Exploring the Impact of Knowledge Management Dimensions on Organizational Performance: A Machine Learning Approach

Knowledge management represents a critical organizational capability for capturing, sharing, and leveraging collective knowledge to achieve strategic objectives in today’s competitive business environment. This research examines how the four essential aspects of knowledge management – sharing, creating, storing and using knowledge – are interrelated and affect the effectiveness of overall knowledge management. Survey data from 30 organizational respondents were analyzed using descriptive statistics, correlation analysis, and two predictive modeling approaches: linear regression and slope-increasing regression. The findings demonstrate strong positive correlations between all knowledge management practices and how well organizations perform, with correlation values between 0.85 and 0.96. Knowledge sharing showed the most powerful correlation with performance at 0.96, while knowledge application came in second at 0.92. Both prediction models performed remarkably well – the linear regression model explained 98.27% of the variance in the experimental data with an R² of 0.9827, and the slope-increasing regression model achieved 0.9283, showing that these four dimensions’ account for more than 92% of the variance in knowledge management performance. The findings suggest that balanced implementation across all knowledge management practices yields better organizational outcomes, with knowledge creation and knowledge use emerging as influential drivers of success. This research provides empirical evidence supporting integrated knowledge management strategies and offers practical insights for organizations looking to improve their knowledge management capabilities.