| description abstract | The primary concern in the residential projects industry is to implement a project with the optimal quality within the planned schedule and planned budget. Simulation is considered an effective tool for analyzing the construction process in residential projects because it considers behavior of feedback as well as the frequent changes with time. This study aimed to develop a system dynamics (SD) model to estimate the overall cost overrun risks in addition to allowing decision makers to anticipate the feedback of indefinite numbers of what-if questions considering highly dynamic uncertainty and dynamic risk interactions influencing residential project performance that traditional methods may miss. Major risks that can cause cost overruns in residential projects were initially identified through a review of related literature, a questionnaire survey, and several workshop rounds. Then, the model boundaries’ variables were identified, and a qualitative model was created through a causal loop diagram (CLD). Afterward, mathematical equations and relationships between variables were established in a stock-flow diagram. The proposed model consists of five subsystems to simulate how changes in dynamics of inspecting the completed works from the contractor’s and the consultant’s points of view; the probability of scope change; the material resources management process; the workforce hire-quit cycle; and the work-rework cycle can influence the cost performance of a residential project. The model was tested and validated using data derived from a residential project located in Egypt, and testing results showed that the simulated behavior of the model is the same as the actual behavior of the project. The sensitivity analysis results showed that increasing workforce more than the desired, scope changes, and rework rate are the parameters that cause the largest cost performance regression in residential projects. Simulation is considered an effective tool for analyzing the construction process in residential projects because it considers the behavior of feedback as well as frequent changes with time. In this research, a SD model is presented to estimate the overall cost overrun risks in addition to allowing decision makers to anticipate the feedback of indefinite numbers of what-if questions. The whole model is divided into five subsystems, which simplified the whole system into some more understandable ones. The model provides a framework for uncertain events that may influence cost performance in the construction industry such as the impact of global events (e.g., Russia–Ukraine war) on the supplies of building materials and their prices. The proposed system dynamics model provided a material-resource subsystem to simulate those kinds of global events and their influence on cost performance on construction projects. | |
