Impact of Organizational Context on Construction Project-based Organizations’ Learning from Incidents based on Structural Equation Modelling and System Dynamics
DOI:
https://doi.org/10.56042/jsir.v84i8.4954Keywords:
Conservation of resource (COR) theory, Learning from incidents, Organizational context, System dynamicsAbstract
Current research paradigms examining factors influencing Learning from Incidents (LFI) primarily rely on static, unidirectional, and linear frameworks that fail to account for nonlinear interactions between causal elements and systemic dependencies, consequently perpetuating structural deficiencies in LFI implementation. Addressing this critical gap, our research develops an integrated SEM-SD analytical framework through a socio-psychological lens and Conservation of Resource (COR) theory, systematically mapping both exogenous and endogenous determinants alongside their synergistic co-evolution trajectories within construction project systems. Utilizing 154 valid questionnaires from Chinese construction organizations, the study employs dual validation approaches – SEM and SD to analyze multi-level relationships between factors. Key findings demonstrate that psychological safety exerts greater influence on the LFI systems in dynamic environments than in static conditions. Leader inclusiveness shows a significant positive impact on psychological safety alongside nonlinear progressive effects on LFI behaviors. Organizational support maintains direct positive correlations with both psychological safety and leader inclusiveness while dynamically enhancing relational identification and LFI outcomes through evolutionary system interactions. Incentive mechanisms operate as double-edged swords, necessitating context-sensitive calibration to balance their effects. Crucially, positive organizational contexts significantly improve LFI performance, which subsequently strengthens contextual conditions through performance feedback, creating self-reinforcing improvement cycles. This methodological advancement combines empirical validation with dynamic feedback analysis, surpassing traditional static approaches and deepening theoretical understanding of behavioral mechanisms driving effective LFI implementation in construction contexts.