{"title":"DIGITIZATION MEASURES IN THE REGULATION OF LABOR MIGRATION PROCESSES IN UZBEKISTAN","authors":"B. Islamov, Zulaykho Kadirova, Sulkhiya Gazieva","doi":"10.1145/3584202.3584250","DOIUrl":null,"url":null,"abstract":"Modern Uzbekistan has favorable conditions for using digitization opportunities to support labor migrants. In particular, the number of mobile communication subscribers has increased by almost 3 million in the last three years. Processes related to the implementation of temporary labor activities of citizens of the Republic of Uzbekistan abroad, including vocational training and retraining and improvement of skills. Furthermore, receiving financial support measures, providing legal and social support, and foreign employers monitoring information on labor contracts promote regulation of labor migration processes abroad. Current research denotes the digitalization process's influence on labor migrant work performance. For data collection, it was asked 454 personally abroad 20 questions. As observed variables are classified into 14 binary variables, 3 categorical variables, and 3 numerical variables. In the process of econometric analysis, we used the multifactor linear regression model, SEM, and Confirmatory Factor Analysis. Results obtained in STATA 15.0 software. The adequacy of the OLS regression results was not so robust. There we tested our hypothesis in the SEM model which was quietly statistically significant in p<0.05 level. Among variables, there are four Latent unobserved variables generalized. According to the PCA, it was found that caused by 0.18-unit Digital technology (L2), 0.30-unit Income from migration (L3), and 0.092-unit Labor migrants (L3) Migration regulation (L1). According to the Pearson pairwise correlation test Digital technology (L2) and Labor migrants (L3) 18 percent relationship in p<0.05 level is statistically significant and 19 percent with significance level. According to the Cronbach-Alpha test, the reliability of the model is 31 percent and the coefficient of determination is 52 percent.","PeriodicalId":438341,"journal":{"name":"Proceedings of the 6th International Conference on Future Networks & Distributed Systems","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Future Networks & Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3584202.3584250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Modern Uzbekistan has favorable conditions for using digitization opportunities to support labor migrants. In particular, the number of mobile communication subscribers has increased by almost 3 million in the last three years. Processes related to the implementation of temporary labor activities of citizens of the Republic of Uzbekistan abroad, including vocational training and retraining and improvement of skills. Furthermore, receiving financial support measures, providing legal and social support, and foreign employers monitoring information on labor contracts promote regulation of labor migration processes abroad. Current research denotes the digitalization process's influence on labor migrant work performance. For data collection, it was asked 454 personally abroad 20 questions. As observed variables are classified into 14 binary variables, 3 categorical variables, and 3 numerical variables. In the process of econometric analysis, we used the multifactor linear regression model, SEM, and Confirmatory Factor Analysis. Results obtained in STATA 15.0 software. The adequacy of the OLS regression results was not so robust. There we tested our hypothesis in the SEM model which was quietly statistically significant in p<0.05 level. Among variables, there are four Latent unobserved variables generalized. According to the PCA, it was found that caused by 0.18-unit Digital technology (L2), 0.30-unit Income from migration (L3), and 0.092-unit Labor migrants (L3) Migration regulation (L1). According to the Pearson pairwise correlation test Digital technology (L2) and Labor migrants (L3) 18 percent relationship in p<0.05 level is statistically significant and 19 percent with significance level. According to the Cronbach-Alpha test, the reliability of the model is 31 percent and the coefficient of determination is 52 percent.