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Guided by the quest concept, this study aims to explore how profession-focused PhD candidates, who are concurrently lecturing at a Dutch University of Applied Sciences (UAS), make sense of change while pursuing doctoral objectives. The research question was: How do these PhD candidates navigate, experience and evaluate their enduring profession-focused doctoral quests across the nexus of research, education and professional fields, considering their aspirations?

Eight PhD candidates shared one-year quest experiences, illustrating how interactions with ‘actors’, ‘settings’ and ‘events’ shape doctoral transitions. These narratological concepts guided within-case and cross-case analyses, while grounded theory methodologies served to explore candidates’ sense-making of change over time.

Four story types of doctoral transitions emerged: “ups and downs”, “turnaround”, “continuous growth” and “scholarly recognition”. Candidates valued the Dutch UASs’ formal policy of supporting academic research with professional relevance. Across the story types, differences in aligning doctoral expectations among research and workplace supervisors and candidates affected knowledge exchange throughout the doctorate. When available, engagement in varied and comprehensive doctoral learning resources advanced candidates’ research competencies, including bridging diverse knowledge types. Autonomous candidate navigation was crucial for building partnerships, accessing dispersed learning resources and responding to uncertainties. Collaborative learning involving BSc-MSc students, colleagues and practitioners varied in strength across the story types, but enhanced the doctorate’s relevance, visible outcomes, feasibility and sustainability. The story types represent transition patterns that shaped how candidates developed new knowledge and contributed to their fields. While passion was a key motivator for candidates, it also heightened their vulnerability.

Analysing patterns in doctoral transitions provided actionable insights for optimising conditions and candidate navigation within the science–profession nexus.

The findings highlight that diverse actors can contribute to and benefit from profession-focused doctorates, driving momentum in integrating this research into education and innovation.

Research on knowledge creation within eSports learning is scarce. This study extends the understanding of competition-oriented collaborative learning in eSports by examining the relationship between the dynamics of knowledge creation modes and the continuum of the motivational profile, along with the moderating effects of mutualistic co-presence therein.

Participants were recruited from the community of massively multiplayer online gamers (MMOGs). Through a quantitative survey, their motivations (i.e. self-extrinsic, self-intrinsic, peer-extrinsic and peer-intrinsic motivations), knowledge creation involvements (i.e. internalization, externalization, combination and socialization) and perception of mutualistic benefit of self and peers were captured for hypothesis testing.

Significant and positive direct relationships were observed between four motivations and four knowledge creation modes. The mutualistic co-presence positively moderated the positive relationship between the self-extrinsic, peer-extrinsic and peer-intrinsic motivations and socialization. When mutualistic self-benefit were outweighed, peer-extrinsic motivated gamers became less likely to perform internalization, whereas self-extrinsic and peer-extrinsic motivated gamers were less likely to perform combination.

This study is among the first to rationalize the relationship between motivational profile and the dynamics of knowledge creation in eSports learning. The conceptualization of the new construct – mutualistic co-presence – using the ecological concept of symbiosis is uncommon in prior literature. The findings also demonstrate that the four modes of knowledge creation in eSports learning are continuous and interwoven; they can be initiated at any point and do not necessarily occur in a specific sequence.

This study explores key factors influencing individuals' intentions to invest in NFTs, focusing on personal innovativeness, reward sensitivity, knowledge, subjective norms, perceived value and perceived risk. The aim is to provide insights into what motivates investors within this emerging market, addressing a gap in the understanding of NFT adoption from an investor perspective.

An online survey collected data from 272 participants in China and Hong Kong. The research employs partial least squares-structural equation modeling (PLS-SEM) to assess the relationships between various individual, social and market factors and NFT investment intentions.

The results suggest that personal innovativeness, reward sensitivity, NFT knowledge, subjective norms and perceived value positively impact NFT investment intentions. Additionally, age and income moderate the effects of subjective norms and perceived value on investment intentions, highlighting demographic influences.

For practitioners, insights into investor motivators can inform strategies to promote NFT investments, such as promoting the high reward potential, enhancing investor knowledge, leveraging social proof and emphasizing NFTs' perceived value. For academics, the findings open pathways for further research into investor psychology and the evolving dynamics of NFT and traditional investment markets.

This study advances NFT literature by identifying determinants of NFT investment behavior, a relatively uncharted area. By incorporating theories from investment behavior and technology adoption, it provides a new framework to understand the psychological and social drivers specific to NFT investments.

A study was conducted in Gran Canaria to analyse the driving factors that lead to higher loyalty amongst tourists staying in green hotels.

A conceptual model was designed to assess whether circular preferences and behaviour amongst guests (at home/in the hotel) and a hotel’s environmental policy affect guest loyalty to green hotels. A survey in hotels collected 211 responses. A new conceptualisation of the loyalty to green hotels construct was defined.

The model detects key success predictors and connects them to different measures to improve performance in terms of circular hotel practices. This paper identifies tourist segments with more pro-circular behaviour and the highest loyalty levels to green hotels and uses a multi-group analysis by partial least squares to assess the moderation of control variables for the proposed theoretical model, identifying segments with more pro-circular behaviour and loyalty levels to green hotels.

This study determines tourism segments with higher loyalty to green hotels by analysing commitment levels across market segments. The findings help eco-friendly hotels design plans to attract and retain guests that are environmentally aware and evaluate their acceptance of circular behaviour. Insights also support revenue strategies to encourage repeat business.

The study enhances research on tourists’ circular behaviour by focusing on island destinations, bridging a gap from continental studies. It highlights 3R-based practices, explores factors like gender, age, booking channel, board and traveller type that influence pro-circular behaviour and offers insights for destination management organizations and hotel marketers to attract long-term sustainable demand.

This study aims to examine the mediating effect of psychological safety on the relationship between socially responsible leadership and job satisfaction.

A cross-sectional design was used to obtain quantitative data from staff of 214 public universities in Uganda. The authors used Mplus to conduct structural equation modeling (SEM) for this study. Questionnaires were used to collect data.

Socially responsible leadership and psychological safety have a significant positive direct effect on job satisfaction. Further psychological safety significantly mediates the relationship between socially responsible leadership and job satisfaction.

Psychological safety and socially responsible leadership have been found to be important factors in determining how satisfied employees are at work. Furthermore, psychological safety is essential for creating a supportive workplace culture where staff members may freely voice their opinions without worrying about unfavorable consequences. Having a sense of security at work may boost job happiness. It is crucial to remember that there may be a complex link between these elements and job happiness, one that is influenced by a number of other variables including organizational culture, personal traits of employees and the unique circumstances of the Ugandan workplace.

This study contributes theoretically to the examination on the relationship between socially responsible leadership and job satisfaction. This study examined the role of psychological safety as a mediator in the relationship between socially responsible leadership and job satisfaction. Moreover, it has significant effects on the development of literature about socially responsible leadership, psychological safety and job satisfaction in Ugandan public universities.

This study explores green consumer behaviour among Generation Y (Gen Y) and Generation Z (Gen Z) in India, applying the Theory of Planned Behaviour (TPB) to assess how digital literacy and eco-friendly behaviour, alongside knowledge, attitude, subjective norms, and perceived behavioural control, shape purchase intentions in line with Sustainable Development Goal 12 (SDG 12).

The research involved a survey of 680 randomly selected respondents from educational institutions across three northern Indian cities. Data collection was conducted using a structured questionnaire with items measured on a 5-point Likert scale. Statistical methods, including confirmatory factor analysis, were used to validate the measurement model, while descriptive statistics, reliability analysis, and regression analysis were employed to analyse the data.

The study uncovers differences between Gen Y and Gen Z regarding the factors influencing green product purchase intentions. Gen Y’s purchase intentions are shaped by attitude, digital literacy, eco-friendly behaviour, and perceived behavioural control, whereas Gen Z’s intentions are also affected by environmental knowledge and subjective norms.

This research provides significant insights into the factors determining green consumer behaviour among Gen Y and Gen Z in India, enriching the knowledge of sustainable consumption practices. It highlights the importance of digital literacy and eco-friendly behaviour in promoting green purchase intentions, and the differing roles of environmental knowledge and subjective norms across generational cohorts.

Understanding the drivers behind green product purchase intentions for Gen Y and Gen Z enables stakeholders to craft specific marketing strategies, educational programs, and policy initiatives that promote sustainable behaviours and mitigate environmental impacts.

The study’s findings have significant social implications, promoting sustainable lifestyles and behaviours among younger generations. By influencing peer groups and communities, and guiding the development of effective public campaigns and CSR initiatives, the study contributes to fostering a more informed and engaged citizenry that advocates for environmental sustainability.

The uniqueness of this study comes from its focus on the Indian youth demographic, the application of the TPB framework with additional variables, and its contribution to SDG 12, enhancing our comprehension of green consumer behaviour and supporting sustainability advancements in India and globally.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

This study aims to systematically consolidate and quantitatively integrate the mixed empirical results on the association between ownership mechanisms and voluntary carbon disclosure using meta-analysis and further propose potential country-level moderators of this relationship.

The authors apply meta-analytic procedures on 55 empirical studies conducted during 2008–2022, covering 13 countries, 85 effect sizes and 226,473 firm-year observations. To gauge the significance of the estimated mean effect size, a random-effects Hedges and Olkin meta-analysis procedure is adopted, followed by a restricted maximum likelihood based meta-regression, to test the effect of possible moderators.

Aligned with agency and stakeholder theories, the results highlight institutional and state ownership (SO) as having a significant positive impact on voluntary carbon disclosure. On the other hand, ownership concentration, managerial and foreign ownership have an insignificant effect on voluntary carbon disclosure. Based on institutional theory perspectives, the authors confirm the impact of institutional ownership on voluntary carbon disclosure to be more prominent in civil law countries and those countries that have implemented an emission trading scheme (ETS).

The finding that institutional and SO in firms can translate into higher voluntary disclosures deems investors and the government as crucial stakeholders in achieving carbon neutrality. Furthermore, the finding that the effect of institutional investors on carbon disclosure is heightened in ETS-implemented countries provides evidence to the regulatory authorities in favour of this scheme.

The positive impact of institutional and government ownership on voluntary carbon disclosure highlights that these ownership structures not only have the potential to transform corporate decisions but also have implications for the wider society. As firms owned by institutional investors disclose their carbon information, it provides access to critical information about their environmental practices to the public. This fosters an environment of transparency and trust between the firm and its stakeholders (the community), leading to an overall well-informed society.

While prior meta-reviews studied the impact of corporate governance on voluntary disclosures, the meta-literature, as of 2024, has yet to address its influence specifically on carbon disclosures, which are pertinent amidst the ongoing global climate change crisis. The findings inform policymakers about the pivotal institutional factors that can amplify the impact of effective ownership structures on voluntary carbon disclosure. Future scope exists for investigating the effects of ownership mechanisms on firm-level sustainable investments. Furthermore, future empirical analysis could consider the moderating influence of “culture” and “ease of doing business” on the ownership-carbon disclosure relationship.

A new research domain known as the Quantified Self has recently emerged and is described as gaining self-knowledge through using wearable technology to acquire information on self-monitoring activities and physical health related problems. However, very little is known about the impact of time window models on discovering self-quantified patterns that can yield new self-knowledge insights. This paper aims to discover the self-quantified patterns using multi-time window models.

This paper proposes a multi-time window analytical workflow developed to support the streaming k-means clustering algorithm, based on an online/offline approach that combines both sliding and damped time window models. An intervention experiment with 15 participants is used to gather Fitbit data logs and implement the proposed analytical workflow.

The clustering results reveal the impact of a time window model has on exploring the evolution of micro-clusters and the labelling of macro-clusters to accurately explain regular and irregular individual physical behaviour.

The preliminary results demonstrate the impact they have on finding meaningful patterns.

This study aims to analyze online responses to gain insights into public attitudes and concerns regarding traditional Chinese medicine (TCM) among Hong Kong residents. By addressing gaps in understanding public sentiment, this study contributes to the development of effective health-care policies.

Responses were collected from Baby-Kingdom.com using Python, gathering 17,568 TCM-related comments from 2016 to 2023. Analysis involved an eight-theme codebook and sentiment and semantic network analyses with DiVoMiner.

Most responses expressed positive sentiments and attitudes toward TCM. The analysis revealed recurring topics related to conditioning and specific diseases, including gynecological problems. Clinic service quality, fair pricing and convenient locations were also highlighted.

This study examines the networked public sphere and the Theory of Planned Behavior regarding TCM, emphasizing online forums’ impact on attitudes and highlighting gaps in service access, using big data and an interdisciplinary approach.

The findings of this study from Baby-Kingdom.com emphasize the need to improve the accessibility of TCM-related discussions. An official platform for professionals is proposed, with government support for reliable information and partnerships with local universities to expand services.

This study provides valuable insights into the popularity of TCM in Hong Kong, which may encourage uptake and use of TCM services in the health-care sector in not only Hong Kong but also the Greater Bay Area, China and potentially other countries in the future.