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Bullying knowledge hiding has been recently identified as a manifestation of knowledge hiding behavior. As a relatively new concept, it is still underexplored. Previous research has focused on the antecedents of bullying hiding. However, there is a lack of research on the negative consequences that bullying hiding may have on employees. This study aims to uncover the effects of supervisor bullying hiding on employees knowledge behavior. The study also aims to examine the moderating effect of power values and the mediating effect of job stress.

Data were gathered in two waves from 444 employees with higher education in Poland. Data collection was conducted in July and August 2022. A general linear model mediation analysis with jamovi Advanced Mediation Models software was used to examine the hypotheses.

The results indicate that bullying knowledge hiding by supervisors triggers subordinates’ job stress and aggression in the form of bullying knowledge hiding toward co-workers. Contrary to expectations, job stress does not mediate the relationship between supervisor bullying hiding and subordinate bullying hiding toward co-workers. Power-dominance values, contrary to power-resources values, moderate the above relationship.

As bullying hiding has significant potential to spread among organizational members, managers seeking to reduce it should check the personal values of job applicants and employees.

Based on the behavioral contagion and frustration–aggression–displacement theories, to the best of the author’s knowledge, this study is the first to investigate the relationships between supervisor bullying hiding, job stress, power values and subordinate bullying hiding toward co-workers.

This book aimed to conceptualise a construction workforce management model suitable for effectively managing workers in construction organisations. To this end, this chapter presents the conceptualised model, which consists of seven workforce management practices with their respective measurement variables. Drawing from existing theories, models, and practices, the chapter concludes that a construction organisation that will attain its strategic objectives in the current fourth industrial revolution era must be willing to promote effective recruitment and selection, compensation and benefits, performance management and appraisal, employee involvement and empowerment, training and development, as well as improving workers emotional intelligence and handling external environment pressure. These practices can promote proactiveness, participation, and improved skills and can lead to effective commitment, better quality, and flexibility within the organisation.

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three distinct periods of excessive growth of regional Czech housing prices, identified through the formation of large positive GAPs – (1) before the entrance of Czechia to the European Union (EU), (2) at the onset of the Global Financial Crisis GFC, (3) in 2021. In all these periods, we identify significant differences among regions. We find that GAPs above 15% may be considered an indication of unsustainable long-term housing price growth that will be followed by a correction.

We then employ fixed effect panel data model to determine the drivers of flat and house prices in 14 Czech regions. Our results show that wage growth, migration and crime rate are significant factors affecting the prices of both flats and houses. Nevertheless, the impact of GDP per capita and job market indicators differs between flats and houses. Moreover, we find that higher migration into the region increases the difference between the prices of houses and flats, while increasing GDP per capita growth and crime rate mitigate this difference significantly.

This study aims to assess the effect of job insecurity, customer incivility and work–life imbalance on Lebanese bank employee workplace well-being (EWW), while investigating the moderating role that positive and negative affect might have.

Quantitative data was collected from 202 respondents and analyzed using structural equation modeling system through IBM SPSS and AMOS.

Results revealed that each of the independent variables has a negative, statistically significant effect on Lebanese bank EWW. The positive affect and the negative one are shown to have a moderating effect that lessens and boosts, respectively, these negative effects.

The study adds to the literature on EWW while highlighting the high-power distance and collectivist society that the research took place in.

Limitations include the sample size that was hoped to be larger, in addition to the self-reporting issue and what it entails in the data collection process.

The study has many practical implications, including the validation of a questionnaire in a developing Arab country, hence providing a reliable tool for researchers. HR specialists should lean toward applicants with positive affect, ensuring that their workplace is occupied by members with enhanced resilience. Furthermore, employers should support their employees’ professional growth, thus, boosting their employability during turmoil and consequently making them less vulnerable in times of economic recession.

The study’s unique context, depicted in the harsh economic and financial crisis, makes the findings on EWW of a high value.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

This study was aimed at obtaining a micro understanding of corporate social responsibility (CSR) by investigating the effect of perceived CSR on job performance. Especially, an attempt is made to explore the mediating role of perceived organizational support and the moderating role of collectivism on the relationship between perceived CSR and job performance.

This study collected questionnaire data from 219 employees of Chinese manufacturing firms, then used hierarchical multiple regression analysis to test our theoretical model.

Our empirical results demonstrate that perceived internal and perceived external CSR are positively associated with job performance. In addition, perceived organizational support mediates the relationship between perceived CSR and job performance, and collectivism positively moderates the relationship between perceived external CSR and perceived organizational support.

This study highlights the importance of adopting various strategies to conduct CSR practices, enhancing perceived organizational support and leveraging employee collectivism, which would be beneficial to improve job performance.

This study reveals employees’ underlying attitudes and behaviors responses to perceived CSR, thereby deepening the micro understanding of CSR. In addition, it extends the literature on social exchange theory by dividing perceived CSR into perceived internal and perceived external CSR and exploring their separate effects on job performance. Moreover, the study reveals the mediating role of perceived organizational support and the moderating role of collectivism, enriching the knowledge based on social exchange theory.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

There is an emerging interest in Lesbian, Gay, Bisexual, Transgender and Queer (LGBTQ) inclusion among researchers and practitioners. However, the interplay of macro-, meso- and micro-level factors that influence the behavior of various agencies, systems, structures and practices in different national, cultural and social contexts still needs to be researched. This paper aims to examine how organizations meaningfully engage with the marginalized and underrepresented workforce, especially the LGBTQ community, to promote diversity and inclusion through comprehensive policies and practices, thereby developing a sustainable inclusivity culture.

Adopting a practice theory lens and using a case study design, including multilevel interviews with 28 different stakeholders, this study examines how organizations institutionalize LGBTQ inclusion practices in an emerging market context with a historically low acceptance of the LGBTQ community.

Findings indicate that macro influences, such as regulatory, societal and market pressures and adopting international standards and norms, impact meso-level structures and practices. At the organizational level, leadership evangelism and workforce allyship serve as relational mechanisms for institutionalizing LGBTQ-inclusive practices. Furthermore, collaboration, partnerships and enabling systems and processes provide the structural frameworks within which organizations build an LGBTQ-inclusive culture. Lastly, at the micro level, cisgender allyship and the LGBTQ micro work environments provide the necessary psychological safety to build trust for authentic LGBTQ self-expressions. This study also indicates that organizations evolve their LGBTQ inclusion practices along a trajectory, with multiple external and internal forces that work simultaneously and recursively to shape HRM policies and practices for building an inclusive culture.

This study addresses the significant gaps in diversity and inclusivity research on LGBTQ employees and contributes to the literature in three significant ways. First, this study examines the diversity management mechanisms at the organizational level and explicates their interplay at the micro, meso and macro levels to create congruence, both internally and externally, for engaging with LGBTQ talent. Second, this study adopts a practice theory lens to examine the behavior of various actors, their agencies, the “flow” of underlying and emerging structures and processes, the continuous interplay between structure and action and how they enable inclusive culture for the LGBTQ community as a whole. Last, it addresses the call by diversity researchers for context-specific multilevel research design, including qualitative research, focusing on national, cultural and institutional contexts, where socio-organizational and historical factors and interactions among them shape diversity practices. Much of the literature on LGBTQ inclusion has, thus far, been within the Western context. By examining the emergence of inclusion practices in emerging markets like India, this study contributes to diversity and inclusion research.

The purpose of this paper is to explore two financial inclusion measures adopted within the local welfare context of the city of Milan, Italy, examining their functioning and underpinning representations. The aim is also to understand how such representations take concrete shape in the practices of local actors, and their implications for the opportunities and constraints regarding individuals' effective inclusion. To this end, this paper takes a wide-ranging look at the interplay between the rise of financial inclusion and the individualisation and responsibilisation models informing welfare policies, within the broader context of financialisation processes overall.

This paper draws on the sociology of public action approach and provides a qualitative analysis of two case studies, a social microcredit service and a financial education programme, based on direct observation and semi-structured interviews conducted with key policy actors.

This paper sheds light on the rationale behind two financial inclusion services and illustrates how the instruments involved incorporate and tend to reproduce, individualising logics that reduce the problem of financial exclusion, and the social and economic vulnerability which underlies it, to a matter of personal responsibility, thus fuelling depoliticising tendencies in public action. It also discusses the contradictions underlying financial inclusion instruments, showing how local actors negotiate views and strategies on the problems to be addressed.

The paper makes an original contribution to the field of sociology and social policy by focusing on two under-researched instruments of financial inclusion and improving understanding of the finance-welfare state nexus and of the contradictions underpinning attempts at financial inclusion of the most vulnerable.

The purpose of this study is to investigate the phenomenon of defensive biasing in work stress surveys, which occurs when employees trivialize potential stressors and strains due to fear of negative consequences from their supervisors or management. This study aims to better understand the factors that influence this behavior and to develop a scale to measure it.

The study used an online survey of 200 employees to investigate the factors influencing defensive biasing behavior. The researchers developed a scale for defensive biasing with the help of subject matter experts and derived possible factors from the literature. Participants were presented with a hypothetical scenario in which they imagined a work stress survey in their organization and were asked to answer related items. The data were analyzed using regression analysis.

The study found that defensive biasing behavior was significantly predicted by perceived anonymity and neuroticism. Participants who felt less anonymous and had higher levels of neuroticism were more likely to engage in defensive biasing. Job insecurity and trust in supervisors were not found to be significant predictors of defensive biasing.

This study contributes to the literature on work stress surveys by developing a scale for defensive biasing and investigating the factors that influence this behavior. The study highlights the importance of making the survey process more transparent to reduce defensive biasing and obtain trustworthy results.