Intense competitive pressures have forced firms to go beyond their
neighbourhoods to achieve competitive advantage. A feasible course of action
for firms is embracing supply chain integration. However, there is concern on
whether implementing supply chain integration results in enhanced firm
performance. Hence, the major aim of this research was to investigate the link
connecting supply chain integration implementation and performance of large
manufacturing companies in Kenya. In particular, the study examined the link
connecting supply chain integration, competitive advantage, environmental
dynamism to firm performance. The study was anchored on four theories;
resource-based view, resource dependence theory, systems theory and network
theory. A cross-sectional descriptive research design was applied with primary
data. The respondents of the study were persons overseeing supply chain
functions in the sampled firms. From a sample size of 200 firms, 94 usable
questionnaires were obtained resulting in a response proportion of 47%. The
main data analysis method was partial least squares structural equation
modelling (PLS-SEM). The study found that supply chain integration, competitive
advantage and environmental dynamism had a significant combined effect on firm performance.
The study affirms that the performance of manufacturing firms in Kenya can be
strengthened by implementation of supply chain integration. This helps to
settle the debate to some extent on whether it is fruitful for organizations to
integrate their supply chain operations. These outcomes are also in congruence
with resource-based perspective in the sense that integrating internal
operations can be regarded as a rare, non-substitutable, valuable and
imperfectly imitable resource. Moreover, the findings of the study are expected
to provide directions to scholars on the possible influence of supply chain
integration on organisational performance with the possibility of competitive
advantage and environmental dynamism acting as mediation and moderation
variables respectively. This is particularly pertinent in the context of the
developing world where such studies are scarce.
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