Worker absenteeism is identified as the greatest threat to not meeting the completion date of a construction project. The purpose of this paper is to quantify the impact of employee absenteeism risk on the probabilistic lead time of a construction project. Calculations of employee absenteeism risk values were performed using data from the Central Statistical Office (Big Data). Probabilistic schedules with probability density functions (Normal, Exponential, Reyleigh, Triangle, Gamma, Cauchy) with and without calculated employee absenteeism risk were prepared. Student’s t-test and MAPE analysis of mean absolute percentage errors were performed to determine differences between groups. It was found that with respect to the probability of completing the task in the range of 75 to 95% for all functions, an unacceptable MAPE error of 32.82% to 69.23% arises. Therefore, the authors postulate that the risk of worker absenteeism should be considered in every construction process when performing probabilistic scheduling, i.e., in the Building Information Modeling BIM methodology.

This paper introduces an advanced framework for modeling and scheduling construction processes using causal inference techniques, with particular emphasis on capturing complex technological and organizational interdependencies. By integrating causal calculus and counterfactual reasoning, the study demonstrates how construction schedules can be analyzed and optimized not only through temporal relationships but also through explicit cause–effect structures. A matrix-based scheduling methodology is presented, incorporating diagonal and reverse-diagonal time couplings consistent with the Time Coupling Method (TCM). The computational procedure is detailed, including the determination of earliest and latest event times, identification of the critical path, and computation of activity floats. Based on an in-depth examination of technological and organizational constraints, eight theorems are formulated and proven, establishing the fundamental properties of a scheduling approach that embeds causal mechanisms. The findings indicate that the integration of causal inference into construction planning enables more accurate identification of factors influencing project duration, enhances synchronization of dependent activities, and minimizes conflicts and idle times. This causally informed framework strengthens decision-making by allowing practitioners to predict the consequences of modifications in project execution strategies. The developed models constitute a robust foundation for future research on leveraging causal inference algorithms and artificial intelligence to advance construction process management.

MATEC Web of Conferences, open access proceedings in Materials science, Engineering and Chemistry

The article attempts to determine the value of the duration of the building process depending on the risk of the occurrence of temperatures below –10°C in Poland. It summarizes the results of measurements of the temperature study over 62 years (from 1950 to 2011) in Poland. The number of days with temperatures below –10°C in future years was forecasted. The method of ARIMA (Autoregressive Integrated Process Average) STATISTICA STAT SOFT was used. Stationarity series was tested using an IDW Durbin Watson integrative statistics and homoscedasticity was tested by the Levene test. The forecast error was verified using autocorrelation and partial autocorrelation residues functions. On the basis of calculations, the risk values for outdoor works in each month in Poland was established. It is a part of BIM 6-D calculation. The calculated risk value can be used for the calculation in Risky Project Professional and in other programs. The proposed risk values and the method of calculation are the upcoming modification product, which has not been reported yet.

Omówiono zagadnienie zarządzania projektem inwestycyjnym. Proces zarządzania projektem inwestycyjnym rozpoczyna się w momencie pojawienia się potrzeby sformułowania i rozwiązania problemu. Dokonano analizy czynników rozpatrywanych w realizacji przedsięwzięcia budowlanego w systemie zarządzania typu project management.