Diffusion and adoption of technology amongst engineering and business management students

This study aimed to identify profiles of technology adoption amongst engineering and business management students based on Rogers' theory of diffusion of innovations and on Hirschman's studies of innovativeness, novelty seeking, creativity behavior and role accumulation. A systematic liter...

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Bibliographic Details
Published in:International Journal of Innovation (São Paulo) 2017-01, Vol.5 (1), p.20-31
Main Authors: Gabriel, Marcelo Luiz Dias Da Silva, Silva, Dirceu Da
Format: Article
Language:English
Subjects:
adoption of innovations
Adoção de Inovações
Age
Business administration
Colleges & universities
Consumer behavior
Creativity
diffusion of innovations
Difusão de Inovações
Engineering education
Estudantes Universitários
Females
Innovations
Literature reviews
Males
Management
Mathematical models
Modelagem de Equações Estruturais
Normality
Society
structural equation modeling
Students
Studies
Technological change
technology
Technology adoption
Technology utilization
Tecnologia
Theory
undergraduate students
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Summary:This study aimed to identify profiles of technology adoption amongst engineering and business management students based on Rogers' theory of diffusion of innovations and on Hirschman's studies of innovativeness, novelty seeking, creativity behavior and role accumulation. A systematic literature review was performed and an item pool was generated to measure the constructs found on theory. The questionnaire was presented to an experts' panel for content validity and to a sample of subjects in the population for semantic validity. The final research instrument was then submitted to 390 students from private and public universities in Brazil. Mean age of sample was 22.5 years (SD = 4.9) and was well distributed between males (50.6%) and females (49.4%). Data was analyzed using SPSS 22.0 and SmartPLS 2.0. A hypothetical model was specified and alternative models as well. Univariate and multivariate normality was tested and PLS-SEM was chosen due to the non-parametric nature of collected data. Final results proved that Roger's theoretical profiles (e.g.: innovator, early adopter, etc) are predictors of Hirschman's adoption typology and these findings are useful to understand the generational patterns of technology diffusion and adoption and to support corporate initiatives on technology deployment amongst employees
ISSN:2318-9975
2318-9975
DOI:10.5585/iji.v5i1.80