Knowledge Management drivers and Organizational Preformance: A PLS-SEM and FSQCA approach

Aim Knowledge is a key strategic resource for modern organizations, crucial for achieving competitive advantage, resilience, and long-term performance. Although organizations increasingly invest in knowledge management (KM) initiatives and systems, the success of their implementation largely depends on the broader organizational context and the interaction of various organizational drivers. Hence, this study aims to examine how organizational drivers shape knowledge management practices and contribute to organizational performance (OP). Methodology: Empirical analysis was conducted on a sample of organizations in Serbia, using a combined methodological approach that integrates structural equation modeling based on partial least squares (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). Results The results of PLS-SEM analysis confirmed theoretical model showing that studied organizational elements have significant positive impact on KM. The fsQCA results reveal that KM alone does not guarantee high performance, and it rather must be part of certain organizational configurations to be effective. In this sense, there are six configurations for successful KM implementation in Serbian companies, that results in high OP. Implications and recommendations: The findings indicate that high organizational performance can be achieved through different KM-driven configurations, meaning that firms should avoid one-size-fits-all solutions and instead align KM practices with their dominant organizational drivers, depending on their organizational context and resource constraints. Originality/value: By integrating two complementary methodologies, the study provides novel insights from a transition economy and highlights the value of this approach for exploring both direct and complex causal relationships, offering results that can serve as a benchmark for other transition economies.