Year: 2026
Type: conference-paper
Abstract: The energy sector in Latvia is widely recognized as a cornerstone of sustainable economic development, with increasing emphasis on technological advancement, digitalization, and innovation. Despite this focus, limited attention has been paid in the academic literature to internal alignment challenges within the sector, particularly the mismatch between human resource capacity and the rapidly evolving engineering and technological requirements. This study analyses data obtained during the first stage of a broader research framework, focusing on the application of adaptive forecasting approaches in human resource development and planning within the energy sector. The methodological approach is based on quantitative analysis of workforce data, applying adaptive forecasting principles to assess human resource demand under dynamic technological and operational conditions. The results of the research indicate that workforce qualification and responsibility data are limiting effective human resource planning. The findings show that workforce capacity modelling demonstrates the applicability of adaptive forecasting approaches for analysing workforce demand under dynamic operational conditions, highlighting their potential to support more coherent and responsive workforce planning. These initial results provide a critical foundation for the subsequent stages of the research, which will further explore integrated forecasting tools and policy recommendations for workforce development in the Latvian energy sector.
Authors: Rimants Jelinsks, Una Libkovska
Institution: Ventspils University of Applied Sciences
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W7165196751