Supply Chain Management Case Study
Read this journal article, which examines supply chain management drivers and the motivation of sustainability for manufacturing enterprise supply chains in Pakistan.
Results
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
Table 2 Outer Model Results |
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Construct | Indicators | Loadings | Cronbach's Alpha | Composite Reliability | AVE |
Supply chain Sustainability (SCS) | SCS2 SCS3 SCS5 SCS7 SCS9 |
0.785 0.901 0.752 0.812 0.797 |
0.902 | 0.907 | 0.710 |
Green Supply Chain Integration (GSCI) |
GCMI1 GCMI2 GCMI3 GCMI4 GCMI5 GCMI6 |
0.873 0.753 0.900 0.860 0.830 0.806 |
0.899 | 0.801 | 0.688 |
Inventory (INV) | INV2 INV3 INV4 INV6 |
0.796 0.736 0.897 0.814 |
0.815 | 0.807 | 0.664 |
Sourcing (SRC) | SRC1 SRC2 SRC6 SRC7 SRC8 |
0.897 0.821 0.641 0.560 0.646 |
0.825 | 0.888 | 0.780 |
Facility (FCL) | FCL1 FCL2 FCL3 FCL4 FCL5 |
0.740 0.748 0.824 0.827 0.754 |
0.899 | 0.901 | 0.688 |
Transport (TRANS) | TR1 TR2 TR3 TR7 |
0.755 0.719 0.744 0.707 |
0.799 | 0.801 | 0.588 |
Information (INF) | INF1 INF2 INF3 INF4 |
0.828 0.792 0.757 0.767 |
0.879 | 0.751 | 0.678 |
Pricing (PRC) | PR1 PR2 PR4 PR6 |
0.752 0.854 0.837 0.767 |
0.889 | 0.731 | 0.778 |
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.
Table 3 The Square Root Of Ave |
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SCS | GSCI | INV | SRC | FCL | TRANS | INF | PRC | |
SCS | 0.785 | |||||||
GSCI | 0.440 | 0.869 | ||||||
INV | 0.424 | 0.401 | 0.770 | |||||
SRC | 0.429 | 0.430 | 0.622 | 0.726 | ||||
FCL | 0.430 | 0.466 | 0.524 | 0.424 | 0.635 | |||
TRANS | 0.520 | 0.536 | 0.450 | 0.764 | 0.535 | 0.869 | ||
INF | 0.450 | 0.436 | 0.523 | 0.524 | 0.615 | 0.401 | 0.770 | |
PRC | 0.520 | 0.516 | 0.503 | 0.637 | 0.515 | 0.430 | 0.622 | 0.726 |
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.
Table 4 Direct Effect Results |
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Hypotheses | Relationship | (β) | Standard Deviation (STDEV) | T Statistics (|O/STDEV|) | P Values | Decisions |
H1 | INV-> SCS | 0.211 | 0.075 | 2.912 | 0.004 | Supported |
H2 | SRC-> SCS | 0.168 | 0.076 | 2.161 | 0.031 | Supported |
H3 | FCL-> SCS | 0.260 | 0.066 | 3.833 | 0.000 | Supported |
H4 | TRANS-> SCS | 0.538 | 0.063 | 8.518 | 0.000 | Supported |
H5 | INF-> SCS | 0.147 | 0.074 | 2.008 | 0.045 | Supported |
H6 | PRC-> SCS | 0.206 | 0.093 | 2.145 | 0.032 | Supported |
H7 | GSCI -> SCS | 0.362 | 0.069 | 5.295 | 0.000 | Supported |
H8 | INV-> GSCI | 0.111 | 0.035 | 3.161 | 0.002 | Supported |
H9 | SRC-> GSCI | 0.207 | 0.043 | 4.810 | 0.000 | Supported |
H10 | FCL-> GSCI | 0.447 | 0.109 | 3.999 | 0.025 | Supported |
H11 | TRANS-> GSCI | 0.332 | 0.108 | 3.051 | 0.003 | Supported |
H12 | INF-> GSCI | 0.151 | 0.013 | 11.580 | 0.000 | Supported |
H13 | PRC-> GSCI | 0.113 | 0.022 | 5.119 | 0.000 | Supported |
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.
Table 5 Indirect Effect |
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Hypotheses | Relationship | (β) | Standard Deviation (STDEV) | T Statistics (|O/STDEV|) | P Values | Decisions |
H14 | INV-> GSCI-> SCS | 0.133 | 0.046 | 2.908 | 0.004 | Supported |
H15 | SRC-> GSCI-> SCS | 0.108 | 0.041 | 2.690 | 0.007 | Supported |
H16 | FCL-> GSCI-> SCS | 0.109 | 0.017 | 6.399 | 0.000 | Supported |
H17 | TRANS-> GSCI-> SCS | 0.217 | 0.105 | 2.031 | 0.035 | Supported |
H18 | INF-> GSCI-> SCS | 0.325 | 0.111 | 2.909 | 0.003 | Supported |
H19 | PRC-> GSCI-> SCS | 0.231 | 0.021 | 2.809 | 0.023 | Supported |
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).
Table 6 Variance Explained |
|
Variance explained | |
SCS | 0.697 |