Combination of a Nonlinear Regression Model and Earned Schedule to Forecast a Project Final Cost

Tipo di pubblicazione: Articolo in atti di convegno
Tipologia MIUR: Contributo in Atti di Convegno (Proceeding) > Contributo in atti di convegno
Titolo: Combination of a Nonlinear Regression Model and Earned Schedule to Forecast a Project Final Cost
Autori: Narbaev T., De Marco A.
Autori di ateneo:
Intervallo pagine: pp. 22-25
Tipo di referee: Tipo non specificato
Editore: EVM Europe Association
Titolo del convegno: The 4th European Conference on Integrated Projects Controls
Luogo dell'evento: Twente (The Netherlands)
Data dell'evento: 28-29 November 2012
Rilevanza dell'evento: Internazionale
Luogo di pubblicazione: Amsterdam
Abstract: Accurate forecasting of a project's Cost Estimate at Completion (CEAC) based on current performance and progress is one the main issues in project monitoring and control. For decades, Earned Value Management (EVM) has been proved itself as a valuable tool to fulfill this task and cost estimates calculated by its Cost Performance Index (CPI) are widely applicable for projects of any type and size. However, recent studies show that the CPI-based method may be valid only for large projects with long durations. As an alternative to the index-based method, techniques with regression analysis gained a great insight in this direction. The purpose of this work is to propose a new regression-based nonlinear CEAC methodology which integrates Earned Schedule (ES) concept to assume a project progress in calculating CEAC as early as when a project is 20 percent complete. The paper sets three objectives to achieve the research purpose: development of the new equation based on a nonlinear regression modelling and ES method; validation of the new technique through case study application; and, providing a comparison with CPI-based estimates to determine the best performing equation. Testing the prediction accuracy of the proposed and index-based formulae is performed by comparing values of Percentage Error (PE) and Mean Absolute Percentage Error (MAPE). Based on six case studies from construction industry, the comparison reveals that the new methodology generates better estimates (MAPE=2,88 percent) than those calculated by traditional index-based equation (MAPE=9,98 percent)
Data: 2012
Status: Pubblicato
Lingua della pubblicazione: Inglese
Parole chiave: earned value, earned schedule, cost estimate at completion, nonlinear models, construction projects, project management
Dipartimenti (originale): DIGEP - Dipartimento di Ingegneria Gestionale e della Produzione
Dipartimenti: DIGEP - Dipartimento di Ingegneria Gestionale e della Produzione
URL correlate:
    Area disciplinare: Area 09 - Ingegneria industriale e dell'informazione > IMPIANTI INDUSTRIALI MECCANICI
    Data di deposito: 10 Dic 2012 17:28
    Data ultima modifica (IRIS): 10 Dic 2013 08:06:43
    Data inserimento (PORTO): 29 Ott 2014 19:00
    Link resolver URL: Link resolver link


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