**1. Introduction**

Cost overruns in construction projects are a common phenomenon, occurring in different market and legal conditions and, unfortunately, often negatively influencing the achievement of project goals. Numerous research results indicate the scale of this problem. For instance, Love et al. [1] analyzed cost overruns from 276 construction and engineering projects. The research revealed a mean cost overrun of 12.22%. According to research performed by Andri´c et al. [2] on cost overruns in infrastructure projects in Asia, the mean value of cost overrun is 26.24%. Senouci et al. [3] in their study on the increase in term cost in 122 construction contracts in Qatari showed that 54% had their costs increased and 72% their deadlines increased. Larsen et al. [4] established that more than half of Malaysian construction projects (55%) experienced cost overruns.

Different types of construction investments can be specified in various stages of their implementation, and these are characterized by different technological, organizational, and economic specificities. When determining the risk of cost overruns, this specificity and different symmetry and asymmetry data must be taken into account. However, when attempting to determine the risk of exceeding the costs of a given element of a facility, one should consider, for instance, the share of a given element in the total cost of the facility, the risk of changes in the number of works, as well as exposure of a given type of works to changes in the unit price, including the price of construction materials [5].

In the literature, various approaches have been described to estimate the real costs of construction projects, including the value of cost overrun. The novelty of the proposed methodology is the assumption of the analysis of individual works included in the project, which allows for a more detailed analysis of the cost overrun risk. The model takes into account the impact of three elements on the risk of cost overrun for a given construction work, which are input variables, namely share of element costs in the building costs (SE), predicted changes in the number of works (WC), and expected changes in the unit price (PC). For each of the variables, a fuzzy interpretation was proposed. The first variable depends on the type of the building and is therefore the most difficult to describe. The authors decided to analyze different types of buildings in the context of determining for each of the them a fuzzy interpretation of the linguistic input variable SE. This can greatly simplify the use of the model in practice.

The aim of the paper is to present a model allowing to assess the risk of exceeding the costs of individual stages of a construction project, adapted to various construction investments.
