Ukrainian Human Resource (HR) practices have multiple difficulties from economic changes combined with digital transformation and workforce instability brought on by the war in 2022. The study examines Ukrainian HR practices between 2015 and 2024, focusing on the digitalization of HR systems, talent development, staff engagement, and hiring strategies. It considers the effects of organizational size and industry type. The study combined interviews with 30 HR professionals and surveyed 150 organizations from different industry groups and sizes. Our data required both quantitative statistical tests and manual content breakdown with codes. Research has shown significant differences between Information Technology (IT) and farming firms, as 89% of IT businesses have integrated artificial intelligence (AI)-powered HR tools. In comparison, only 15% of agricultural companies have adopted them. Small and medium-sized enterprises (SMEs) showed less commitment to digital transformation and European Union (EU) requirements than large enterprises, which adopted these systems at rates of 75% and 88%, respectively. Western Ukraine first established mental health initiatives during the crisis, and Eastern Ukraine moved toward decentralized administration. Digitalization assistance for small businesses, along with EU and local human resources frameworks, should form the basis of our suggestions. This research calls for flexible people management methods to boost the Ukrainian workspace’s ability to recover from shocks.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

This paper discusses the use of workforce ecosystems to manage human intellectual capital. The need for work ecosystems has emerged in the digital age because of the rapid growth in the number of engaged partners and freelancers in the digitalization of enterprises. It is shown that this growth is directly related to the use of agile management systems in design and development: agile, DevOps, microservice architecture, turquoise practices, etc. The information systems needed to manage workforce ecosystems should have competency-based metrics to link business needs, recruitment and training, and finding new partners. At the same time, training should be prioritized over recruitment and the search for new partners in the context of staff shortages. When automating workforce ecosystems, a platform approach should be used to integrate both corporate HR, time and business process management systems, and similar systems from partners.