# Systematic Review on the Use of CCPM in Project Management: Empirical Applications and Trends
## 4 Discussion
Using algorithms such as NSGA-II and utility-based evaluation methods, these solutions are tested in multi-project environments with severe resource constraints, showing significant improvements in schedule stability and decision-making support [17; 45; 50; 51; 55; 66]. Regarding risk management, CCPM has been enhanced with analytical techniques such as Fuzzy FMEA, Fault Tree Analysis (FTA), Event Tree Analysis (ETA), and Schedule Risk Analysis (SRA). These models increase the capacity to anticipate failures, quantify impacts, and proactively adjust buffers--even in engineering scenarios with high structural and operational risks [9; 57]. From a strategic perspective, studies like [PERSON] et al. [76] emphasize that the effectiveness of models, such as CCPM, depends on a deep understanding of project success criteria, considering the expectations of multiple stakeholders. This reinforces the need to align planning tools, such as CCPM, with the qualitative dimensions of project management, including value perception, cross-functional collaboration, and strategic alignment. An important contribution--though still concentrated in theoretical modeling and simulation--comes from generic and cross-sectoral models proposing new buffer sizing methods based on attributes such as network complexity, activity criticality, flexibility, network propagation, and risk distribution. Although lacking empirical validation, these approaches are essential for expanding the applicability of CCPM [10; 27; 28; 34; 39; 48; 60; 61; 65; 68; 70; 73; 76]. The advancement of such generic approaches is further supported by the incorporation of real-time digital monitoring platforms, as demonstrated by [PERSON] et al. [11], who proposed a scalable platform for machine tool monitoring that could be integrated with CCPM. This digitalization of shop floor or construction site operations enables real-time buffer updates, improving the accuracy of consumption management and responsiveness to unexpected events. Several studies report real-world applications of CCPM in sectors such as aircraft maintenance [58], energy infrastructure [10], and industrial product development [59; 62; 67]. These cases demonstrate that CCPM can be successfully adapted to environments with high resource interdependence and customization demands, underscoring the need to further investigate its potential in complex and dynamic sectors. This article offers a comprehensive and methodologically rigorous contribution to the field of project management by mapping and critically analyzing 62 empirical and conceptual studies on the application of Critical Chain Project Management (CCPM). Through a systematic literature review, the research presents a comprehensive overview of the evolution of CCPM in both academic and practical contexts over the past decade. One of its key contributions lies in identifying trends that reflect increasing methodological sophistication and interdisciplinary integration of CCPM, particularly through combinations with agile methods, BIM, Lean tools, and advanced modeling techniques, such as fuzzy logic and genetic algorithms. The temporal scope, spanning since 2014, enables a longitudinal and in-depth analysis of the current state of CCPM research. The findings reveal a clear predominance of modeling and simulation approaches, which, although valuable, also point to a gap in qualitative and empirically grounded investigations. Furthermore, the concentration of applications in sectors such as construction, IT, and energy, and the relative scarcity of studies in Engineer-to-Order (ETO) environments or service-based organizations, emphasize the need for future research in underexplored organizational contexts. The article also stands out for its ability to articulate theoretical contributions with practical relevance.