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Using activity sensitivity and network topology information to monitor project time performance


  • Vanhoucke, Mario


The interest in activity sensitivity from both the academics and the practitioners lies in the need to focus a project manager's attention on those activities that influence the performance of the project. When management has a certain feeling of the relative sensitivity of the various parts (activities) on the project objective, a better management's focus and a more accurate response during project tracking should positively contribute to the overall performance of the project. In the current research manuscript, a simulation study is performed to measure the ability of four basic sensitivity metrics to dynamically improve the time performance during project execution. We measure the use of sensitivity information to guide the corrective action decision making process to improve a project's time performance, while varying the degree of management's attention. A large amount of simulation runs are performed on a large set of fictitious project networks generated under a controlled design.

Suggested Citation

  • Vanhoucke, Mario, 2010. "Using activity sensitivity and network topology information to monitor project time performance," Omega, Elsevier, vol. 38(5), pages 359-370, October.
  • Handle: RePEc:eee:jomega:v:38:y:2010:i:5:p:359-370

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    References listed on IDEAS

    1. Elmaghraby, Salah E., 2000. "On criticality and sensitivity in activity networks," European Journal of Operational Research, Elsevier, vol. 127(2), pages 220-238, December.
    2. Williams, Terry, 1999. "Towards realism in network simulation," Omega, Elsevier, vol. 27(3), pages 305-314, June.
    3. Hans, E.W. & Herroelen, W. & Leus, R. & Wullink, G., 2007. "A hierarchical approach to multi-project planning under uncertainty," Omega, Elsevier, vol. 35(5), pages 563-577, October.
    4. Eilat, Harel & Golany, Boaz & Shtub, Avraham, 2008. "R&D project evaluation: An integrated DEA and balanced scorecard approach," Omega, Elsevier, vol. 36(5), pages 895-912, October.
    5. Bajis M. Dodin & Salah E. Elmaghraby, 1985. "Approximating the Criticality Indices of the Activities in PERT Networks," Management Science, INFORMS, vol. 31(2), pages 207-223, February.
    6. Genaro J. Gutierrez & Panagiotis Kouvelis, 1991. "Parkinson's Law and Its Implications for Project Management," Management Science, INFORMS, vol. 37(8), pages 990-1001, August.
    7. Anthony A. Mastor, 1970. "An Experimental Investigation and Comparative Evaluation of Production Line Balancing Techniques," Management Science, INFORMS, vol. 16(11), pages 728-746, July.
    8. Fatemi Ghomi, S. M. T. & Teimouri, E., 2002. "Path critical index and activity critical index in PERT networks," European Journal of Operational Research, Elsevier, vol. 141(1), pages 147-152, August.
    9. Elmaghraby, S. E. & Fathi, Y. & Taner, M. R., 1999. "On the sensitivity of project variability to activity mean duration," International Journal of Production Economics, Elsevier, vol. 62(3), pages 219-232, September.
    10. Durbach, Ian N. & Stewart, Theodor J., 2009. "Using expected values to simplify decision making under uncertainty," Omega, Elsevier, vol. 37(2), pages 312-330, April.
    11. Huang, Chi-Cheng & Chu, Pin-Yu & Chiang, Yu-Hsiu, 2008. "A fuzzy AHP application in government-sponsored R&D project selection," Omega, Elsevier, vol. 36(6), pages 1038-1052, December.
    12. M. Vanhoucke, 2008. "The effect of project schedule adherence and rework on the duration forecast accuracy of earned value metrics," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 08/524, Ghent University, Faculty of Economics and Business Administration.
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    Cited by:

    1. 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.
    2. Cui, Nanfang & Demeulemeester, Erik & Bie, Li, 2016. "Incorporation of activity sensitivity measures into buffer management to manage project schedule riskAuthor-Name: Hu, Xuejun," European Journal of Operational Research, Elsevier, vol. 249(2), pages 717-727.
    3. Colin, Jeroen & Vanhoucke, Mario, 2014. "Setting tolerance limits for statistical project control using earned value management," Omega, Elsevier, vol. 49(C), pages 107-122.
    4. repec:eee:ejores:v:262:y:2017:i:1:p:274-286 is not listed on IDEAS
    5. repec:eee:reensy:v:167:y:2017:i:c:p:464-473 is not listed on IDEAS
    6. Plaza, Malgorzata, 2016. "Balancing the costs of human resources on an ERP project," Omega, Elsevier, vol. 59(PB), pages 171-183.
    7. Vanhoucke, Mario, 2011. "On the dynamic use of project performance and schedule risk information during projecttracking," Omega, Elsevier, vol. 39(4), pages 416-426, August.

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