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Despite being a seminal explanation of the workforce emotional experiences, capable of mapping the path from the antecedents to consequences, affective events theory (AET) only offers a “macrostructure” of a working environment. To date, little is known about the universal features of the work environment that may guide the understanding of imperative work aspects triggering employees’ emotions at work. Hence, the study proposes and validates that Stafford Beer’s viable system model (VSM) can provide a holistic view of the organizational work environment, enabling a comprehensive understanding of work events or factors triggering workforce emotions.

First, the VSM structural layout is used to fill in the “macrostructure” of the “working environment” in AET to diagnose the functional and relational aspects of the work and the related work events occurring within. Using a deductive approach, 31 work events were adopted to determine the impact of VSM-based work environment events on the employees’ emotional experiences and subsequent work attitudes (job satisfaction) and behaviors (citizenship behavior). To field test the proposed nexus of VSM and AET, the survey was conducted on two hundred and fifteen employees from 39 different organizations. PLS-SEM tested the explanatory power of the suggested VSM’s systemic approach for understanding the affective work environment in totality.

The findings confirmed that the VSM metalanguage provides a holistic view of the organizational functioning and social connectivity disposing of affective work events, helpful in assessing their aggregate influence on employees’ emotions and work-related outcomes.

The findings identify how employees' emotions can be triggered by everyday work operations and social relations at work, which can affect their extra-role behaviors and necessary work-related attitudes.

The study utilized Beer’s VSM framework based on the systemic principle of “holistic view” for ascertaining the affective work environment and its related features holistically, which filled in well the macrostructure of “work environment features” with micro-structures of organizational inter-related aspects which are yet to be known in AET – a seminal explanation for managing workforce emotions.

Can managerial supplication lead subordinates to engage in undesirable work behavior? What role, if any, do negative emotions play in this process? Are there factors that moderate these emotions and their harmful implications? Relying on the affective events theory, the current study investigated these questions using a moderated mediation model in which: (a) perceived managerial supplication elicited sadness that resulted in counterproductive work behavior and (b) political skill and emotional intelligence moderated these relationships.

The moderated mediation model was tested using a sample of 167 employees. The data were collected in three waves.

Perceived managerial supplication was positively related to subordinates' sadness and both dimensions of counterproductive work behavior, namely, organizational and interpersonal counterproductive work behavior. Moreover, sadness was positively related to both dimensions of counterproductive work behavior and mediated the relationships between perceived supplication and these two undesirable outcomes. Nevertheless, contrary to our expectations, all moderation effects included in our model were insignificant.

Human resource departments should implement training programs to develop the awareness of their managers about the harmful consequences of perceived supplication, encouraging them to use other behaviors with subordinates.

This study is the first to (a) suggest and validate the view that subordinates' perceptions about their managers' use of supplication can result in undesirable work behavior and (b) demonstrate that sadness, an emotion that is not associated with the tendency to express external aggression, can lead employees to engage in counterproductive work behavior toward both their organizations and colleagues.

Although numerous studies have been conducted to explore the impact of various factors on employees' turnover intention and intention to remain with the organization, the relationship between these two constructs remains largely unexplored. Considering the significance of these constructs, particularly in the context of the COVID-19 pandemic, the authors aimed to investigate their association within an academic environment using a dynamic modeling approach.

This study follows a quantitative approach and utilizes a longitudinal survey design. The authors utilized a cross-lagged panel model (CLPM) and employed the parametric efficient partial least squares (PLSe2) methodology to estimate the dynamic model using data gathered from lecturers associated with both public and private universities in Malaysia. In order to offer methodological insights to applied higher education researchers, the authors also compared the results with maximum likelihood (ML) estimation.

The findings of the authors' study indicate a reciprocal relationship between turnover intention and intention to remain with the organization, with intention to remain with the organization being a stronger predictor. Moreover, situational factors were found to have a greater influence on eliciting turnover intention within academic settings. As anticipated, the use of the PLSe2 methodology resulted in higher R² values compared to ML estimation, thereby reinforcing the effectiveness of PLS-based methods in explanatory-predictive modeling in applied studies.

The authors' findings suggest prioritizing policies that enhance training and consultation sessions to foster positive attitudes among lecturers. Positive attitudes significantly impact judgment-driven behaviors like turnover intention and intention to remain with the organization. Additionally, improving working environments, which indirectly influence judgment-driven behaviors through factors like affective work events, affect and attitudes, should also be considered.

This study pioneers the examination of the causal relationship between turnover intention and intention to remain with the organization, their stability over time and the association of changes in these variables using a dynamic CLPM in higher education. It introduces the novel application of the cutting-edge PLSe2 methodology in estimating a CLPM, providing valuable insights for researchers in explanatory-predictive modeling.

This study aims to uncover the theoretical role and the effects of mindfulness on psychological strain as well as job satisfaction among young German employees. The study took place during the COVID-19 pandemic, which was a stressful time for German employees. Thus, the role of mindfulness should be explained.

A sample of 198 participants was used for analysing the relationships by applying partial least squares structural equal modelling.

This study highlights that, in the working context, mindfulness was statistically significantly and negatively related to psychological strain (ß = −0.498, p < 0.000) and positively as well as statistically significantly related to job satisfaction (ß = 0.263, p < 0.000). Furthermore, psychological strain is negatively but statistically significant related to job satisfaction (ß = −0.207, p < 0.017). Additionally, psychological strain mediates the relationship between mindfulness and job satisfaction positively and significantly (ß = 0.103, p < 0.026).

This study contributes by firstly setting up a conceptual model that explicitly uncovers the paramount importance of mindfulness at work in relation to job satisfaction. Moreover, the authors contribute by highlighting that psychological strain is negatively affected by mindfulness. To the best of the authors knowledge, this is the first study examining this interplay and setting up a new conceptual model.

This study investigates the profound impact of artificial intelligence (AI) capabilities on decision-making processes and organizational performance, addressing a crucial gap in the literature by exploring the mediating role of decision-making speed and quality.

Drawing upon resource-based theory and prior research, this study constructs a comprehensive model and hypotheses to illuminate the influence of AI capabilities within organizations on decision-making speed, decision quality, and, ultimately, organizational performance. A dataset comprising 230 responses from diverse organizations forms the basis of the analysis, with the study employing a partial least squares structural equation model (PLS-SEM) for robust data examination.

The results demonstrate the pivotal role of AI capabilities in shaping organizational decision-making processes and performance. AI capability significantly and positively affects decision-making speed, decision quality, and overall organizational performance. Notably, decision-making speed is a critical factor contributing significantly to enhanced organizational performance. The study further uncovered partial mediation effects, suggesting that decision-making processes partially mediate the relationship between AI capabilities and organizational performance through decision-making speed.

This study contributes to the existing body of literature by providing empirical evidence of the multifaceted impact of AI capabilities on organizational decision-making and performance. Elucidating the mediating role of decision-making processes advances our understanding of the complex mechanisms through which AI capabilities drive organizational success.

This study aims to examine the relationship between a team’s value diversity (VD) and creativity and investigate the moderating effect of emotional intelligence (EI) to explain inconsistent results regarding this relationship.

We conducted a cross-sectional sequential study with 340 employees and tested the hypothesis in a laboratory setting with 180 undergraduate students.

EI had a moderating effect on the relationship between a team’s VD and creativity in that the relationship was positive among teams with high EI. However, the relationship tended to be negative in the long term among teams with low EI.

Managers should pay attention to how teams benefit from VD because it can help or harm team performance. By assigning people with different EI levels into suitable teams and providing EI interventions, organizations may manage affective consequences and enjoy more benefits of cognitive consequences resulting from VD.

No previous study has investigated the effect of a team’s EI in the relationship between VD and team creativity. Drawing on the categorization-elaboration model of diversity and affective events theory, through the present two-study design, we obtained data from multiple sources and improved limitations in measurements of previous studies, thereby broadening the literature by highlighting the dynamic relationship between a team’s EI, VD and creativity in the Vietnamese context.

Relying on the affective events theory, this study conceptualizes abusive supervision as a micro-affective event and tests a multilevel moderated mediation arguing that abusive behaviors from the supervisor trigger negative affective reactions that, in turn, will enhance the likelihood of counterproductive work behaviors (interpersonal and organizational). We further propose that mindfulness will shape how employees react to abusive behaviors from supervisors.

A daily diary study conducted for five consecutive days was developed with Portuguese working adults (N = 176*5 = 880).

The multilevel findings showed that abusive behaviors triggered negative affect and this, in turn, promoted both forms of counterproductive work behaviors. The indirect effect regarding interpersonal counterproductive work behavior was moderated by mindfulness in such a way that the indirect effect was stronger for those who scored lower on mindfulness (versus higher levels). The indirect effect on organizational counterproductive work behavior was not significantly moderated by mindfulness.

The examination of mindfulness as a moderating factor contributes significantly to management by delineating practical strategies to assist employees in effectively managing micro-events involving abusive behaviors from supervisors. Consequently, these findings may inform the development of research-backed strategies aimed at mitigating the affective and behavioral repercussions of an abusive supervisor.

The inclusion of mindfulness in the model is an added value.

This paper analyzes employees’ perceptions of data collection processes for human resource analytics (HRA). More specifically, we study the effect that information sharing practices have on employees’ attributions (i.e. benevolent vs malevolent) through the perceived legitimacy of data collection and monitoring processes. Moreover, we investigate whether employees’ emotional reaction (i.e. fear of datafication) depends on their perceived legitimacy and attributions.

The research is based on a sample of 259 employees operating for an Italian consulting firm that developed and implemented HRA processes in the last 3 years. The hypothesized model has been tested using structural equation modeling (SEM) on Stata 14.

This paper demonstrates the mediating role of perceived legitimacy in the relationship between information sharing practices and employees’ benevolent and malevolent attributions about data collection and monitoring processes for HRA practices. Results also reveal that perceived legitimacy predicts employees’ fear of datafication, with benevolent attributions that partially mediate this relationship.

This research indicates that employees perceive, try to make sense of and emotionally react to HRA processes. Moreover, we reveal the crucial role of information sharing practices and perceived legitimacy in determining employees’ attributions and emotional reactions to data collection and monitoring processes.

Combining human resource (HR) attributions, HR system strength, information processing and signaling theories, this work explores employees’ perception, attributive processes and emotional reactions to data collection processes for HRA practices.

Prior research and theory have shown that transformational leadership can be developed through leader development programs (LDPs). To explain how this happens, research suggests a strong connection between an individual’s leader self-concept and their leadership behavior that can be manipulated through LDPs. The purpose of this article is to delve deeper into this phenomenon to understand how development occurs and to better understand how an LDP can improve leadership behaviors by influencing one’s self-concept and ultimately reduce the training transfer gap. As a broader goal, this article contributes to the existing literature on the value proposition of investing in LDPs.

We conducted an explanatory sequential design mixed-methods study to measure the development of participants and the impact of the program. The quantitative phase of the study used self-report surveys to measure the LDP’s impact on participants’ transformational leader behavior (TLB) and concept of themselves regarding leadership, their leader self-views (LSVs). The study also measured the relationship between LSVs and later enactment of leadership behaviors as the second hypothesis. The subsequent qualitative study was designed to understand the mechanisms that might explain the quantitative results.

The study’s empirical findings indicate a positive relationship between LSVs (efficacy, self-awareness and identity) and distal leader development outcomes (TBLs). The study’s findings also provide support for the claim that LDPs convert knowledge and skills into TLB, expanding an individual’s capacity to be effective in leadership roles and processes (Day & Dragoni, 2015). Qualitative results also show LDPs improve leader behavior by influencing their self-efficacy via providing tools and knowledge as well as building experimental mindset.

By showing LDPs' long term impacts, this paper demonstrates why short-term leadership development programs are worth investing.

This article aims to examine whether the organizational changes brought about by digital transformation (DT) -such as a new organizational culture, new leadership and new business models-influence talent management, with the latter being seen as one of the major challenges facing companies in their process of digital transformation.

Using a quantitative methodology, a survey was applied to 314 companies in order to analyze the results of their talent management in the DT process. DT is not only digitalization as demonstrated in this study. Talent management is the key piece that can facilitate or block achieving high levels of digital maturity.

The study finds that the changes brought about by DT impact talent attraction, talent retention, and talent management in general, and also shows that digital transformation does not depend on digitalization, but rather that talent management is the key to either helping or preventing high levels of digital maturity being achieved.

The originality of this work lies in examining the influence of the changes that DT entails in talent management.