# Systematic Review on the Use of CCPM in Project Management: Empirical Applications and Trends
## 4 Discussion
Although these models exhibit a high level of technical sophistication (e.g., fuzzy logic, genetic algorithms, machine learning, or stochastic simulations), they lack empirical validation. As such, their practical feasibility and required adaptations for real-world scenarios remain uncertain. Nonetheless, these studies are methodologically valuable, as they advance the theoretical foundation of CCPM and provide adaptable tools for future research. The integration of CCPM with complementary methodologies, tools, and technologies has emerged as a central vector of innovation in contemporary project management applications. This trend not only enhances the classical benefits of methods, such as schedule reduction and efficient resource utilization, but also expands their adaptability to different organizational contexts, particularly in high-variability and complexity environments. One of the most evident approaches is the combination of CCPM with agile methods, especially SCRUM. This integration has proven particularly effective in software development and IT project environments, where iterative cycles and flexibility are critical. SCRUM contributes with responsiveness and continuous stakeholder interaction, while CCPM provides a solid framework for schedule control and strategic buffers, supporting on-time delivery [19; 52]. The result is a balance between adaptability and reliability, essential in innovation-driven settings. In the construction industry, the integration of CCPM with Building Information Modeling (BIM)--especially in its 4D format--is gaining traction. Studies report significant reductions in project timelines, such as optimizing structural timelines from 432 to 293 days, as well as improvements in spatial coordination and scheduling [6; 8]. This synergy between 3D planning and project timeline management enhances predictability and cost control. Another promising avenue is the combination of CCPM with Lean approaches, such as the 5 Whys, FMEA, and waste mapping techniques. These strategies improve operational efficiency by eliminating waste and increasing the reliability of estimates without buffer consumption, as demonstrated in dam construction projects [7]. The Theory of Constraints (TOC)--the conceptual foundation of CCPM--has been deepened in studies that employ its logical tools, such as the Current and Future Reality Trees, to identify and mitigate systemic bottlenecks in multi-project systems. Practical applications in highway construction and production systems demonstrate that these tools facilitate strategic prioritization and organizational alignment [20; 26; 36; 69]. Integration fosters a continuous improvement environment that focuses on delivering value. It is evident that the integration between CCPM and other tools and methodologies is being applied and yields positive results for the projects. A wide range of studies highlights the use of advanced modeling and simulation for buffer sizing and schedule optimization, employing techniques such as fuzzy logic, genetic algorithms, support vector regression, and Monte Carlo analysis, among others. These approaches allow for more accurate uncertainty representation and tailored planning according to project dependencies, variability, and resource constraints [5; 9; 10; 29; 31; 33; 36; 38; 40; 41; 42; 44; 46; 60; 72], and the result is more robust schedules, lower rework rates, and improved delivery reliability. Moreover, the number of studies combining CCPM with schedule monitoring and control systems is growing. These include the Last Planner System (LPS), Linear Scheduling Method (LSM), and Earned Value Management (EVM/ES). Such integrations enhance responsiveness to deviations through dynamic buffer tracking and the definition of control triggers, such as the Activity Criticality Index (CRI) [29; 37; 47; 50; 51; 53; 56; 60; 74]. Some studies on multi-objective and multi-attribute optimization have also incorporated CCPM into frameworks designed to balance time, cost, quality, and robustness.