Bibliometric and Visual Analysis Review of Employment Migration: Characteristics and Trends Perspective

Authors

  • Fu, S.
  • Wareewanich, T.
  • Chankoson, T.

DOI:

https://doi.org/10.59670/ml.v20i7.4576

Abstract

Purpose: This study aims to provide a systematic knowledge graph for the field of employment migration research, including author collaboration, institutional collaboration, research hotspots, scholar evolution, and cutting-edge research.

Methodology: This study adopts bibliometric methods and uses CiteSpace to analyze the retrieved literature data quantitatively. This study presents the analysis results through tables and visualization graphs.

Results: The results indicate that research on employment migration has grown rapidly in recent years, and interdisciplinary research has received much attention. The cooperation between scholars could be more robust. At present, the research field of employment migration has scattered content and uses single research methods but has expanded its focus to areas such as childcare, health, youth employment, etc. Future research can focus on the strategic choices, employment issues, health status, freelance employment, and entrepreneurship of migrants and explore the relationship between employment migration and urban choice, exploring the economic returns and quality of life trade-offs of cities.

Value: Previous literature reviews have conducted qualitative research on employment migration, with little quantitative research conducted. Therefore, this study adopts quantitative research methods such as bibliometrics, data mining, and knowledge mapping to systematically and intuitively reveal the research progress and trends of research data themes based on published literature, providing references for further research on future research.

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Published

2023-10-13

How to Cite

Fu, S., Wareewanich, T., & Chankoson, T. (2023). Bibliometric and Visual Analysis Review of Employment Migration: Characteristics and Trends Perspective . Migration Letters, 20(7), 820–834. https://doi.org/10.59670/ml.v20i7.4576

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Articles