5.2. The structural models and hypothesis testing
Testing of the research hypotheses involved examination of four structural modlels assessing the restive causal paths as shown in Table 3.
The results indicate that all four models achieve acceptable fit. The modle diagnostics are shown in Table 4.
The Q-plot for the models was approximately linear with a slope near I suggesting the absence of major model misspecifications (Bagozzi and Yi, 1998; Bentler, 1990; Joreskog and Sorbom, estimated structural co-efficients. The results are shown in Table 5.
The results indicate the support for Hypotheses H1-H5. Hypothesis H6 that is tested in two of the models is not supported. For Hypothese H1-H5 the oath loadings between the latent variables had positive parameters and magnitudes that support the theoretical causal relationships. All parameters are significant as indicated by their t-values, which are well in excess of 2.00 (t-values for path co-efficients greater than 1.65 are significant at p<0.10; t-values greater than 1.96 are significant at p<0.05; t-values greater than 2.58 are significant at p<0.01).
Effectiveness (H4). Improvement in supply chain effectiveness is found to have strong positive influence on supply chain performance (H5). Overall the findings suggest that relationship orientation is extremely beneficial in the context of supply chains. Howerer, relationship orientation will not lead to greater innovation in supply chain (H6) but will only lead to innovation indirectly via organizational learning.
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