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The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether social media affordances and media richness as environmental stimuli to learners’ involvement elicited by massive open online courses (MOOCs) can affect their learning persistence in MOOCs and, in turn, their learning outcomes in MOOCs. This study further examines whether demographic variables can moderate the relationship between learners’ learning persistence in MOOCs and their learning outcomes.

Sample data for this study were collected from learners who had experience in taking MOOCs provided by the MOOCs platform launched by a well-known university in Taiwan, and 396 usable questionnaires were analyzed using structural equation modeling.

This study proved that learners’ perceived social media affordances and media richness in MOOCs positively influenced their cognitive involvement and affective involvement elicited by MOOCs, which concurrently expounded their learning persistence in MOOCs and, in turn, uplifted their learning outcomes in MOOCs. The results support all proposed hypotheses and the research model, respectively, explains 70.5% and 61.8% of the variance in learners’ learning persistence in MOOCs and learning outcomes. Besides, this study showed that learners’ usage experience moderated the relationship between learners’ learning persistence in MOOCs and their learning outcomes.

This study uses the S-O-R model as a theoretical groundwork to construct learners’ learning outcomes in MOOCs as a series of the psychological process, which is affected by social media affordances and media richness. Noteworthily, while the S-O-R model has been extensively used in previous literature, little research uses the S-O-R model to explain the media antecedents of learners’ learning persistence and learning outcomes in MOOCs. Hence, this study enriches the research for understanding how learners value their learning gains via using media features to support them in MOOCs.

In light of the stimulus-organism-response (SOR) theoretical paradigm, this paper explores how information relevance and media richness affect social network exhaustion and, moreover, how social network exhaustion ultimately leads to health anxiety and COVID-19-related stress.

The conceptual model is explicitly analyzed and estimated by using data from 309 individuals of different ages in mainland China. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were utilized to validate the proposed hypotheses through the use of online data.

The findings suggest that information relevance is negatively associated with social network exhaustion. In addition, social network exhaustion is a significant predictor of health anxiety and stress. Furthermore, information relevance and media richness can indirectly influence health anxiety and stress through the mediating effect of social network exhaustion.

Theoretically, this paper verifies the causes and consequences of social network exhaustion during COVID-19, thus making a significant contribution to the theoretical construction and refinement of this emerging research area. Practically, the conceptual research model in this paper may provide inspiration for more investigators and scholars who are inclined to further explore the different dimensions of social network exhaustion by utilizing other variables.

Although social network exhaustion and its adverse consequences have become prevalent, relatively few empirical studies have addressed the deleterious effects of social network exhaustion on mobile social media users’ psychosocial well-being and mental health during the prolonged COVID-19. These findings have important theoretical and practical implications for the rational development and construction of mobile social technologies to cultivate proper health awareness and mindset during the ongoing worldwide COVID-19 epidemic.

Artificial intelligence (AI) allows the brand to co-create value with young customers through mobile apps. However, as many brands claim that their mobile apps are using the most updated AI technology, young customers face app fatigue and start questioning the authenticity of this touchpoint. This paper aims to study the mediating effect of authenticity for the value co-creation of AI-powered branded applications.

Drawing from regulatory engagement theory, this study conceptualize authenticity as the key construct in customers’ value experience process, which triggers customer value co-creation. Two scenario-based online experiments are conducted to collect data from 444 young customers. Data analysis is performed using ANOVA and Process Hayes.

The results reveal that perceived authenticity is an important mediator between media richness (chatbot vs AI text vs augmented reality) and value co-creation. There is no interaction effect of co-brand fit (high vs low) and source endorsement (doctor vs government) on the relationship between media richness and perceived authenticity, whereas injunctive norms (high vs low) strengthen this relationship.

The finding provides insights for marketing managers on engaging young customers suffering from app fatigue. Authenticity holds the key to young customers’ technological perceptions.

This research highlights the importance of perceived authenticity in encouraging young customers to co-create value. Young customers consider authenticity as a motivational force experience that involves customers through the app’s attributes (e.g. media richness) and social standards (e.g. norms), rather than brand factors (e.g. co-brand fit, source endorsement).

This paper aims to explore the extent, nature and communication potential of companies’ use of three popular social media platforms (Facebook, X and LinkedIn) to report on sustainability.

Qualitative methodology through the use of the netnography approach was adopted to evaluate the use of social media for sustainability communication by the Top 50 ASX companies. Content analysis of all company posts determined those with social and environmental content. A thematic analysis was performed using the global reporting initiative (GRI) framework to examine the nature of the reporting. The media richness framework was used to measure the communication potential of the social media platforms for sustainability communication.

The results indicated that the extent of sustainability posts on social media represented less than 20% of total social media posts. The nature of posts by the Top 50 ASX companies was higher on social issues than on environmental issues, which is contradictory to many previous studies. The study also found that while the social media platforms afforded high levels of media richness, most companies failed to exploit the platforms’ full potential to disseminate sustainability information.

This work provides both empirical and theoretical contributions to the ongoing debate concerning the use of social media for sustainability communication. The paper extends Lodhia et al.’s (2020) study of social media use for legitimation purposes and adapts Lodhia’s (2004) media richness framework to social media for sustainability reporting. It adds empirical insights into social media’s communication potential and value for communicating sustainability information.

The extent and nature to which organisations use social media to disclose their sustainability performance has significant practical implications for a variety of stakeholders. The results reveal to these stakeholders and the companies themselves the level of utilisation of social media along with the potential that can be harnessed. These results can potentially improve the quantity, timeliness and usability of sustainability reporting using social media platforms.

The study provides valuable evidence to increase understanding of the sustainability social media communication landscape, which organisations can potentially leverage to communicate their messages. Additionally, sustainability awareness is increased across various demographics by disseminating sustainability information to the wider public. This study will assist policy-setters in developing guidance for using social media for sustainability reporting.

This study extends existing literature, particularly the Lodhia et al. (2020) study, which has primarily focused on examining sustainability content in the media with limited exploration of the communication potential of social media platforms to communicate sustainability content.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether media richness and social interaction as environmental feature antecedents to nurses’ learning engagement (LE) can affect their continuance intention of massive open online courses (MOOCs) and task performance.

Sample data for this study were collected from nurses at five university-/medical university-affiliated hospitals in Taiwan. A total of 500 questionnaires were distributed, and 303 (60.6%) usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that nurses’ perceived media richness and social interaction in MOOCs positively influenced their behavioral LE and psychological LE elicited by MOOCs, which jointly caused their continuance intention of MOOCs and, in turn, enhance their task performance. The results support all proposed hypotheses and the research model, respectively, explains 84.3% and 63.7% of the variance in nurses’ continuance intention of MOOCs and task performance.

This study uses the S-O-R model as a theoretical base to frame nurses’ continuance intention of MOOCs and task performance as a series of the internal process, which is affected by environmental stimuli (i.e. media richness and social interaction) and organismic states. Noteworthily, while the S-O-R model has been extensively used in prior literature, little research uses this paradigm to expound nurses’ continuance intention of MOOCs in the work settings. Besides, there is a dearth of evidence on the antecedents of nurses’ task performance in the context of MOOCs. Hence, this study’s empirical evidence contributes significantly to the existing literature on bridging the gap of limited evaluation for the research on the impact of nurses’ MOOCs learning on their task performance in the work settings, which is very scarce in the S-O-R view.

Through the theoretical lenses of media richness, perceived realism and customer engagement, this study aims to investigate the mechanisms that promote customer engagement in metaverse-mediated environments in the meetings, incentives, conferences and exhibitions (MICE) context, as well as the impact of customer engagement on customers’ metaverse usage intensity and future visit intention.

A survey of customers who have experience with metaverse-mediated MICE activities was conducted. Data from 267 respondents were analysed using partial least squares-structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) to test our research framework.

Media richness dimensions, including multiple cues, immediate feedback and personal focus, were found to enhance perceived metaverse realism, which in turn affects the dimensions of customer engagement, leading to customers’ metaverse usage intensity and future visit intention. The fsQCA analysis identifies three configurations that lead to high event visit intention.

This research helps developers and marketers better understand how rich media contents create realistic experiences in the metaverse, aiding them to devise strategies for customer engagement and improve resource allocation.

Despite its potentially revolutionary impacts, empirical studies on the mechanisms driving customer engagement in the metaverse and its effects are scarce. This study contributes by revealing the multiple-phase mechanism of the customer engagement journey in the metaverse-mediated MICE context. By expanding the media richness theory into this area, our study provides new insights by illustrating how media richness dimensions create multisensory experiences and real-time interactions, enhancing perceived metaverse realism and customer engagement. It also addresses the debate on whether metaverse-mediated events substitute or complement real-life events.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.

This study conducted a primary survey utilizing a structured questionnaire. In total, 1,360 tourists were surveyed, and quantitative data analysis was done using PLS-SEM.

The results indicate that the factors that affect the tourists' visit intention after watching deepfake videos include information manipulation tactics, trust and media richness. This study also found that perceived deception and cognitive load do not influence the tourists' visit intention.

The originality/salience of this study lies in the fact that this is possibly among the first to combine the Media Richness Theory and Information Manipulation for understanding tourists' visit intention and post-viewing deepfake destination videos.

This study aims to explore how social media affects decision-making among tourists and whether there is a potential effect of age, which is studied through generations. For this purpose, baby boomers, Gen X, Gen Y and Gen Z tourists are studied and real-time implications are offered.

The study adopts a descriptive and exploratory design where the conceptual model of social media-based decision-making is developed through a review of the literature. Quantitative analysis is conducted on primary data from 600 Indian tourists. This is done using a self-administered questionnaire adopted from Gulati (2022) after checking its validity and reliability. The statistical analysis for hypothesis testing is done using PLS-SEM path modelling on pooled data. To study the categorical moderating effect of generations, partial least squares multigroup analysis (PLS-MGA) is performed as a paired comparison on every successive generation.

After testing every successive younger generation with an older generation through PLS-MGA, none of the pairs found any significant differences in path coefficients, as the values obtained were 0.05 < p < 0.95 for all five paths (SM → NR, SM → IS, SM → E, SM → P, SM → PPB). This indicates all the generations behave in a similar manner irrespective of them being older or younger, and age does not moderate social media’s impact on decision-making among Indian tourists.

The study establishes India as a unique geographical market and suggests tourism marketers to treat all generations at par, irrespective of age, as they behave and interact with social media in a similar manner. But, because this study is restricted to a single geographical location, i.e. India, further regions can be explored for global generalisation. Future research can also explore other demographics for combined, moderated analysis. Findings from the study suggest that marketers should ensure that equal attention is given to all generations as they engage with social media in a similar manner. Targeted marketing using artificial intelligence can help in ensuring custom ads. Personalisation according to generations can also facilitate greater purchases.

The study fills a major population and knowledge gap by exploring a topic that has been highly under-researched. Also, the study adopts an inclusive approach by analysing all the generations, both younger and older, to understand the potential effect of age on moderating the impact that social media has on tourist decision-making. Further, real-time suggestions and implications are offered to tourism marketers with special reference to the Indian tourism industry.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether media richness (MR), human-system interaction (HSI) and human-human interaction (HHI) as technological feature antecedents to medical professionals’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from medical professionals at six university-/medical university-affiliated hospitals in Taiwan. A total of 600 questionnaires were distributed, and 309 (51.5%) usable questionnaires were analyzed using structural equation modeling in this study.

This study certified that medical professionals’ perceived MR, HSI and HHI in MOOCs positively affected their emotional LE, cognitive LE and social LE elicited by MOOCs, which together explained their LP in MOOCs. The results support all proposed hypotheses and the research model accounts for 84.1% of the variance in medical professionals’ LP in MOOCs.

This study uses the S-O-R model as a theoretical base to construct medical professionals’ LP in MOOCs as a series of the psychological process, which is affected by MR and interaction (i.e. HSI and HHI). Noteworthily, three psychological constructs, emotional LE, cognitive LE and social LE, are adopted to represent medical professionals’ organisms of MOOCs adoption. To date, hedonic/utilitarian concepts are more commonly adopted as organisms in prior studies using the S-O-R model and psychological constructs have received lesser attention. Hence, this study enriches the S-O-R model into an invaluable context, and this study’s contribution on the application of capturing psychological constructs for completely explaining three types of technological features as external stimuli to medical professionals’ LP in MOOCs is well-documented.