**4. Data Analysis**

Statistical Package for Social Sciences (SPSS) and partial least square structural equation modeling (PLS-SEM) were used to analyze the data. We utilized SPSS for data purification and assessing common method bias, and PLS-SEM for the analysis of measurement and structural model.

#### *4.1. Data Screening*

Before conducting the final analysis, we applied the Mahalanobis distance technique for the identification of outliers in the data. There were seven outliers whose probability values were less than 0.001. Therefore, we excluded these multivariate outliers from our final analysis. This made our final sample size 354. Further, we performed Harman's [81] single factor test to assess whether common method bias was a threat or not. Common method bias occurs when the researchers use self-reported data and rely on a single source [82]. A substantial bias exists in the data if a single factor explains more than 50% variance [83]. The study result showed that a single factor explaining 28.32% variance in the data depicted that common method bias was not a threat to data credibility [83].
