Settlement intention of foreign workers in Japan: Bayesian multinomial logistic regression analysis

This study examines the intentions of foreign workers living in Okayama, Japan, to stay long-term in Japan. Utilizing a Bayesian multinomial logistic regression model, this research provides a novel analytical approach that captures parameter uncertainty and accommodates the categorical nature of migrants' settlement intentions using primary data collected via a questionnaire survey from January to March 2024. The findings reveal that residence status, previous experience of living in Japan, and graduation from a Japanese education institution significantly influence long-term settlement intentions. In addition, respondents aged 26-35 intend to stay longer than those of other ages, and those from less developed countries, such as Myanmar and Vietnam, intend to stay longer than those from China. Conversely, highly educated migrants express lower settlement intentions, suggesting a potential loss of skilled foreign labor in Japan. Notably, migrants in the Technical Intern Training Program are more likely to stay longer than those with other residence statuses, such as Highly Skilled Professional. In contrast, workers with higher education levels tend to have less intention to stay long-term, indicating a high probability of Japan losing educated foreign labor in the future. These findings contribute to understanding the dynamics of migrant workers in Japan, which is crucial for creating policies for foreign workers that can attract and support long-term settlement. These findings have important implications for policy, particularly in enhancing community integration, reducing workplace discrimination, and designing residence pathways that support long-term retention.