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Because of the nature of nurses’ daily jobs, their work passion is critical for their quality performance and well-being. However, more research must examine the antecedents of nurses' work passion. Against this backdrop, in the present study, we draw on the conservation of resources (COR) theory to hypothesize that the negative relationship between nurses’ depressed mood at work and work passion is moderated by their enactment such that a relatively high level of personal enactment weakens the negative effect of depressed mood at work on their work passion.

We examine our hypothesis using a three-wave time-lagged design involving 147 nurses (RN or LPN) working at a medium-sized healthcare facility in the rural Southern USA.

Results support our hypothesis that nurses’ personal enactment moderates the relationship between their depressed mood at work and work passion.

Nurses' depressed mood at work can be less harmful to their work passion, particularly when they demonstrate a relatively higher level of personal enactment.

This study demonstrates that personal enactment attenuates the adverse effects of depressed mood at work when nurses possess elevated work passion levels.

This paper aims to discuss the scholarship over the past 30 years on what used to be called Melanesian warfare or “tribal fighting” and is termed in this paper “intergroup conflict” in the Highlands of Papua New Guinea. The paper categorises the drivers of intergroup conflict that make up the landscape for conflict in the Highlands. It starts with cultural factors and the understandings about conflict that have long been used to explain such violence, then adds newer factors. It argues that while the individual existence of each driver is important, far more important is the way in which they interact with each other in reinforcing feedback loops that propel the actors involved towards violence.

The paper is based on a thorough review of the scholarly and grey literature on the topic, drawing from the fields of anthropology, criminology, political science, law, justice and peacebuilding.

The overall finding of the paper is that the nature of intergroup conflict, its scale and dynamics, has changed considerably over the past 30 years, most prominently in the entanglement of the state with local-level conflicts. This has significantly affected the nature of intergroup conflict today, deepening the attractors towards violence and conflict, while weakening the ability of existing state and non-state systems to prevent it. The picture that emerges is one in which the interconnectivity of factors promoting violence has intensified, the rate of change is accelerating and levels of violence are amplified.

This paper is an original work.

Metaverse technology has attracted much attention in many contexts, including industry, education, marketing and business. Some recent studies have focused on qualitative studies based on the actual definition of the metaverse. However, practical research related to metaverse platforms remains in its infancy. This study provides actionable insights into the determinants of metaverse adoption by using perceived fluidity.

A two-stage structural equation modeling (SEM) approach and Hayes’ Macro approach are used to examine the proposed hypotheses.

Results show that technology features (e.g. real-time rendering, interactivity and immersion) increase users’ perceived fluidity, which in turn leads to positive intentions to use the metaverse. A high level of perceived realism is not an advantage for metaverse technology and plays a negative moderating role in this mechanism. The interaction of awe with technological features can enhance the negative moderating effects of realism.

This study pioneers the examination of perceived fluidity as a key determinant of metaverse adoption, offering a novel perspective beyond traditional factors. It uniquely identifies the paradoxical role of perceived realism, demonstrating its potential negative impact on user experience. In addition, the research highlights the reinforcing effect of awe on this relationship.

The construction of megaprojects often involves substantial risks. While insurance plays an important role as a traditional risk transfer means, owners and insurance companies may still suffer huge losses during the risk management process. Therefore, considering the strong motivation of insurance companies to participate in the on-site risk management of megaprojects, this study aims to propose a collaborative incentive mechanism involving insurance companies, to optimize the risk management effect and reduce the risk of accidents in megaprojects.

Based on principal-agent theory, the research develops the static and dynamic incentive models for risk management in megaprojects, involving both the owner and insurance company. The study examines the primary factors influencing incentive efficiency. The results are numerically simulated with a validation case. Finally, the impact of parameter changes on the stakeholders' benefits is analyzed.

The results indicate that the dynamic incentive model is available to the achievement of a flexible mechanism to ensure the benefits of contractors while protecting the benefits of the owner and insurance company. Adjusting the incentive coefficients for owners and insurance companies within a specified range promotes the growth of benefits for all parties involved. The management cost and economic benefit allocation coefficients have a positive effect on the adjustment range of the incentive coefficient, which helps implement a more flexible dynamic incentive mechanism to motivate contractors to carry out risk management to reduce risk losses.

This study makes up for the absence of important stakeholders in risk management. Different from traditional megaproject risk management, this model uses insurance companies as bridges to break the island effect of risk management among multiple megaprojects. This study contributes to the body of knowledge by designing appropriate dynamic incentive mechanisms in megaproject risk management through insurance company participation, and provides practical implications to both owner and insurance company on incentive contract making, thus achieving better risk governance of megaprojects.

This study introduces a new type of platform recommendation about mutual funds and draws on the signaling theory to conduct a quasi-experimental design to investigate how the platform recommendation influences investors’ investment decisions. Moreover, the authors examine the combined effect of star ratings and the platform recommendation on fund flow and test the investment value of recommended funds.

This study implements a quasi-experimental design based on 1,295 mutual funds traded on Alipay’s online platform to test the hypotheses.

The empirical results show that the recommended funds received higher fund flows from investors when the platform recommendation was established. Moreover, a substitution effect between tag recommendation and star ratings on fund flow was identified. We also uncovered that investing in platform-recommended funds can yield significant and higher fund returns for investors than those without platform recommendations.

Our findings shed new insights into the role of platform recommendations in helping fund investors make investment decisions and contribute to the business of online mutual fund transactions by investigating the effect of platform recommendations on fund flow and performance.

The lack of physical contact and the absence of nonverbal clues could make some learners uncomfortable interacting with others via online learning platforms. Hence, understanding the determinants of students' motivation and engagement in online learning platforms is crucial in harnessing digital technology as an enabler of unrestricted and quality learning experiences.

Drawing on the self-determination theory (SDT), this study investigates the factors associated with student’s motivation to learn (MOL) and their influence on online learning engagement (OLE). Data were collected from 228 university students from the Klang Valley region of Malaysia using the online survey method.

The results of data analysis using the partial least squares structural equation modeling indicate that self-directed learning, computer and Internet self-efficacy and online communication self-efficacy significantly influence MOL. Besides, these factors indirectly influence OLE through MOL.

This study adds to the SDT framework by demonstrating how students' perceptions of autonomy, competence and relatedness through online interaction relate to MOL and OLE.

Drawing on the integrative perspective of the technology acceptance model (TAM) and theory of planned behaviour (TPB) and extending it further by examining the role of organisational facilitators and perceived HR effectiveness in this integrative perspective, we examine HR professionals’ AI-augmented HRM (HRM^(AI)) acceptance in this research.

The data (N=375) were collected from HR professionals working in different organisations in India. Structural equation modelling (SEM) was employed to analyse the data.

The results of the study suggest that along with organisational facilitator antecedents to the relevant components of both TAM and TPB, perceived HR effectiveness also enhanced the HRM^(AI) acceptance levels of HR professionals.

The research findings are expected to contribute to the understanding of the factors that influence the acceptance of AI-augmented HRM in organizations. The results may also help organisations to identify the facilitators that can enhance the adoption and implementation of AI-augmented HRM by HR professionals. Finally, the study provides a composite TAM-TPB theoretical framework that can guide future research on the acceptance of AI-augmented HRM.

To the best of our knowledge, this is one of the first attempts to factor in the effect of contextual factors (i.e. organisational facilitators and perceived HR effectiveness) in the TAM and TPB equations.

This paper examines the evolution of massive open online courses (MOOCs) literature over the past 15 years and identifies its significant developments.

Utilizing main path analysis (MPA) on a dataset of 1,613 articles from the Web of Science (WoS) databases, the authors construct the main pathway in MOOC literature through a citation analysis. Pajek software is used to visualize the 34 influential articles identified in the field.

Three phases emerge in MOOC research: connectivism as a learning theory, facilitating education reform and breaking barriers to MOOCs adoption. Multiple-Global MPA highlights sub-themes including self-regulated learning (SRL), motivation, engagement, dropouts, student performance and the impact of COVID-19.

First, data limitations from the WoS core collection might not cover all research, but using reputable sources enhances data validity. Second, despite careful algorithm selection to enhance accuracy, there remains a limitation inherent in the nature of citations. Such biased citations may result in findings that do not fully align with scholars' perspectives.

The authors' findings contribute to the understanding of MOOCs literature development, enabling educators and researchers to grasp key trends and focus areas in the field. It can inform the design and implementation of MOOCs for more effective educational outcomes.

This study presents novel methodologies and important findings for advancing research and practice in MOOCs.

Based on the principles of the social capital theory (SCT), this study aimed to generate hypotheses and evaluate a mediated moderated model that examined the impact of social capital on online brand community happiness (OBCH).

Using 215 online questionnaires from users of private online brand communities (OBCs) , researchers examined the hypothesized connections between variables. The SPSS 21.0 and AMOS 26.0 were applied to fulfill the purpose.

For the goodness of model fit, the authors have applied cut off criteria for fit indexes given by Hu and Bentler (1999) and model-fit measures indicators, i.e. CMIN/DF 1.397, CFI 0.958, SRMR 0.045, RMSEA 0.043 and PCLOSE 0.866, which meet the minimum acceptable criteria. Based on the results, social capital significantly affects psychological well-being (PWB), which, consequently, leads toward increased happiness among OBCs. Furthermore, membership duration moderates the relationship between PWB and OBCs.

The authors have utilized a cross-sectional research design, and it limits the researcher’s ability to generalize the findings. These findings imply how social capital leverages PWB and OBCH. Moreover, the presence of membership duration helps to understand that members who spend more time in the community are happier in the OBCs.

In this age of social media, it provides valuable guidance to the administrators of private Facebook groups dedicated to specific brands, enhancing the definition and development of OBC operations and community interactions.

This research takes a broader look at social capital’s impact on happiness among private OBCs. The current research contributes to the existing body of work by emphasizing the role of PWB in generating happiness. The study is novel in examining the mediating moderating model of PWB and membership duration to explore deep insights for social media platforms.

By applying the American Customer Satisfaction Index (ACSI) model to virtual art exhibitions, this research aims to reveal insights into the factors impacting visitor satisfaction and electronic word-of-mouth (e-WOM). Furthermore, the investigation of exhibition promotion seeks to understand how external factors contribute to the overall visitor experience in virtual art exhibitions.

With advancements in virtual communication technology and the transformative impact of the COVID-19 pandemic in recent years, there has been a notable surge in the popularity of virtual art exhibitions based on the Internet. This study uses the ACSI model to examine visitor satisfaction and e-WOM in virtual art exhibitions. Additionally, it explores the influence of exhibition promotion on the ACSI model.

Key findings revealed that 1) both promotion efforts and e-WOM exhibited significant relationships with the ACSI model, and 2) most of the relationships within the ACSI model were consistent with previous research outcomes.

This study extends the ACSI model’s application to virtual art exhibitions, enhancing its relevance. Additionally, it addresses the knowledge gap concerning the direct impact of promotion on audience expectations and its relationship with the ACSI model in virtual art exhibitions. Furthermore, the research explores the influence of customer satisfaction on electronic word-of-mouth in exhibitions, offering valuable insights for exhibition evaluation systems. The study serves as a guide, providing data and models for researchers investigating virtual art exhibitions.