Forecasting the course of construction project management in conditions of uncertainty

• Autorzy: Konior Jarosław

Identyfikatory

DOI

10.24425/ace.2023.146097

Warianty tytułu

PL

Prognozowanie przebiegu przedsięwzięć budowlanych w warunkach niepewności

• Języki publikacji: EN

Abstrakty

EN

The methodology and research results presented in the article indicate the practical possibility of conducting optimization of construction project management course. The goal of the achievement leads to the rationalization of the management of investment tasks, in which there are a series of uncertain parameterized events. The goal was achieved through many years of the author’s own research, which was personally carried out on several hundred construction projects according to original methodology for assessing and forecasting the characteristic parameters of construction investments (cost and time) in conditions of uncertainty: from determinism, through probability and randomness, to fuzziness. The presented and documented achievement stands for accomplishment in project management of construction projects, where decision-making with an increasing degree of uncertainty takes place and requires the course of investment tasks that will be implemented in the future to be forecasted. In the conducted research and conclusions it was proven that construction processes should be considered as phenomena with random events and various degrees of uncertainty, to which methodology with developed modelling parameters should be used.

PL

Metodyka i wyniki badań zaprezentowane w artykule wskazują na praktyczną możliwość optymalizacji kosztowej przebiegu przedsięwzięć budowlanych. Cel osiągnięcia prowadzi do racjonalizacji zarządzania zadań inwestycyjnych, w których występują sparametryzowane przeze mnie serie zdarzeń niepewnych. Cel został osiągnięty na drodze kilkunastoletnich badań własnych, które są prowadzone na kilkuset obiektach i budowach według autorskiej metodyki oceny i prognozy ich charakterystycznych parametrów (koszt i czas) w warunkach niepewności: od determinizmu, poprzez probabilistykę i przypadkowość, aż do rozmytości. Zarządzanie przedsięwzięciami budowlanymi i podejmowanie decyzji zarządczych następuje w rosnącym stopniu niepewności i wymaga prognozowania przebiegu zadań inwestycyjnych, które zostaną zrealizowane w przyszłości. W prezentowanych badaniach udowodniono, że procesy budowalne powinny być rozważane jako zjawiska ze zdarzeniami losowymi o różnym stopniu niepewności, do których stosować metodykę o zbliżonych parametrach modelowania.

Słowa kluczowe

EN

construction project management; construction project; cost; fuzziness; time; randomness; risk; uncertainty

PL

zarządzanie przedsięwzięciem; przedsięwzięcie budowlane; koszt; przypadkowość; rozmytość; niepewność; ryzyko; czas

• Wydawca: Komitet Inżynierii Lądowej i Wodnej PAN ; Politechnika Warszawska, Wydział Inżynierii Lądowej
• Czasopismo: Archives of Civil Engineering
• Rocznik: 2023
• Tom: Vol. 69, nr 3
• Strony: 557--572
• Opis fizyczny: Bibliogr. 37 poz., il., tab.

Twórcy

autor

Konior Jarosław

• Wroclaw University of Science and Technology, Faculty of Civil Engineering, Wrocław, Poland

• https://orcid.org/0000-0002-3824-1948

Bibliografia

• [1] J. Konior, “Monitoring of construction projects feasibility by Bank Investment Supervision Approach”, Civil Engineering and Architecture, vol. 7, no. 1, pp. 31-35, 2019, doi: 10.13189/cea.2019.070105.
• [2] J. Konior, “Feasibility study of construction project in compliance with Bank Investment Supervision requirements”, Journal of Civil Engineering and Architecture, vol. 12, pp. 831-837, 218, doi: 10.17265/1934-7359/2018.12.001.
• [3] J. Konior, “Determining cost and time performance indexes for diversified investment tasks”, Buildings, vol. 12, no. 8, 2022, doi: 10.3390/buildings12081198.
• [4] J. Konior and M. Szóstak, “Methodology of planning the course of the cumulative cost curve in construction projects”, Sustainability, vol. 12, no. 6, 2020, doi: 10.3390/SU12062347.
• [5] J. Konior and M. Szóstak, “The S-curve as a tool for planning and controlling of construction process-case study”, Applied Sciences, vol. 10, no. 6, 2020, doi: 10.3390/app10062071.
• [6] J. Konior, “Random and fuzzy measure of unpredictable construction works”, Archives of Civil Engineering, vol. 61, no. 3, pp. 75-84, 2015, doi: 10.1515/ace-2015-0026.
• [7] J. Konior, “Fuzziness over randomness in unforeseen works of construction projects”, Civil Engineering and Architecture, vol. 7, no. 2, pp. 42-48, 2019, doi: 10.13189/cea.2019.070202.
• [8] J. Konior, “Enterprise’s risk assessment of complex construction projects”, Archives of Civil Engineering, vol. 61, no. 3, pp. 63-74, 2016, doi: 10.1515/ace-2015-0025.
• [9] J. Konior, “Mitigation of correlated risk in construction projects”, Civil Engineering and Architecture, vol. 7, no. 1, pp. 17-22, 2019, doi: 10.13189/cea.2019.070103.
• [10] J. Konior, “Significance risks evaluation of commercial construction projects”, Archives of Civil Engineering, vol. 65, no. 2, pp. 19-33, 2019, doi: 10.2478/ace-2019-0016.
• [11] S. Al-Jibouri, “Monitoring systems and their effectiveness for project cost control in construction”, International Journal of Project Management, vol. 21, pp. 145-154, 2003.
• [12] S. Gardezi, I. Manarvi, and S. Gardezi, “Time extension factors in construction industry of Pakistan”, Procedia Engineering, vol. 77, pp. 196-204, 2014, doi: 10.1016/j.proeng.2014.07.022.
• [13] S. Makesh and M. Mathivanan, “Analysis on causes of delay in building construction”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 7, pp. 335-341, 2019.
• [14] T. Gebrehiwet and H. Luo, “Analysis of delay impact on construction project based on RII and correlation coefficient: empirical study”, Procedia Engineering, vol. 196, pp. 366-374, 2017, doi: 10.1016/j.proeng.2017.07.212.
• [15] G. Barraza, W. Back, and F. Mata, “Probabilistic forecasting of project performance using stochastic Scurves”, Journal of Construction Engineering and Management, vol. 130, no. 1, pp. 25-32, 2004, doi: 10.1061/(ASCE) 0733-9364(2004)130:1(25).
• [16] J. Yao, M. Chen, and H. Lu, “A fuzzy stochastic single-period model for cash management”, European Journal of Operational Research, vol. 170, no. 1, pp. 72-90, 2006, doi: 10.1016/j.ejor.2004.06.017.
• [17] V. Kumar, A. Hanna, and T. Adams, “Assessment of working capital requirements by fuzzy set theory”, Engineering, Construction and Architectural Management, vol. 7, pp. 93-103, 2000.
• [18] M. Cheng and A. Roy, “Evolutionary fuzzy decision model for cash flow prediction using time-dependent support vector machines”, International Journal of Project Management, vol. 29, no. 1, pp. 56-65, 2011, doi: 10.1016/j.ijproman.2010.01.004.
• [19] M. Cheng, H. Tsai, and C. Liu, “Artificial intelligence approaches to achieve strategic control over project cash flows”, Automation in Construction, vol. 18, no. 4, pp. 386-393, 2009, doi: 10.1016/j.autcon.2008.10.005.
• [20] A. Leśniak and K. Zima, “Cost calculation of construction projects including sustainability factors using the case based reasoning (CBR) method”, Sustainability, vol. 10, no. 5, 2018, doi: 10.3390/su10051608.
• [21] T. Kasprowicz, “Quantitative assessment of construction risk”, Archives of Civil Engineering, vol. 63, no. 2, pp. 55-62, 2017, doi: 10.1515/ace-2017-0016.
• [22] T. Kasprowicz, “Quantitative identification of construction risk”, Archives of Civil Engineering, vol. 63, no. 1, pp. 63-75, 2017, doi: 10.1515/ace-2017-0005.
• [23] J. Cristóbal, “The S-curve envelope as a tool for monitoring and control of projects”, Procedia Computer Science, vol. 121, pp. 756-761, 2017, doi: 10.1016/J.PROCS.2017.11.097.
• [24] N. Ibadov, “Fuzzy estimation of Activities Duration in Construction Projects”, Archives of Civil Engineering, vol. 61, no. 2, pp. 23-34, 2015, doi: 10.1515/ace-2015-0012.
• [25] N. Ibadov, “The alternative net model with the fuzzy decision node for the construction projects planning”, Archives of Civil Engineering, vol. 64, no. 2, pp. 3-20, 2018, doi: 10.2478/ace-2018-0013.
• [26] N. Ibadov and J. Kulejewski, “Construction projects planning using network model with the fuzzy decision node”, International Journal of Environmental Science and Technology, vol. 16, no. 8, pp. 4347-4354, 2019, doi: 10.1007/s13762-019-02259-w.
• [27] N. Ibadov and J. Kulejewski, “The assessment of construction project risks with the use of fuzzy sets theory”, Technical Transactions, vol. 1-B, pp.175-182, 2014.
• [28] S. Vandevoorde and M. Vanhoucke, “A comparison of different project duration forecasting methods using earned value metrics”, International Journal of Project Management, vol. 24, no. 4, pp. 289-302, 2006, doi: 10.1016/j.ijproman.2005.10.004.
• [29] M. Vanhoucke and S. Vandevoorde, “A simulation and evaluation of earned value metrics to forecast the project duration”, Journal of the Operational Research Society, vol. 58, no. 10, pp. 1361-1374, 2007, doi: 10.1057/palgrave.jors.2602296.
• [30] M. Khamidi, W. Ali, and A. Idrus, “Application of earned value management system on an infrastructure project : A Malaysian case study”, International Conference on Management Science & Engineering, vol. 8, pp. 1-5, 2011.
• [31] O. Kwon, S. Kim, J. Paek, and S. Eom “Application of earned value in the Korean construction industry”, Journal of Asian Architecture and Building Engineering, vol. 7, pp. 69-76, 2008.
• [32] M. Połoński and P. Komendarek, “Earned value method for operational cost control of civil structure”, Metody Ilościowe w Badaniach Ekonomicznych, vol. 12, pp. 279-290, 2011.
• [33] E. Kozień “Application of approximation technique to on-line updating of the actual cost curve in the earned value method”, Czasopismo Techniczne, vol. 9, pp. 181-195, 2017, doi: 10.4467/2353737XCT.17.158.7170.
• [34] A. Leśniak, D. Kubek, E. Plebankiewicz, K. Zima, and S. Belniak, “Fuzzy AHP application for supporting contractors’ bidding decision”, Symmetry, vol. 10, no. 11, art. no. 642, 2018, doi: 10.3390/sym10110642.
• [35] A. Leśniak and E. Plebankiewicz, “Modeling the decision-making process concerning participation in construction bidding”, Journal of Management in Engineering, vol. 31, no. 2, 2015, doi: 10.1061/(ASCE)ME.1943-5479.0000237.
• [36] J. Konior and M. Szóstak, “Course of planned, actual and earned cost curves of diverse construction investments”, International Journal of Construction Management, vol. 23, no. 5, pp. 1-13, 2023, doi: 10.1080/15623599.2021.1942769.
• [37] M. Szóstak, “Planning the time and cost of implementing construction projects using an example of residential buildings”, Archives of Civil Engineering, vol. 67, no. 4, pp. 243-259, 2021, doi: 10.24425/ace.2021.138497.