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The present study contributes to our understanding of how to curb burnout among hospital staff over time. The authors extend existing research by examining the mediating role of mission valence in the link between transformational leadership and burnout.

Self-administered questionnaire data from employees in a Canadian general hospital (N = 185) were analyzed using a time-lagged research design to examine whether transformational leaders can increase employees' attraction to the organization's mission (i.e. mission valence) and in turn alleviate long-term burnout.

Structural equation modeling analysis demonstrated that transformational leadership (time 1) was negatively related to the burnout components of emotional exhaustion and depersonalization (time 2). Further, the results showed that mission valence mediated these relationships.

The study findings are important for managers and professionals as they identify transformational leadership as a potent strategy to alleviate employee burnout and clarify the process through which this is achieved, namely, by increasing mission valence.

To date, surprisingly little research has explored how transformational leadership influences followers' burnout. To address this issue, the present study examined the role of transformational leadership on staff burnout through the mechanism of increasing mission valence. Understanding how to mitigate burnout is particularly critical in health care organizations given that burnout not only negatively impacts employee wellbeing but also the wellbeing and quality of care provided to patients.

The purpose of this paper is to present data that begin to detail the deficiencies of log file analytics reporting methods that are commonly built into institutional repository (IR) platforms. The authors propose a new method for collecting and reporting IR item download metrics. This paper introduces a web service prototype that captures activity that current analytics methods are likely to either miss or over-report.

Data were extracted from DSpace Solr logs of an IR and were cross-referenced with Google Analytics and Google Search Console data to directly compare Citable Content Downloads recorded by each method.

This study provides evidence that log file analytics data appear to grossly over-report due to traffic from robots that are difficult to identify and screen. The study also introduces a proof-of-concept prototype that makes the research method easily accessible to IR managers who seek accurate counts of Citable Content Downloads.

The method described in this paper does not account for direct access to Citable Content Downloads that originate outside Google Search properties.

This paper proposes that IR managers adopt a new reporting framework that classifies IR page views and download activity into three categories that communicate metrics about user activity related to the research process. It also proposes that IR managers rely on a hybrid of existing Google Services to improve reporting of Citable Content Downloads and offers a prototype web service where IR managers can test results for their repositories.

This exploratory study innovates the pedagogy of undergraduate business research courses by integrating Generative Artificial Intelligence (GAI) tools, guided by human-centered artificial intelligence, social-emotional learning, and authenticity principles.

An insider case study approach was employed to examine an undergraduate business research course where 72 students utilized GAI for coursework. Thematic analysis was applied to their meta-reflective journals.

Students leverage GAI tools as brainstorming partners, co-writers, and co-readers, enhancing research efficiency and comprehension. They exhibit authenticity and human-centered AI principles in their GAI engagement. GAI integration imparts relevant AI skills to students.

Future research could explore how teams collectively interact with GAI tools.

Incorporating meta-reflections can promote responsible GAI usage and develop students' self-awareness, critical thinking, and ethical engagement.

Open discussions about social perceptions and emotional responses surrounding GAI use are necessary. Educators can foster a learning environment that nurtures students' holistic development, preparing them for technological challenges while preserving human learning and growth.

This study fills a gap in exploring the delivery and outcomes of AI-integrated undergraduate education, prioritizing student perspectives over the prevalent focus on educators' viewpoints. Additionally, it examines the teaching and application of AI for undergraduate research, diverging from current studies that primarily focus on research applications for academics.

This paper aims to assess whether the current eResearch Knowledge Centre’s (eRKC) research support practices align with researchers’ requirements for achieving their research objectives. The study’s objectives were to assess the current eRKC research support services and to determine which are adequate and which are not in supporting the Human Sciences Research Council (HSRC) researchers.

This study uses interviews as part of the qualitative approach. The researcher chose to use interviews, as some aspects warranted further explanation during the interview. The interviews were scheduled using Zoom’s scheduling assistant. The interviews were semi-structured, guided by a flexible interview procedure and supplemented by follow-up questions, probes and comments. The research life cycle questions guided the interviews. The data obtained were coded and transcribed using MS Excel. The interview data were analysed, using NVivo, according to the themes identified in the research questions and aligned with the theory behind the study. Pre-determined codes were created in line with the six stages of the research life cycle and applied to group the data and extract meaning from each category. Interviewee responses were assigned to groups in line with the stages of the research life cycle.

The current eRKC research support services are aligned with the needs of HSRC researchers and highlight services that could be expanded or promoted more effectively to HSRC researchers. It proposes a new service, data analysis, and suggests that the eRKC could play a more prominent role in research impact, research data management and fostering collaboration with HSRC research divisions.

This study is limited to assessing the eRKC’s support practices at the HSRC in Pretoria, South Africa. A more comprehensive study is needed for HSRC research services, capabilities and capacity.

Assessment of eRKC followed a comprehensive interviewee schedule that followed Raju and Schoombee’s research life cycle model.

Zoom’s scheduling assistant may have generated Zoom fatigue and reduced productivity. Technical issues, losing time, communication gaps and distant time zones may have affected face-to-face interaction.

eRKC research support practices are rare in South Africa and most parts of the world. This study bridges the gap between theory and practice in assessing eRKC research support practices.

Mountaineering and related activities are increasingly becoming popular and are accompanied by an increase in medical incidents. Emergency operations in mountainous terrain are time-critical and often pose major logistical challenges for rescuers. Drones are expected to improve the operational performance of mountain rescuers. However, they are not yet widely used in mountain rescue missions. This paper examines the determinants that drive the behavioral intention of mountain rescuers to adopt drones in rescue missions.

This is a behavioral study that builds upon an extended model of the unified theory of acceptance and use of technology (UTAUT) and investigates the relationship between individual attitudes, perceptions, and intentions for drone adoption. Original survey data of 146 mountain rescuers were analyzed using moderated ordinary least squares (OLS) regression analysis.

Results indicate that the behavioral intention to use drones in mountain rescue missions is driven by the expected performance gains and facilitating conditions. Favorable supporting conditions and experience with drones further moderate the relationship between performance expectancy and behavioral intention. The effects for effort expectancy, social influence, and demonstrations were not significant.

Rescue organizations and stakeholders are recommended to consider the identified determinants in the implementation of drones in emergency logistics. Drone manufacturers targeting mountain rescue organizations are advised to focus on operational performance, provide sufficient support and training, and promote the gathering of practical experience.

A tailored-model that provides first empirical results on the relevance of personal and environmental factors for the acceptance of drones in emergency logistics is presented.