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Seekers who visit professional virtual communities (PVCs) are usually motivated by knowledge-seeking, which is a complex cognitive process. How do seekers search for knowledge, and how is their search linked to prior knowledge or PVC situation factors? From the cognitive process and interactional psychology perspectives, this study investigated the three-way interactions between seekers’ expertise, task complexity, and perceptions of PVC features (i.e. knowledge quality and system quality) on knowledge-seeking strategies and resultant outcomes.

A field experiment was conducted with 119 seekers in a PVC using a 2 × 2 factorial design of seekers’ expertise (i.e. expert versus novice) and task complexity (i.e. low versus high).

The study reveals three significant insights: (1) For a high-complexity task, experts adopt an ask-directed searching strategy compared to novices, whereas novices adopt a browsing strategy; (2) For a high-complexity task, experts who perceive a high system quality are more likely than novices to adopt an ask-directed searching strategy; and (3) Task completion time and task quality are associated with the adoption of ask-directed searching strategies, whereas knowledge seekers’ satisfaction is more associated with the adoption of browsing strategy.

We draw on the perspectives of cognitive process and interactional psychology to explore potential two- and three-way interactions of seekers’ expertise, task complexity, and PVC features on the adoption of knowledge-seeking strategies in a PVC context. Our findings provide deep insights into seekers’ behavior in a PVC, given the popularity of the search for knowledge in PVCs.

Although governments have used social media platforms to interact with the public in an attempt to minimize anxiety and provide a forum for public discussion during the pandemic, governments require sufficient crisis communication skills to engage citizens in taking appropriate action effectively. This study aims to examine how the National Health Commission of China (NHCC) has used TikTok, the leading short video–based platform, to facilitate public engagement during COVID-19.

Building upon dual process theories, this study integrates the activation of information exposure, prosocial interaction theory and social sharing of emotion theory to explore how public engagement is related to message sensation value (MSV), media character, content theme and emotional valence. A total of 354 TikTok videos posted by NHCC were collected during the pandemic to explore the determinants of public engagement in crises.

The findings demonstrate that MSV negatively predicts public engagement with government TikTok, but that instructional information increases engagement. The presence of celebrities and health-care professionals negatively affects public engagement with government TikTok accounts. In addition, emotional valence serves a moderating role between MSV, media characters and public engagement.

Government agencies must be fully aware of the different combinations of MSV and emotion use in the video title when releasing crisis-related videos. Government agencies can also leverage media characters – health professionals in particular – to enhance public engagement. Government agencies are encouraged to solicit public demand for the specific content of instructing information through data mining techniques.

Addressing Environmental, Social and Governance (ESG) issues has become a critical aspect of business strategy. Since ESG has primarily focused on ratings and measures for reporting, there is a scarcity of methods to assist stakeholders in better comprehending corporate risk and addressing ESG-related issues and problems. The purpose of this paper is to propose a new model to narrow the critical gap.

This study is based on several well-known structural frameworks for managing risks and projects in various industries. Two case studies on topics related to environment (E) and social (S) responsibility are used to demonstrate the practical implementation of the CEPAR® model.

The CEPAR® model, a trademarked five-step methodology (the Challenge-Evaluation-Planning-Action-Review model) was developed by the International Chamber of Sustainable Development (ICSD). The method and guidelines are outlined for easier appreciation by stakeholders of corporations to analyze ESG-related challenges and dilemmas, then able to make principled decisions, take actions, and review the outcomes. Each phase of the new model adheres to the theoretical and practical frameworks for problem-solving and decision-making, emphasizing the iterate process of addressing challenges, evaluating materiality, planning actions, taking actions, and reviewing the outcomes.

The new model is applicable for business corporations and organizations seeking to gain insight and tackle crucial ESG issues, ultimately improving their short- and long-term decision-making and business opportunities.

The teaching and learning of anatomy has experienced a significant paradigm shift. The present study assessed the level of knowledge in anatomy in medical postgraduate students and explored the impact of interventions in the form of anatomical videos on knowledge obtained. An awareness of the importance of human anatomy for clinical skills was created to ensure a certain level of competence be achieved by the end of the anatomy course.

Postgraduate medical students were recruited from various specialties on voluntary basis. The first step was to conduct a preliminary screening exam to determine the level of anatomical knowledge. The students were then divided into two groups at random, one of which received no intervention (the control group), and the other of which watched the videos with content that was pertinent to the practical demonstrations (intervention). To assess the effects of the video intervention, a post-test was administered to all students.

Both spot tests (SPOTs) and short answer question (SAQ) components for scores of all the regions from the intervention groups were comparable to the scores obtained by the post-test control group, although the findings were not significant (p > 0.05). However, the intervention group from the abdomen (ABD) region did perform significantly better (p < 0.05) than the screening test score.

The results of the research study imply that interventions like anatomical videos can bridge the postgraduate trainee’s anatomy knowledge gap in a practical method which will immensely help in increasing their knowledge.

This study examines the transformation of labour non-governmental organisations (NGOs) operating in Mainland China since the enactment of the 2017 Overseas NGO Management Law, which aims to regulate foreign concerns functioning outside the direct control of the state. It focuses on the extent to which these organisations have responded to the rapidly changing political and social environment by altering their goals and strategies in support of migrant workers. It also considers the relevance of Western social movement theories (SMTs) to China's grassroots labour movement in the 2020s. 

The research is based on case studies of ten labour NGOs operating in Beijing, Tianjin and Yunnan. It draws upon fifteen semi-structured interviews with the founders, leaders and activists affiliated with those organisations, as well as records and documented information of each of those organisations.

While the power and influence of labour NGOs markedly diminished, most have been able to adapt their goals and the strategies remain sustainable amidst both China's changing political and social climates and the global pandemic. It suggests that conventional SMTs can still offer valuable insights into understanding the development of labour NGOs in China, although they might not fully interpret the specific conditions and challenges faced by these organisations.

This study stands out as one of very few to offer empirical evidence on the inner workings of China's labour NGOs over the last six years. It also contributes to our understanding of social movements in a non-Western context.

In this chapter, we describe the importance of good governance in the metaverse. It offers unlimited opportunities and presents unique governance challenges. First, we describe the concept of good governance and its relevance to the metaverse. We emphasize that the speed of metaverse adoption depends upon the presence or absence of effective governance. Recognizing the metaverse as the next iteration of the internet, we present significant governance issues. Some issues such as interoperability, security, safety, privacy, law, and digital inequality are critical governance issues in the metaverse. Next, we explore the diverse governance frameworks to ensure the implementation of policies and regulations. These frameworks include decentralized governance, cross-sector collaboration, and standards-based governance. We also describe the best practices which are essential for good governance. To materialize the concepts and principles discussed, we present a compelling case study centered on Decentraland. This insightful exploration dissects a decentralized autonomous organization (DAO)-based governance structure, offering valuable insights into the intricacies and stages of governance proposals. We acknowledge both the merits and potential drawbacks inherent to this approach. This chapter aims to offer an all-encompassing view of metaverse governance, essentially serving as a comprehensive roadmap for traversing the multifaceted landscape of this digital frontier.

Utilizing the Social Cognitive Theory framework, this research aims to illuminate how self-efficacy acts as a mediating factor, enhancing employability among working university students by fostering essential capabilities in digital leadership and intercultural competence.

Quantitative study with 206 working undergraduates from an Indonesian university. Questionnaires and structural equation modeling (SEM) with SPSS and SmartPLS were used.

Findings showed that working undergraduate students possess a high level of digital leadership capability and intercultural competence and tend to display increased confidence in their ability to perform challenging tasks and attain anticipated outcomes, thereby enhancing their employability. The integration of these skills, coupled with a solid self-efficacy belief, emerges as a powerful combination in the modern employment landscape in the digital transformation and Artificial Intelligence age.

This research is conducted in one university in Indonesia, potentially limiting its generalizability. Future studies could expand its regions to multiple universities across different countries for a more comprehensive implication.

This research answered the call for strategies from the university level on enhancing the development of essential competencies for working undergraduate students’ employability. It further highlights the necessity for shaping the curriculum to prioritize digital leadership capability, intercultural competence, and the cultivation of self-efficacy among working students.

This insight of the research has profound social implications, indicating that educational institutions must adapt their curricula to prioritize these competencies. By doing so, universities can better prepare students to navigate the complexities of the modern workplace, thereby contributing to a workforce that is not only technologically proficient but also culturally adept and resilient in the face of challenges. This adaptation is essential for fostering a generation of graduates who are well-equipped to contribute positively to a diverse and rapidly evolving labor market, ultimately benefiting both the individuals and the wider society by promoting economic development and cultural understanding.

Adopting a quantitative approach, this research offers a data-driven lens of employability determinants, deepening the understanding of how intertwined competencies shape employment outcomes in the AI age.

Although several studies evidence the positive outcomes of facilitation coaching style in various professional settings, it has received less attention in the health-care context. Thus, drawing on previous research and the tenets of Self-Determination Theory (Deci and Ryan, 1985), Job Demands-Resources Theory (Demerouti et al., 2001) and Conservation of Resources Theory (Hobfoll, 1989), this study aims to investigate the relationship between facilitation coaching style and adaptive performance in health-care professionals, considering a serial mediation mechanism in which job-related anxiety and informal field-based learning are antecedents of positive psychological capital (PsyCap).

Self-reported data were collected from 253 Romanian health-care professionals using a cross-sectional research design.

The authors found that facilitation coaching style reduces job-related anxiety and promotes informal field-based learning, thereby improving PsyCap and, ultimately, contributing to higher adaptive performance.

These results emphasize the critical role of facilitation coaching style in the health-care sector and provide actionable insights for health-care organizations seeking to enhance their staff’s adaptive performance and, consequently, patient care.

The present study examined the psychometric properties of the EGame- flow scale in a Mexican sample, presenting evidence of construct validity (exploratory factor analysis and confirmatory factor analysis), reliability (Cronbach’s alpha and McDonald’s omega) and discriminant validity (mean variance extracted).

Participants: Of the 255 Mexican participants in the non-probabilistic sample who had previously interacted with the LOST logistics simulator, 166 (65%) were men and 89 (35%) were women; their ages ranged from 22 to 45. The statistical packages SPSS 25, JASP 0.16 and AMOS 23 facilitated the corresponding analyses. First, we calculated the means and standard deviations of the scale items. Next, we performed an exploratory factor analysis to examine the measurement model’s internal structure and a confirmatory factor analysis to confirm the structure proposed in the exploratory factor analysis. To analyze the internal structure of the measurement model so that the estimates were not affected by multivariate normality problems, we utilized the AMOS bootstrap method (with 500 repetitions, 95% CI), the maximum likelihood (MV) estimation method, and the fit indices: X2, p (chi-square and associated likelihood), Tucker–Lewis index (TLI), standardized statistical mean square residual (SRMR), comparative fit index (CFI) and root mean Square error approximation (RMSEA) with its confidence interval, the values of X2 with p < 0.001; TLI, CFI, AGFI = 0.95; RMSEA and SRMR = 0.08 (Byrne, 2016). Finally, we estimated the reliability of the measurement model with Cronbach’s alpha (a), McDonald’s omega (ω) coefficient and the mean variance extracted (VME).

An exploratory factor analysis with the MV method and obliminal rotation showed a good fit of the data to the model, which aligns with the significance of the Barlette sphericity test (X2 = 8443.2, p < 0.000) and the Kaiser–Meyer-Olkin (KMO) value of 0.94. The indices confirmed the fit of the data to the six-dimensional model for measuring the users' level of enjoyment of online games (X2 = 678.2 gl = 411, p = 0.000; SRMR = 0.05; TLI = 0.95, CFI = 0.95 and RMSEA = 0.05, IC 90% [0.04, 0.05]).

The self-reporting format of the scale increases the social desirability of the responses, but the sample only collects information from a specific geographic location, so these findings cannot extrapolate to populations with very marked cultural differences. Finally, the study did not measure other validity evidence, such as predictive and concurrent validity, which should be considered in future studies.

From a practical perspective, the study offers a measurement scale with fewer items and robust psychometric evidence that ensures the fit of the data to the EGame-flow measurement scale. Further research must continue to learn about the behavior of the EGame-flow scale in different samples that new evidence of psychometric properties continues to appear and that other factors associated with the users' gaming enjoyment experience are analyzed.

The value and originality of the study lie in the type of evidence of psychometric properties that the instrument has and particularly in the style of sample in which the study is carried out, in this case, in the context of Mexico, where there are not enough instruments that measure the flow experience of users.

The study aims to assess the impact of disruptive frugal digital technology and small and medium-sized enterprises' (SMEs') innovation performance on the food sector in Masvingo urban, Zimbabwe. A descriptive research design was used, and quantitative data were obtained using a questionnaire survey on 50 restaurant employees and 100 customers. The empirical findings demonstrated that the performance of SMEs was significantly improved by social media, cloud computing, virtual reality (VR), augmented reality (AR), and robotics. The study concludes that disruptive digital technologies (social media, cloud computing, AR, VR and robots affect the performance of SMEs by improving food production, streamlining information transfer, and utilizing cutting-edge technical applications. This chapter recommends that the government, through those in charge of formulating policy, educate and encourage the adoption of disruptive digital technology. The application of social media, cloud computing, VR, AR, and robotics will increase local food producers' access to the market. Digitalization will have a significant effect on Zimbabwe's local food system in the future.