Supply Chain Collaboration and Logistics Performance: The Role of Supply Chain Integration and Big Data Analytics
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Date
2023
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KNUST
Abstract
This study examined the effects of supply chain integration and big data analytics on the relationship between supply chain collaboration and logistics performance. The motivation for the study is that although supply chain collaboration is recognized as critical for supply chain efficiency, research has shown inconsistent results regarding its impact on performance outcomes. Furthermore, the mechanisms through which supply chain collaboration drives performance have not been thoroughly examined. Using the resource-based view as the theoretical lens, the study develops a model that posits supply chain integration and big data analytics as moderators in the supply chain collaboration-logistics performance relationship. The objectives are to examine the direct effect of supply chain collaboration on logistics performance and the moderating roles of supply chain integration and big data analytics. The study adopts a quantitative approach with a sample of 385 firms. Data is collected via questionnaires and analyzed using regression analysis. The key findings indicate a significant positive relationship between supply chain collaboration and logistics performance. However, supply chain integration and big data analytics individually do not significantly moderate this relationship. Rather, the interaction between supply chain integration and big data analytics positively and significantly moderates the effect of supply chain collaboration on logistics performance. The study recommends supply chain managers to improve collaborative practices with partners through increased information sharing, coordinating decision-making, and aligning incentives. The research recommends that supply chain integration and big data analytics tools should be used together to enhance collaboration, which can lead to improved logistics performance. The study contributes by elucidating the mechanisms through which supply chain collaboration drives logistics performance.
Description
A thesis submitted to the Department of Supply Chain and Information Systems, Institute of Distance Learning, in partial fulfilment of the requirements of the award of the degree of Master of science in Logistics and supply chain management