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Labour productivity management using health factors: Technique and models

Author

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  • Ekaterina V. Orlova

    (Ufa State Aviation Technical University, Ufa, Russia)

Abstract

The processes of modernization and technological evolution have emphasized the problem of human capital development. The quality of human capital, including physical well-being, makes a significant contribution to the growth of workforce productivity. The paper examines the feasibility of investing in employees’ health in order to ensure the growth of labour productivity at enterprises, as well as develop techniques and models of such investment. The theories of human capital constitute the methodological basis of the study. The research methods used are economic-statistical modeling, cluster analysis and methods of managerial decision-making. The article examines statistical data of management and accounting reports of a large enterprise engaged in the electric power industry, as well as data from a survey of its employees. The study analyzes the existing approaches, methods and models to control employees’ health and labour productivity. It identifies a number of significant shortcomings inherent in the current approaches that limit the scope of their application: there are no quantitative methods for assessing how the level and state of health affect labor productivity and no methods for forming a set of managerial decisions aimed at increasing the efficiency of labor resources with respect to their quality. This necessitates the development of a new approach, technique and its supporting models that reflect the important features of enterprises’ socio-economic system, i.e. the high dynamics of the ongoing processes, the uncertainty of the internal and external environment, and employees’ inclination to distort information about their health. The theoretical significance of the study is due to the proposed technique for managing labor productivity based on stage-by-stage processing of quantitative and qualitative data and modeling, which takes into account objective data on economic, demographic, social factors and subjective data on the quality of employees’ health. The technique provides sup port for making managerial decisions when planning trajectories of labour productivity growth. The practical value of the study lies in the methodology for forming the profiles of employees’ groups with similar characteristics, and in the development of adequate solutions for each group that allow increasing labor productivity quickly and at minimum costs.

Suggested Citation

  • Ekaterina V. Orlova, 2020. "Labour productivity management using health factors: Technique and models," Upravlenets, Ural State University of Economics, vol. 11(6), pages 57-69, December.
  • Handle: RePEc:url:upravl:v:11:y:2020:i:6:p:57-69
    DOI: 10.29141/2218-5003-2020-11-6-5
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    References listed on IDEAS

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    Cited by:

    1. E.V. Orlova, 2021. "Assessment of the Human Capital of an Enterprise and its Management in the Context of the Digital Transformation of the Economy," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(4), pages 666-700.
    2. Ekaterina V. Orlova, 2022. "Impact of Companies' Social Capital on Person's Innovativeness in Russia: Economic Mechanisms and Diagnostic Tools," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 21(3), pages 545-575.

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    More about this item

    Keywords

    labour productivity; data analysis; clustering; labour productivity management; health condition; economic return on health;
    All these keywords.

    JEL classification:

    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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