Original Research

Industry and geographic dynamics of employee productivity levels for different major job code and age categories in the South African workplace

Gerhardus van Zyl
Journal of Economic and Financial Sciences | Vol 15, No 1 | a708 | DOI: https://doi.org/10.4102/jef.v15i1.708 | © 2022 Gerhardus van Zyl | This work is licensed under CC Attribution 4.0
Submitted: 13 September 2021 | Published: 26 April 2022

About the author(s)

Gerhardus van Zyl, School of Economics, College of Business and Economics, University of Johannesburg, Johannesburg, South Africa


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Abstract

Orientation: This study was part of an ongoing research project on various aspects of employee productivity in the South African workplace.

Research purpose: The aim of this study was to determine the impact of industry and geographic dynamics on the employee productivity levels of different major job code and age categories.

Motivation for the study: None of the South African publications in this particular field exist, and it was deemed to be important to close this gap in the employee productivity literature.

Research approach/design and method: This study adopted a marginal productivity model to estimate marginal employee productivity levels, employee remuneration cost levels and net marginal productivity levels for different major job code and age categories within different industries and geographical areas.

Main findings: The age categories 30–45 and 45–55 years presented, in general, higher net marginal productivity levels in relation to the other age groups. Marginal employee productivity levels per major job code differ between different geographical areas and industries.

Practical/managerial implications: The estimations indicated the importance of focusing on the diffusion of new technologies and innovations at important major job code and age categories to maximise net employee productivity levels within firms and industries.

Contribution/value-added: The study contributed to policy debates on the attainment of higher levels of employee productivity when industry and geographic dynamics on the net productivity levels of different major job code and age categories are considered.


Keywords

marginal productivity model; marginal employee remuneration costs; fixed-effect panel data estimation; net marginal productivity

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