Submitted:
04 September 2024
Posted:
04 September 2024
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Abstract
Keywords:
1. Introduction
2. Literature Review
2.1. Affective Event Theory
2.2. Push-Pull-Mooring Theory
3. Hypothesis
4. Methods
4.1. Research Design and Data Collection
4.2. Measurement
5. Results
6. Implications
6.1. Theoretical Implications
6.2. Practical Implications
7. Discussion
8. Conclusions
9. Limitations and Future Research
References
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| Authors | Research Factors | Research Object |
|---|---|---|
| Li et al. (2016) [15] | Risk, Benefit, Innovativeness | Healthcare wearable devices adoption |
| Zhang et al. (2017) [16] | Convenience, Credibility, Usefulness | Healthcare wearable devices adoption |
| Shin et al. (2019) [8] | Privacy, Behavior change, Technology focus | Wearable activity trackers adoption |
| Kim & Park (2019) [17] | Utility, Attractiveness, Appeal, Usability | Interactive wearable devices adoption |
| Farivar et al. (2020) [18] | Complexity, cognitive age, Subjective Wellbeing | Wearable device adoption among older adults |
| Ogbanufe & Gerhat (2022) [19] | Value incongruence, Social influence, Freedom Restriction | Status quo behavior towards smart watch |
| Huarng et al. (2022) [20] | Economic, data privacy, ease of use, usefulness | Healthcare wearable devices adoption |
| Wang et al. (2022) [21] | Social capital, Perceived values, Individual characteristics | Smart wearable products adoption |
| Hayat et al. (2022) [22] | Reliability, Expectancy, Health consciousness, Price value | Wearable healthcare devices adoption among Pakistan |
| Category | Subject | N | % |
|---|---|---|---|
| Gender | Male | 198 | 75.2% |
| Female | 65 | 24.8% | |
|
Education level |
High school | 98 | 37.2% |
| Bachelor | 158 | 60.0% | |
| Master | 7 | 2.8% | |
| Ph.D. | 0 | 0% | |
|
Age |
20-30 | 181 | 68.8% |
| 31-40 | 68 | 25.8% | |
| 41-50 | 14 | 5.4% | |
| More than 50 | 0 | 0% | |
|
Yearly income |
< 10,000$ | 69 | 26.2% |
| 10,000-15,000$ | 83 | 31.5% | |
| 15,000-20,000$ | 96 | 36.5% | |
| >20,000$ | 15 | 5.8% | |
|
Term of using wearable devices |
<3 months | 78 | 29.6% |
| 3-6months | 121 | 46.0% | |
| 6-12moths | 50 | 19.0% | |
| >12months | 14 | 5.4% |
| Construct | Item | Standardized loading |
AVE | Composite Reliability |
Cronbach’s α |
|---|---|---|---|---|---|
| Affective Event Reaction | AER1 | 0.933 |
0.961 |
0.964 |
0.960 |
| AER2 | 0.901 | ||||
| AER3 | 0.947 | ||||
| Perceived Security | PS1 | 0.954 |
0.970 |
0.932 |
0.923 |
| PS2 | 0.968 | ||||
| PS3 | 0.912 | ||||
|
Social Influence |
SI1 | 0.942 |
0.959 |
0.919 |
0.945 |
| SI2 | 0.927 | ||||
| SI3 | 0.927 | ||||
| Personal Innovativeness |
PI1 | 0.863 |
0.963 |
0.907 |
0.931 |
| PI2 | 0.923 | ||||
| PI3 | 0.834 | ||||
|
Usage |
U1 | 0.914 |
0.955 |
0.926 |
0.958 |
| U2 | 0.912 | ||||
| U3 | 0.947 |
| AER | PI | PS | SI | U | PI*AER | PI*SI | PI*PS | |
|---|---|---|---|---|---|---|---|---|
| AER | ||||||||
| PI | 0.062 | |||||||
| PS | 0.443 | 0.334 | ||||||
| SI | 0.109 | 0.117 | 0.156 | |||||
| U | 0.478 | 0.560 | 0.268 | 0.398 | ||||
| PI*AER | 0.057 | 0.018 | 0.034 | 0.081 | 0.077 | |||
| PI*SI | 0.259 | 0.291 | 0.136 | 0.053 | 0.014 | 0.042 | ||
| PI*PS | 0.146 | 0.314 | 0.088 | 0.034 | 0.039 | 0.058 | 0.425 |
| 2.5% | 97.5% | |
| AER-U | 0.217 | 0.395 |
| PI-U | 0.593 | 0.781 |
| PS-U | 0.205 | 0.389 |
| SI-U | 0.150 | 0.292 |
| PI*AER-U | 0.063 | 0.223 |
| PI*PS-U | 0.025 | 0.192 |
| PI*SI-U | 0.141 | 0.001 |
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