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This paper examines whether technological changes that promote communications between investors and managers help bridge the gap in the cost of equity capital among firms in different regions.

We use the online interaction platforms of listed firms in China and utilize brokerage presence (BP) to capture the geographic distribution of financial factors. We explore whether online interactions would reduce the cost of equity to a greater extent for firms located in low brokerage presence regions (hereafter “low-BP firms”) than those in high brokerage presence regions (hereafter “high-BP firms”).

We find low-BP firms benefit more from an improved information environment created by online interactions. We also find that posts about low-BP firms are more value-relevant and useful in processing corporate disclosures. Further, a higher number of interactions significantly enhances more informational efficiency for low-BP firms, and the effect of reducing the gap in financing costs is more pronounced when corporate information is complex.

We conclude that online interactions alleviate geography-induced information frictions and create a relatively level playing field for firms located in all regions.

As online learning is the embryonic form of education in the metaverse, it is extremely important to explore the behavioral preferences of users. The aim is to explore the impact of interactive features on continuous use in online learning and to further explore what kind of interaction mode should be constructed for different types of students to obtain the best educational experience.

The study developed an empirical model and used a real-world dataset to test hypotheses. Specifically, the interaction in online learning is analyzed from different dimensions, including the interaction intensity of multiple subjects, the immersion of interactive technology, the timeliness of interactive feedback, and the fun in interaction.

The authors found that the intensity of interaction, immersion, timeliness of feedback and fun in the interaction all had significant positive effects on continuous use. Among them, the most important is the interaction between teachers and students. With the growth of user grades, the role of parents in the interaction is getting smaller and smaller, and the fun in the interaction is gradually becoming unnecessary. For high school students, gamified interactions can even have a negative impact. In addition, from the perspective of gender, males prefer immersive interaction, while females pay more attention to themselves and have negative feedback on fees.

The authors deepened the interaction and summarized the impact of different interactive features on continuous use in online learning platforms. The authors focused on the impact of the immersive experience brought by the application of interactive technology, which can confirm the user behavior preferences of online learning in the context of the metaverse. The research also provides a reference for online learning institutions to set up course interaction modes and targeted marketing programs.

Online collaboration in today's world is a topic of genuine interest to Internet researchers. The purpose of this paper is to explore the role of group knowledge heterogeneity (GKH) in open collaboration performance using the mediating mechanisms of group cognition (GC) and interaction to understand the determinants of the success of online open collaboration platforms.

Study findings are based on partial least squares structural equation modeling (PLS-SEM), the formal mediation test and moderating effect analysis from Wikipedia's 160 online open collaborative groups.

For online knowledge heterogeneous groups, open collaboration performance is mediated by both GC and collaborative interaction (COL). The mediating role of GC is weak, while the mediating role of COL is strengthened when knowledge complexity (KC) is higher. By dividing group interaction into COL and communicative interaction (COM), the authors also observed that COL is effective for online open collaboration, whereas COM is limited.

These findings suggest that for more heterogeneous large groups, group interaction would explain more variance in performance than GC, offering an in-depth understanding of the relationship between group heterogeneity and open collaboration performance, answering what determines the success of online open collaboration platforms as well as explaining the inconsistency in prior findings. In addition, this study expands the application of Interactive Team Cognition (ITC) theory to the online open collaboration context.

The duality of online socialization can be examined by looking at the dynamic contrast between cyberbullying and online friendships. From the beginning of instant messaging to what we know now as direct messaging, the impact of rapid and continuous interactions in online spaces can have a widespread impact on youth. As the landscape of technology and technological access continues to evolve, the virtual interactions that arise in daily life also evolve. Therefore, understanding the impact of these interactions becomes an increasing concern. This chapter evaluates the unique characteristics, and related reciprocity, of online friendships and cyberbullying by assessing the impact of online socialization on school-aged youth. Overall, by juxtaposing both cyberbullying and online friendships, this chapter aims to provide a comprehensive understanding of the complexities that increased online socialization can have on youth in a digital age.

This article aims to explore the impact of interpersonal relationship stimuli and click-like on purchase intention across different generations of bank customers, with a focus on the moderating effect of online trust.

The sample consists of 435 online bank customers from the Facebook community and the data collection was conducted using an online survey method. The model estimation utilized the partial least squares technique, along with multigroup analysis and importance-performance map analysis.

The empirical evidence supports the hypothesized relationships between interpersonal relationship stimuli, click-like and purchase intention, but varies across different generations and is contingent upon online trust. The analysis reveals commonalities in how Generation Z, Millennials and Generation X respond to interpersonal relationship stimuli while exhibiting distinct responses to click-like.

The empirical evidence confirms the hypothesized relationships between interpersonal relationship stimuli, click-like and purchase intention. However, these relationships exhibit variations across different generations and are contingent upon the level of online trust. The analysis highlights shared responses to interpersonal relationship stimuli among Generation Z, Millennials and Generation X, while also revealing distinct reactions to click-like within these generational groups.

This research investigates the collective impact of interpersonal relationship stimuli and click-like on purchase intention, taking into account the moderating role of online trust within various generational cohorts in the banking sector.

The purpose of this study is to examine how the constructs of false self, preference for online social interaction (POSI), compulsive internet use (CIU), and online disinhibition affect social withdrawal in a social media context. The mediating effects of moral disengagement and cyber aggression are also tested.

Data were collected using an online survey (n = 533) from consumers in Japan. This study used structural equation modeling and PROCESS to examine the proposed relationships.

The study revealed that false self positively affects moral disengagement while online disinhibition positively affects cyber aggression and moral disengagement. Preference for online social interaction and compulsive internet use both positively impacts social withdrawal. Cyber aggression and moral disengagement were established mediators between false self/ Preference for online social interaction/ compulsive internet use/ online disinhibition and social withdrawal.

Although restricted to cyberaggression, owing to the reciprocal relationship between cyber victimization and cyberaggression, cyber victimization can be included for further study. This study expands the understanding of social withdrawal within the context of social media.

Based on the findings, policies and programs that address mental health that build self-esteem, self-confidence and reduce anxiety ought to be undertaken. Managing and formulating guidelines on anonymity should also be taken into consideration.

This research demonstrates the crucial constructs that affect social media users negatively from the aspects of cyberaggression, moral disengagement and social withdrawal. It also establishes the importance of mental health in reducing adverse effects from social media.

Grounded in emotional dissonance and social presence theories, this study examines whether the characteristics of employee–customer interaction (frequency, routineness and duration) and emotional intelligence (EI) have an impact on emotional labor (surface acting (SA), deep acting and naturally felt emotions (NFE)) and whether the type of interaction (face to face, voice to voice and online) moderates this relationship.

A survey method was employed to collect data from employees working in hotels, customer care and e-booking services (n = 604). The model was tested using structural equation modeling (SEM).

The study showed that EI was positively linked to deep acting and NFE but negatively associated with SA. Frequency of interaction had a negative relationship with deep acting and NFE but a positive association with SA. Duration of interaction (DOI) had a positive relationship with deep acting and NFE but a negative association with NFE. Routineness of interaction had a negative relationship with deep acting and NFE but surprisingly had a negative relationship with SA. Online interaction moderated the relationship between EI and deep acting.

This pioneering study examines the relationship between EI and characteristics of employee–customer interaction with emotional labor in the Indian hospitality context. While the association between EI and emotional labor has been studied, this study is unique in substantiating the moderating effects of interaction type and is among the first to do so empirically.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

Online customer communities have become a strategic tool for business-to-business (B2B) firms to drive collaboration among customers around the company’s products and services. This paper aims to argue that the three social capital dimensions, that is, structural, relational and cognitive, themselves driven by brand community trust, can affect brand loyalty for the organization.

The authors use a survey to collect data and structural equation modeling to test the conceptual framework by collecting data from 214 participants across three online B2B communities operated by three technology firms in India.

Brand community trust is found to have a strong association with social network ties, identification and norm of reciprocity and shared vision. These three have concomitant effects on the quality of customer-to-customer (C2C) interactions. Such communication generates functional, emotional and social benefits, which, in turn, curate brand loyalty.

The authors’ findings guide community managers in leveraging such conversations in shaping customer loyalty for the corporate brand.

This work provides an integrated framework to explain the important role of C2C interactions in B2B online brand communities.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.