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Organisational identification-based model of job performance in the IT sector: mediating role of work engagement and organisational citizenship behaviour

Open Access
|Oct 2025

Abstract

High employee job performance is considered one of the key factors contributing to a company’s commercial success, especially in such service-oriented sectors as IT. Researchers recognise a significant role of employee organisational identification, work engagement, and organisational citizenship behaviour in improving job performance; however, a complex model showing the relationship between those variables has not been provided so far. Moreover, a discrepancy exists between the theoretical conceptualisation and definition of organisational identification and its empirically proven measurements. In this context, the article aims to develop a holistic measurement for organisational identification and analyse the roles of organisational identification, work engagement, and organisational citizenship behaviour in improving job performance of the IT sector employees.

An empirical study was conducted with 246 employees from IT sector organisations in Poland and Germany. The study was performed using the CAWI technique. The research tool was a questionnaire. The gathered data were analysed using IBM SPSS Statistics (descriptive statistics, scale reliability testing, and EFA) and IBM SPSS AMOS (CFA and path analysis) to verify the model.

The analysis results show a positive influence of organisational identification on job performance through work engagement and organisational citizenship behaviour, i.e., organisational identification has a strong, positive and statistically significant effect on work engagement; work engagement has a positive and statistically significant impact on job performance and organisational citizenship behaviour; and organisational citizenship behaviour has a positive and statistically significant impact on job performance of the IT sector employees.

DOI: https://doi.org/10.2478/emj-2025-0021 | Journal eISSN: 2543-912X | Journal ISSN: 2543-6597
Language: English
Page range: 83 - 100
Submitted on: Apr 25, 2025
Accepted on: Aug 30, 2025
Published on: Oct 8, 2025
Published by: Bialystok University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Katarzyna Żak, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.