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The aims of this paper are to share how one cohort of tourism practitioners viewed the transformative change needed within the tourism industry and to explore the implications for leadership in the future.

The research design is based on a virtual whiteboard brainstorming activity incorporating both the individual and collective thinking of 20 participants in a global cohort class. Using conversational techniques to elicit cognitive knowledge and felt experience, the methodology generates shared understandings about the opportunities and challenges of implementing regenerative tourism.

The conversations reported in the findings of this paper provide important insights into the challenges and opportunities faced by tourism professionals as enablers of regenerative tourism. Findings included, first, that participants within the course demonstrated characteristics of transformational leadership including a strong moral positioning, embodied self-awareness, collaboration and collective action. Second, specific points of inertia that impede regenerative tourism are identified including embedded culture, power and organisational structures. Third, professionals are calling for practical tools, new frames of reference, and examples to help communicate regenerative tourism.

This is a viewpoint, not a research paper. Nonetheless, it provides a rich vein of future research in terms of disruptive pedagogy, potentially gendered interest in regenerative tourism, issues of transforming the next generation and power.

Governance, organisational, destination management strategies, planning and policy frameworks, individual issues as well as contradictions within the tourism system were revealed. Transformative change in an uncertain future requires transformational leadership, characterised by moral character and behaviours that trigger empowered responses.

This paper shares insights from a unique global cohort class of tourism professionals wherein the challenges and opportunities for regenerative tourism are identified. The methodology is unusual in that it incorporates both individual and collective thinking through which shared understandings emerge.

The study examined the personal information management (PIM) challenges encountered by faculty in six universities in Ghana, their information refinding experiences and the perceived role of memory. The study tested the hypothesis that faculty PIM performance will significantly differ when the differences in the influence of personal factors (age, gender and rank) on their memory are considered.

The study was guided by a sample survey design. A questionnaire designed based on themes extracted from earlier interviews was used to collect quantitative data from 235 faculty members from six universities in Ghana. Data analysis was undertaken with a discrete multivariate Generalized Linear Model to investigate how memory intermediates in the relationship between age, gender and rank, and, refinding of stored information.

The paper identified two subfunctions of refinding (Refinding 1 and Refinding 2) associated with self-confidence in information re-finding, and, memory (Memory 1 and Memory 2), associated with the use of complimentary frames to locate previously found and stored information. There were no significant multivariate effects for gender as a stand-alone variable. Males who were aged less than 39 could refind stored information irrespective of the memory class. Older faculty aged 40–49 who possess Memory 1 and senior lecturers who possess Memory 2 performed well in refinding information. There was a statistically significant effect of age and memory; and rank and memory.

This study was limited to faculty in Ghana, whereas the study itself has implications for demographic differences in PIM.

Identifying how memory mediates the role of personal factors in faculty refinding of stored information will be necessary for the efforts to understand and design systems and technologies for enhancing faculty capacity to find/refind stored information.

Understanding how human memory can be augmented by technology is a great PIM strategy, but understanding how human memory and personal factors interplay to affect PIM is more important.

PIM of faculty has been extensively examined in the literature, and limitations of memory has always been identified as a constraint. Human memory has been augmented with technology, although the outcome has been very minimal. This study shows that in addition to technology augmentation, personal factors interplay with human memory to affect PIM. Discrete multivariate Generalized Linear Model applied in this study is an innovative way of addressing the challenges of assimilating statistical methodologies in psychosocial disciplines.

Applying the institutional logics perspective to applicant attraction, this study investigates the level of uniformity among preferences for consulting job attributes associated with the institutional logics of the corporation, the profession and the family, and tests for the influence of anticipatory socialization differences.

The study uses a discrete choice experiment with 232 business students. A hierarchical Bayes approach to conjoint analysis uncovers part-worth heterogeneity and allows for subsequent cluster and regression analysis of the choice data.

The findings identify a dominant job-oriented preference type and a minor career-oriented preference type. Anticipatory socialization through personal prior work experience and the occupation of friends decreases adherence to the logic of profession and increases the relevance of the family logic. The parents' occupation has only a minimal influence on preferences.

The study provides attribute-based recommendations on how professional service firms can effectively address the complex expectations of potential applicants in their job ads for an entry position and underlines the role of intra-generational reference groups as important anticipatory socializers.

By testing individual socialization effects at the pre-hire stage and beyond the organizational level, the study fills a void in both the recruitment and the institutional literature.

This paper analyses how firm births and deaths are influenced by previous firm births and deaths in related and unrelated sectors. Competition and multiplier effects are used as the theoretical lens for this analysis.

This paper uses 2008–2016 Irish business demography data pertaining to 568 NACE 4-digit sectors within 20 NACE 1-digit industries across 34 Irish county and sub-county regions within 8 NUTS3 regions. A three-stage least squares (3SLS) estimation is used to analyse the impact of past firm deaths (births) on future firm births (deaths). The effect of relatedness on firm interrelationships is explicitly modelled and captured.

Findings indicate that the multiplier effect operates mostly through related sectors, while the competition effect operates mostly through unrelated sectors.

This paper's findings show that firm interrelationships are significantly influenced by the degree of relatedness between firms. The raw data used to calculate firm birth and death rates in this analysis are count data. Each new firm is measured the same as another regardless of differing features like size. Some research has shown that smaller firms have a greater propensity to create entrepreneurs (Parker, 2009). Thus, it is possible that the death of differently sized firms may contribute differently to multiplier effects where births induce further births. Future research could seek to examine this.

These findings have implications for policy initiatives concerned with increasing entrepreneurship. Some express concerns that public investment into entrepreneurship can lead to “crowding out” effects (Cumming and Johan, 2019), meaning that public investment into entrepreneurship could displace or reduce private investment into entrepreneurship (Audretsch and Fiedler, 2023; Zikou et al., 2017). This study’s findings indicate that using public investment to increase firm births could increase future firm births in related and unrelated sectors. However, more negative “crowding out” effects may also occur in unrelated sectors, meaning that public investment which stimulates firm births in a certain sector could induce firm deaths and crowd out entrepreneurship in unrelated sectors.

This paper is the first in the literature to explicitly account for the role of relatedness in firm interrelationships.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

The purpose of this paper is make a significant contribution to the supply chain knowledge system through research on modern supply chain system in China, providing guidance for theoretical research such as methodology of dynamic resource allocation and application of innovative small- and middle-sized service system in the supply chain.

The paper uses structural analysis of Chinese competitive advantage, and it applies comparative analysis of supply chain models in China, the USA and Japan through the factor disintegration of trading environment.

China’s supply chain model has virtual scale and virtual capabilities. The relationship with suppliers is more dynamic. The requirements for resolving uncertainty are higher. Business transfer is more frequent.

Researchers are encouraged to propose the specific supply chain models in China further with the game theory, auction theory, etc.

It provides advice for government policy making and gives Chinese enterprises guidance to improve operation management.

This paper specifically analyzes characteristics of China supply chain and gives enlightenment for supply chain innovation.

This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.