System of recommendations on migration and in-migration immigration of Ecuadorian nationals to other countries

Main Article Content

José Milton Jiménez Montenegro
Nelson Fabricio Samaniego Guanga
Doménica Dayana Tamayo García
Gabriela Ángeles Montenegro Cáceres

Abstract

The purpose of this research is to implement a system of recommendations on the migration and immigration of Ecuadorian citizens to other countries, in a context where emigration has generated significant changes in the economy and culture of the country. A comprehensive understanding of this phenomenon will not only benefit Ecuador, but also the countries that have established labor and social ties with migrants. This system will seek to analyze the economic impacts of emigration, considering factors beyond the merely financial, such as development dynamics and the conditions that have fostered migration. The limitations of emigration in development will be explored, in a framework of globalization that has expanded life opportunities for many Ecuadorians, facilitated by technological advances in communication and transportation, as well as by social networks of migrants that offer information and connections. In addition, various economic positions that explain migration will be addressed, including wage differences and other factors such as the quality of employment and life, which influence the decisions of migrant individuals. Through this approach, it is hoped to provide concrete recommendations that will help optimize migration policies and improve the quality of life of Ecuadorian citizens abroad.

Downloads

Download data is not yet available.

Article Details

How to Cite
System of recommendations on migration and in-migration immigration of Ecuadorian nationals to other countries. (2025). Neutrosophic Computing and Machine Learning. ISSN 2574-1101, 36, 103-110. http://fs.unm.edu/NCML2/index.php/112/article/view/671
Section
Articles

How to Cite

System of recommendations on migration and in-migration immigration of Ecuadorian nationals to other countries. (2025). Neutrosophic Computing and Machine Learning. ISSN 2574-1101, 36, 103-110. http://fs.unm.edu/NCML2/index.php/112/article/view/671