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This study uses third-person effect theory to examine the mechanisms of public opinion about self-regulatory efforts to deal with COVID-19 vaccine-related misinformation on social media, focusing on the roles of social undesirability perceptions and misinformation beliefs.

A national survey of 600 US adults from the Qualtrics panel was conducted. The study examines how perceived social desirability and misinformation beliefs moderate the relationship between exposure to misinformation and behavioral responses.

The results show that the perceived disparity in misinformation exposure relates to third-person perception (TPP), which increases support for content moderation and intentions for corrective actions. Perceiving misinformation as socially undesirable strengthens the link between the exposure gap and TPP. Individual beliefs about misinformation are identified as a crucial moderator, reducing the TPP effect on those who have high misinformation beliefs, leading to less support for content moderation and corrective actions.

This research enhances understanding of TPP in the context of COVID-19 vaccine misinformation by highlighting how social undesirability perceptions and misinformation beliefs moderate this effect. It emphasizes the significance of personal misinformation beliefs in shaping attitudes toward content moderation and corrective actions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2024-0220

This study examines various artificial intelligence (AI) models for predicting financially distressed firms with poor profitability (“Zombie firms”). In particular, we adopt the Explainable AI (“XAI”) approach to overcome the limitations of the previous AI models, which is well-known as the black-box problem, by utilizing the Local Interpretable Model-agnostic Explanations (LIME) and the Shapley Additive Explanations (SHAP). This XAI approach thus enables us to interpret the prediction results of the AI models. This study focuses on the Korean sample from 2019 to 2023, as it is expected that the COVID-19 pandemic increases the number of zombie firms. We find that the XGBoost model based on a boosting technique has the best predictive performance among several AI models, including the traditional ones (e.g. the logistic regression). In addition, by using the XAI approach, we provide visualized interpretations for the prediction results from the XGBoost model. The analysis further reveals that the return on sales and the selling, general and administrative costs are the most impactful variables for predicting zombie firms. Overall, this study focusing on several AI models not only shows the improvement for the prediction of zombie firms (relative to the traditional models) but also increases the reliability of the prediction results by adopting the XAI approach, providing several implications for market participants, such as financial institutions and investors.

This study explores the influence of textual social cues on virtual influencers' perceived attractiveness, homophily and credibility, and their impact on consumers' purchase intentions. The moderating role of perceived anthropomorphism is also assessed.

A randomized between-subjects experiment with 265 participants (134 low social cue/131 high social cue) was conducted. Participants viewed a fictional virtual influencer’s social media profile and post, then completed a survey. Partial least squares structural equation modeling (PLS-SEM) analysis was used to examine the effects of textual social cues on attractiveness, attitude homophily, credibility and purchase intention as well as the moderating role of perceived anthropomorphism.

The study found that textual social cues directly influence attractiveness and attitude homophily, which significantly impact virtual influencer credibility. Credibility, in turn, strongly predicted purchase intention.

Incorporating textual social cues into a virtual influencer’s profile to create a likable persona can help overcome the novelty effect and build lasting relationships with followers. Marketers should use textual cues, like emojis and self-disclosure, to enhance marketing effectiveness and select virtual influencers aligned with their target audience.

This study is among the first to explore the role of textual social cues in virtual influencers, extending the source credibility model and social information processing theory to the influencer marketing context.

This study aims to investigate the impact of virtual tours on the engagement and travel intentions of older adults, emphasizing the role of emotional and informative content. It aims to enhance travel confidence and reduce stress among older travelers, fostering inclusive tourism through advanced avatar technology.

Using two between-subjects experiments, this research compares the effects of emotion-driven and knowledge-centric virtual tours on older adults. It explores the mediating role of travel confidence and stress reduction, along with the moderating influence of positive psychological cues on engagement and travel intentions.

The results highlight the potential of technology in promoting inclusive tourism. Emotionally engaging virtual tours significantly increase travel intentions among older adults by boosting confidence and alleviating stress, with positive psychological cues enhancing these effects.

This study offers valuable insights for tourism industry stakeholders by suggesting the development of avatar-based virtual tours tailored to the emotional and cognitive needs of older travelers. This approach could create more accessible and satisfying tourism experiences for older travelers.

This study extends the socioemotional selectivity theory to the realm of metaverse travel, providing a novel perspective on the emotional and cognitive engagement of older adults in the metaverse. This underscores the importance of inclusive technology in addressing the needs of older travelers.

The 4th Industrial Revolution changed various aspects of our lives. Those influences also led to many changes in the sports field. The emergence of different wearable devices which adapted Information Technology (IT) played a pivotal role in enhancing the field of sports science. As an example, smartwatches are one of the most popular wearable devices. They monitor an appropriate amount of exercise and manage individual health. These functions reflect people's desire to pursue an individual lifestyle, which leads to a trend of “quantified self.” A diversified market related to smart fitness equipment also provided a reasonable opportunity for people to select various training options. Combining online content with fitness equipment created an environment where people compete globally for individual fitness.

As such, the Fourth Industrial Revolution impacted sports field's development but yielded unexpected results. It has been criticized due to taking care of the body relying on machines, misconceptions of figures, and subordination of tools. Like Nomophobia which indicates a fear of being without a mobile phone, No-watchphobia confuses people. Boundaries between sports and game collapse, jobs of personal trainers are threatened, and inequality index of sports participation is enormously broad.

Critical scholars argue the need for in-depth reflection on whether the rationalization of society influenced by the development of science and technology is truly for human happiness and liberation or leads to restraint and alienation. From the critical scholars' perspective, academic concerns and phenomenological considerations should be contemplated based on the aspects of sports sociology.

Despite the growth of hotel guests’ mobile application use, limited studies identify hotel mobile application attributes and their roles in mobile application satisfaction and dissatisfaction. Therefore, drawing onto the information system success model and the two-factor theory, this study aims to establish a comprehensive framework of hotel mobile application attributes categorized into system, information and service attributes and investigate their roles in mobile application satisfaction and dissatisfaction.

A comprehensive framework of hotel mobile application attributes has been developed, drawing on the information system success model and using text analytics. A total of 88,309 mobile application reviews were collected for analysis. Furthermore, an impact asymmetry analysis was conducted to examine the extent of influence of mobile application attributes on satisfaction and dissatisfaction, thereby elucidating the contribution of mobile application attributes to both outcomes and expanding upon the two-factor theory.

Research findings present a holistic mobile application attributes framework and their roles in mobile application satisfaction and dissatisfaction by integrating theories and methodologies. Regarding the information quality, relevance emerged as the key factor for enhancing customer satisfaction, serving as a satisfier. In the realm of system quality, features stood out as the principal attribute leading to dissatisfaction. For the aspects of service quality, reliability was identified as the critical factor for achieving satisfaction. Overall, the findings confirm that mobile application attributes have unique roles in developing mobile application (dis)satisfaction.

The study extends an understanding of hotel mobile application attributes’ roles, providing rigorous and practical guidance for improving customers’ mobile application experience in the hotel industry. The study sheds light on the importance of considering mobile applications from various perspectives. However, the current study is limited to using text analytics as its methodological approach. Therefore, future research can benefit from including interviews to achieve a deeper comprehension of the underlying factors contributing to the outcomes of this research.

The novel theoretical and methodological approach enhances the application of existing theories and uses of impact asymmetry analysis. Such an approach uncovers hidden patterns of the roles of mobile applications in customer satisfaction and dissatisfaction. The study also sheds light on the importance of considering mobile applications from various perspectives, such as information, system and service quality.

This study aims to examine the effects of network externalities and diffusion of innovation on users’ perceived usefulness and perceived enjoyment, and in turn subjective well-being and intention to use in the smart living context.

To explore different types of smart living services, the data collected come from surveying 512 users of smart home services and 570 users of smart living apps. Structural equation modeling is used to analyze the data, and post hoc interviews are conducted to provide insights into our conceptual model of smart living services.

Compatibility and perceived service complementarity are the most influential determinants of users’ perceived usefulness and perceived enjoyment toward smart living services. Perceived usefulness has a greater impact on users’ intention to use and their subjective well-being than perceived enjoyment. Interestingly, perceived enjoyment exerts a stronger influence on subjective well-being than on intention to use.

This study is one of the first to provide empirical evidence in the context of smart living services, contributing to transformative service literature by extending the understanding of technology use and its influence on user well-being into a less explored service context. This study also advances users’ intention to use and subjective well-being of technology adoption in the service context by integrating perspectives from network externalities and diffusion of innovation.

Autonomous floor-cleaning robots (AFCRs) have become increasingly popular due to their ability to provide efficient and effective cleaning without the need for human intervention. These robots can perform various cleaning tasks, such as vacuum cleaning, mopping, scrubbing or sweeping, in domestic or industrial setups. As the use of floor-cleaning robots continues to grow, this paper aims to document key technological advancements.

The structure of the present work relies on published research articles excavated from general online research databases such as Google Scholar, Web of Science and Scopus. The authors use a variety of keywords and titles to search for research papers. Finally, 93 research articles are selected for review based on abstracts and key results that match AFCRs.

According to market trends, floor-cleaning robots dominate other cleaning areas. This review mainly focuses on five attributes of floor-cleaning robots: design and development of AFCR, complete coverage path planning, the application of machine learning (ML)/deep learning (DL), optimisation strategies for qualitative output and ethnographic studies. It also consists of discussions based on the results of reported technical works. Hence, AFCRs have dominated the market in the past decade and are likely to be more aggressive in the coming years.

To the best of the authors’ knowledge, only a survey article based on US-granted patents published in 2013 constitutes a review work in the research domain on AFCRs. In 2021, another review conducted a survey on the latest technological advancements in window-cleaning robots. It reviewed in detail the locomotion aspects, control mechanisms, adhesion mechanisms, sensors and actuators required for window-cleaning robots. In 2019, a comprehensive review was published on cleaning robots from a control strategy perspective for domestic applications. Therefore, the authors have crafted this review to understand the evolution of floor-cleaning robots in the past decade.

The circular economy (CE) is a sustainable economic model that has the potential to create new opportunities, reduce environmental impact and enhance social well-being. Ho Chi Minh City (HCMC), the largest city in Vietnam, has experienced rapid economic growth in recent years, but at the cost of the environment and public health. The city could reduce waste, conserve resources and promote sustainable production and consumption by adopting CE principles. Employing qualitative research, including content analysis, we construct a SWOT analysis to assess HCMC's strengths, weaknesses, opportunities and threats in the CE context. The city possesses several strengths, such as a vast potential for a CE and a robust economic foundation. However, it also faces multiple weaknesses, including insufficient infrastructure, inadequate citizen and business awareness and participation, ineffective policy enforcement and a deficiency of standards for recycled products. This chapter will conclude that the CE presents an opportunity for HCMC to reduce its dependence on imported raw materials, increase local value creation and create new jobs in the CE sector.

This study examined how people assess health information from AI and improve their diagnostic ability to identify health misinformation. The proposed model was designed to test a cognitive heuristic theory in misinformation discernment.

We proposed the heuristic-systematic model to assess health misinformation processing in the algorithmic context. Using the Analysis of Moment Structure (AMOS) 26 software, we tested fairness/transparency/accountability (FAccT) as constructs that influence the heuristic evaluation and systematic discernment of misinformation by users. To test moderating and mediating effects, PROCESS Macro Model 4 was used.

The effect of AI-generated misinformation on people’s perceptions of the veracity of health information may differ according to whether they process misinformation heuristically or systematically. Heuristic processing is significantly associated with the diagnosticity of misinformation. There is a greater chance that misinformation will be correctly diagnosed and checked, if misinformation aligns with users’ heuristics or is validated by the diagnosticity they perceive.

When exposed to misinformation through algorithmic recommendations, users’ perceived diagnosticity of misinformation can be predicted accurately from their understanding of normative values. This perceived diagnosticity would then positively influence the accuracy and credibility of the misinformation.

Perceived diagnosticity exerts a key role in fostering misinformation literacy, implying that improving people’s perceptions of misinformation and AI features is an efficient way to change their misinformation behavior.

Although there is broad agreement on the need to control and combat health misinformation, the magnitude of this problem remains unknown. It is essential to understand both users’ cognitive processes when it comes to identifying health misinformation and the diffusion mechanism from which such misinformation is framed and subsequently spread.

The mechanisms through which users process and spread misinformation have remained open-ended questions. This study provides theoretical insights and relevant recommendations that can make users and firms/institutions alike more resilient in protecting themselves from the detrimental impact of misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0167