How Inclusive Digital Financial Services Impact User Behavior: A Case of Proximity Mobile Payment in Korea
Abstract
:1. Introduction
2. Theoretical Background
2.1. Switching Research
2.2. PPM Framework and the Migration Theory
2.3. Mobile Payment Research
3. Hypothesis Development
3.1. Push Factor
3.2. Pull Factors
3.3. Mooring Factors
3.4. Control Variable: Self-Efficacy, Gender, Age, Length of Use, and Occupation
4. Research Methodology
4.1. Measurements of Constructs
4.2. Data Collection and Descriptive Analysis
5. Results
5.1. Measurement Model
5.2. Structural Assessment
6. Conclusions and Discussion
6.1. Research Findings
6.2. Theoretical Implications
6.3. Managerial Implications
6.4. Limitations
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
Construct | Indicators | Mean | Items | Sources |
---|---|---|---|---|
Dissatisfaction | How do you feel about your overall experience using traditional payment (e.g., cash, bank cards) in a physical store? | [39] | ||
DIS1 | 3.51 | Satisfied | ||
DIS2 | 3.65 | Pleased | ||
DIS3 | 3.66 | Contented | ||
DIS4 | 3.75 | Delighted | ||
Perceived technical compatibility | TCP1 | 5.16 | The proximity mobile payment (e.g., Samsung Pay, Kakao Pay) is compatible with my mobile device’s hardware (e.g., NFC, Bluetooth, camera). | [64] |
TCP2 | 5.27 | The proximity mobile payment is compatible with my mobile device’s legacy operational system. | ||
TCP3 | 5.49 | The proximity mobile payment is compatible with my mobile device’s applications. | ||
Perceived risk | PER1 | 4.38 | I am worried that my data stored in my proximity mobile payment will be used by the proximity mobile payment provider without my authorization. | [64,73,91] |
PER2 | 4.28 | I am worried that my data stored in my proximity mobile payment will be sold to some profit-seeking organizations without my authorization. | ||
PER3 | 2.97 | I think it is risky to use the proximity mobile payment platform for transactions in a physical store. | ||
PER4 | 2.72 | I think there will be monetary losses when using proximity mobile payment to pay in a physical store. | ||
PER5 | 3.87 | I am worried that my proximity mobile payment provider does not implement security measures to protect my stored data. | ||
PER6 | 3.69 | I am worried that my proximity mobile payment provider does not have effective mechanisms to ensure that my transaction data are protected from being altered or destroyed accidentally during transaction in a physical store. | ||
Perceived substitutability | PSS1 | 4.49 | In a physical store, traditional payment offers the same services as the proximity mobile payment. | [92] |
PSS2 | 4.22 | In a physical store, traditional payment offers services in the same way as the proximity mobile payment. | ||
PSS3 | 4.26 | In a physical store, traditional payment satisfies the same needs as the proximity mobile payment. | ||
Perceived usefulness | PUF1 | 5.21 | Proximity mobile payment allows to do my transactions more quickly in a physical store. | [32] |
PUF2 | 5.31 | The use of the proximity mobile payment would improve my effectiveness in conducting my transactions in a physical store. | ||
PUF3 | 5.46 | Using proximity mobile payment would make the handing of transactions easier in a physical store. | ||
PUF4 | 5.47 | Overall, proximity mobile payment is useful. | ||
Perceived ease of use | PEU1 | 5.59 | Learning to use proximity mobile payment in a physical store would be easy for me. | [32,93] |
PEU2 | 5.70 | Using proximity mobile payment in a physical store is not challenging. | ||
PEU3 | 5.56 | It would be easy to follow all the steps to use proximity mobile payment in a physical store. | ||
PEU4 | 5.66 | Overall, I find proximity mobile payment to be easy to use. | ||
Self-efficacy | SEF1 | 5.33 | If there was nobody to tell me what to do, I would be able to complete my payment using proximity mobile payment in a physical store. | [20] |
SEF2 | 5.52 | If I had only the proximity mobile payment manuals for reference, I would be able to make a transaction using it in a physical store. | ||
SEF3 | 5.51 | If I could call someone for help when needed, I could complete my payment using proximity mobile payment in a physical store. | ||
SEF4 | 5.58 | If I have used a similar proximity mobile payment in the past, I could complete my payment using it in a physical store. | ||
SEF5 | 5.59 | If someone showed me how to use it, I could complete my payment using proximity mobile payment in a physical store. | ||
Switching intention | SWI1 | 5.21 | Please rate the possibility of you switching from traditional payment to proximity mobile payment in a physical store in the near future. (1 = Improbable…7 = Probable) | [18,19,22] |
SWI2 | 5.54 | The possibility of me switching to proximity mobile payment in a physical store in the near future is high. | ||
SWI3 | 5.40 | I intend to increase time on proximity mobile payment in a physical store in the near future. |
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Prior Study | Specific Context | Factors of Switching | ||
---|---|---|---|---|
Incumbent Product or Service (Push Factor) | Alternative Product or Service (Pull Factor) | Others | ||
[16] | Personal information technologies | Satisfaction (+) | Perceived relative ease of use (+) Perceived relative security (+) Relative advantage (+) | Subjective norm (−) Habit (−) Perceived switching costs (−) |
[21] | Social networking sites | Weak connection (+) Writing anxiety (+) | Enjoyment (+) Relative usefulness (+) Relative ease of use (+) | Past experience (−) Switching cost (−) |
[22] | PC to mobile shopping | Inconvenience (+) | Peer influence (+) Alternative attractiveness (+) | Low security and privacy (−) Low trust (−) High switching cost (−) |
[23] | Social networking sites | Regret (+) Dissatisfaction (+) | Alternative attractiveness (+) | Switching cost (−) |
[24] | Cloud computing | Dissatisfaction with client IT (+) | Relative usefulness (+) Expected omnipresence (+) | Switching cost (−) Security concerns (−) |
[25] | Technology product | Disconfirmation (+) Low satisfaction (+) | Relative advantage (+) | Inertia (−) Switching cost (−) Network effect (−) |
[26] | Healthcare service | Low satisfaction (+) Low commitment (+) | Ubiquitous care (+) Responsiveness (+) Personalized care (+) | Low government support (−) Low trust (−) High switching cost (−) Low privacy and security (−) |
[27] | Mobile instant messaging | Dissatisfaction (+) Fatigue (+) | Alternative attractive (+) Subjective norm (+) | Inertia (affective commitment, switching cost, and habit) (−) |
[19] | Cloud storage services | Perceived risk (+) | Transfer trust (+) Critical mass (+) | Social norm (+) Low switching cost (+) |
Prior Study | Research Context | Dimensions | Conceptual and Operational Definitions |
---|---|---|---|
[69] | Technology product | Normative or cognitive compatibility | Compatibility with what people feel. |
Practical or operational compatibility | Compatibility with what people do. | ||
[70] | Telecommuting | Practical compatibility | Climate for the innovation’s implementation. |
Value compatibility | Compatibility with people’s values at the organizational level. | ||
[66] | Customer relationship management system in the context of a large bank | Compatibility with preferred work style | The possibility provided by the technology of being consistent with an individual’s desired work style. |
Compatibility with values | The compatibility between the possibilities offered by the technology and an individual’s dominant value system. | ||
Compatibility with existing work practices | The degree of change a person may experience when adopting a new technology. | ||
Compatibility with prior experience | The degree of compatibility between the technology and the diversity of individuals’ past encounters with technology. | ||
[71] | Electronic products | Lifestyle compatibility | An innovation’s compatibility in terms of situational properties. |
Infrastructural compatibility | An innovation’s compatibility with other products in terms of its connectivity or shared infrastructure. | ||
[64] | Mobile personal cloud storage services | Perceived lifestyle compatibility | The degree to which an innovation is adopted to be compatible with one’s lifestyle. |
Perceived technical compatibility | The degree of compatibility of the innovation with users’ mobile devices, apps, and operational systems (OSs). |
Category | Count | % | |
---|---|---|---|
Gender | Male | 184 | 59.2% |
Female | 127 | 40.8% | |
Age | Open-ended question | 19–57 | |
Do you have experience engaging in the proximity mobile payment activities in the past six months? For instance, making a transaction in a physical store or downloading the proximity mobile payment app and learning how to use it. | Yes | 311 | 100% |
Length of use | <6 months | 89 | 28.6% |
6 months–1 year | 51 | 16.4% | |
1–3 years | 137 | 44.1% | |
3–6 years | 32 | 10.3% | |
>6 years | 2 | 0.6% | |
Occupation | Undergraduate student | 284 | 91.3% |
Graduate or Ph.D. student | 5 | 1.6% | |
Employee | 10 | 3.2% | |
Others | 12 | 3.9% |
The First 25% of Responses (n = 78) | The Final 25% of Responses (n = 78) | Significance (p-Value) | Valid Responses (n = 311) | Invalid Responses (n = 61) | Significance (p-Value) | |
---|---|---|---|---|---|---|
DIS | 3.679 | 3.599 | 0.732 | 3.644 | 3.462 | 0.365 |
TCP | 5.256 | 5.145 | 0.611 | 5.308 | 5.044 | 0.156 |
PER | 3.823 | 3.899 | 0.692 | 3.654 | 3.809 | 0.169 |
PSS | 4.389 | 4.385 | 0.986 | 4.324 | 4.098 | 0.265 |
PUF | 5.366 | 5.282 | 0.673 | 5.363 | 5.102 | 0.129 |
PEU | 5.696 | 5.429 | 0.163 | 5.629 | 5.365 | 0.157 |
SEF | 5.474 | 5.462 | 0.947 | 5.507 | 5.219 | 0.094 |
SWI | 5.466 | 5.325 | 0.549 | 5.414 | 5.109 | 0.185 |
Fit Indices | χ2/df | IFI | GFI | CFI | NFI | RMSEA |
---|---|---|---|---|---|---|
Recommended value | <3.0 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 |
Measurement value indices | 1.696 | 0.962 | 0.878 | 0.961 | 0.911 | 0.047 |
Structural value indices | 1.714 | 0.953 | 0.868 | 0.952 | 0.894 | 0.048 |
Variables | Measurements | Estimate | Cronbach’s Alpha | C.R. | AVE |
---|---|---|---|---|---|
Dissatisfaction | DIS1 | 0.811 | 0.924 | 0.926 | 0.758 |
DIS2 | 0.859 | ||||
DIS3 | 0.905 | ||||
DIS4 | 0.905 | ||||
Perceived technical compatibility | TCP1 | 0.817 | 0.881 | 0.885 | 0.720 |
TCP2 | 0.901 | ||||
TCP3 | 0.825 | ||||
Perceived risk | PER1 | 0.696 | 0.886 | 0.870 | 0.535 |
PER2 | 0.721 | ||||
PER3 | 0.587 | ||||
PER4 | 0.558 | ||||
PER5 | 0.874 | ||||
PER6 | 0.888 | ||||
Perceived substitutability | PSS1 | 0.805 | 0.825 | 0.828 | 0.616 |
PSS2 | 0.834 | ||||
PSS3 | 0.711 | ||||
Perceived usefulness | PUF1 | 0.820 | 0.907 | 0.908 | 0.712 |
PUF2 | 0.886 | ||||
PUF3 | 0.851 | ||||
PUF4 | 0.817 | ||||
Perceived ease of use | PEU1 | 0.864 | 0.925 | 0.925 | 0.755 |
PEU2 | 0.938 | ||||
PEU3 | 0.848 | ||||
PEU4 | 0.822 | ||||
Self-efficacy | SEF1 | 0.727 | 0.925 | 0.922 | 0.705 |
SEF2 | 0.827 | ||||
SEF3 | 0.884 | ||||
SEF4 | 0.871 | ||||
SEF5 | 0.879 | ||||
Switching intention | SWI1 | 0.842 | 0.929 | 0.932 | 0.822 |
SWI2 | 0.941 | ||||
SWI3 | 0.933 |
DIS | TCP | PER | PSS | PUF | PEU | SEF | SWI | |
---|---|---|---|---|---|---|---|---|
DIS | 0.870 | |||||||
TCP | −0.012 | 0.849 | ||||||
PER | −0.155 ** | −0.221 ** | 0.731 | |||||
PSS | −0.265 ** | 0.140 * | −0.106 | 0.785 | ||||
PUF | 0.023 | 0.382 ** | −0.238 ** | 0.194 ** | 0.844 | |||
PEU | −0.043 | 0.476 ** | −0.186 ** | 0.199 ** | 0.543 ** | 0.869 | ||
SEF | 0.004 | 0.393 ** | −0.276 ** | 0.309 ** | 0.542 ** | 0.648 ** | 0.840 | |
SWI | 0.180 ** | 0.415 ** | −0.365 ** | 0.222 ** | 0.595 ** | 0.476 ** | 0.530 ** | 0.907 |
Manifest Items | Standardized Loadings without CLF | Standardized Loadings with CLF | Differences |
---|---|---|---|
DIS1 | 0.811 | 0.747 | 0.064 |
DIS2 | 0.859 | 0.786 | 0.073 |
DIS3 | 0.905 | 0.823 | 0.082 |
DIS4 | 0.905 | 0.853 | 0.052 |
TCP1 | 0.817 | 0.712 | 0.105 |
TCP2 | 0.901 | 0.796 | 0.105 |
TCP3 | 0.825 | 0.679 | 0.146 |
PER1 | 0.696 | 0.729 | −0.033 |
PER2 | 0.721 | 0.753 | −0.032 |
PER3 | 0.587 | 0.663 | −0.076 |
PER4 | 0.558 | 0.653 | −0.095 |
PER5 | 0.874 | 0.774 | 0.100 |
PER6 | 0.888 | 0.788 | 0.100 |
PSS1 | 0.805 | 0.713 | 0.092 |
PSS2 | 0.834 | 0.707 | 0.127 |
PSS3 | 0.711 | 0.63 | 0.081 |
PUF1 | 0.82 | 0.687 | 0.133 |
PUF2 | 0.886 | 0.728 | 0.158 |
PUF3 | 0.851 | 0.657 | 0.194 |
PUF4 | 0.817 | 0.623 | 0.194 |
PEU1 | 0.864 | 0.679 | 0.185 |
PEU2 | 0.938 | 0.769 | 0.169 |
PEU3 | 0.848 | 0.657 | 0.191 |
PEU4 | 0.822 | 0.631 | 0.191 |
SEF1 | 0.727 | 0.603 | 0.124 |
SEF2 | 0.827 | 0.707 | 0.120 |
SEF3 | 0.884 | 0.737 | 0.147 |
SEF4 | 0.871 | 0.716 | 0.155 |
SEF5 | 0.879 | 0.738 | 0.141 |
SWI1 | 0.842 | 0.734 | 0.108 |
SWI2 | 0.941 | 0.816 | 0.125 |
SWI3 | 0.933 | 0.802 | 0.131 |
Indicators | Substantive Factor Loading (R1) | R12 | Method Factor Loadings (R2) | R22 |
---|---|---|---|---|
DIS1 | 0.867 | 0.751 | 0.009 | 0.000 |
DIS2 | 0.898 | 0.807 | 0.004 | 0.000 |
DIS3 | 0.925 | 0.856 | 0.006 | 0.000 |
DIS4 | 0.925 | 0.855 | −0.001 | 0.000 |
TCP1 | 0.920 | 0.846 | 0.049 | 0.002 |
TCP2 | 0.971 | 0.943 | 0.050 | 0.002 |
TCP3 | 0.807 | 0.651 | 0.060 | 0.004 |
PER1 | 0.927 | 0.859 | −0.021 | 0.000 |
PER2 | 0.914 | 0.836 | −0.027 | 0.001 |
PER3 | 0.617 | 0.381 | −0.051 | 0.003 |
PER4 | 0.562 | 0.316 | −0.053 | 0.003 |
PER5 | 0.880 | 0.775 | −0.031 | 0.001 |
PER6 | 0.857 | 0.734 | −0.036 | 0.001 |
PSS1 | 0.879 | 0.772 | 0.027 | 0.001 |
PSS2 | 0.877 | 0.769 | 0.030 | 0.001 |
PSS3 | 0.825 | 0.681 | 0.028 | 0.001 |
PUF1 | 0.953 | 0.909 | 0.061 | 0.004 |
PUF2 | 0.914 | 0.835 | 0.067 | 0.005 |
PUF3 | 0.884 | 0.782 | 0.067 | 0.004 |
PUF4 | 0.790 | 0.624 | 0.068 | 0.005 |
PEU1 | 0.876 | 0.767 | 0.070 | 0.005 |
PEU2 | 0.907 | 0.822 | 0.073 | 0.005 |
PEU3 | 0.897 | 0.804 | 0.069 | 0.005 |
PEU4 | 0.936 | 0.875 | 0.066 | 0.004 |
SEF1 | 0.779 | 0.607 | 0.069 | 0.005 |
SEF2 | 0.875 | 0.766 | 0.073 | 0.005 |
SEF3 | 0.938 | 0.880 | 0.071 | 0.005 |
SEF4 | 0.868 | 0.753 | 0.072 | 0.005 |
SEF5 | 0.932 | 0.868 | 0.070 | 0.005 |
SWI1 | 0.949 | 0.901 | 0.066 | 0.004 |
SWI2 | 0.934 | 0.873 | 0.071 | 0.005 |
SWI3 | 0.930 | 0.865 | 0.071 | 0.005 |
Average | 0.875 | 0.774 | 0.036 | 0.003 |
DIS | TPC | PER | PSS | PUF | PEU | SEF | Age | SWI | |
---|---|---|---|---|---|---|---|---|---|
DIS | 1 | ||||||||
TCP | −0.025 | 1 | |||||||
PER | −0.185 ** | −0.178 ** | 1 | ||||||
PSS | −0.282 ** | 0.155 ** | −0.113 * | 1 | |||||
PUF | 0.022 | 0.416 ** | −0.229 ** | 0.221 ** | 1 | ||||
PEU | −0.061 | 0.521 ** | −0.151 ** | 0.210 ** | 0.584 ** | 1 | |||
SEF | −0.025 | 0.411 ** | −0.247 ** | 0.353 ** | 0.576 ** | 0.695 ** | 1 | ||
Age | 0.069 | 0.057 | −0.017 | −0.096 | 0.040 | −0.111 * | 0.032 | 1 | |
SWI | 0.172 ** | 0.449 ** | −0.309 ** | 0.254 ** | 0.656 ** | 0.519 ** | 0.547 ** | 0.011 | 1 |
0.163 | 0.443 | −0.324 | 0.246 | 0.652 | 0.514 | 0.542 | 0 |
Hypothesis | Path | β | p-Value | Results |
---|---|---|---|---|
H1 | DIS → SWI | 0.184 | *** | Supported |
H2 | PSS → SWI | 0.118 | 0.029 | Supported |
H3 | PUF → SWI | 0.560 | *** | Supported |
H4 | PEU → SWI | 0.059 | 0.536 | Rejected |
H5 | PEU → PUF | 0.526 | *** | Supported |
H6 | PTC → SWI | 0.164 | 0.005 | Supported |
H7 | PER → SWI | −0.095 | 0.043 | Supported |
PEU → PUF → SWI | 0.294 | 0.006 | - |
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Mu, H.-L.; Lee, Y.-C. How Inclusive Digital Financial Services Impact User Behavior: A Case of Proximity Mobile Payment in Korea. Sustainability 2021, 13, 9567. https://doi.org/10.3390/su13179567
Mu H-L, Lee Y-C. How Inclusive Digital Financial Services Impact User Behavior: A Case of Proximity Mobile Payment in Korea. Sustainability. 2021; 13(17):9567. https://doi.org/10.3390/su13179567
Chicago/Turabian StyleMu, Hong-Lei, and Young-Chan Lee. 2021. "How Inclusive Digital Financial Services Impact User Behavior: A Case of Proximity Mobile Payment in Korea" Sustainability 13, no. 17: 9567. https://doi.org/10.3390/su13179567