The digitalisation of work is resulting in a transformation in the relationship between employees and employers as well as the perception of quality of life. Under the conditions of the COVID-19 pandemic, individuals whose work could be done with digital tools were directed to work remotely. Performing work duties at a distance from the workplace, colleagues, and supervisors affects the workplace resources available to employees and can have an impact on employee well-being. The main purpose of this paper is to analyse the relationship between remote working and employee well-being. The research hypothesis was that there is a relationship between employee well-being and the level of digitisation of work performed, as measured by the frequency of remote working. This article presents the results of empirical research conducted in January 2021, using the CAWI method, on a representative sample of Polish workers (n = 1000). An exploratory factor analysis and logistic regression were carried out. The results point to the three-dimensional nature of employee well-being, which includes workplace relationships, health, and work–life balance. Based on the results, working exclusively remotely was shown to negatively affect well-being in terms of workplace relationships and work–life balance. There was no statistically significant association between remote working and subjective health assessment. The results have important implications for the management of employee well-being in remote working settings. Originality/value lies in the fact that the article provides practical guidance in planning hybrid work arrangements.
PurposeExisting literature on algorithmic management practices – defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice and – as a result – workplace well-being. Literature review revealed a significant gap in empirical research on the nature and direction of these relationships. Therefore the purpose of this paper is to analyse how algorithmic management practices directly influence workplace well-being, as well as investigating its relationships with job autonomy and total rewards practices.Design/methodology/approachConceptual model of relationships between algorithmic management practices, job autonomy, total rewards and workplace well-being has been formulated on the basis of literature review. Proposed model has been empirically verified through confirmatory analysis by means of structural equation modelling (SEM CFA) on a sample of 21,869 European organisations, using data collected by Eurofound and Cedefop in 2019, with the focus of investigating the direct and indirect influence of algorithmic management practices on workplace well-being.FindingsThis research confirmed a moderate, direct impact of application of algorithmic management practices on workplace well-being. More importantly the authors found out that this approach has an indirect influence, through negative impact on job autonomy and total rewards practices. The authors observed significant variation in the level of influence depending on the size of the organisation, with the decreasing impacts of algorithmic management on well-being and job autonomy for larger entities.Originality/valueWhile the influence of algorithmic management on various workplace practices and effects is now widely discussed, the empirical evidence – especially for traditional work contexts, not only gig economy – is highly limited. The study fills this gap and suggests that algorithmic management – understood as an automated decision-making vehicle – might not always lead to better, well-being focused, people management in organisations. Academic studies and practical applications need to account for possible negative consequences of algorithmic management for the workplace well-being, by better reflecting complex nature of relationships between these variables.
There are only a few fragmented studies available on the relationship between engagement, employability and sustainable HRM practices. This research gap justifies the investigation of a relationship between these constructs. The research findings presented in this article, to the authors' knowledge, are the first to simultaneously address Sustainable Human Resource Management, Work Engagement and Perceived Employability. The aim of this research is to identify the impact of Sustainable HRM on Work Engagement and Perceived Employability. A quantitative study was conducted among employees to test the model of the relationship between mentioned above variables. The purposive-quota sampling was chosen to survey representatives of organisations with a minimum of 10 employees. The survey was conducted on a survey panel accredited by PKJPA and ESOMAR using the CAWI platform. The results confirm a strong correlation between Sustainable HRM and Work Engagement, as well as a moderate influence of Sustainable HRM on Perceived Employability. Further research would need to delve deeper into the impact of specific Sustainable HRM practices on Work Engagement and Perceived Employability. It would be worth extending the research to include other types of commitment like organisational attachment, and to include determinants in the analysis of Perceived Employability.
Objective: The purpose of this article is to analyse the relationship between employee well-being and three aspects of engagement: vigour, dedication to work and absorption.Research Design & Methods: The research hypotheses are derived from the subject literature. Exploration of the relationships between the constructs was based on a CAWI survey conducted in January 2021 on a sample of 1,000 working Poles. The relationships were examined using Rho Spearman correlation and multiple regression analyses.Findings: Energy, pleasure, enthusiasm for work, a sense of pride and meaning in one's tasks all have a positive impact on employee well-being. For Poles, being absorbed in work and doing it with passion has no bearing on well-being.Implications / Recommendations: The survey results confirmed the existence of a relationship between employee engagement and the well-being of working Poles. Employee well-being is positively affected by vigour and dedication to one’s work. Work absorption was not found to have an effect on well‑being.Contribution: The study contributes to the knowledge base on the impact of engagement factors on employee well-being. The results suggest that employee well-being can be explained with comprehensive models.
Sprawiedliwość jest kluczowym parametrem oceny poziomu wynagrodzenia. W polskiej literaturze brakuje analiz empirycznych analizujących istotę tego konstruktu. Główny celem przeprowadzonych badań była identyfikacja czynników wpływających na ocenę sprawiedliwości i ich zróżnicowania w zależności od poziomu płac. Wyniki analizy SEM‑PLS na podstawie danych zebranych na reprezentatywnej próbie pracujących Polaków wykazały, że rodzaj czynników zmienia się przy miesięcznej kwocie wynagrodzenia 3500 PLN netto. Poniżej tej kwoty na ocenę sprawiedliwości wynagradzania wpływa troska przełożonego, system wynagradzania oraz przekonanie o słuszności różnicowania wynagrodzeń na podstawie nakładów, zadań i wyników. Powyżej wymienionej kwoty na tę ocenę również wpływa troska przełożonego oraz relacje w miejscu pracy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.