A hybrid forecasting model to predict the duration and cost performance of projects with Bayesian Networks

Izel Ünsal-Altuncan and Mario Vanhoucke

European Journal of Operational Research, 2024, vol. 315, issue 2, 511-527

Abstract: This paper presents a new hybrid forecasting model to predict the final time and cost of a project using input parameters from the project scheduling and risk analysis literature. The hybrid method integrates two well-known risk models. A Structural Equation Modeling constructs and validates a theoretical risk model to represent known relations between project indicators and the project performance. A Bayesian Networks is used to train the theoretical model using artificial project data from the literature. These two integrated models are then used to predict the final duration and cost of a new unseen project.

Keywords: Project scheduling; Project forecasting; Risk models; Earned value management (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:315:y:2024:i:2:p:511-527

DOI: 10.1016/j.ejor.2023.12.029

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