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Journal Article

Citation

Forteza FJ, Carretero-Gómez JM, Sese A. J. Saf. Res. 2022; 81: 270-282.

Copyright

(Copyright © 2022, U.S. National Safety Council, Publisher Elsevier Publishing)

DOI

10.1016/j.jsr.2022.03.004

PMID

35589298

Abstract

INTRODUCTION: This study develops an empirical test of two theoretical models using the approach of Structural Equation Model (SEM) to test the relationships between specific organizational factors of safety management system (SMS) and specific risk variables.

METHOD: Two SEM models with two and four latent variables, respectively, and 10 observed risk variables were used to identify the strongest relationships that may lead to an accident on site. A random sample of 474 construction sites were visited and assessed in Spain from 2003 to 2010. Most of the samples were small and medium sized enterprises (SMEs), which is the predominant type of company in the Spanish construction industry. To assess the risk on sites and get the measurements of the variables included in the models, the validated method CONSRAT (Construction Sites Risk Assessment Tool) was used. After estimating the proposed models, an adequate fit was obtained for both of them.

RESULTS: Results provide empirical evidence that: (a) the factor "Resources on site" is more determinant in explaining influences on risk variables because of their influence on all risk variables (Model 1); (b) the factor "Site structure complexity" (which includes structure and organization, and safety resources available on site) has a stronger effect on risk variables than other factors related to intrinsic characteristics of the work, site, or companies (Model 2).

CONCLUSIONS: These results mean that the complexity and resource factors that depend on companies are those that have the greatest impact on risks, which makes it possible for companies to undertake the appropriate risk control measures.

PRACTICAL APPLICATION: These results can help construction firms obtain earlier information about which organizational elements can affect future safety conditions on site, improve those elements for preventing risks, and consequently, avoid accidents before they occur.


Language: en

Keywords

Risk onsite; Site complexity; Site resources; Structural Equation Modeling

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