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Impacts of Individual Innovativeness on the Acceptance of IT-based Innovations in Health Care Fields

OBJECTIVES: The purpose of this study is to identify the role of individual innovation to demographic variables for determining IT adoption behaviors. This study also examines the effect of individual innovation on IT adoption behaviors across IT types. METHODS: To verify the invariant effect of ind...

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Detalles Bibliográficos
Autores principales: Park, Jae Sung, Kim, Hye Sook
Formato: Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3092138/
https://www.ncbi.nlm.nih.gov/pubmed/21818448
http://dx.doi.org/10.4258/hir.2010.16.4.290
Descripción
Sumario:OBJECTIVES: The purpose of this study is to identify the role of individual innovation to demographic variables for determining IT adoption behaviors. This study also examines the effect of individual innovation on IT adoption behaviors across IT types. METHODS: To verify the invariant effect of individual innovativeness, two groups of persons working in the health care field were surveyed. The first study subject group was radiologists and their adoption of e-purchasing the second group was emergency rescue crews and their adoption of GPS. RESULTS: Adopter categories in innovations (ACI) as the measurement of individual innovation were a significant variable in both studies. Innovative adopters were more likely to use new IT tools than the majority of early adopters, and the early majority was more likely to adopt IT than the laggards. After merging the two data sets into one for testing the role of IT types as a moderator, the significance of ACI did not change, compared to the two separate analyses. In the merged data set, innovative adopters were 2.34 times more likely to be adopters than the early majority. The early majority was 2.32 times more likely to be adopters than laggards. Moreover, there were no moderating effects of IT types. Thus, there were no reversed adoption rates according to levels of ACI and demographic variables. CONCLUSIONS: ACI has invariant effects on IT adoption behaviors regardless of IT types and demographic differences. To implement a new innovation, understanding individual innovativeness will provide more sophisticated implementation strategies for health care organizations and appropriate education programs for their employees.