BUS606: Operations and Supply Chain Management

Analysis of the study is divided into two major parts. Part one was based on an outer model assessment in which reliability and validity were examined. Whereas, second part was focused on an inner model assessment in which, hypotheses were tested. First part was mandatory to proceed for inner model assessment. In the first part, convergent validity and discriminant validity was examined. Convergent validity was examined through composite reliability, factor loadings and Average Variance Extracted (AVE). According to the literature, the value of factor loading for each item should be more than 0.4, composite reliability should be more than 0.7 and Average Variance Extracted (AVE) should not be less than 0.5.

Results of the inner model assessment are shown in Figure 2 & Table 2. According to these results, factor loading is above 0.7 for all items, Average Variance Extracted (AVE) is more than 0.5 and composite reliability is also more than 0.7. To achieve the satisfactory level of validity, few items with factor loading below than 0.7 were deleted.

Figure 2: Outer Model Assessment

Discriminant validity is shown in Table 3. It was examined by the square root of Average Variance Extracted (AVE). Measurement of discriminant validity through Average Variance Extracted (AVE) was suggested by Fornell-Larcker.

After assessment of the outer model, the inner model was examined to check the relationship between dependent and independent variables. This is the second part of the analysis. In this part, both direct, as well as an indirect hypothesis with a mediating variable was examined.

To test the direct hypothesis, t-value was examined, where the value of 1.96 levels was considered as the minimum level to accept the hypothesis. According to the results, the entire direct hypothesis has t-value more than 1.96 which is the evidence to accept the entire direct hypothesis.

In Table 4 shows, the first set of hypotheses (H1-H7) was about the impact of Green Supply Chain Integration (GSCI), Inventory (INV), Sourcing (SRC), Facility (FCL), Transport (TRANS), Information (INF), and Pricing (PRC) on Supply Chain Sustainability (SCS). The results of the study have revealed the fact that Transport (TRANS), Information (INF), and Pricing (PRC) on Supply Chain Sustainability (SCS have a significant positive relationship Supply Chain Sustainability (SCS). Whereas the second set of hypotheses which was hypothesizing the relationship between Inventory (INV), Sourcing (SRC), Facility (FCL), Transport (TRANS), Information (INF), and Pricing (PRC) on Supply Chain Sustainability (SCS) and Green Supply Chain Integration (GSCI) were also approved significantly.

The indirect effect is shown in Table 5. According to the indirect effect, the mediation effect Green Supply Chain Integration (GSCI) between Inventory (INV), Sourcing (SRC), Facility (FCL), Transport (TRANS), Information (INF), and Pricing (PRC) and Supply Chain Sustainability (SCS) was significant.

Additionally, the Table 6 shows the variance explained. It shows that Green Supply Chain Integration (GSCI) Inventory (INV), Sourcing (SRC), Facility (FCL), Transport (TRANS), Information (INF), and Pricing (PRC) were collectively explained 69.7% variance in Supply Chain Sustainability (SCS).