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The study aims to describe the impact of supervisor’s and co-worker’s ostracism on the employee's responses (emotional, psychological and behavioral) through the mediation of employees' efficacy needs and relational needs. Moreover, psychological capital is treated as a moderator to handle the adverse responses of ostracized employees.

The study employed a three-wave quantitative research design to gather data from employees and their respective supervisors who belonged to various healthcare units (N = 510) using self-administered close-ended questionnaires. After that, SmartPLS software was used to analyze the data through a structured equation modeling (SEM) technique.

The empirical results of the study endorsed that ostracism adversely (negatively) affects employees' responses (comprised of emotional, behavioral and psychological). Moreover, the results revealed that employees' needs (efficacy and relational) mediate the relationship between ostracism experienced by employees (supervisor’ and co-workers’ ostracism) and their emotional, behavioral and psychological responses. In addition, it is also evidenced that employees' psychological capital improves the negative association between employees' needs and responses.

The literature in this domain is scarce, and the theoretical stance is weak due to the traditional approaches that are more concerned with the outcomes rather than analyzing the employee's conditional what they are going through. The present study enhances the knowledge of the transactional mode of coping and its application to ostracism in the workplace. The results of the current study may also support the practitioners in formulating interventions to foster a favorable workplace environment.

Mothers play important roles in their families' lives. When they are high performance athletes, they need specific supports that will enable them to excel in their roles as mother athletes. The feminist qualitative research in this chapter is based on data from two studies drawn from semi-structured interviews with elite female distance runners: 14 in 2013–2014 and 11 in 2021. We address two questions: (1) what are the considerations that elite female distance runners make around planning their pregnancy(ies) and family lives? and (2) how have experiences shifted between athlete interviews in 2013–2014 and a new cohort of athletes in 2021? In order to address these questions, we drew on three complementary theoretical approaches: liberal feminism, radical feminism, and strategic essentialism. Further, we then used thematic analysis and generated three broader themes about elite female distance runners that aligned with both cohorts of athletes. First, athletes are forced to plan/strategize their pregnancies around finances, competitions, contracts, and spousal supports due to the lack of support from athletic governing bodies or corporate sponsors. Second, female athletes who choose to have children experience stress and uncertainty in their athletic careers that their male counterparts do not. Third, elite female athletes are demanding that further change occur to address these inequalities, and participants offered a number of potential solutions to improve supports for these athletes. Although solid progress has been noted in the timeframes of our two cohorts, further commitment from athletic governing bodies and corporate sponsors is needed to work toward gender equity in athletics.

This study examines whether there are unintended consequences that emerge from status interventions in task groups in relation to cohesion and solidarity. Past theorists have argued that inconsistent status structures produce weaker levels of cohesion and solidarity in comparison to consistent status structures.

Data come from an online experiment involving mixed-sex dyads interacting in one of three conditions. Participants individually completed an ambiguous problem-solving task and then worked together over Zoom audio to form a group decision. In the three conditions, participants were either given no performance feedback before the problem-solving task or were informed the male or the female participant performed better on a pretest related to the task. The conversations were recorded and analyzed using measures related to paraverbal synchronization and accommodation.

In terms of self-reported cohesion, there appeared to be a difference, albeit a weak one, in only the inconsistent-status condition, with female participants reporting higher levels of cohesion in comparison to males. However, in terms of solidarity, there was no significant difference between the conditions.

Although inconsistent status structures were associated with weaker perceptions of cohesion, it did not appear to impact solidarity like theorists have suggested. Status structures do not appear to impact group solidarity.

The nature of group membership in conjunction with status consistency/inconsistency may produce the significant differences in solidarity that theorists have suggested.

To date, there has been little empirical examination of how status consistency affects cohesion and solidarity. Relatedly, the current study advances the research on vocal accommodation by analyzing status and solidarity simultaneously.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

This chapter focusses on analysing the origins and evolution of the SWOT analysis. It explains the drivers and limitations of the conventional SWOT analysis, laying the groundwork for new decision-making models that can aid researchers and practitioners in comprehending both the external landscape and the internal characteristics of a company. This chapter demonstrates how the strengths, weaknesses, opportunities, and threats of the SWOT analysis can be approached dynamically. Conventional SWOT analysis offers only a limited perspective on the environment and employs terminology that can confuse users, hindering their clear understanding of the factors that influence an organisation’s situation. This chapter provides a concise literature review of tools for evaluating quality management, its resources, and the surrounding environment, which serves as a valuable means to grasp the economic and social context within which a firm operates.

Blockchain technology (BT) is creating a new standard for all business operations. It can assist businesses in handling the complexity of circular digital supply chain (DCM) management. Despite this optimistic view, several barriers hinder its implementation. In this regard, this study contributes to Industry 4.0, circular economy (CE), the viability with a critical emphasis on its potential ramifications and influence on the future agenda while using BT technology in the supply chain (SC). In addition, the research reduces the knowledge gap by investigating and ranking the key barriers to the deployment of BT in viable circular digital supply chains (VCDSCs) and studies their interdependencies and causal relationships. The purpose of this paper is to address these issues.

The barriers to BT adoption in the VCDSC are identified through a thorough literature review and considering viability performance. These barriers are then classified using the analytical hierarchy process (AHP) method. Decision-making trial and evaluation laboratory (DEMATEL) is then employed to examine the cause/effect, correlation, and connection among the 14 barriers selected barriers from the AHP classification to estimate each barrier's overall degree of impact over the others.

This paper identifies and analyzes the BT adoption barriers in the VCDSC as well as examines how the key barriers interact. As a result, according to the AHP/DEMATEL method, the most prominent influencing barriers to the BT implementation in the VCDSC are “Data transparency,” “Market competition,” “Missing infrastructure,” “Lack of standardization,” “Complex protocol,” “Lack of industry involvement,” “Financial constraints,” “Missing infrastructure,” “Data transparency” and “Interoperability.” The outcomes offer a potential path for identifying important barriers as well as insight into the implementation of BT in the SC while integrating different capabilities such as viability, sustainability and CE principles.

Managers and researchers will benefit from this research by gaining an understanding of the challenges that must be prioritized and examined for BT to be implemented successfully in the VCDSC.

The use and implementation of blockchain-enabled VCDSC continue to face challenges despite an increase in relevant practice and research. Despite the benefits of BT, managers struggle to apply such technology in the context of their company. In this respect, this paper uses an integrated AHP–DEMATEL for categorizing the BT barriers as well as the interrelationship between them. In this respect, this paper presents the BT barriers studied are those related to the use of BT in the SC while integrating different paradigms such as viability, digitalization and CE. While many studies look at the barriers to BT adoption; none of them has ever included the viable capability, which means the ability to “react agilely to positive changes, be resilient to absorb negative events and re-cover after disruptions and survive at long-term periods.” The study concludes with insightful comments based on the findings and suggestions for eradicating those obstacles and their associated effects.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.