Project Efficiency Estimation Based on Dynamic Simulation Model of Earned Value Management

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Earned Value Management (EVM) is known as an efficient and well-known tool for project management. Examining various sources, it was observed that although the EVM analytical model has introduced good indicators for measuring project progress, it is weak in estimating the final cost of the project and does not predict the process of cost change and project efficiency. On the other hand, nothing has been done so far to use system dynamics in EVM.Therefore, considering the capacity of system dynamics in modeling complex systems and setting parameters dynamically based on model variables, the main problem of modeling research is the value model obtained by simulating system dynamics. The dynamic hypothesis of the research was that there are dynamics between the main indicators of EVM. Identifying these dynamics and the way they affect each other can lead to estimating the process of changing costs and project efficiency by the end of the project.Through presenting the causal loop diagram and the stack flow diagram of the proposed model, the variables were determined and after simulation, the model was validated by performing various tests and different policy scenarios were presented.The comparison of the results of the research simulation model with the results of the EVM analytical model revealed that there is a slight difference between the results and the efficiency. The main contribution of the research is the creation of a simulation model based on system dynamics as the core of the simulation to estimate the trend and the final amount of efficiency and cost of the project, which can be part of a more comprehensive simulation model.This can be used to determine the impact of various project management functions on improving project efficiency, which is the main suggestion for further research.
Language:
Persian
Published:
Journal of Productivity Management, Volume:17 Issue: 64, 2023
Pages:
49 to 69
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