Modeling the productivity management process in agriculture: a case study of Ukraine

Abstract

The purpose of the study is to form an economic and statistical toolkit for quantitative analysis of the impact of determining factors on the level of labor productivity in the agricultural sector of Ukraine. as well as to substantiate directions for improving the effectiveness of managerial decision-making based on correlation and regression analysis. The study examines factors of labour productivity management in the agrarian sector of Ukraine using a correlation–regression approach and forecasting modelling. It is substantiated that the dynamics of output per employee are shaped by the combined influence of interrelated financial, economic, and production factors, among which the availability of fixed assets, financial performance, and parameters of labour resource utilisation play a decisive role. The empirical basis of the research comprises official statistical data for the period 2010–2024. The study applies methods of correlation and multivariate regression analysis to quantitatively assess the impact of fixed assets, capital investment, net profit, and average monthly wages on the level of labour productivity. It is established that the most significant positive effect on output is exerted by the volume of fixed assets and net profit, which confirms their determining role in enhancing the efficiency of labour utilisation in the agricultural sector. Based on the estimated model, a forecast of labour productivity up to 2030 is developed, indicating the preservation of an upward growth trajectory of output under an inertial development scenario.