INFLUENCE OF E-LOGISTICS ON SUPPLY CHAIN PERFORMANCE OF MANUFACTURING FIRMS, IN UASIN GISHU COUNTY, KENYA. MODERATED BY ELECTRONIC RESOURCE PLANNING

Abstract

Supply chain performance is crucial for businesses to increase efficiency, reduce expenses, and meet changing client needs in a competitive environment. However, manufacturing firms in Kenya face challenges such as competition, high production costs, and untimely product availability. This study aimed to examine the moderating

influence of Enterprise Resource Planning (ERP) on the relationship between e- logistics and supply chain performance of manufacturing firms in Uasin Gishu

County, Kenya. Specific objectives were to assess the influence of electronic order processing, transportation management, automated warehousing, inventory management, and enterprise resource planning systems on supply chain performance. The study further assessed the moderating influence of enterprise resource planning on the relationship between electronic order processing, transportation management, automated warehousing, inventory management systems, and supply chain performance of these firms. The study was guided by Resource-Based, Innovation, and Transaction Cost Theories. Explanatory research design and a census approach were adopted in collecting data using a closed-ended questionnaire from 270 Heads of 9 Departments closely linked to the study variables in 30 manufacturing firms. Cronbach’s alpha and factor analysis were used to assess reliability and construct validity. Data analysis was performed using descriptive and inferential statistics, with a hierarchical regression model used to test all the study hypotheses. Results indicate that firm age (β=0.190, p = 0.021) significantly influences supply chain performance while firm size (β=0.101, p=0.223) does not. These control variables explain 4.8% of the variance in supply chain performance, as shown by an R2

of 0.048. Findings further revealed that electronic order processing system (β1=0.316, p=0.001), transportation management system (β2=0.167, p=0.011), automated warehousing systems (β3=0.217, p=0.008), and inventory management system (β4=0.232, p=0.001) significantly influence supply chain performance. These variables explain 56.6% of the variance in supply chain performance (R2 = 0.566 inclusive of the controls) and 51.8% (∆R2 = 518 exclusive of the controls). Results further indicate that ERP (β=0.094, p=0.010), influences supply chain performance. It explains 1.2% of the variation in supply chain performance (∆R2 =0.12). Furthermore, ERP was found to moderate the relationship between electronic order processing system (β=0.100, p=0.000), transportation management system (β=0.054, p=0.012), inventory management system (β=-0.120, p=0.002), and does not moderate the link between automated warehousing system and supply chain performance (β=-0.013, p=0.701). The entire Hierarchical model accounts for 64.5% (R2 = 0.645) of the variance in supply chain performance, much more than the direct effect model, which explains 56.6% (R2 = 0.566). The study concludes that electronic order processing, transport management, automated warehousing, inventory management systems, and ERP influence supply chain performance. ERP moderates the link between electronic order processing, transport management, inventory management systems, and supply chain performance, but does not moderate automated warehousing systems and supply chain performance. This study contributes to knowledge by examining the interaction of ERP and study variables. Future scholars will benefit from the study's findings as they conduct new research in e-logistics and supply chains in various industries. The policymakers and management may use the results to develop policies and strategies for investing in e-logistics and ERP, as these enhance efficiency in supply chain performance.