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Despite the increasing interest in the metaverse—immersive three-dimensional virtual worlds wherein personalized avatars interact with one another—little is known about how users cognitively appraise and emotionally experience it. To fill this gap, the present study explores the emotional, behavioral and social consequences of users' cognitive appraisals, while focusing on social virtual reality (VR) as a representative entry point to the metaverse.

Drawing on cognitive appraisal theory against the backdrop of a framework for classifying emotions, this study develops and tests a theoretical model to account for users' continuance intention and its consequences in the social VR context based on two-wave panel survey data collected from 216 users of social VR platforms, including AltspaceVR, VRChat, Bigscreen and Rec Room.

The results of the first survey showed that perceived opportunity was more strongly influenced by technological opportunity than social opportunity, whereas perceived threat was more strongly affected by social threat than technological threat. Integrating the data collected from the first survey with those of the second survey, we also found that users' continuance intention positively influenced both their behavioral engagement and social self-efficacy.

By adopting a longitudinal approach, this study provides insights that may be valuable to researchers and practitioners who seek to use social VR for business purposes. This study also contributes to the metaverse literature by conceptualizing and operationalizing the opportunity and threat factors of social VR and identifying salient emotions that users experience in this context. Finally, this study has practical implications for addressing the social and technological features that may cause adverse user experiences in social VR.

The usage rate of mobile financial services (MFS) has shown an uptick since the emergence of the COVID-19 pandemic in Bangladesh. This study aims to reveal the underpinning reasons for such MFS surge and its continuance by integrating health belief model (HBM) and expectation confirmation model (ECM).

The study analyzes 529 MFS users' responses during the second wave of the COVID-19 outbreak in Bangladesh using the partial least square method.

Satisfaction is more predictive than perceived usefulness in explaining continuance usage intention. Expectation confirmation also indirectly affects continuance intention. Among the HBM constructs, the indirect effect of perceived severity on continuance intention via perceived usefulness and satisfaction is significant. Besides, the impact of self-efficacy on continuance intention is also significant. Moreover, perceived credibility significantly affects satisfaction and indirectly affected continuance usage intention via satisfaction.

The study projects boosting customers' satisfaction is critical for the successful retention of existing MFS customers. MFS service providers should emphasize the factors that amplify satisfaction. They must evaluate preadoption factors so that customers can have positive confirmation. Especially, the service providers, the policymakers and the regulators should take an active role in improving the users' self-efficacy and the system's credibility. Undertaking the MFS literacy program, installing hotline service to provide emergency help will boost users' confidence in using the system.

The study is a unique contribution in the context of Bangladesh. To the best of the authors’ knowledge, no previous MFS studies in Bangladesh explored MFS continuance usage intention during COVID-19 and beyond. Besides, the inclusion of “perceived credibility” in the framework will supplement the earlier studies conducted on this aspect.

Although previous research has acknowledged the significance of comprehending the initial acceptance and adoption of ChatGPT in educational contexts, there has been relatively little focus on the user’s intention to continue using ChatGPT or its continued usage. Therefore, the current study aims to investigate the students’ continuance intentions to use ChatGPT for learning by adopting the stimulus–organism–response (SOR) model.

This study has employed the SOR model to investigate how UTAUT factors (such as performance expectancy, facilitating conditions, effort expectancy and social influence) influence the cognitive responses of students (e.g. trust in ChatGPT and attitude towards ChatGPT), subsequently shaping their behavioral outcomes (e.g. the intention to continue using ChatGPT for study). A sample of 392 higher students in Vietnam and the PLS-SEM method was employed to investigate students’ continuance intention to use ChatGPT for learning.

This study reveals that students’ continuance intention to use ChatGPT for learning was directly affected by their attitude toward ChatGPT and trust in ChatGPT. Meanwhile, their attitude toward ChatGPT was built on effort expectancy, social influence, and facilitating conditions and trust in ChatGPT was developed from effort expectancy and social influence.

By extending the analysis beyond initial acceptance, this research provides valuable insights into the factors that influence the sustained utilization of ChatGPT in an educational environment.

This study aims to investigate what drives tourists to continue using ChatGPT for travel purposes. This study focuses on the impact of parasocial interaction on tourists’ intention to continue using ChatGPT. It also examines how satisfaction mediates this relationship and the role of technology anxiety as a moderating factor.

Using a sample of 606 tourists in popular Vietnamese tourist destinations, this study used the SPSS PROCESS macro (Model 4 and Model 14) to estimate the research model.

The study found that tourists’ satisfaction and parasocial interactions positively influenced their intention to continue using ChatGPT for travel purposes. The tourists’ satisfaction was found to play a partial role in mediating the relationship between parasocial interactions and their intention to continue using ChatGPT. Technology anxiety was found to be a negative moderator of the direct effect of satisfaction and the indirect impact of parasocial interaction on this intention.

This study stands out as a pioneering exploration into the novel intersection of parasocial interaction, satisfaction, and technology anxiety and their influence on tourists’ intention to persist with using ChatGPT for travel-related purposes.

Just as the Covid-19 pandemic has hit all areas of life, it has also hit the working life. Towards the end of the pandemic period, the concept of quiet quitting entered people's lives. The phenomenon of quiet quitting has been introduced as a brand new concept in the mainstream media and social media in general. The primary objective of this study is to investigate and define the emerging phenomenon of quiet quitting. Furthermore, this study aims to compare this novel phenomenon with other established theoretical approaches in the field of management.

This review study specifically examines the concept of quiet quitting, aiming to gain a deeper understanding of this phenomenon.

Contrary to popular belief, the phenomenon of “quiet quitting” is not a recent or trendy occurrence. Instead, it has persisted for numerous years and is intertwined with various theories such as motivation, commitment, engagement and social exchange theory.

This study provides employers, managers, HR practitioners with recommendations on how to address the employee's quiet quitting behavior.

This study represents a pioneering work that explores an uncharted territory, the phenomenon of quiet quitting. The authors demonstrated and relate the historical processes of management theories to the phenomenon of quiet quitting, which is a concept that appears to lack roots.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether gamification and personalization as environmental stimuli to learners’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs) and, in turn, their learning outcomes in MOOCs.

Sample data for this study were collected from learners who had experience in taking gamified MOOCs provided by the MOOCs platform launched by a well-known university in Taiwan, and 331 usable questionnaires were analyzed using structural equation modeling.

This study demonstrated that learners’ perceived gamification and personalization in MOOCs positively influenced their cognitive LE and emotional LE elicited by MOOCs, which jointly explained their LP in MOOCs and, in turn, enhanced their learning outcomes. The results support all proposed hypotheses and the research model, respectively, explaining 82.3% and 65.1% of the variance in learners’ LP in MOOCs and learning outcomes.

This study uses the S-O-R model as a theoretical base to construct learners’ learning outcomes in MOOCs as a series of the psychological process, which is influenced by gamification and personalization. Noteworthily, while the S-O-R model has been extensively used in prior studies, there is a dearth of evidence on the antecedents of learners’ learning outcomes in the context of MOOCs, which is very scarce in the S-O-R view. Hence, this study enriches the research for MOOCs adoption and learning outcomes into an invaluable context.

Based on the conservation of resource theory, this study aims to develop and test the relationship between workplace technostress and affective organizational commitment. It assumes that the direct relationship between workplace technostress and affective organizational commitment is moderated by perceived organizational support.

For this, this study used a survey method and multiple regression analyses with multisource data from 257 Korean employees.

The results suggest the following. First, workplace technostress was negatively associated with affective organizational commitment fully. Second, there was a stronger negative relationship between workplace technostress and affective organizational commitment for employees with low as opposed to those with high levels of leader–member exchange.

This study provides practical implications that are directly related to the performance management of employees under technostress.

To the best of the authors’ knowledge, this study is the first one to examine the moderating effect of leader–member exchange on the relationship between technostress and affective organizational commitment.

This study aims to integrate Delone and McLean’s information system success (DMISS) model with the innovation resistance model to evaluate the relationship between behavioural intention to use (BIU) and innovation resistance in the context of neo-banking. The primary objective of this study is to identify the drivers of neo-banking adoption and the barriers to its adoption and incorporate constructs such as e-trust (ETR) and personal innovativeness (PIV) to provide a more comprehensive understanding of the factors influencing neo-banking adoption.

A structured survey-based questionnaire was used to gather data from a diverse sample population in India. The Partial Least Squares Structural Equation Modeling (PLS-SEM) model was employed to further examine the adoption of neobanking services and users' intention to use neobanking services.

This study reveals a significant correlation between BIU and the uptake of neobanking services, demonstrating the value of consumers' readiness to embrace these offerings. However, resistance to usage has emerged as a major obstacle for consumers concerned about data security, technology reluctance and perceived risks associated with digital-only neobanks.

Analysing the driving and restraining factors will provide substantial information on the formation of consumers' decision-making processes in the Indian banking industry, which is undergoing rapid digital transformation. This information is of great importance to scholars, practitioners and policymakers, as it highlights the factors that may facilitate or impede the adoption of neobanking in India. The outcomes of this analysis will be of particular interest to researchers, experts and stakeholders in the field as they will provide valuable insights into the dynamics of consumer behaviour in the Indian banking sector.

This study represents an initial effort to examine BIUs and usage resistance within the rapidly developing neobanking sector in India. The findings of this study build on the existing research in this area and contribute to the ongoing discussion on the adoption of neo-banking.

The purpose of this study is to investigate the role and features of internal online events (IOE) in organizations and measure their impact on employee outcomes (communication satisfaction and loyalty in active and passive forms).

The study conducted a mixed-method process – first, which involved three semistructured interviews in India, Russia and France, and the data were analyzed through a qualitative coding procedure. Subsequently, a survey was conducted among employees regarding their perceptions of IOE. One hundred eighty-four fully completed questionnaires were collected, and the results were analyzed using structural equation modeling.

The analysis of qualitative data revealed common patterns in IOEs in the organizations across India, Russia and France. The quantitative analysis showed the significant impact of IOEs on perceived communication satisfaction. Which in turn primarily stimulates the development of active employee loyalty rather than passive loyalty.

This study acknowledges that the samples were limited to only a few geographical regions of India, Russia and France. Also, the research is subject to sampling limitations due to snowball approach.

Internal communication (IC) managers can use this research findings to develop more effective IOEs to address organizational goals and create synergy-based positive outcomes (such as loyalty) within the employees of the organization.

Research contributes to exploring the role and characteristics of IOEs by applying engagement theory, emphasizing their capacity as a strategic IC channel to enhance employee involvement. Moreover, the study investigated the impact of IOEs on communication satisfaction and employee loyalty by applying affective events theory to communication.

This study aims to examine the effects of multidimensional factors of platform features, group effects and emotional attitudes on social media users’ privacy disclosure intention.

This study collected the data from 426 respondents through an online questionnaire survey and conducted two approaches of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) for theoretical hypothesis testing and configuration analysis of the data.

The results show that social media platform features (rewards of information disclosure, personalized service quality and data transparency), group effects (group similarity, group information interaction and network externality), individual emotional attitudes (trust and privacy concern) and control variable (gender) have a significant impact on privacy disclosure intention, as well as trust and privacy concern play mediating roles. Additionally, the fsQCA method reveals five causal configurations that explain high privacy disclosure intentions. Furthermore, the study reveals that male users pay more attention to platform features, while female users are more inclined to group effects.

This study attempts to construct a comprehensive model to examine the factors that affect users' intention to disclose their privacy on social media platforms. Drawing on the cognition-affect-conation model and multidimensional development theory, the model integrates multidimensional factors of platform features, group effects, trust and privacy concern to complement existing theoretical frameworks and privacy disclosure literature. By understanding the complex dynamics behind privacy disclosure, this study helps platform providers and policymakers develop effective strategies to ensure the vitality and momentum of the social media ecosystem.