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This study aims to explore the management learning during a long-term crisis like a pandemic. The paper addresses both what health-care managers have learnt during the COVID-19 pandemic and how the management learning is characterized.

The paper is based on a qualitative case study carried out during the COVID-19 pandemic at two different public hospitals in Sweden. The study, conducted with semi-structured interviews, applies a combination of within-case analysis and cross-case comparison. The data were analyzed using thematic deductive analysis with the themes, i.e. sensemaking, decision-making and meaning-making.

The COVID-19 pandemic was characterized by uncertainty and a need for continuous learning among the managers at the case hospitals. The learning process that arose was circular in nature, wherein trust played a crucial role in facilitating the flow of information and enabling the managers to get a good sense of the situation. This, in turn, allowed the managers to make decisions meaningful for the organization, which improved the trust for the managers. This circular process was iterated with higher frequency than usual and was a prerequisite for the managers’ learning. The practical implications are that a combined management with hierarchical and distributed management that uses the normal decision routes seems to be the most successful management method in a prolonged crisis as a pandemic.

The gained knowledge can benefit hospital organizations, be used in crisis education and to develop regional contingency plans for pandemics.

This study has explored learning during the COVID-19 pandemic and found a circular process, “the management learning wheel,” which supports management learning in prolonged crises.

The purpose of this study is to gain insight into the dynamics and considerations of professionals regarding the sharing of tacit, personal knowledge in their practice.

Adopting a social-constructivist ontology, the qualitative design deploys semi-structured interviews and focus groups. Data were coded, and analysed through interrelating and reasoning.

Personal knowledge is difficult to share precisely, but can be shared to some extent using reflection and stories. Knowledge also provides a position and professional agency, emphasising boundaries and impacting the decisions on interaction and sharing. As such, professional commitment is vulnerable and contextual and, by extension, material becomes part of this interplay of professional practice and collaborative development.

Findings imply that exchange and use of knowledge and material present in organisations are impacted by individual professionals’ autonomy and decisions, which consequently impact on employees’ practice. This calls for research that focuses on individual factors such as autonomy, professionalism and attitudes in addition to organisational and facilitative matters.

Stimulating professional commitment and interpersonal learning is a matter of valuing personal knowledge and practice to avoid protectionism, boundaries and segregated agency. Management and professionals should consider how and why individuals exchange their personal knowledge, paying attention to social structures and individuals’ voices and objectives in forming communities.

This study combines the concept of tacit knowledge with the younger field of practice theory. By connecting personal knowledge to practice, it extends agency to the material world and offers a more individual perspective to knowledge sharing in and between entities.

The purpose of the research is to analyze the factors that determine the intention of small- and medium-sized enterprises (SMEs) to adopt the Metaverse. For this purpose, the analysis of the effort expectancy and performance expectancy of the constructs in relation to business satisfaction is proposed.

The analysis was performed on a sample of 182 Spanish SMEs in the technology sector, using a PLS-SEM approach for development. For the confirmation of the model and its results, an analysis with PLSpredict was performed, obtaining a high predictive capacity of the model.

After the analysis of the model proposed in this research, it is recorded that the valuation of the effort to be made and the possible performance expected by the companies does not directly determine the intention to use immersive technology in their strategic behavior. Instead, the results obtained indicate that business satisfaction will involve obtaining information, reducing uncertainty and analyzing the competition necessary for approaching this new virtual environment.

The study represents one of the first approaches to the intention of business behavior in the development of performance strategies within Metaverse systems. So far, the literature has approached immersive systems from perspectives close to consumer behavior, but the study of strategic business behavior has been left aside due to the high degree of experimentalism of this field of study and its scientific approach. The present study aims to contribute to the knowledge of the factors involved in the intention to use the Metaverse by SMEs interested in this field.

This study aims to illustrate how white supremacy culture can be produced within nonprofit organizations with a mandate to serve marginalized communities and provide practical suggestions for preventing oppression.

The site of inquiry was a nonprofit organization in south central Texas that provides social support to queer and trans youth. Through critical ethnography, the researchers evaluated the organization's processes and structure (including hierarchy, decision-making, fundraising and interactions between leaders, partners and affected groups) to explore how the organization perpetuated attributes of white supremacy culture.

Data reveal that the organization alienates the youth, volunteers and employees through defensiveness, fear of open conflict, paternalism, perfectionism and power-hoarding.

A dearth of research focuses on how white supremacy culture manifests in organizations serving marginalized communities. This paper addresses this gap by focusing on a nonprofit organization in central Texas that supports queer and trans youth. The authors offer recommendations for addressing white supremacy culture in organizations and suggest future research opportunities.

Ovarian cancer (OC) is the most common type of gynecologic cancer in the world with a high rate of mortality. Due to manifestation of generic symptoms and absence of specific biomarkers, OC is usually diagnosed at a late stage. Machine learning models can be employed to predict driver genes implicated in causative mutations.

In the present study, a comprehensive next generation sequencing (NGS) analysis of whole exome sequences of 47 OC patients was carried out to identify clinically significant mutations. Nine functional features of 708 mutations identified were input into a machine learning classification model by employing the eXtreme Gradient Boosting (XGBoost) classifier method for prediction of OC driver genes.

The XGBoost classifier model yielded a classification accuracy of 0.946, which was superior to that obtained by other classifiers such as decision tree, Naive Bayes, random forest and support vector machine. Further, an interaction network was generated to identify and establish correlations with cancer-associated pathways and gene ontology data.

The final results revealed 12 putative candidate cancer driver genes, namely LAMA3, LAMC3, COL6A1, COL5A1, COL2A1, UGT1A1, BDNF, ANK1, WNT10A, FZD4, PLEKHG5 and CYP2C9, that may have implications in clinical diagnosis.

The aim of this research is to assess the influence of the underlying service quality variable, usually related to university students' perception of the educational experience. Another aspect analysed in this work is the development of a procedure to determine which variables are more significant to assess students' satisfaction.

In order to achieve both goals, a twofold methodology was approached. In the first phase of research, an assessment of the service quality was performed with data gathered from 580 students in a process involving the adaptation of the SERVQUAL scale through a multi-objective optimization methodology. In the second phase of research, results obtained from students were compared with those obtained from the teaching staff at the university.

Results from the analysis revealed the most significant service quality dimensions from the students' viewpoint according to the scores that they provided. Comparison of the results with the teaching staff showed noticeable differences when assessing academic quality.

Significant conclusions can be drawn from the theoretical review of the empirical evidences obtained through this study helping with the practical design and implementation of quality strategies in higher education especially in regard to university education.

This study investigated the relationship between last-mile distribution or delivery (LMD) and commodity access through the mediating role of commodity availability and commodity security and the moderating effect of supply chain integration (SCI).

The study adopted the survey research design and employed the questionnaire instrument in collecting primary data from respondents in Eastern Regional Health Institutions in Ghana. The total number of valid responses received was 204. The partial least squares structural equation modeling (PLS-SEM) approach was adopted to analyze the relationship between the study variables.

The findings showed that there is a positive and significant relationship between LMD and commodity availability as well as LMD and commodity security. Moreover, while the relationship between commodity availability and commodity access is positive and significant, that between commodity security and commodity access is positive but insignificant. Furthermore, there is a positive and statistically significant relationship between LMD and commodity access. The study discovered that the interaction between LMD and commodity access is insignificant and negatively affected by SCI.

To the best of the authors' knowledge, no previous studies have empirically verified the effect of LMD on commodity access in the presence of mediating factors such as commodity availability and commodity security and SCI as the moderating factors.