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Antecedents of Intention to Adopt Mobile Health (mHealth) Application and Its Impact on Intention to Recommend: An Evidence from Indonesian Customers.

Gilbert Sterling OctaviusFerdi Antonio
Published in: International journal of telemedicine and applications (2021)
There are 787 respondents in our study, with the majority of them being female, young adults. Our model could explain 53.2% of the variance of intention to adopt while explaining 48.3% of the variance of intention to recommend. Initial trust in mHealth platform (β = 0.373, p = <0.001), facilitating conditions (β = 0.131, p = <0.01), and performance expectancy (β = 0.099, p = <0.05) are the top three most important drivers of intention to adopt mHealth applications. Lastly, importance-performance map analysis (IPMA) showed that the mHealth application's initial trust is the most important construct with a high-performance score. Discussion. Mobile health developers and managers need to improve initial trust in the mHealth platform, facilitating conditions, and performance expectancy when developing the applications. With a medium Q 2 predict, these factors can be applied out of the research context with medium predictive power.
Keyphrases
  • young adults
  • health information
  • high throughput
  • healthcare
  • social media
  • data analysis