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.

Authors

Institutions

Publication Details

Journal
Economies
Published
2025-04-17
DOI
https://doi.org/10.3390/economies13040112
Citations
1
Primary Topic
Migration, Ethnicity, and Economy
Type
article
Field-Weighted Citation Impact
4.20
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Settlement Intention of Foreign Workers in Japan: Bayesian Multinomial Logistic Regression Analysis

Shyam Kumar Karki, Tokiko Inoue, Chukiat Chaiboonsri, Mi Moe Thuzar et al.
1 citations
Economies
Migration, Ethnicity, and Economy
4.20
article

Settlement Intention of Foreign Workers in Japan: Bayesian Multinomial Logistic Regression Analysis

Shyam Kumar Karki, Tokiko Inoue, Chukiat Chaiboonsri, Mi Moe Thuzar, Andi Holik Ramdani, Waode Hanifah Istiqomah
article en
1 citations

Abstract

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.

EconomiesVol. 13(4)
Chiang Mai University (TH)
Openalex Percentile: Top 9%
Migration, Ethnicity, and Economy
4.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Settlement Intention of Foreign Workers in Japan: Bayesian Multinomial Logistic Regression Analysis — Shyam Kumar Karki, Tokiko Inoue, et al. · Economies (2025) | TGRS Research Map | TGRS