## 4 Data Analysis and Results  
The relationships between the variables were identified through correlation analysis via IBM software package SPSS version 22; subsequently, the extent to which the independent variables explain the dependent variables was identified through linear regression analysis [69]. Correlation analyses for the mediating effect performed via the IBM software package SPSS Amos version 24 were conducted on 455 questionnaires without any missing value. The Cornell-Larcker criterion was used to ensure the discriminant validity. For this, \begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline \multirow{2}{*}{**Factors**} & \multicolumn{2}{c}{**EFA**} & \multicolumn{2}{c}{**CFA**} \\  & **Item** & **Std. Loads** & **AV** & \(\mathbf{\alpha}\) & **CR** & **AVE** \\ \hline \multirow{9}{*}{Green Supplier Development (GSD)} & GSD1 & 0.59 & & & & & \\  & GSD2 & 0.80 & & & & & \\  & GSD3 & 0.76 & & & & & \\  & GSD6 & 0.52 & & & & & \\  & GSD7 & 0.73 & & 17.51\% & 0.90 & 0.90 & 0.53 & \\  & GSD8 & 0.53 & & & & & \\  & GSD10 & 0.63 & & & & & \\  & GSD11 & 0.76 & & & & & \\ \hline \multirow{9}{*}{Green Supplier Collaboration (SSC)} & GSC1 & 0.72 & & & & & \\  & GSC5 & 0.74 & & & & & \\  & GSC11 & 0.55 & & 14.43\% & 0.80 & 0.81 & 0.46 & \\  & GSC12 & 0.68 & & & & & \\  & GSC14 & 0.60 & & & & & \\ \hline \multirow{9}{*}{Green Supplier Evaluation (GSE)} & GSE1 & 0.93 & & & & & \\  & GSE3 & 0.94 & & 11.24\% & 0.87 & 0.89 & 0.73 & \\ \cline{1-1}  & GSE7 & 0.72 & & & & & \\ \hline \multirow{9}{*}{Total AV KMO Bartlett’s Test of Sphericity Chi-square Defrees of Freedom (df) Significance (Sig.)} & & & 63.46\% & & & Goodness of Fit Index & \\ \cline{1-1}  & & & 0.94 & & CMIN & 492.830 & CFI & 0.95 \\ \cline{1-1}  & & & DP & 203 & & & & \\ \cline{1-1}  & & & 5638.863 & CMIN/DF & 2.428 & AGFI & 0.89 \\ \cline{1-1}  & & & 231 & P & 0.000 \({}^{*}\) & NFI & 0.91 \\ \cline{1-1}  & & & 0.000 \({}^{*}\) & & RMSEA & 0.056 & & \\ \hline \multicolumn{9}{c}{N = 455,* \(p<0.01\).} \\ \end{tabular}
\end{table} 
Table 2: _Cont._ \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline \multirow{2}{*}{**Factors**} & \multicolumn{2}{c}{**EFA**} & \multicolumn{2}{c}{**CFA**} \\  & **Item** & **Std. Loads** & **AV** & \(\mathbf{\alpha}\) & **CR** & **AVE** \\ \hline Company Performance & & & & 0.93 & 0.94 & 0.60 & \\ \hline \multirow{9}{*}{Environmental Performance (EP)} & EP1 & 0.73 & & & & & \\  & EP2 & 0.74 & & & & \\ \cline{1-1}  & EP3 & 0.81 & & & & & \\ \cline{1-1}  & EP4 & 0.79 & & 37.33\% & 0.90 & 0.90 & 0.60 & \\ \cline{1-1}  & EP5 & 0.74 & & & & & \\ \cline{1-1}  & EP6 & 0.70 & & & & & \\ \hline \multirow{9}{*}{Financial Performance (FP)} & FP1 & 0.81 & & & & & \\ \cline{1-1}  & FP2 & 0.84 & & & & & \\ \cline{1-1}  & FP3 & 0.79 & & 30.79\% & 0.88 & 0.89 & 0.61 & \\ \cline{1-1}  & FP4 & 0.67 & & & & & \\ \cline{1-1}  & FP5 & 0.57 & & & & & \\ \hline Total AV & & & 68.12\% & & & Goodness of Fit Index & \\ \cline{1-1}  & KMO & & 0.93 & & CMIN & 158.520 & CFI & 0.96 \\ \cline{1-1}  & Bartlett’s Test of Sphericity Chi-square Defrees of Freedom (df) Significance (Sig.) & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Factor Analysis for EP and FP. the values on the diagonal in Table 4, the square roots of the AVE shown in Tables 2 and 3, were compared with the correlations in the respective rows and columns. Accordingly, discriminant validity was accepted because the values on the diagonal were greater than or equal to the correlations [77]. \(H_{1}\)_Hypothesis:_ As a result of the correlation analysis in Table 4, a positive and significant relationship was found between GPP and EP (H\({}_{1}\)). The linear regression between GPP and EP in Table 5 indicates that 46% of the GPP variances (R\({}^{2}\)) seemed to be attributable to EP, and GPP have a significant and positive (\(\beta\) = 0.68, \(p\) < 0.01) effect on EP. \(H_{1a}\)-\(p\)-\(c\)_4 Sub-hypotheses_: It is revealed in Table 4 that there is a positive and significant relationship between GSS, GSD, GSC, GSE, and EP.