IDEAS home Printed from https://ideas.repec.org/a/cmj/seapas/y2017i15p331-346.html
   My bibliography  Save this article

Analysis Of Forecasting Methods From The Point Of View Of Early Warning Concept In Project Management

Author

Listed:
  • Florin POPESCU

    (Doctoral School - Entrepreneurship, Business Engineering & Management; University “Politehnica” of Bucharest, Romania)

Abstract

Early warning system (EWS) based on a reliable forecasting process has become a critical component of the management of large complex industrial projects in the globalized transnational environment. The purpose of this research is to critically analyze the forecasting methods from the point of view of early warning, choosing those useful for the construction of EWS. This research addresses complementary techniques, using Bayesian Networks, which addresses both uncertainties and causality in project planning and execution, with the goal of generating early warning signals for project managers. Even though Bayesian networks have been widely used in a range of decision-support applications, their application as early warning systems for project management is still new.

Suggested Citation

  • Florin POPESCU, 2017. "Analysis Of Forecasting Methods From The Point Of View Of Early Warning Concept In Project Management," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 15, pages 331-346, December.
    • Handle: RePEc:cmj:seapas:y:2017:i:15:p:331-346
    as

    Download full text from publisher

    File URL: http://seaopenresearch.eu/Journals/articles/SPAS_15_2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M Vanhoucke & S Vandevoorde, 2007. "A simulation and evaluation of earned value metrics to forecast the project duration," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1361-1374, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Richard E. Wendell & Timothy J. Lowe & Mike M. Gordon, 2023. "Dangers in using earned duration and other earned value metrics to measure a project’s schedule performance," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 665-680, June.
    2. H. Ooghe & C. Spaenjers & P. Vandermoere, 2005. "Business failure prediction: simple-intuitive models versus statistical models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/338, Ghent University, Faculty of Economics and Business Administration.
    3. Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
    4. D. Vantomme & M. Geuens & S. Dewitte, 2005. "How to Portray Men and Women in Advertisements? Explicit and Implicit Evaluations of Ads Depicting Different Gender Roles," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/319, Ghent University, Faculty of Economics and Business Administration.
    5. G. Poels & F. Gailly & A. Maes & R. Paemeleire, 2005. "Object Class or Association Class? Testing the User Effect on Cardinality Interpretation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/323, Ghent University, Faculty of Economics and Business Administration.
    6. Maarten Dossche & Gerdie Everaert, 2005. "Measuring Inflation Persistence: A Structural Time Series Approach," Computing in Economics and Finance 2005 459, Society for Computational Economics.
    7. I. Vermeir & M. Geuens, 2005. "Need for Closure and Youngsters’ Leisure Time Preferences," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/318, Ghent University, Faculty of Economics and Business Administration.
    8. E. Labro & M. Vanhoucke, 2005. "A simulation analysis of interactions between errors in costing system design," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/333, Ghent University, Faculty of Economics and Business Administration.
    9. J. Albrecht & M. Neyt & T. Verbeke, 2005. "Bureaucratisation and the growth of health care expenditures in Europe," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/335, Ghent University, Faculty of Economics and Business Administration.
    10. Bert Weijters & Maggie Geuens, 2002. "Evaluation of age-related labels by senior citizens," Vlerick Leuven Gent Management School Working Paper Series 2002-22, Vlerick Leuven Gent Management School.
    11. A. Karas & K. Schoors, 2005. "Heracles or Sisyphus? Finding, cleaning and reconstructing a database of Russian banks," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/327, Ghent University, Faculty of Economics and Business Administration.
    12. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2020. "The impact of a limited budget on the corrective action taking process," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1070-1086.
    13. Ünsal-Altuncan, Izel & Vanhoucke, Mario, 2024. "A hybrid forecasting model to predict the duration and cost performance of projects with Bayesian Networks," European Journal of Operational Research, Elsevier, vol. 315(2), pages 511-527.
    14. Ö Hazır & A Shtub, 2011. "Effects of the information presentation format on project control," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2157-2161, December.
    15. H. De Witte & E. Verhofstadt & E. Omey, 2005. "Testing Karasek’s learning- and strain hypothesis on young workers in their first job," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/326, Ghent University, Faculty of Economics and Business Administration.
    16. Wauters, Mathieu & Vanhoucke, Mario, 2017. "A Nearest Neighbour extension to project duration forecasting with Artificial Intelligence," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1097-1111.
    17. Knockaert, M. & Lockett, A. & Clarysse, B. & Wright, M., 2005. "Do human capital and fund characteristics drive follow-up behaviour of early stage high tech vcs?," Vlerick Leuven Gent Management School Working Paper Series 2005-20, Vlerick Leuven Gent Management School.
    18. P. Windels & J. Christiaens, 2005. "Management Reform in Flemish Local Authorities: Testing the Institutional Framework," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/331, Ghent University, Faculty of Economics and Business Administration.
    19. N. Geeroms & P. Van Kenhove & W. Verbeke, 2005. "Health Advertising to promote Fruit and Vegetable Intake: Application of need-related Health Audience Segmentation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/336, Ghent University, Faculty of Economics and Business Administration.
    20. Mostafa Salari & Homayoun Khamooshi, 2016. "A better project performance prediction model using fuzzy time series and data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(10), pages 1274-1287, October.

    More about this item

    Keywords

    Early warning; Forecasting methods; Project management;
    All these keywords.

    JEL classification:

    • L00 - Industrial Organization - - General - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cmj:seapas:y:2017:i:15:p:331-346. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Serghie Dan (email available below). General contact details of provider: https://seaopenresearch.eu/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.