Prediction model of seasonality in the construction industry based on the accidentality phenomenon

• Autorzy: Hoła Bożena , Topolski Mariusz , Szer Iwona , Szer Jacek , Blazik-Borowa Ewa

Identyfikatory

DOI

10.1007/s43452-021-00348-7

• Języki publikacji: EN

Abstrakty

EN

The construction industry is an economic sector that is characterized by seasonality. Seasonal factors affect the volume of production, which in turn affects the accident rate. The aim of the research presented in the article was to develop a model for predicting the number of people injured in occupational accidents in the construction industry. Based on the analysis of statistical data and previous studies, the occurrence of certain regularities of the accidentality phenomenon was found, namely the long-term trend over many years, as well as seasonality and cyclicality over the course of a year. The found regularities were the basis for the assumptions that were made for the construction of the model. A mathematical model was built in the non-linear regression dimension. The model was validated by comparing the results of prediction errors generated by the developed model with the results of prediction errors generated by other known models, such as ARIMA, SARIMA, linear and polynomial models, which take into account the seasonality of the phenomenon. The constructed model enables the number of people injured in accidents in the construction industry in selected months of future years to be predicted with high accuracy. The obtained results can be the basis for making appropriate decisions regarding preventive and prophylactic measures in the construction industry. Commonly known mathematical tools available in the STATISTICA package were used to solve the given task.

Słowa kluczowe

EN

construction industry; seasonality in the construction industry; nonlinear regression; occupational safety; accidentality prediction; long-term trend

PL

budownictwo; bezpieczeństwo pracy; przypadkowość

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2022
• Tom: Vol. 22, no. 1
• Strony: art. no. e30, 2022
• Opis fizyczny: Bibliogr. 43 poz., tab., wykr.

Twórcy

autor

Hoła Bożena

• Faculty of Civil Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

• https://orcid.org/0000-0001-6630-8065

autor

Topolski Mariusz

• Faculty of Information and Communication Technology, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370 Wrocław, Poland

• https://orcid.org/0000-0002-5213-6845

autor

Szer Iwona

• Faculty of Civil Engineering, Architecture and Environmental Engineering, Lodz University of Technology, Politechniki 6, 90-924 Lodz, Poland

autor

Szer Jacek

• Faculty of Civil Engineering, Architecture and Environmental Engineering, Lodz University of Technology, Politechniki 6, 90-924 Lodz, Poland

autor

Blazik-Borowa Ewa

• Faculty of Civil Engineering and Architecture, Lublin University of Technology, Nadbystrzycka 40, 20-618 Lublin, Poland

• https://orcid.org/0000-0001-8200-3827

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)