Linear correlation between cost and schedule overruns in the execution of multifamily buildings

• Autorzy: Stachoń Tomasz

Identyfikatory

DOI

10.15199/33.2025.09.19

Warianty tytułu

PL

Liniowa korelacja przekroczenia kosztu i terminu realizacji budynków wielorodzinnych

• Języki publikacji: EN PL

Abstrakty

EN

The article presents a correlation analysis between cost overrun and schedule overrun in the execution of multifamily residential buildings, using the Pearson correlation coefficient. The study was based on processed data obtained from 14 construction residential projects carried out between 2006 and 2021. The results revealed a weak negative correlation, indicating no statistically significant linear relationship between the examined variables, in which the cost variable corresponds in 70% to the value of built-in building materials.

PL

Artykuł przedstawia analizę korelacji pomiędzy przekroczeniem kosztu i terminu realizacji budynków wielorodzinnych z zastosowaniem współczynnika korelacji Pearsona. Przedmiotem badania były przetworzone dane uzyskane z czternastu przedsięwzięć mieszkaniowych, realizowanych w latach 2006-2021. Wyniki wykazały słabą ujemną korelację, wskazującą na brak istotnej zależności liniowej między badanymi cechami, w której zmienna kosztu odpowiada w 70% nakładom wbudowanych materiałów budowlanych.

Słowa kluczowe

EN

cost overrun; time overrun; Pearson correlation; multi-family building; construction execution; research sample

PL

przekroczenie kosztów; przekroczenie terminu; korelacja Pearsona; budynek wielorodzinny; realizacja budowy; próba badawcza

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Materiały Budowlane
• Rocznik: 2025
• Tom: nr 9
• Strony: 145--151
• Opis fizyczny: Bibliogr. 24 poz., tab.

Twórcy

autor

Stachoń Tomasz

• Politechnika Wrocławska, Wydział Budownictwa Lądowego i Wodnego

• https://orcid.org/0000-0002-1220-0494

Bibliografia

• [1] Gruszczynski M., Kuszewski T., Podgórska M. Econometrics and operations research. 1st. ed. Warsaw: Wydawnictwo Naukowe PWN. 2009.
• [2] Szóstak M., Stachoń T., Konior J. Course of Cumulative Cost Curve (CCCC) as a Method of CAPEX Prediction in Selected Construction Projects. Applied Sciences. 2024; https://doi.org/10.3390/app14135597.
• [3] Makesh S., Mathivanan M. Analysis on causes of delay in building construction. International Journal of Innovative Technology and Exploring Engineering. 2019;7: 335-41.
• [4] Rachid Z., Toufik B., Mohammed B. Causes of schedule delays in construction projects in Algeria. International Journal of Construction Management. 2019; https://doi.org/10.1080/15623599.2018.1435234.
• [5] Kowalski J., Polonski M., Lendo-Siwicka M., Trach R., Wrzesinski G. Method of assessing the risk of implementing railway investments in terms of the cost of their implementation. Sustainability (Switzerland). 2021; https://doi.org/10.3390/su132313085.
• [6] Flyvbjerg B., Skamris Holm M.K., Buhl SøL. What causes cost overrun in transport infrastructure projects? Transp Rev. 2004; https://doi.org/10.1080/0144164032000080494a.
• [7] Cantarelli C.C., Molin E.J.E., Van Wee B., Flyvbjerg B. Characteristics of cost overruns for Dutch transport infrastructure projects and the importance of the decision to build and project phases. Transp. Policy (Oxf). 2012; https://doi.org/10.1016/j.tranpol.2012.04.001.
• [8] Miranda Sarmento J., Renneboog L. Cost Overruns in Public Sector Investment Projects. Public Works Management and Policy. 2017; https://doi.org/10.1177/1087724X16668357.
• [9] Senouci A., Ismail A., Eldin N. Time Delay and Cost Overrun in Qatari Public Construction Projects Procedia Engineering. 2016; https://doi.org/10.1016/j.proeng.2016.11.632.
• [10] Senouci A.B., Mubarak S.A. Multiobjective optimization model for scheduling of construction projects under extreme weather. Journal of Civil Engineering and Management. 2016; https://doi.org/10.3846/13923730.2014.897968.
• [11] Hoffman G.J., Thal A.E., Webb T.S., Weir J.D. Estimating Performance Time for Construction Projects. Journal of Management in Engineering. 2007; https://doi.org/10.1061/(as-ce)0742-597x(2007)23:4(193).
• [12] Konior J., Szóstak M. Course of planned, actual and earned cost curves of diverse construction investments. International Journal of Construction Management. 2023; https://doi.org/10.1080/15623599.2021.1942769.
• [13] Szóstak M. Planning the time and cost of implementing construction projects using an example of residential buildings. Archives of Civil Engineering. 2021; https://doi.org/10.24425/ace.2021.138497.
• [14] Szóstak M. Best fit of cumulative cost curves at the planning and performed stages of construction projects. Buildings. 2023; https://doi.org/10.3390/buildings13010013.
• [15] Ngwenya L., Aigbavboa C., Thwala W. Critical success factors for improved organizational performance. International Conference on Construction in the 21st Century. 2019; https://www.researchgate.net/publication/335831229_Critical_Success_Factors_for_Improved_Organizational_Perormance.
• [16] Naji K., Gunduz M., Salat F. Assessment of preconstruction factors in sustainable project management performance. Engineering, Construction and Architectural Management. 2021; https://doi.org/10.1108/ECAM-05-2020-0333.
• [17] Zhang W., Yuan G., Xue R., Han Y., Taylor J.E. Mitigating common method bias in construction engineering and management research. J Constr Eng Manag. 2022; https://doi.org/10.1061/(ASCE)CO.1943-7862.0002364.
• [18] Zhao T. Correlation and causation in construction claims. Journal of Legal Affairs and Dispute Resolution in Engineering and Construction. 2023; https://doi.org/10.1061/JLADAH.LADR-979.
• [19] Lowe D.J., Emsley M.W., Harding A. Relationships between total construction cost and project strategic, site related and building definition variables. Journal of Financial Management of Property and Construction. 2006; https://doi.org/10.1108/13664380680001087.
• [20] Tran D., Bypaneni S. Impact of correlation on cost-risk analysis for construction highway projects. Construction research congress 2016: Old and new construction technologies converge in historic San juan – proceedings of the 2016 Construction Research Congress, CRC 2016. 2016; https://doi.org/10.1061/9780784479827.068.
• [21] Koch C., Shayboun M. Sorting things out? Machine learning in complex construction project. Proceedings of the European Conference on Computing in Construction. 2019; https://doi.org/10.35490/EC3.2019.161.
• [22] Sekar G., Viswanathan K., Sambasivan M. Effects of project-related and organizational-related factors on five dimensions of project performance: a study across the construction sectors in Malaysia. EMJ – Engineering Management Journal. 2018; https://doi.org/10.1080/10429247.2018.1485000.
• [23] Polonski M., Pruszynski K., Pisarska E., Bogusz W. Managing the construction investment process. 2nd ed. Warsaw: SGGW Publishing House. 2018. available: Dec. 16, 2024; https://katalogi.bn.org.pl/permalink/48OMNIS_NLO-.P/1aot9i7/alma9910882923005606.
• [24] Krysicki W., Bartos J., Dyczka W., Królikowska K., Wasilewski M. Probability calculus and mathematical statistics in tasks. Warsaw: Wydawnictwo Naukowe PWN, 2004.