1,720,995 research outputs found

    The Intricate Pathways From Empowering Leadership to Burnout: A Deep Dive Into Interpersonal Conflicts, Work-Home Interactions, and Supportive Colleagues

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    Aim/Purpose:This study builds upon existing research by investigating the elements contributing to or buffering the onset of burnout symptoms. We examine the relationship between empowering leadership and burnout, considering the concurrent mediation effects of interpersonal workplace conflict, work-home conflict, and support from coworkers. Background: Burnout is a phenomenon that has been widely considered in the scientific literature due to its negative effect on individual and organizational well-being, as well as implications for leadership, coworker support, and conflict resolution. A deeper understanding of burnout prevention strategies across various professional contexts is paramount for enhancing productivity and job satisfaction. Methodology: Using a survey-based cross-sectional design, we employed a combination of Structural Equation Modelling (SEM) and Artificial Neural Network (ANN) to investigate the direct and indirect influences of empowering leadership on four dimensions of employee burnout, mediated by coworker support, interpersonal conflict at work, and work-home conflict. Contribution: This study provides initial insights into the direct and indirect influences of empowering leadership on various dimensions of burnout, highlighting the complex interplay with coworker support, work-home conflict, and workplace interpersonal conflicts. Ultimately, the study provides a comprehensive approach to understanding and mitigating burnout. Findings: Empowering leadership and coworker support can significantly reduce burnout symptoms, while high levels of work-home conflict and interpersonal conflict at work can exacerbate them. Our findings underscore the paramount role of interpersonal conflict in predicting burnout, urging organizations to prioritize resolving such issues for burnout prevention. Recommendation for Researchers: Following our findings, organizations should (a) promote empowering leadership styles, (b) foster coworker support and work-life balance, and (c) address interpersonal conflicts to reduce the likelihood of employee burnout while ensuring that these strategies are tailored to the specific context and culture of the workplace. Future Research: Future research should broaden the exploration of leadership styles’ effects on burnout, identify additional mediators and moderators, expand studies across sectors and cultures, examine differential impacts on burnout dimensions, leverage advanced analytical models, and investigate the nuanced relationship between work contract types and burnout

    Assessing the Relationship between Cognitive Workload, Workstation Design, User Acceptance and Trust in Collaborative Robots

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    Collaborative robots are revolutionising the manufacturing industry and the way workers perform their tasks. When designing shared workspaces between robots and humans, human factors and ergonomics are often overlooked. This study assessed the relationship between cognitive workload, workstation design, user acceptance and trust in collaborative robots. We combined subjective and objective data to evaluate the cognitive workload during an assembly task in three different scenarios in which we manipulated various features of the workstation and interaction modalities. Our results showed that participants experienced a reduction in cognitive workload in each of the three trials, indicating an improvement in cognitive performance. Additionally, we found that user acceptance predicted perceived stress across the trials but did not significantly impact the cognitive workload. Trust was not found to moderate the relationship between cognitive workload and perceived stress. This study has the potential to make a significant contribution to the field of collaborative assembly systems by providing valuable insights and helping to bridge the gap between researchers and practitioners. This study can potentially impact companies looking to improve safety, productivity and efficiency

    The Impact of Artificial Intelligence on Workers’ Skills: Upskilling and Reskilling in Organisations

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    Aim/Purpose This paper aims to investigate the recent developments in research and practice on the transformation of professional skills by artificial intelligence (AI) and to identify solutions to the challenges that arise. Background The implementation of AI in various organisational sectors has the potential to automate tasks that are currently performed by humans or to reduce cognitive workload. While this can lead to increased productivity and efficiency, these rapid changes have significant implications for organisations and workers, as AI can also be perceived as leading to job losses. Successfully adapting to this transformation will lead companies and institutions to new working and organisational models, which requires implementing measures and strategies to upskill or reskill workers. Organisations, therefore, face considerable challenges such as guiding employees towards the change process, dealing with the cost of training, and ensuring fairness and inclusion posed by age, gender, and cultural diversity. Methodology A narrative review has been conducted to analyse research and practice on the impact of AI on human skills in organisations. Contribution This work contributes to the body of knowledge by examining recent trends in research and practice on how AI will transform professional skills and workplaces, highlighting the crucial role played by transversal skills and identifying strategies that can support organisations and guide workers toward the upskilling and reskilling challenges. Findings This work found that introducing AI in organisations combines many organisational strategies simultaneously. First, it is critical to map the transversal skills needed by workers to mitigate the current skills gap within the workplace. Secondly, organisations can help workers identify the skills required for AI adoption, improve current skills, and develop new skills. In addition, the findings show that companies need to implement processes to support workers by providing ad hoc training and development opportunities to ensure that workers’ attitudes and mental models towards AI are open and ready for the changing labour market and its related challenges. Recommendation for Researchers AI is a complex and multifaceted field that encompasses a wide range of disciplines, including computer science, mathematics, engineering, and behavioural and social sciences. Researchers should take a transdisciplinary approach to enable the integration of knowledge and perspectives from different fields that are essential to understanding the full range of implications and applications of AI. Future Research Further research is needed to understand the impact of AI on human skills and the role of soft skills in the adoption of AI in organisations. Future studies should also consider the challenges presented by Industry 5.0, which is likely to involve the integration of new technologies and automation on an even greater scale

    Updating design guidelines for cognitive ergonomics in human-centred collaborative robotics applications: An expert survey

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    Within the framework of Industry 5.0, human factors are essential for enhancing the work conditions and well-being of operators interacting with even more advanced and smart manufacturing systems and machines and increasing production performances. Nevertheless, cognitive ergonomics is often underestimated when implementing advanced industrial human-robot interaction. Thus, this work aims to systematically update, develop, and validate guidelines to assist non-experts in the early stages of the design of anthropocentric and collaborative assembly applications by focusing on the main features that have positively influenced workers' cognitive responses. A methodology for structured development has been proposed. The draft guidelines have been created starting from the outcomes of a systematic and extended screening of the scientific literature. Preliminary validation has been carried out with the help of researchers working in the field. Inputs on comprehensibility and relevance have been gathered to enhance the guidelines. Lastly, a survey was used to examine in depth how international experts in different branches can interpret such guidelines. In total, 108 responders were asked to qualitatively and quantitatively evaluate the guideline's comprehensibility and provide general comments or suggestions for each guideline. Based on the survey's results, the guidelines have been validated and some have been reviewed and re-written in their final form. The present work highlights that integrating human factors into the design of collaborative applications can significantly bolster manufacturing operations' resilience through inclusivity and system adaptability by enhancing worker safety, ergonomics, and wellbeing

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

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