Integration of risk-oriented planning into schedule forecasting of construction projects under economic instability
DOI:
https://doi.org/10.32347/2707-501x.2022.49(2).293-304Keywords:
risk-oriented planning, schedule forecasting, construction projects, calendar planning, risk management, network modelsAbstract
The article is devoted to the study of integrating risk-oriented planning into the forecasting of construction project timelines in the context of economic instability. The proposed approach enables the consideration of various risks to improve the accuracy of schedule planning and to enhance the resilience of construction projects. The aim of the study is to develop methodological foundations for integrating risk-oriented planning into the process of timeline forecasting for construction projects, contributing to the creation of flexible schedule models capable of minimizing the impact of economic fluctuations and other risk factors. A systems approach is applied, incorporating network planning methods, statistical analysis of data from previous projects, and risk modeling based on a hierarchical data structure. The scientific results reveal that risk-oriented planning ensures more accurate forecasting by accounting for risk hierarchies at the project, system, and organizational levels. The proposed model allows for the identification of key risks, such as economic volatility, delays in material supply, and accidents, and integrates them into execution schedules through buffer time and scenario modeling. The use of network models and predictive analytics increases management flexibility, enabling timely adjustments to plans and resource optimization. The findings confirm that systematic risk consideration reduces the likelihood of schedule disruptions and enhances the organizational and technological reliability of construction projects and decision-making processes. Future research prospects include improving quantitative risk assessment methods using artificial intelligence to forecast complex scenarios and developing automated risk management systems integrated with BIM technologies. Further studies may also focus on analyzing the impact of global economic trends on the construction industry and creating universal models for projects of various scales and implementation timelines.
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