Model of Predicting Cost Overrun in Construction Projects

Edyta Plebankiewicz
Additional contact information
Edyta Plebankiewicz: Institute of Construction Management Cracow University of Technology, Warszawska 24, 31-155 Kraków, Poland

Sustainability, 2018, vol. 10, issue 12, 1-14

Abstract: During the construction phase, significant differences between the planned and actual costs of construction projects frequently occur. The paper describes the concept of a model of prediction of the increase in the costs of construction works in relation to those planned. The assumption of the model is to determine the probability of the cost increase for the elements of the object for which it is the largest. A fuzzy Mamdani inference method was proposed for the selection of the elements to be evaluated. In the cost prediction model, fuzzy relations and the compound max-min relations were used. The result of the model are the probabilities of cost overrun for works most exposed to changes in costs. The model can be helpful mainly for the contractor who wants to know not only the probability of the total cost overrun but also the possibility and amount of increase in the costs of individual packages of works or detailed construction works necessary to complete a construction project. Such an approach may help to properly plan expenses related to the implementation and schedule of works along with the cash flow for the project.

Keywords: cost overrun; construction project; fuzzy sets (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.mdpi.com/2071-1050/10/12/4387/pdf (application/pdf)
https://www.mdpi.com/2071-1050/10/12/4387/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2018:i:12:p:4387-:d:185187

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().