Digital Economy & Innovations

Integration of regional human resource management into the process of achieving goals of national economy is of particular importance in the context of the need for a comprehensive and systemic approach to the development of territories. Considering human resources not as a separate sphere, but as a key resource and factor determining the possibilities of implementing the strategic goals of the region, allows increasing the validity of management decisions, which become a logical result of an effective model of regional human resource management. The conducted analysis of existing mechanisms of regional human resource management allowed identifying the advantages and limitations of their use, taking into account the fact that a centralized top-down management model is currently used, which in contemporary institutional conditions is losing its effectiveness and speed of response to changes in local labor markets. The conceptual decentralized model of the mechanism of regional human resource management in the context of strategic planning of regional economic policy is clarified. An improved mechanism of regional human resource management is developed. The study showed that the decentralized bottom-up model of regional human resource management has significant potential for the development of the regional economy. However, its effectiveness increases significantly with the integration of a new institution that ensures coordination and strategic management of local initiatives, promotes synergy between actors, extension of best practices and more complete consideration of the needs of the regional economy in the strategic planning process.

Application of artificial intelligence in various spheres of life is a critical task. International trade is not an exception for the introduction of innovations. The key issue of inter-country movement is the commodity identification for customs purposes. The paper presents the results of a comprehensive practical comparative study of the possibility of using artificial intelligence to classify commodities for customs purposes. As a model, the neural network of artificial intelligence developed by the World Customs Organization is used. The study included four stages, including the selection of goods to improve the reliability of the results obtained, a study of the applicability of the model for classifying commodities and the possibility of its use for customs purposes, as well as a criteria analysis of the features taken into account by the model when classifying commodities. The limited applicability of the model proposed by the World Customs Organization was revealed both for identification based on classification and for customs purposes based on direct analysis of the texts of the Harmonized Commodity Description and Coding System. The model does not see the degree of completeness in the descriptions of commodities, does not take into account the feature of independence of the goods in terms of use. An increase in the number of words in the description of the commodities also reduces the likelihood of its correct identification. The model takes into account most successfully the characteristics of goods related to the scope of application and functional purpose. The result of the complex study allowed considering comprehensively the possibilities of practical application of artificial intelligence and evaluating the actually obtained results for the studied group of goods. The obtained data on identifying the classification features of commodities taken into account in the model can be used for its further development.