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2023 | z. 188 Współczesne zarządzanie = Contemporary management | 243--257
Tytuł artykułu

Metrics Based Project Time Management - Application of Linear Programming

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: The purpose of the article is to develop an algorithm updating the estimated duration based on metrics and linear programming in the execution phase of the project. A secondary objective is to prove that the acceptance of the metrics-based approach by practitioners is highly probable.

Design/methodology/approach: We combine linear programming with metrics based project management and propose an algorithm updating the initial project duration estimation during project execution. Survey has been used to verify the knowledge and acceptance degree of metrics based management among project management practitioners. An computational example is used to illustrate the application and potential benefits of the proposed algorithm. Findings: It has been shown that metrics based updating of initial project duration estimation can be extremely important for project time management, and thus project success, and that this approach is technically not difficult to implement in practice. It has been also proven that such an approach has high chances of being accepted in practice.

Research limitations/implications: In our research a theoretical example has been used with a limited selection of metrics. Real world cases and close cooperation with project managers and other stakeholders is needed in order to improve and adapt the approach to actual needs of practical project management.

Practical implications: The proposed approach may substantially improve the prediction quality of project duration and, consequently, increase project success probability.

Originality/value: An original algorithm for project duration updating during project execution has been proposed. This algorithm is based on metrics that should measure all the important phenomena that decrease the quality of the prediction of project duration, also human related ones, and on linear programming. No similar approach has been identified in the literature.(original abstract)
Twórcy
autor
  • Wroclaw University of Science and Technology, Wroclaw, Poland
  • Wrocław University of Science and Technology, Poland
  • Wrocław University of Science and Technology, Poland
Bibliografia
  • 1. Batselier, J., Vanhoucke, M. (2017). Improving project forecast accuracy by integrating earned value management with exponential smoothing and reference class forecasting. International Journal of Project Management, 35(1), 28-43. https://doi.org/https://doi.org/ 10.1016/j.ijproman.2016.10.003
  • 2. Espinoza, R., Presbitero, A.F. (2022). Delays in public investment projects. International Economics, 172. https://doi.org/10.1016/j.inteco.2021.10.002
  • 3. Fleming, Q.W., Koppelman, J.M. (1997). Earned value project management. Cost Engineering (Morgantown, West Virginia), 39(2). https://doi.org/10.1016/s0263- 7863(97)82251-x
  • 4. Flyvbjerg, B. (2006). From Nobel Prize to Project Management: Getting Risks Right. Project Management Journal, 37(3). https://doi.org/10.1177/875697280603700302
  • 5. Flyvbjerg, B. (2021). Top Ten Behavioral Biases in Project Management: An Overview. Project Management Journal, 52(6). https://doi.org/10.1177/87569728211049046
  • 6. Hulett, D. (2016). Integrated Cost-Schedule Risk Analysis. Taylor & Francis. https://books.google.pl/books?id=iPc2DAAAQBAJ
  • 7. Hulett, D.T., Nosbisch, M.R. (2012). Integrated cost-schedule risk analysis. AACE International Transactions, 3. https://doi.org/10.4324/9781315589015
  • 8. Kerzner, H. (2013). Project Management Metrics, KPIs, and Dashboards: A Guide to Measuring and Monitoring Project Performance. New York: International Institute for Learning, Inc., Willey.
  • 9. Kerzner, H. (2017). Project Management Metrics, KPIs, and Dashboards. New York: International Institute for Learning, Inc., Wiley.
  • 10. Kerzner, H. (2022). Project Management Metrics, KPIs, and Dashboards: A Guide to Measuring and Monitoring Project Performance. New York: International Institute for Learning, Inc., Willey.
  • 11. Kim, Y.-W., Ballard, G. (2002). Earned Value Method and Customer Earned Value. Journal of Construction Research, 3(1). https://doi.org/10.1142/s1609945102000096
  • 12. Koke, B., Moehler, R.C. (2019). Earned Green Value management for project management: A systematic review. Journal of Cleaner Production, Vol. 230. https://doi.org/10.1016/ j.jclepro.2019.05.079
  • 13. Kuchta, D., Canonico, P., Capone, V., Capaldo, G. (2023). Uncertainty in the Planning Phase of Public Projects-Its Scope, Consequences, and Possible Remedies. Administrative Sciences, 13(6). https://doi.org/10.3390/admsci13060145
  • 14. Macdonald, M. (2002). Review of Large Public Procurement in the UK. HM Treasury, 44(April).
  • 15. Morris, P.W.G., Hough, G.H. (1987). The anatomy of major projects: a study of the reality of project management.
  • 16. Prater, J., Kirytopoulos, K., Ma, T. (2017). Optimism bias within the project management context: A systematic quantitative literature review. International Journal of Managing Projects in Business, 10(2). https://doi.org/10.1108/IJMPB-07-2016-0063
  • 17. The Standish Group (2015). Chaos Report. In: Standish Group - Chaos Report, Vol. 49.
  • 18. Vanhoucke, M. (2010). Measuring Time - Improving Project Performance using Earned Value Management, Vol. 136. https://doi.org/10.1007/978-1-4419-1014-1
  • 19. Vytlačil, D. (2020). The model for the description of the dynamic behaviour of the project processing. IOP Conference Series: Materials Science and Engineering, 960(3). https://doi.org/10.1088/1757-899X/960/3/03209.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171682296

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