Enhancing employees’ quality of work life and engagement to foster corporate social responsibility: a data mining approach
Industrial and Commercial Training
ISSN: 0019-7858
Article publication date: 3 June 2024
Issue publication date: 11 June 2024
Abstract
Purpose
This paper aims to present a dynamic model for strategic and personalized decision-making in human resources (HR), using data mining techniques to enhance corporate social sustainability (CSS). The focus is on the interconnectedness of employee engagement (EE), enablement and the quality of work life.
Design/methodology/approach
The proposed model integrates various HR data, including demographic information, job specifications, payment and rewards, attendance and absence, alongside employees’ perceptions of their work-life quality, engagement and enablement. Data mining processes are applied to generate meaningful insights for senior and middle managers.
Findings
The study implemented the model within a production organization, revealing that factors influencing EE and enablement differ based on gender, marital status and occupational group. Performance-based rewards play a significant role in enhancing engagement, regardless of the reward amount. Factors such as “being recognized for competency” influence engagement for women, while payment has a greater impact on men. Engagement does not directly influence the quality of work life, but subcomponents like perceived transparency and the organization’s processes, particularly the “employee performance evaluation system,” improve work-life quality.
Research limitations/implications
The findings are specific to the studied organization, limiting generalizability. Future research should explore the model’s effectiveness in different cultural and organizational settings.
Practical implications
The proposed model provides practical implications for organizations that enhance CSS. Organizations can gain insights into factors influencing EE and enablement by using data mining techniques, enabling informed decision-making and tailored human resource management practices.
Social implications
This research addresses the societal concern regarding the impact of business activities on sustainability. Organizations can contribute to a more socially responsible and sustainable business environment by focusing on work-life quality and EE.
Originality/value
This paper offers a dynamic model using data mining and machine learning techniques for sustainable human resource management. It emphasizes the importance of customization to align practices with the unique needs of the workforce.
Keywords
Acknowledgements
Compliance with ethical standards: Disclosure of potential conflict of interest: The authors declare that they have no conflict of interest.
Ethical approval: The authors hereby accept the terms of your journal’s ethical codes.
Research involving human participants and/or animals: Not applicable.
Competing interests: The authors have no competing interests to declare that are relevant to the content of this article.
Informed consent: Not applicable.
Data availability statement: The data sets gathered during the current study are not publicly available due to organizational privacy but part of the anonymous data is available from the corresponding author on reasonable request.
Citation
Sareminia, S. and Sajedi Haji, F. (2024), "Enhancing employees’ quality of work life and engagement to foster corporate social responsibility: a data mining approach", Industrial and Commercial Training, Vol. 56 No. 3, pp. 213-239. https://doi.org/10.1108/ICT-10-2023-0078
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited