文摘
Supply-chain management has become very challenging because business bathers are down, competition is up, stakes are higher, and profit margins are low. Logistics professionals are under tremendous pressure to remain competitive as retail firms are experiencing an annual customer exchange rate of about 25%, reducing the profit by 3.8% per firm, and resulting in a loss of approximately $100 billion per year in the United States. A conceptual model was developed and an ordinal regression model adopted to determine the relationship among three predictor variables: inventory control, logistics improvement, supply-chain management system, and one criterion variable: system-performance improvement. The survey participants were from logistics industries across the contiguous United States, using an area cluster sampling method for a required sample size of 212 respondents. The resulting analysis for Model 1 indicates that inventory control accounted for 37% of the variance in supply-chain management (
R2 = .37, p < .001). In Model 2, logistics improvement accounted for 18% of the variance in supply-chain management (R2 = .18, p < .001) in the first step. With the inventory control variables entered in Step 2, the proportion accounted for by logistics improvement increased (β = .231, p < .001) by about 5% (β2 ). The inclusion of the supply-chain management variables raised the proportion to a total of 24% (ΔR2 = .24, p < .001). The total amount of variance accounted for by Model 2 was 42% (R2 = .42, p < .001). Therefore, logistics improvement operates as a moderator variable between inventory control and supply-chain management. It is recommended that logistics professionals should focus on the strong relationship between the three predictor variables and one criterion variable identified as essential for the success of the supply chain system. Additionally, logistics improvement is a moderating predictor variable that influences the relationship between inventory control and supply-chain management for the overall success of the system-performance improvement (criterion variable). Further research should include using other nonparametric regression models to replicate these results and replicating study to ascertain the predictor and criterion variables identified as essential to the success of the supply-chain management system.
