Development of a Model for Determining Factors Affecting Safety Performance in the Saudi Arabian Construction Industry Using Structural Equation Modelling (SEM)

As large-scale infrastructure investments drive rapid growth, the Saudi construction industry is among the largest in the region—and, for workers, among the most dangerous industries on the planet. Using a quantitative survey measure adapted from the Ontario Leading Indicators Project (OLIP) and administered to a small (n = 276) sample of individuals who currently work in the industry, this study aimed to contribute to empirical understandings of hazards, sources of risk, and perceptions of safety in this unique context. A multivariate safety performance model was developed based on a systematic literature review and with an eye to ensuring compatibility with the structure of the adapted OLIP measure. The model's key variables were OHS Planning; OHS Policy; OHS Promotion; Communication & Awareness; OHS Training; Control, Monitoring, & Review; OHS Leadership; Safety Climate; Hazard Management; and Safety Performance. The survey data revealed a strong consensus expressing negative views of every safety dimension and variable tested, with only tiny minorities selecting positively-valenced responses. Using the survey data as a substrate, correlation analysis found significant relationships between all individual variables. In order to test the descriptive power of the model as a whole, a structural equation modeling (SEM) technique was used in order to assess the correspondence between the relationships constituting the model and their significance relative to empirical data. This analysis found that Hazard Management, OHS Training, and OHS Promotion had no significant impact on Safety Climate, and that OHS Training, Safety Climate, and Control, Monitoring, & Review had no significant impact on Safety Performance, when evaluated in the context of the model as a whole. This result, which is attributed to significant reciprocal relationships between individual variables balancing one another out in the multiple regression analysis, is not consistent with previous findings in the scholarly literature. It is possible that this result reflects a limitation in the model or in the underlying data, and further scholarly attention is recommended. Overall, however, the need to take urgent steps to improve the safety landscape of the Saudi construction industry, even in the absence of further empirical study of the topic, is stressed throughout the study. Attention from scholars, policymakers, and organizational leaders is indicated.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Industrial and Manufacturing Systems Engineering

Grantor

University of Windsor

Year dc:date.issued

2018

Author dc:creator

• Moosa, Majed

Advisor dc:contributor.advisor

• Oriet, Leo

Contributors dc:contributor

• mita@uwindsor.ca

Licence

• http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language.iso

en_CA

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14776/7838

OAI identifier oai:identifier

oai:uwindsor.scholaris.ca:20.500.14776/7838