Presentation Type
Oral Presentation
Start Date
5-8-2024 1:00 PM
End Date
5-8-2024 3:00 PM
Subjects
Immigration Policy and Research, Decision Making
Student Level
Doctoral
Abstract
The U.S. Immigration System is complex for technology professionals seeking to relocate to the United States for employment or education. The United States relies on its employment-based immigration to attract and select the best talent to fill the shortage of skilled jobs. Technology professionals, a stream of highly skilled immigrants, tend to contribute and be more beneficial to the U.S. economy, which is one of the principles of U.S. immigration policies. Although U.S. immigration policies are constantly updating, policymakers, experts, and scholars suggest that the United States needs significant immigration reform to solve current issues, such as improving technological capabilities to process applications, backlog, paths for permanent residence, numerical limits per visa category, and others.
Therefore, this research aims to develop a Hierarchical Decision Model (HDM) to evaluate U.S. immigration policies for technology professionals. Moreover, this research can guide policymakers to fix current U.S. immigration issues. The research process of this dissertation is organized as follows: (1) a systematic literature review was conducted to identify gaps, research questions, objectives, and an initial four-level HDM. The second level of the model includes five criteria: Technological, Regulatory Landscape, Economic, Political Interpretation & Proposals, and Social. The third level includes twenty-one sub-criteria, and the fourth level includes five alternatives: Permanent Residence and visas H-1B, O-1, F-1 STEM OPT, and L-1. (2) 60 experts working in some vein in U.S. immigration policies participated in this study to validate the HDM criteria, sub-criteria, and alternatives and quantify the HDM criteria, sub-criteria, and alternatives using a pairwise comparison technique to provide their judgment. The last sections of this dissertation include (1) a sensitivity analysis to demonstrate the HDM's flexibility and (2) policy guide recommendations for decision-makers based on the HDM results.
Creative Commons License or Rights Statement
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
Evaluation of US Immigration Policies for Technology Professionals
The U.S. Immigration System is complex for technology professionals seeking to relocate to the United States for employment or education. The United States relies on its employment-based immigration to attract and select the best talent to fill the shortage of skilled jobs. Technology professionals, a stream of highly skilled immigrants, tend to contribute and be more beneficial to the U.S. economy, which is one of the principles of U.S. immigration policies. Although U.S. immigration policies are constantly updating, policymakers, experts, and scholars suggest that the United States needs significant immigration reform to solve current issues, such as improving technological capabilities to process applications, backlog, paths for permanent residence, numerical limits per visa category, and others.
Therefore, this research aims to develop a Hierarchical Decision Model (HDM) to evaluate U.S. immigration policies for technology professionals. Moreover, this research can guide policymakers to fix current U.S. immigration issues. The research process of this dissertation is organized as follows: (1) a systematic literature review was conducted to identify gaps, research questions, objectives, and an initial four-level HDM. The second level of the model includes five criteria: Technological, Regulatory Landscape, Economic, Political Interpretation & Proposals, and Social. The third level includes twenty-one sub-criteria, and the fourth level includes five alternatives: Permanent Residence and visas H-1B, O-1, F-1 STEM OPT, and L-1. (2) 60 experts working in some vein in U.S. immigration policies participated in this study to validate the HDM criteria, sub-criteria, and alternatives and quantify the HDM criteria, sub-criteria, and alternatives using a pairwise comparison technique to provide their judgment. The last sections of this dissertation include (1) a sensitivity analysis to demonstrate the HDM's flexibility and (2) policy guide recommendations for decision-makers based on the HDM results.