APPLYING REGRESSION ANALYSIS TO IDENTIFY KEY FACTORS AFFECTING SUPPLY CHAIN EFFICIENCY AND DELIVERY TIMES

This study applies regression analysis to identify key factors influencing supply chain efficiency and delivery times between 2020 and 2024. The research aims to quantify the impact of transportation costs, inventory management, supplier lead times, and technological adoption on overall supply chain performance. A multiple regression model was employed using secondary data from industry reports, academic journals, and supply chain databases. Results indicate that technology adoption has the highest positive effect on efficiency (β = 1.40, p < 0.01), while supplier lead time negatively impacts performance (β = -0.50, p < 0.01). Additionally, customer satisfaction correlates negatively with delivery times (r = -0.75, p < 0.01), emphasizing the importance of faster order fulfillment. The overall correlation coefficient (r = 0.91) demonstrates a strong positive relationship between technological advancements and supply chain efficiency. Based on these findings, businesses should invest in AI-driven logistics, enhance supplier reliability, and optimize transportation strategies to improve operational resilience and market competitiveness.