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Given declining tuition funds and government grants, Kenyan universities need to develop strategies, including increased research grants and collaborations, to diversify their income sources. Well-managed doctoral students can boost a university’s teaching and research outputs. However, numbers of students enrolled in doctoral programmes at Kenyan universities are low, and graduation rates and time-to-graduate statistics are disturbing. Research undertaken elsewhere underline the important role played by supervisors and peers in facilitating students’ sense of belonging and their success. Therefore, this study aims to investigate the influence of supervisory and peer support on PhD students’ sense of belonging and their success at Kenyan universities.

In this cross-sectional study, data were gathered through an online questionnaire from 614 students admitted to doctoral programmes at Kenyan universities between 2010 and 2018. We used multi-item scales to collect data on PhD students’ self-efficacy, supervisory and peer support and a sense of belonging.

Structural equation modelling results revealed that PhD students’ modes of study and self-efficacy were significantly associated with the quality of supervision, peer support and a sense of belonging. However, only age, a sense of belonging and the quality of supervision were directly linked to their success.

This study contributes to the literature on doctoral-level education, responding to the need for research on the influence of relationships with supervisors and peers on PhD students’ sense of belonging and their success, especially in developing countries.

This study aims to advance the understanding on individual variations in PhD candidates’ personal interest in their doctorate and supervisory and research community support, and several individual and structural attributes potentially having an impact on the profiles.

The authors explored the interrelationship between personal interest – social support profiles, and nationality, gender, research group and study status and the risk of dropping out. A total of 768 PhD candidates from a research-intensive university in Finland responded to a modified version of the cross-cultural doctoral experience survey. Latent profile analysis was used to explore the individual variations in PhD candidates’ interest and support from the supervisor and research community.

Three distinctive PhD interest-social support profiles were detected; the high interest–high support profile (74.4%, n = 570), the high interest–moderate support profile (18.2%, n = 140) and the moderate interest–moderate support profile (7.4%, n = 56). The profiles exhibited high to moderate levels of research, development and instrumental interest. Individuals in the high interest–moderate support and in the moderate interest–moderate support profiles were more prone to consider dropping out from their PhD than in the high interest–high support profile.

The results indicate that by cultivating PhD candidates’ interest and providing sufficient supervisory and the research community offers a means for preventing candidates from discontinuing their doctorate. Hence, building a supportive learning environment that cultivates a PhD candidate’s personal interest is likely to reduce high dropout rates among the candidates.

The purpose of this study is to explore the benefits and barriers for learning in industrial PhD education through the perspectives of industrial PhD students. A work-integrated learning (WIL) approach is applied to highlight key issues that university and industry need to consider promoting mutual learning.

The empirical context is a Swedish university profiling WIL offering PhD programs in three disciplines for industrial PhD students from both the private and public sectors. Data was gathered using qualitative methods; 19 semistructured interviews with industrial PhD students.

Findings show that industrial PhD students are developing practical and transferable skills, hence, contributing to research of interest for academia and work–life. Identified benefits for learning include proximity and access to data, project and networks and contextual understanding and tacit knowledge. Barriers for learning are the perceived limited understanding of employers, the dilemma of balancing and switching between different roles, lack of belonging and identity, deficient collaboration agreements and ethical dilemmas.

Contributes insights into an industrial PhD education transforming along with societal needs promoting a future workforce of researchers with skills, new work practices and learning capabilities applicable in the work–life of contemporary society.

This study contributes to the emerging field of studies of alternative doctoral educations by identifying benefits and barriers for learning and providing recommendations for how university and industry may promote learning in a resilient industrial PhD education collaboration.

The COVID-19 pandemic has had its impact on research and researchers, potentially influencing the future of academia. Yet, to the best of the authors’ knowledge, there are no empirical studies on the alignment between supervisors’ and supervisees’ estimates of the impact of COVID-19. This study aims to contribute to bridging this gap by exploring PhD candidates’ and supervisors’ perceptions of the impact of COVID-19 on candidates’ study progress and study well-being, and whether the estimates were related to supervisors’ and supervisees’ well-being.

A total of 768 PhD candidates and 561 doctoral supervisors from a large multifield research-intensive university in Finland participated in this quantitative study. Data were collected with the doctoral experience survey and the supervisory experience survey.

In general, the results show that both supervisors and supervisees recognised the negative impact of the pandemic on candidates’ well-being and progress, and their perceptions were quite well aligned. However, supervisors estimated that the impact had been more detrimental than the supervisees did. The results also show that the supervisors’ perceptions of the negative impact of COVID-19 on candidates’ progress and well-being were related to reduced levels of their own well-being.

Results can be used in developing effective support means for both the supervisors and supervisees to overcome the hardships caused by the COVID-19 pandemic and to avoid long-term negative consequences for the candidates in degree completion, career trajectories and the future of the academy.

This article explores challenges faced by doctoral candidates using grounded theory (GT) in their theses, focusing on coding, theory development and time constraints. It also examines the impact of doctoral committees on GT dissertations, addressing epistemological clashes and the desire for familiarity over novelty.

Drawing from a multilevel autoethnography and related literature, this study offers pragmatic solutions and strategies for a seamless research journey.

Coding, theory development and time constraints pose universal challenges, requiring mentorship for effective navigation. Addressing committee dynamics is crucial for developing novel theoretical frameworks.

The article empowers researchers to overcome GT challenges, delving into various positions within the GT paradigm, fostering transparency and facilitating original contributions to their fields.

The effects of the spread of COVID-19 across the world are devastating, both from a health and an economic perspective. However, we also see encouraging examples of collaborative and innovative initiatives, in society and in organizations. The purpose of this paper is to focus on initiatives related to digital business model innovation. The authors explore how organizational characteristics provide a variety of opportunities for digital responses to the COVID-19 pandemic and discuss the potential consequences for the speed of digital transformation in organizations and society.

In this paper, the authors analyze how organizations attempt to mitigate the negative effects of fighting COVID-19 using digital business model responses. The authors draw on a qualitative study where they have collected data from the retail and service industries. They have analyzed the data in relation to theory to better understand this ongoing phenomenon.

The authors have identified four categories of organizations (crisispreneurs, accelerators, endurers and thrivers). Each category faces different challenges and shows a different intensity in their digital transformation. The authors propose that the rapid turn toward digital business models will have enduring effects, as organizations have gained transformational capabilities that will remain, and that the digital trajectory has, as a result, changed forever.

The findings in this paper point toward new challenges for leaders and policymakers in terms of how to support initiatives and meet the needs of different categories of organizations while simultaneously being conscious of the potential societal effects of this rapid digital shift. The authors hope that this paper can be of value for managing this shock and learning how to adapt for the future taking certain aspects of current business models as the departure point.

The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

This study aims to add to the understanding of the interactive nature of brand love by using a multilayer perspective that incorporates individual, group and societal contexts.

The qualitative empirical study uses abductive reasoning. Its theories and conclusions are grounded in naturally occurring data from an online brand community. The approach revealed new interactive processes of brand love.

This study extends our understanding of the interactive nature of brand love by adopting a layered perspective incorporating micro- (individual), meso- (in-group), macro- (in-group vs out-group) and mega-layer (societal) social dynamics that complements the predominant focus on individual psychological processes. It challenges the linear, monodirectional trajectory approach to brand love, suggesting that brand love is in constant flux as individuals move across the layers in their identification with the brand.

This study provides data from one destination brand in Finland. Future studies could consider other types of brands and contexts in other countries and cultures.

This study shows brand managers that brand lovers can be divided into subgroups with distinct drivers of their love to which brand managers should attend.

To the best of the authors’ knowledge, this is the first attempt to describe the interactive nature of brand love through interactions between and within four layers of brand love. Furthermore, this study enhances our understanding of the contradictory aspects of brand love.