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Verification of the Job Performance Model based on Employees’ Dynamic Capabilities in organisations under the COVID-19 pandemic crisis Cover

Verification of the Job Performance Model based on Employees’ Dynamic Capabilities in organisations under the COVID-19 pandemic crisis

Open Access
|Oct 2021

Abstract

The paper aims to verify the Job Performance Model based on Employees’ Dynamic Capabilities (EDC) and explain the mechanisms shaping job performance based on EDC in an initial phase of the crisis in an organisation due to the Black Swan phenomena, on the example of the COVID-19 pandemic of 2020. Empirical research on Italian organisations affected by the crisis shows that the Model is significantly distorted under such conditions. To verify the internal structure of the Job Performance Model based on EDC under critical conditions, the statistical correlation analysis, linear regression analysis and path analysis were executed using SPSS and SPSS AMOS. The research result of the statistical analysis confirmed that the new version of the Model for organisations under the Black Swan phenomenon was statistically significant without work motivation and job satisfaction. It was also proven that P–J fit still linked EDC and job performance through strengthening work engagement. The research confirmed that the Job Performance Model based on EDC, which has so far been verified under normal working conditions, radically changed its structure during the COVID-19 crisis. This means that factors previously considered important in the Job Performance Model based on EDC have become insignificant in shaping job performance. Therefore, this is an inspiration for further research to verify the Job Performance Model based on EDC in different phases of the crisis.

DOI: https://doi.org/10.2478/emj-2021-0022 | Journal eISSN: 2543-912X | Journal ISSN: 2543-6597
Language: English
Page range: 66 - 85
Submitted on: Apr 1, 2021
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Accepted on: Sep 10, 2021
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Published on: Oct 30, 2021
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2021 Agnieszka Bieńkowska, Anna Koszela, Katarzyna Tworek, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.