The development of a forecast model of labour productivity management at industrial enterprises

Abstract

The article gives the analysis of the applicability of the concepts "labour productivity" and "productivity of an economic system" at different stages of creating added value in the new industrialization. The main tools for managing productivity have been identified and those that can be applied in short term and with minimal costs by identifying internal production reserves have been selected. The structuring of short-term and long-term goals of increasing labour productivity has been carried out, and tools for managing labour productivity that are effective in short term have been proposed. On the basis of the study of the level and dynamics of labour productivity at some enterprises of the machine-building complex of Samara region and with the use of economic and statistical methods of analysis, namely, time series analysis, index method and factor analysis forecast tools have been developed. The constructed econometric model of the correlation dependence of labour productivity on the capital productivity index has a high degree of approximation and can be recommended as a model for forecasting labour productivity at industrial enterprises. This is especially important when developing a strategy for the transition to digital industrialization.

Structure of the Performance Management at the Regional Level

“…They would include technological upgrading of manufacture [5], when due to mechanization and automatization, number of personnel decrease, but the reduction of time to produce products happens, improvement in the quality and enhancing the competitiveness of products [6]. At the same time, in most cases, there are capital and other restrictions for quick investment under the existing need in improving productivity of production [7]. The lack of financial resources holds upgrading of basic means of production, which is the main engine of labor productivity growth [8].…”

Enhancing the accuracy and precision of forecasting the productivity of a factory: a fuzzified feedforward neural network approach

“…Instead of forecasting the future productivity, Grabner et al [19] estimated the impacts of improvement actions, such as lean production, on productivity. Repina et al [31] applied several statistical analysis techniques, including time series analysis, index method, and factor analysis, to forecast the productivity of a machine-building company. Chen et al [12] proposed a fuzzy polynomial fitting and mathematical programming approach.…”