The purpose of this research is to define what are the factors that lead smart phone non-users to use smart phones, and to analyze the difference in intentions of accepting smart phones according to the difference in the degree of innovation. The mode...
The purpose of this research is to define what are the factors that lead smart phone non-users to use smart phones, and to analyze the difference in intentions of accepting smart phones according to the difference in the degree of innovation. The model suggested in the study is based on Technology Acceptance Model and Innovation Adoption Curve, and added four external variables that are considered as important after examining the previous research.
To achieve purpose of the research, empirical analysis was conduct through survey. The method of analysis regards to path analysis utilizing Amos 18 for statistical hypothesis testing and parameter analysis, mediation effect analysis utilizing SPSS 18, One‐way ANOVA, and hierarchical regression analysis. As a result of statistical hypothesis analysis, 11 out of 16 hypotheses were selected.
The outcome of path analysis showed that acceptance factor which directly influenced the intention of acceptance were perceived usefulness, social and amusement attribute among the established variables in the research model. Moreover, and it showed that other variables had indirect effect. Therefore, to analyze the effect of the factors that have indirect effect, mediation effect analysis was conducted.
Mediation effect analysis was conducted upon perceived facilitation and usefulness suggested as parameters in the research model. As a result, it showed that factors of acceptance had influence on the intention of acceptance through perceived usefulness. However, it showed that perceived facilitation did not have mediation effect. Through such result, it was known that partial modification is required in TAM (Davis, 1989) concerning the research about intention to accept smart phones.
Finally, to figure out the difference of acceptance factors for each category of innovative accepters of smart phone non-users, one‐way ANOVA and hierarchical regression analysis were conducted. As a result, it depicted that there is a difference in the degree of influence of acceptance factor which influence the intention of acceptance for each category regarding innovative accepters of smart phone non-users.
The greatest significance of the research is proposal of a research model by combining TAM and Innovation Adoption Curve. Not only research on causal relationship regarding the acceptance factor, but also suggesting the difference in the influence of acceptance factor according to the category of innovative accepters, which previous studies on intention of acceptance of smart phone have not shown.