Measuring knowledge management capabilities in project-based engineering firms: evidence from China’s water engineering sector

Purpose This study aims to develop and validate a measurement framework for assessing knowledge management (KM) as an organizational capability in project-based engineering firms, with a specific focus on China’s water engineering sector. Design/methodology/approach Survey data were collected from middle- and senior-level managers in member firms of the China Water Engineering Association. A two-stage scale validation approach was employed. Exploratory factor analysis was first conducted to identify the underlying factor structure, followed by confirmatory factor analysis to assess measurement reliability and construct validity. Findings The results support a four-dimensional KM framework comprising knowledge sharing, knowledge application, knowledge acquisition and knowledge creation. The findings indicate that these KM processes are empirically distinct yet interrelated, reflecting the cyclical and capability-based nature of knowledge management in project-intensive engineering environments. Research limitations/implications The study is based on cross-sectional data from a single industry context, which may limit generalizability. Future research could apply the validated scale across different sectors, countries and longitudinal settings to further examine the dynamics and outcomes of KM capabilities. Practical implications The validated measurement scale provides managers with a diagnostic tool to assess strengths and weaknesses in organizational knowledge management practices. By systematically strengthening the four KM dimensions, organizations can enhance learning, adaptation and innovation in complex and uncertain project-based environments. Originality/value Rather than introducing new constructs, this study refines and validates the measurement of established KM processes by demonstrating how they operate as interdependent organizational capabilities in project-based engineering firms, contributing to more rigorous and context-sensitive KM research.