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.

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The aim of the article is to present barriers to human capital development in Poland. The research was carried out on 941 respondents, from medium and large companies categorized as knowledge-intensive service (KIS), less-knowledge intensive service (LKIS) and production. The research indicates the following barriers: lack of financial resources, higher priority of other issues/projects/investments, lack of time for developmental actions, lack of consciousness of Board members and managers concerning the importance of development, lack of employees’ eagerness to learn, organizational culture resistant to change.

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The pork value chain is created by a network of interconnected suppliers and customers, offering meat products to final consumers. Pork production and processing in Poland is highly fragmented, which together with an increasing global pressure weakens the engagement of institutional actors in the social dialogue. This makes difficult to combat negative labour market phenomena such as low wages, long working hours, and lack of appropriate contracts. In order to diagnose the specificity of labour market challenges in Poland and possible ways of combating them, structured interviews with key stakeholders were conducted. They confirmed the existence of abusive practices in the local pork industry and the need for strengthening the social dialogue. Conclusions from the research include recommendations for further exploration of the issue.