## 3 Case Study
### Confirmatory Analysis: Dimension Reduction, Results and Discussion  
The purpose of this study is to examine the relationship between the use of WhatsApp and academic performance in management students. For this, an FA was applied using PCA as extraction method, with varimax rotation on the 14 validated items; see Table 3.  
The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy indicated that we should be confident that the FA is appropriate for considering and theory building. The value of KMO = 0.824 is greater than the recommended value of 0.5, while the Bartlett test of sphericity is also significant with \(\chi^{2}=1183.327\) and \(p\)-value < 0.001 [48]. In addition, the sample size \(n=258\) is more than 10 times the number of variables, which is equal to 14 [49]. All these results suggest that the FA is appropriate and good to draw conclusions. All the items are standardized to ensure proper interpretation on a common scale. Scree plot and eigenvalues are examined to extract the appropriate number of factors; see Figure 3.  
Figure 3: Variance explained by each factor for WhatsApp Indian data. The 14 WhatsApp addiction items considered in this study are grouped into three factors based on the responses from students. Thus, factor 1 (FACT1 = addicted) includes deteriorated grades, usage of WhatsApp while driving, canceling meeting of friends, and worry about WhatsApp if I do not use it. Factor 2 (FACT2 = socially isolated) considers long time use, life is tedious without WhatsApp, and feeling upset if someone stops me from using WhatsApp. Factor 3 (FACT4 = time pass) includes time flies, feeling irritable, and my utilization has increased. Table 5 shows the factor matrix after applying a varimax rotation. We can see that the items have a strong representation on only one factor, except for items 9, 10, 11 and 14. The three factors capture 56.35% of data variability. Figure 4 shows the reduced dimension space for the 14 WhatsApp items. The association of these factors with use of WhatsApp is examined by analyzing the Spearman correlation between students GPA, time spent on WhatsApp, hours that students sleep, use of app during class time, assistance of app in learning, disruption of app on the study. The results show that there is no significant relation between the GPA and factors:  
Figure 4: WhatsApp items space on three factors for Indian data in three different perspectives. FACT1, FACT2, and FACT3. The findings from this study show a positive correlation between times spent on WhatsApp and academic performance measured by the GPA of the students, which is similar to the investigation presented in [25]. In addition, hours of sleep is not related to GPA. From Table 6, note that the time spent on WhatsApp is disruptive to study with both being positively correlated to the factors FACT1, FACT2, and FACT3. It means there is more addiction toward WhatsApp and time spent on WhatsApp by students. From Table 4, it is evident that answering on WhatsApp during class is significantly associated with assistance of WhatsApp in learning, but more use of this app in class is negatively correlated with GPA. Hence, the study concludes that student's performance in GPA has no relationship with use of WhatsApp, but sometimes, this app assists students in their learning and performance. The GPA of students and connections with teachers on WhatsApp is detected by the chi-square test as well as the relationship with the use of WhatsApp in academic activities. According to our findings, there is a substantial relation between students' use of WhatsApp during academic activities and their connections with teachers on the app. However, there is no relation between GPA and WhatsApp utilization through academic activities, which is in accordance with the work presented in [27; 28]. Table 7 illustrates the crosstabulated findings of using WhatsApp for academic purposes with a variety of variables.