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Existing 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.

Conceptual 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.

This 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.

While 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.

Intrinsic motivation affects job satisfaction and turnover intention. Still, previous motivational studies among real estate brokers (brokers) have primarily focused on extrinsic rewards, leaving intrinsic rewards/motivation practically unexplored. The purpose of this study is therefore to evaluate the role of both satisfaction with intrinsic rewards (SIR) and satisfaction with extrinsic rewards (SER) on job satisfaction and turnover intention among Swedish brokers.

This article is a replication, more precisely an empirical generalization and extension, of Mosquera et al.’s (2020) study conducted among brokers in Portugal. Using a sample of 910 Swedish brokers, the study analyzes a conceptual framework and tests hypotheses by using partial least squares (PLS).

Results indicate that SIR has a very strong impact on job satisfaction, which is not the case in the Portuguese sample. On the other hand, SER does not have an impact on job satisfaction, which is the case in the Portuguese sample. SIR does not have an impact on turnover intention in the Swedish sample, whereas SER does. Job satisfaction has twice the positive impact on turnover intention in the Swedish sample compared to the Portuguese. Furthermore, job satisfaction mediates the relationship between SIR/SER and turnover intention.

Findings of this study extend the existing literature of satisfaction with extrinsic and in particular intrinsic rewards on job satisfaction and turnover intention in the context of the brokerage industry. The most interesting difference between the samples is that Swedish brokers display much higher levels of satisfaction with intrinsic rewards. On the other hand, Swedish brokers appear to be less driven by extrinsic rewards, which is not in line with prior studies within brokerage.

Both managers and students planning to become brokers should consider that SIR has a stronger impact on job satisfaction than SER. What are perceived as intrinsic rewards, however, is highly subjective, which is troublesome from a managerial perspective, even more so as SIR is much harder to influence than SER. Given that intrinsic motivation is primarily a consequence of needs fulfillment, screening of applicants for person-job fit ought to increase job satisfaction and reduce turnover given its focus on the congruence between job demands and worker’s needs, respectively, what a job provides and the worker’s needs.

This study contributes to the brokerage research field by indicating that being a broker differs substantially between countries and that intrinsic rewards matter for Swedish brokers.

This study investigated the effects of reward system (RS) and job conditions (JC) on employee retention (ER). In particular, this study addressed the mediating effect of employee engagement (EE) on the relationship between RS, JC and ER.

This paper employed descriptive survey approach and the unit of analysis consisted of public hospital nursing staff. Data were collected using questionnaires with a sample of 370 nurse respondents. Structural equation modelling with Smart-Partial Least Squares (PLS) 3.3.8 was used in a statistical analysis.

The results revealed that RS and JC significantly related to ER. The study also showed the direct effect of RS and JC on EE. These findings indicate that (EE) has a partial mediating role in the relationship between RS, JC and ER.

The study offers important policy insights for public nursing stakeholders who seek to increase retention of skills among their nursing staff. The findings are also crucial because they may help the health sector improve their ER strategies, especially in dynamic and competitive business situations where organisations are challenged to retain personnel from a limited skilled workforce.

The findings of this study contribute to the literature on retention of nursing employees by enhancing the understanding of the influences of EE, RS and JC on ER among public hospitals.

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

This study examines how the strong emphasis placed on the purposes of budgeting, referring to a comprehensive focus on budgeting, is related to top managers' education and tenure while controlling for their functional positions in their respective firms and ages, as well as several company-specific predictors (information quality, firm size, information technology, importance of profit and strategy).

Survey data were collected from senior managers of large manufacturing firms in Finland and Sweden.

The results suggest that academic business education is positively associated with a comprehensive focus on budgeting, but tenure as well as functional position in the company (Chief Financial Officer (CFO) or not) and age are not. Overall, the company-specific control variables in general and information quality in particular are shown to have greater explanatory power than the top management characteristics analyzed.

This study identifies several empirically supported factors that seem to contribute to a comprehensive focus on budgeting. The effects of information quality, business education, the importance of profit and firm size could be considered in future research.

Academic business education matters more than the other top management characteristics analyzed. If organizations want to make comprehensive use of budgets, they should employ business graduates and be mindful of company-specific variables.

This study is the first to address a comprehensive focus on budgeting and some of its determinants. Future research could investigate a broader set of such determinants in different contexts.