J61 - Geographic Labor Mobility; Immigrant WorkersReturn

Migration processes have emerged as crucial social, political and economic concerns, affecting societies, industries and organisations. The challenge lies in effectively utilizing immigrants' resources. This research aims to determine how AI tools can support matching migrants' skills with labour markets in host countries. We propose the application of an ensemble learning methodology. To validate this approach, we collect data to assess the career trajectories of 248 tertiary-educated Ukrainian immigrants in Poland, a new immigration destination. Various machine learning models are evaluated using the decision tree algorithm on these feature sets. To ensure credible results, a 10-fold cross-validation procedure is employed for each training process of every submodel. This research introduces an original ensemble machine learning classifier that combines pre-selected models with the highest performance, thereby reducing the number of parameters to be investigated. Its application in determining the career paths of highly skilled migrants, specifically Ukrainians, is novel. The study offers significant implications for Central Europe, notably Poland, where migration patterns and the integration of highly skilled migrants, mainly from Ukraine, are increasingly important.
Implications for Central European audience: The ensemble machine learning classifier developed in this study could aid in optimising the career paths of these migrants, combating brain waste and facilitating their successful integration into the labour market. Integrating tools like these into decision-making processes may enhance career management and contribute to Central Europe's social and economic growth.

This study investigates the difficulties that expatriates encounter while relocating to a foreign cultural environment. The examination of the issue is based on the results of primary research conducted among the Japanese community living and working in Hungary. Many circumstances make it difficult for an expat to feel at ease in the host country. Integration and thus the success of the posting are greatly hampered by overcoming cultural differences as well as linguistic challenges in a non-English speaking country. Language fluency issues are stated to trigger a series of practical, task-related barriers as well as broader social and emotional difficulties. Japanese multinational corporations use English for internal corporate communication. The typical posting period for Japanese expats in Hungary is 4-6 years. They are typically senior executives who arrive together with their families. Over the years, the preparedness, language skills and cross-cultural competencies of the expatriates have improved significantly, while the infrastructure of the host country is also much better prepared to receive foreigners and their families.
Implications for Central European audience: The first Japanese MNCs arrived in Hungary more than 30 years ago, when the transition from a planned economy to a market-based economy was just beginning (Pierce, 1991; Andor, 2019; Jaklič et al., 2020). Japanese expats arrived in a country where, compared to their home country (Hideo, 1990), human resources management was not a recognized corporate function (Pierce, 1991). A typical posting period at that time was one to two years. Expatriates usually did not experience that as an honour or professional development (Matus, 2006).

This paper aims at describing the issue of undeclared work in the Czech Republic and to explain the burdens it represents for the national economy. It also describes what measures can be undertaken in order to tackle undeclared work and uses some real-life examples to illustrate their outcomes. Undeclared work and the so-called "švarc systém" (the employer-employee relations with a person exercising the employer's normal activities not being an employee in legal terms but acting as an independent entrepreneur) are among the biggest issues on the Czech labor market nowadays. According to some estimations, the Czech state loses about five billion CZK annually in the form of uncollected taxes, unpaid revenues and health and social insurance payments. New changes to the Czech labor legislation that came into force in 2012 were envisaged to tackle undeclared work, reduce tax evasions, fight shadow practices on the labor market, and to prevent social deprivation and other threats for the society by shifting the competences to conduct random checks, and controls of firms and businesses were transferred to the State Labor Inspection Offices (SLIO). The changes in the legislation facilitated the identification of the undeclared work and penalizing of its bearers, which minimized the losses from the illegal employment.