The long-term operation, dynamic environment, and increased legislation of major infrastructure projects in China promote the transition to a sustainable operation and maintenance management model. However, this process is complex, and its underlying mechanism remains underexplored. To address this research gap, this study explores its driving mechanism based on an integrated methodological framework combining systematic literature review (SLR), interpretive structural modeling (ISM), and cross-impact matrix multiplication applied to classification (MICMAC).
The SLR was conducted to extract the factors influencing the sustainable operation and maintenance management transition in major infrastructure projects. The questionnaire survey was applied to identify key factors and their overall correlations. Building upon these findings, the ISM-MICMAC was employed to reveal the interrelationships and driving paths among key factors. Last, the driving mechanism was presented based on the above results.
The SLR analysis of 137 articles identifies 29 influencing factors across four dimensions: technology, organization, environment, and stakeholder. The questionnaire survey of 172 respondents confirms 20 key factors with interrelated relationships and emphasizes the prominent significance of the policy environment. The ISM-MICMAC analysis further delineates a ten-level, three-cluster hierarchical structure with driving paths, thus revealing the driving mechanism. Results indicate that external strategic orientation and core subject cognition constitute primary transition initiators, preparation in operation organizations is perceived as a prerequisite, and continuous improvement mainly depends on dynamic feedback among organizational resources, capabilities, and design.
The originality of this study relies on its attempt to explore the interrelationships and driving paths among multiple influencing factors for promoting sustainable operation and maintenance management transition of major infrastructure projects in China using the qualitative and quantitative analysis (i.e. SLR, questionnaire survey, and ISM-MICMAC analysis). The result provides a panoramic perspective and a valuable reference for the front-end decision-making and continuous improvement of the transition.
