Looking for Meaningful Work in the Architecture, Engineering, and Construction Industry: A Structural Equation Modeling Analysis of Refugee and Migrant Work-Seeking Experiences
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 7
Abstract
This research develops and tests a structural equation model of the factors which determine the work-seeking experiences of refugees and skilled migrants in the Australian architecture, engineering, and construction (AEC) industry. Past studies had identified a number of potential barriers to employment that refugees and migrants face when looking for work, though they are typically treated in isolation, meaning that the way they interact in determining employment outcomes is poorly understood. To address this gap in research, data was collected from 100 migrants and refugees that were either working in or actively seeking employment in the Australian AEC industry. The model, developed through partial least square analysis, provides new insights into the interaction between labor market familiarity, human capital, perceived support structures, labor market discrimination, work-related acculturation and the experiences of securing meaningful work in the Australian AEC industry. The results indicate that the level of familiarity of a candidate with the local market positively influences their perceived support structures, which in turn impacts their work-related acculturation, and opportunities for obtaining meaningful work. Perceived labor market discrimination also influences the relationship between the familiarity of the candidate with the market and their perceived levels of support. It is concluded that policy makers should focus on better integration of skilled migrants and refugees in the local AEC industry via enhancing familiarity in the local market, qualification and experience recognition, raising awareness of work culture, and legal systems and procedures, along with removing negative stereotypes to help reduce the barriers to employment that they face.
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Data Availability Statement
All data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions. See Appendix S1 to view the survey used in this study.
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Information & Authors
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Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 7 • July 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Aug 28, 2022
Accepted: Jan 26, 2023
Published online: Apr 22, 2023
Published in print: Jul 1, 2023
Discussion open until: Sep 22, 2023
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