Unlocking knowledge power in an emerging market: a structural–configurational framework

Purpose The purpose of this study is to explore the determinants of knowledge management system (KMS) adoption among corporate employees in an emerging economy, by using a hybrid methodological approach that combines structural modelling and fuzzy set qualitative comparative analysis (fsQCA) to uncover both net effects and configurational pathways to adoption. Design/methodology/approach A quantitative research design was adopted, using survey data collected from 234 corporate employees in Sri Lanka. The proposed model, grounded in the Technology Acceptance Model and Knowledge-Based View, was tested using Partial Least Squares Structural Equation Modeling to assess direct and moderating relationships among the constructs. In addition, fsQCA was used to identify causal configurations or synergistic combinations of factors that best explain the adoption of KMS. Findings The results of this study show knowledge acquisition and sharing enhance perceived usefulness and ease of use, driving KMS adoption. Technology anxiety weakens usefulness–adoption but strengthens ease–adoption links. Tech-savviness shows no effect. fsQCA reveals multiple causal configurations for high and low adoption, highlighting complex condition interplay and supporting a configurational perspective. Practical implications Organizations should focus on developing intuitive KMS interfaces, fostering knowledge-sharing cultures and implementing targeted training to address technology anxiety. The findings of this study emphasize that system design and organizational support may outweigh individual technical skills in adoption decisions. Originality/value This study advances the understanding of KMS adoption in emerging economy contexts by integrating the Technology Acceptance Model with the Knowledge-Based View. This study uniquely applies a Hybrid Structural–Configurational Approach.