A Review of Data-Driven Immigration Decision Systems and Global Talent Mobility Optimization
Meifu International Group, Shanghai 200030, China
| Abstract: | Global competition for high-skilled talent has made immigration decision-making increasingly complex due to fragmented information, policy variability, and uneven evaluation standards. This paper reviews the conceptual foundations and practical value of data-driven immigration decision systems in improving global talent mobility. It proposes a three-layer analytical framework consisting of a Data Layer, an Evaluation Layer, and a Decision Layer. The Data Layer integrates applicant profiles, pathway requirements, and contextual case information; the Evaluation Layer transforms these inputs into assessments of feasibility, risk, and competitiveness; and the Decision Layer generates pathway recommendations and strategy options. Based on this framework, the paper discusses how structured decision systems can improve decision efficiency, strengthen case preparation, and support talent allocation across sectors of strategic importance. In addition, the study highlights the role of systematic comparison and structured evaluation in reducing information asymmetry and improving the transparency of immigration decision processes. The study also identifies key limitations, including data quality issues, policy change, model bias, and the continuing need for human judgment. It argues that data-driven immigration decision systems should be understood as decision-support tools rather than deterministic mechanisms. The analysis further suggests that integrating analytical frameworks into immigration practice can facilitate more consistent decision-making across different cases and institutional contexts. As global competition for talent intensifies, improving such systems will become increasingly important for both individual applicants and broader talent governance. |
| Keywords: | Global Talent Mobility; Immigration Decision-Making; Data-Driven Systems; Risk Assessment; Talent Allocation Efficiency |
| DOI: | 10.57237/j.ssrf.2026.03.001 |
View:
Downloads:
Received: 19 March 2026
Accepted: 16 April 2026
Published Online: 27 April 2026
References
| [1] | Docquier, F., Rapoport, H. Globalization, Brain Drain, and Development. Journal of Economic Literature. 2012, 50(3), 681-730. https://doi.org/10.1257/jel.50.3.681 |
| [2] | Kerr, S. P., Kerr, W. R. Immigrant Entrepreneurship. NBER Reporter. 2016, (4), 10-14. |
| [3] | Czaika, M., Parsons, C. R. The Gravity of High-Skilled Migration Policies. Demography. 2017, 54(2), 603-630. https://doi.org/10.1007/s13524-017-0559-1 |
| [4] | Beine, M., Docquier, F., Rapoport, H. Brain Drain and Human Capital Formation in Developing Countries: Winners and Losers. Economic Journal. 2008, 118(528), 631-652. https://doi.org/10.1111/j.1468-0297.2008.02135.x |
| [5] | Simon, H. A. Models of Bounded Rationality. Cambridge, MA: MIT Press, 1982. |
| [6] | Kahneman, D., Tversky, A. Prospect Theory: An Analysis of Decision under Risk. Econometrica. 1979, 47(2), 263-291. https://doi.org/10.2307/1914185 |
| [7] | Akerlof, G. A. The Market for “Lemons”: Quality Uncertainty and the Market Mechanism. Quarterly Journal of Economics. 1970, 84(3), 488-500. https://doi.org/10.2307/1879431 |
| [8] | Power, D. J. Decision Support Systems: Concepts and Resources for Managers. Westport: Quorum Books, 2002. |
| [9] | Shim, J. P., Warkentin, M., Courtney, J. F., et al. Past, Present, and Future of Decision Support Technology. Decision Support Systems. 2002, 33(2), 111-126. https://doi.org/10.1016/S0167-9236(01)00139-7 |
| [10] | Janssen, M., Kuk, G., Wagenaar, R. W. A Survey of Web-Based Business Models for E-Government in the Netherlands. Government Information Quarterly. 2008, 25(2), 202-220. https://doi.org/10.1016/j.giq.2007.01.015 |
| [11] | Kettunen, P., Kallio, J. E-Governance in Public Sector Decision-Making. Electronic Journal of e-Government. 2019, 17(2), 90-102. |
| [12] | Hunt, J., Gauthier-Loiselle, M. How Much Does Immigration Boost Innovation? American Economic Journal: Macroeconomics. 2010, 2(2), 31-56. https://doi.org/10.1257/mac.2.2.31 |
Join the Editorial Board
We invite active, qualified and high profile scientists and researchers to join as Editorial Board Members.
Join UsBecome a Reviewer
Scholars with a strong interest in reviewing are invited to join the reviewer panel to ensure the quality of the research to be published.
Join Us