |
Total | 387 | 100.0 |
E-payment usage frequency during the COVID-19 pandemic | ||
10 times or less | 145 | 37.5 |
11–20 times | 92 | 23.8 |
21–30 times | 46 | 11.9 |
31–40 times | 41 | 10.6 |
41–50 times | 16 | 4.1 |
51 times or more | 47 | 12.1 |
Total | 387 | 100.0 |
Increase in usage after COVID-19 | ||
Yes | 294 | 76 |
No | 93 | 24 |
Total | 387 | 100 |
Construct | Item | Model Parameter Estimates | Item Reliability | Residuals | Convergent Validity | |||||
---|---|---|---|---|---|---|---|---|---|---|
Unstd. | S.E. | t-Value | p | Std. | SMC | 1-SMC | CR | AVE | ||
SECU 2 | SECU1 | 1 | 0.705 | 0.497 | 0.503 | 0.929 | 0.687 | |||
SECU3 | 1.371 | 0.084 | 16.366 | *** 1 | 0.863 | 0.745 | 0.255 | |||
SECU4 | 1.161 | 0.081 | 14.278 | *** | 0.751 | 0.564 | 0.436 | |||
SECU5 | 1.523 | 0.093 | 16.335 | *** | 0.873 | 0.762 | 0.238 | |||
SECU6 | 1.54 | 0.093 | 16.536 | *** | 0.89 | 0.792 | 0.208 | |||
SECU7 | 1.447 | 0.089 | 16.243 | *** | 0.872 | 0.760 | 0.240 | |||
PU 2 | PU2 | 1 | 0.795 | 0.632 | 0.368 | 0.936 | 0.746 | |||
PU3 | 1.249 | 0.062 | 20.256 | *** | 0.88 | 0.774 | 0.226 | |||
PU4 | 1.221 | 0.062 | 19.858 | *** | 0.871 | 0.759 | 0.241 | |||
PU5 | 1.228 | 0.06 | 20.616 | *** | 0.902 | 0.814 | 0.186 | |||
PU6 | 1.184 | 0.06 | 19.616 | *** | 0.866 | 0.750 | 0.250 | |||
PER 2 | PER1 | 1 | 0.707 | 0.500 | 0.500 | 0.870 | 0.577 | |||
PER2 | 1.259 | 0.079 | 15.853 | *** | 0.859 | 0.738 | 0.262 | |||
PER3 | 1.095 | 0.083 | 13.215 | *** | 0.757 | 0.573 | 0.427 | |||
PER4 | 1.227 | 0.085 | 14.364 | *** | 0.847 | 0.717 | 0.283 | |||
PER5 | 1.059 | 0.099 | 10.694 | *** | 0.596 | 0.355 | 0.645 | |||
eWOM 2 | eWOM2 | 1 | 0.754 | 0.569 | 0.431 | 0.943 | 0.625 | |||
eWOM 4 | 1.097 | 0.059 | 18.595 | *** | 0.875 | 0.766 | 0.234 | |||
eWOM 5 | 1.107 | 0.068 | 16.233 | *** | 0.786 | 0.618 | 0.382 | |||
eWOM 6 | 1.018 | 0.062 | 16.438 | *** | 0.793 | 0.629 | 0.371 | |||
eWOM 7 | 0.699 | 0.05 | 14.02 | *** | 0.692 | 0.479 | 0.521 | |||
eWOM 11 | 1.084 | 0.059 | 18.253 | *** | 0.869 | 0.755 | 0.245 | |||
eWOM 12 | 0.955 | 0.064 | 14.966 | *** | 0.736 | 0.542 | 0.458 | |||
eWOM 13 | 0.945 | 0.065 | 14.623 | *** | 0.718 | 0.516 | 0.484 | |||
eWOM 14 | 1.143 | 0.064 | 17.754 | *** | 0.848 | 0.719 | 0.281 | |||
eWOM 16 | 0.926 | 0.055 | 16.869 | *** | 0.813 | 0.661 | 0.339 | |||
CI 2 | CI1 | 1 | 0.891 | 0.794 | 0.206 | 0.897 | 0.745 | |||
CI2 | 0.991 | 0.037 | 26.46 | *** | 0.918 | 0.843 | 0.157 | |||
CI3 | 0.915 | 0.05 | 18.367 | *** | 0.774 | 0.599 | 0.401 |
Cronbach’s Alpha | CR | AVE | eWOM | SECU | PU | PER | CI | |
---|---|---|---|---|---|---|---|---|
eWOM 3 | 0.948 | 0.943 | 0.625 | 0.791 1 | ||||
SECU 3 | 0.928 | 0.929 | 0.687 | 0.488 2 | 0.829 1 | |||
PU 3 | 0.935 | 0.936 | 0.746 | 0.529 2 | 0.420 2 | 0.864 1 | ||
PER 3 | 0.858 | 0.870 | 0.577 | 0.233 2 | 0.043 2 | 0.158 2 | 0.759 1 | |
CI 3 | 0.886 | 0.897 | 0.745 | 0.727 2 | 0.393 2 | 0.426 2 | 0.165 2 | 0.863 1 |
R2 (PU) = 0.196, R2 (eWOM) = 0.391, R2 (CI) = 0.531 | |||||||||
---|---|---|---|---|---|---|---|---|---|
Regression Path | β | B | S.E. | C.R. | p Value | Hypothesis | Confirmed (Y/N) | ||
PU 2 | ← | SECU 2 | 0.414 | 0.457 | 0.062 | 7.379 | 0.000 *** 1 | H1 | Y |
PU | ← | PER 2 | 0.140 | 0.119 | 0.044 | 2.724 | 0.006 ** 1 | H2 | Y |
CI 2 | ← | PER | −0.003 | −0.003 | 0.048 | −0.071 | 0.943 | H3 | N |
eWOM 2 | ← | PER | 0.161 | 0.167 | 0.048 | 3.444 | 0.000 *** 1 | H4 | Y |
eWOM | ← | PU | 0.366 | 0.45 | 0.066 | 6.854 | 0.000 *** 1 | H5 | Y |
eWOM | ← | SECU | 0.328 | 0.444 | 0.072 | 6.172 | 0.00 0 *** 1 | H6 | Y |
CI | ← | SECU | 0.040 | 0.058 | 0.070 | 0.825 | 0.409 | H7 | N |
CI | ← | PU | 0.048 | 0.063 | 0.065 | 0.965 | 0.334 | H8 | N |
CI | ← | eWOM | 0.682 | 0.727 | 0.067 | 10.862 | 0.000 *** 1 | H9 | Y |
Goodness-of-fit statistic | |||||||||
χ2 (chi-square) = 367, χ2/df = 3.061, GFI = 0.831, AGFI = 0.80, RMSEA = 0.073, and CFI = 0.916 SRMR = 0.0569 |
Path | Bootstrap 5000 Confidence Interval 2 | |||
Effect | BootSE | LLCI | ULCI | |
Total indirect effect | ||||
PER 1 → CI 1 | 0.153 | 0.039 | 0.078 | 0.230 |
Indirect effects | ||||
Path 1 3 | 0.008 | 0.006 | 0.000 | 0.027 |
Path 2 3 | 0.041 | 0.017 | 0.009 | 0.078 |
Path 3 3 | 0.103 | 0.031 | 0.045 | 0.167 |
Direct effect | ||||
PER → CI | −0.011 | 0.033 | −0.077 | 0.054 |
Path | Bootstrap 5000 Confidence Interval | |||
Effect | BootSE | LLCI | ULCI | |
Total indirect effect | ||||
SECU 1 → CI | 0.357 | 0.043 | 0.276 | 0.448 |
Indirect effects | ||||
Path 4 3 | 0.024 | 0.017 | −0.008 | 0.062 |
Path 5 3 | 0.109 | 0.023 | 0.070 | 0.160 |
Path 6 3 | 0.224 | 0.041 | 0.146 | 0.310 |
Direct effect | ||||
SECU→CI | 0.068 | 0.0430 | −0.016 | 0.152 |
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Liu, T.-L.; Lin, T.T.; Hsu, S.-Y. Continuance Usage Intention toward E-Payment during the COVID-19 Pandemic from the Financial Sustainable Development Perspective Using Perceived Usefulness and Electronic Word of Mouth as Mediators. Sustainability 2022, 14, 7775. https://doi.org/10.3390/su14137775
Liu T-L, Lin TT, Hsu S-Y. Continuance Usage Intention toward E-Payment during the COVID-19 Pandemic from the Financial Sustainable Development Perspective Using Perceived Usefulness and Electronic Word of Mouth as Mediators. Sustainability. 2022; 14(13):7775. https://doi.org/10.3390/su14137775
Chicago/Turabian StyleLiu, Tsai-Ling, Tyrone T. Lin, and Shu-Yen Hsu. 2022. "Continuance Usage Intention toward E-Payment during the COVID-19 Pandemic from the Financial Sustainable Development Perspective Using Perceived Usefulness and Electronic Word of Mouth as Mediators" Sustainability 14, no. 13: 7775. https://doi.org/10.3390/su14137775