Speaker
Description
This study examines the predictive modeling capabilities for migrant inclusivity in South African cities using Partial Least Square Structural Equation Modeling (PLS-SEM). Through analysis of data collected from over 1,000 foreign migrants across nine South African provinces, the research investigates the interrelationships between multiple dimensions of urban integration, including institutional frameworks, economic participation, educational access, housing, public health, political engagement, and safety. The study employs both PLS and Linear Model (LM) approaches to assess predictive accuracy, with results indicating superior performance of LM in most indicators. The measurement model demonstrates robust psychometric properties, with composite reliability values ranging from 0.27% to 92.3%. Analysis reveals significant predictive relevance across dimensions, with Q² (predictive values ranging from 0.048 to 0.338 for PLS and 0.070 to 0.593 for LM). Safety and political constructs demonstrate particularly strong predictive accuracy of over 33.8% and 59% respectively, supporting contemporary theories about their foundational role in successful integration of migrants in the cities. The findings contribute to both theoretical understanding of urban migration dynamics and practical policy implementation, highlighting the complex interplay between institutional effectiveness, economic integration, and social inclusion in South African urban contexts.
| Best Congress Paper Award | Yes |
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