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A better project performance prediction model using fuzzy time series and data envelopment analysis

Author

Listed:
  • Mostafa Salari

    (University of Calgary)

  • Homayoun Khamooshi

    (George Washington University)

Abstract

Earned value management (EVM) is a critical project management methodology that evaluates and predicts project performance from cost and schedule perspectives. The novel theoretical framework presented in this paper estimates future performance of a project based on the past performance data. The model benefits from a fuzzy time series forecasting model in the estimation process. Furthermore, fuzzy-based estimation is developed using linguistic terms to interpret different possible conditions of projects. Eventually, data envelopment analysis is applied to determine the superior model for forecasting of project performance. Multiple illustrative cases and simulated data have been used for comparative analysis and to illustrate the applicability of theoretical model to real situations. Contrary to EVM-based approach, which assumes the future performance is the same as the past, the proposed model can greatly assist project managers in more realistically assessing prospective performance of projects and thereby taking necessary and on-time appropriate actions.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:10:d:10.1057_jors.2016.20
    DOI: 10.1057/jors.2016.20
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    References listed on IDEAS

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    1. Lovell, C. A. Knox & Pastor, Jesus T., 1999. "Radial DEA models without inputs or without outputs," European Journal of Operational Research, Elsevier, vol. 118(1), pages 46-51, October.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. 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.
    4. Osama Moselhi & Ji Li & Sabah Alkass, 2004. "Web-based integrated project control system," Construction Management and Economics, Taylor & Francis Journals, vol. 22(1), pages 35-46.
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    Cited by:

    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. Sabahi, Sima & Parast, Mahour Mellat, 2020. "The impact of entrepreneurship orientation on project performance: A machine learning approach," International Journal of Production Economics, Elsevier, vol. 226(C).

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