# Perceptions and Resistance to Accept Smart Clothing:
## 4. Results
### Hypothesis Testing
To identify the moderating effect of consumer fashion innovativeness and technological innovativeness, the first stage analysis was performed with control variables, second stage analysis with control variables and independent variables, and third stage analysis with control variables, independent variables, and moderating variables. As shown in Table 3, Hypothesis 7 was partially supported by analyzing the moderating effect of fashion innovativeness between the properties of smart clothing and innovation resistance. Consumers' fashion innovativeness did not have any effect on the relationship between compatibility, perceived risk, relative advantage, expectations of future product capabilities, and unavailability of smart clothing. However, in the relationship between cost rationality and innovation resistance of smart clothing, consumers' fashion innovativeness has a positive (+) moderating effect with a standardization factor of 0.130 (_p_ < 0.05). On the other hand, it was found that technological innovation had no effect on the relationship between the properties of smart clothing and the resistance to innovation, so hypothesis 8 was rejected. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Variables** & **Model 1** & **Model 2** & **Model 3** \\ \hline \multirow{2}{*}{**Control Variables**} & Sex & 0.211 *** & 0.078 & 0.079 \\ \cline{2-5}  & Age & 0.094 & 0.082 & 0.068 * \\ \hline \multirow{5}{*}{Independent Variables} & Perceived Compatibility & \(-\)0.090 & \(-\)0.117 \\ \cline{2-5}  & Expectations of Future Product & \(-\)0.363 *** & \(-\)0.341 *** \\ \cline{2-5}  & Capabilities & & & \\ \cline{2-5}  & Perceived Unavailability & 0.265 *** & 0.244 *** \\ \cline{2-5}  & Perceived Risk & 0.219 *** & 0.189 *** \\ \cline{2-5}  & Relative Advantage & 0.005 & 0.007 \\ \cline{2-5}  & Perceived Monetary Value & 0.076 & 0.044 \\ \cline{2-5}  & Fashion Innovativeness (A) & 0.109 * & 0.114 * \\ \cline{2-5}  & Technological Innovativeness (B) & \(-\)0.208 *** & \(-\)0.178 ** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of hierarchical regression analysis on the moderating effect of consumer characteristics for the relationship between innovation characteristics and innovation resistance (H7–H8). \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Variables** & \begin{tabular}{c} **Standardized Reg.** \\ **Coefficient** \\ \end{tabular} & _t-Value_ & _p-Value_ \\ \hline \multirow{2}{*}{\begin{tabular}{c} **Control** \\ **variables** \\ \end{tabular} } & Sex & 0.106 & 2.245 & 0.025 \\ \cline{2-5}  & **Age** & 0.098 & 2.104 & 0.036 \\ \hline \multirow{5}{*}{\begin{tabular}{c} **Independent** \\ **variables** \\ \end{tabular} } & **Perceived Compatibility** & \(-\)0.104 & \(-\)1.659 & 0.098 \\ \cline{2-5}  & \begin{tabular}{c} **Expectations of future** \\ **product capabilities** \\ \end{tabular} & \(-\)0.403 & \(-\)8.176 & 0.000 \\ \cline{2-5}  & \begin{tabular}{c} **Perceived Unavailability** \\ **Perceived Risk** \\ \end{tabular} & 0.251 & 5.049 & 0.000 \\ \cline{2-5}  & \begin{tabular}{c} **Perceived Relative** \\ **Advantage** \\ \end{tabular} & 0.004 & 0.065 & 0.948 \\ \cline{2-5}  & \begin{tabular}{c} **Perceived Monetary Value** \\ \end{tabular} & 0.097 & 1.945 & 0.053 \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} **R2** \\ **Adjusted-R2** \\ \end{tabular} } & \multicolumn{2}{c}{0.401} \\ \hline \multirow{2}{*}{
\begin{tabular}{c} **_p_ < 0.001. \\ \end{tabular} } & \multicolumn{2}{c}{27.730 ***} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of regression analysis for the relationship between innovation characteristics and innovation resistance (H1–H6).