A carregar...
Publicação
Usage intensity of mobile medical apps: A tale of two methods
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 229.58 KB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Web 2.0 technologies have changed the traditional relationship model between doctors and third parties, and a plethora of apps are now available for the medical profession. This study presents unpublished findings about the potential drivers that currently influence mobile medical app usage intensity. Logistic regression and fuzzy-set qualitative comparative analysis (fsQCA) are both used to examine usage intensity. By using two research methods, rather than just one, the findings are greatly enhanced. Logistic regression results show that high usage intensity is explained by high perceived usefulness and high perceived ease of use. FsQCA, on the other hand, highlights that the combinations of multiple conditions are also significant, leading to the finding that low mobile medical app usage intensity is associated with low perceived ease of use, high perceived usefulness, low peer influence, high seniority, and younger female doctors.
Descrição
Palavras-chave
Mobile App m-Health Healthcare Provider fsQCA Logistic Regression Mixed Methods Research
Contexto Educativo
Citação
Veríssimo, José Manuel .(2018). “Usage intensity of mobile medical apps: A tale of two methods”. Journal of Business Research, Volume 89: pp. 442-447
Editora
Elsevier