AUTOMATED SYSTEM-ENHANCED SUPPLY CHAIN PROCESSES AND THEIR EFFECT ON JOB REDUNDANCY AND WORKFORCE ADAPTABILITY AMONG LOGISTICS COMPANIES IN DELTA STATE

This study investigates the effect of automated system-enhanced supply chain processes on job redundancy and workforce adaptability among logistics companies in Delta State. Utilizing an econometric approach with Ordinary Least Squares (OLS), data were collected from 118 respondents across various firms to analyze the relationships between key technological variables and employment dynamics. The study considers six independent variables: Level of supply chain automation, Use of advanced technology, Automated inventory systems, Real-time tracking adoption, Digitalization in procurement and logistics, and Integration of automated systems. Two dependent variables are examined: Automation-related layoffs (Model 1) and Proficiency with automated systems (Model 2). In Model 1, the regression results reveal that Level of supply chain automation (β=0.321, p<0.01), Use of advanced technology (β=0.278, p<0.05), and Integration of automated systems (β=0.245, p<0.05) significantly contribute to automation-related layoffs, indicating that higher automation levels and technology adoption are associated with increased job redundancies. Conversely, Automated inventory systems (β=0.134, p>0.05), Real-time tracking adoption (β=0.089, p>0.05), and Digitalization (β=0.112, p>0.05) were not statistically significant. In Model 2, Proficiency with automated systems is positively influenced by Use of advanced technology (β=0.366, p<0.01), Digitalization (β=0.232, p<0.05), and Integration of automated systems (β=0.198, p<0.05), suggesting that technological integration enhances workforce skills and adaptability. Level of supply chain automation (β=0.095, p>0.05) and Automated inventory systems (β=0.072, p>0.05) did not significantly affect proficiency. The findings underscore that while increased automation and technological adoption may lead to job redundancies, they simultaneously contribute to workforce skill enhancement when proper training and digitalization are prioritized. Accordingly, logistics firms should develop comprehensive retraining programs to facilitate workforce adaptability and mitigate unemployment risks associated with automation. Policymakers should also encourage investments in employee up skilling to maximize the benefits of technological advancements while minimizing adverse employment effects.