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This paper aims to investigate how social capital (e.g. structural, cognitive and relational) influences trust (e.g. cognitive-/affective-based trust), which includes influencing knowledge-sharing behavior for Indonesian Facebook users in the context of social networking sites.

Indonesian students were recruited for an online survey study. Structural equation modeling was used to test the research hypotheses.

Social capital has a crucial role in increasing cognitive-based trust and affective-based trust. Furthermore, affective-based trust is a partial mediator between social capital and knowledge-sharing behavior, whereas cognitive-based trust is a full mediator between social capital and knowledge-sharing behavior.

This study is limited to Indonesian Facebook users. Future research needs to examine specific conditions, situational contexts and sub-cultures that may influence social capital, trust and knowledge-sharing behaviors of Facebook users in other parts of the world.

The education stakeholders can identify the user objectives and rational concerns to improve their social capital and trust and support their valuable and unique experiences to share knowledge.

This study contributes to the literature on virtual communities. Specifically, it considers how social capital influences trust, which subsequently affects knowledge-sharing behavior based on the uses and gratifications theory among Facebook users.

This paper investigates the dynamics between state affect and trusting cognitive beliefs on post-adoptive information technology (IT) use behaviors in the form of intention to explore and deep structure usage. That state affect can influence behaviors is recognized in practice. In fact, some studies examine the impact of affective constructs, but the way state affect impacts how individuals use IT remains largely unexplored. The authors theorize that state affect, in the form of positive and negative affect, will influence trusting cognitive beliefs regarding an IT artifact (in terms of perceived helpfulness, capability and reliability) and, more importantly, directly influence intention to explore and deep structure usage.

The authors test the model using a sample of 357 IT users. Survey items were derived from established measures, and the data were analyzed using structural equation modeling.

Results of this study suggest that positive affect and negative affect impact trusting cognitive beliefs. Trusting cognitive beliefs positively impact intention to explore with an IT and deep structure usage of an IT. Even in the presence of trusting beliefs, though, positive affect directly impacts intention to explore. Positive affect and negative affect both also have various indirect, mediated effects on intention to explore and deep structure usage.

In order to maximize value from workplace IT, the results suggest managers foster an authentic, positive work environment in order to harness or redirect employees' emotional energies.

The purpose of this study was to investigate trust within human-AI teams. Trust is an essential mechanism for team success and effective human-AI collaboration.

In an online experiment, the authors investigated whether trust perceptions and behaviours are different when introducing a new AI teammate than when introducing a new human teammate. A between-subjects design was used. A total of 127 subjects were presented with a hypothetical team scenario and randomly assigned to one of two conditions: new AI or new human teammate.

As expected, perceived trustworthiness of the new team member and affective interpersonal trust were lower for an AI teammate than for a human teammate. No differences were found in cognitive interpersonal trust and trust behaviours. The findings suggest that humans can rationally trust an AI teammate when its competence and reliability are presumed, but the emotional aspect seems to be more difficult to develop.

This study contributes to human–AI teamwork research by connecting trust research in human-only teams with trust insights in human–AI collaborations through an integration of the existing literature on teamwork and on trust in intelligent technologies with the first empirical findings on trust towards AI teammates.

The main aim of this study is to examine the effect of virtual store atmospheric factors on impulsive purchasing in the metaverse context.

Grounded in purposive sampling, 451 individuals with previous metaverse experience were recruited to accomplish the objectives of this research. Next, to identify both linear and nonlinear relationships, the data were analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) approaches.

The findings underscore the significance of the virtual store environment and online trust in shaping impulsive buying behaviors within the metaverse retailing setting. Theoretically, this study elucidates the impact of virtual store atmosphere and trust on impulsive buying within a metaverse retail setting.

From the findings of the study, because of the importance of virtual shop content, practitioners must address its role in impulse purchases via affective online trust. The study’s findings are likely to help retailers strategize and improve their virtual store presentations in the metaverse.

The discovery adds to the understanding of consumer behavior in the metaverse by probing the roles of virtual store atmosphere, online trust and impulsive buying.

This research investigates apparel consumers' psychological and behavioral responses to omnichannel (OC) integration. Specifically, the study applies the cognitive–affective–conative (CAC) model to reveal consumers' decision-making process under the impact of channel integration quality (CIQ), perceived fluency (PF) and cognitive and affective trust (AT).

Primary data were collected through an online survey. In total, 657 eligible responses were received. This study applied partial least square structural equation modeling for data analysis.

The findings demonstrate that the extrinsic cognitive factor, CIQ, substantially affects consumers' intrinsic cognition (cognitive trust [CT] and PF), which consequently fosters consumers' AT and shopping intentions. Specifically, integrated promotion and transaction information positively affects CT, while integrated product and price and information access negatively impact CT. All the dimensions of CIQ, except integrated promotion (IP), significantly affect PF. CT and AT exhibit mediation effects in the CAC model.

Apparel brands and retailers may apply the findings to effectively design their retail channels and implement channel integration to boost consumers' shopping intentions and trust.

This study is one of the pioneering studies applying the CAC model to empirically examine OC consumers' decision-making process. It is also among the first to determine that cognitive and AT have theoretical distinctions in the OC retailing setting.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

Using the analogy of “If you build it, they will come” from the movie Field of Dreams, this study aims to draw on relational signaling and commitment–trust theories to examine the role of different types of trust (cognitive, affective and relational) in the relationship between relational-encounter quality and customer loyalty to service employees and to the organization in the case of an integrated casino resort. The study confirms that building it (trust), they (customers) will come to the casino exhibited in their loyalty to casino hosts and their affiliated casinos.

The study was conducted with very important person (VIP) customers who have a designated VIP host to provide them with personal services at an integrated casino resort in Macau. The questionnaire was distributed to the respondents by VIP hosts using WeChat and Tencent QQ.

The study shows that different types of trust (cognitive, affective and relational) play a significant mediation role in the relationship between relational-encounter quality and the customers’ loyalty to the hosts and their affiliated casinos.

To the best of the authors’ knowledge, this study is the first to investigate the roles of different types of trust (cognitive, affective and relational) in the relational encounter between casino hosts and VIP customers and provides insights into the link between service employees and their firm through the nurturing of the service encounter with the firm’s key accounts.

This study explores the role of smart voice assistants (SVAs) as purchase recommenders, a phenomenon the authors term “word of voice” (WOV) communication. By integrating human–computer interaction (HCI) literature and electronic word of mouth (eWOM) research, the authors examine what makes consumers trust in SVA-transmitted WOV communication following their initial interactions with their SVAs during a purchase process (i.e. post-trust); and the authors propose that consumers' perceptions of their SVAs' smart capabilities (i.e. cognitive, emotional and social) are critically important for building this trust. Moreover, the study explores the influence of post-trust on consumers' adherence to WOV communication, measured by three types of behavioural intentions.

Data from a survey of 202 United States (US)-based SVA users who employ them to obtain purchase recommendations were collected and analysed. They confirmed the validity of the measurement scales and provided input for the partial least squares modelling (PLS-SEM).

The results demonstrated that post-trust in WOV communication partially or totally mediates the effect of smart capabilities on consumer adherence to WOV communication; identified the key role of cognitive, emotional and social smart capabilities for building consumers' post-trust in WOV and demonstrated the influence of this trust on behavioural intentions.

The present study contributes by examining the employment of SVAs as recommenders during the purchase process; the authors term this type of communication WOV. It analyses consumers with experience of using SVAs in their purchase processes, revealing that post-trust in WOV communication is the psychological mechanism that explains how the smart capabilities of SVAs determine consumer adherence to the recommendations they receive.

Although extant research on trust focuses on the dyadic relationship (trustor-trustee), the effectiveness of an employee's outcome may vary depending on the features of trust networks. This study examined how an employee's centrality in two types of trust networks (cognitive and affective) among coworkers is associated with employee job performance. Further, this study highlighted the mediating role of compassionate help in the effect of affective trust networks on individual performance.

Survey data were collected from 204 employees and 39 team leaders in South Korea. Data were analyzed using structural equation modeling.

The results indicated that cognitive trust centrality is positively associated with employee job performance, but affective trust centrality is not. However, an affective trust centrality indirectly increases individual performance via compassionate helping from coworkers.

This study contributes to a better understanding of trust networks and compassionate helping and expands both trust literature and HQR research.

With the development of social media, live-streaming has become an indispensable marketing activity for firms, especially in China. From the initial cooperation with the influencer, firms begin to create their own live-streaming channel, namely, the brands' self-built live-streaming. The purpose of this study is to explore the process of consumer engagement in the brands' self-built live-streaming.

This research comprises two experimental studies. Study 1 examined the effect of streamer types (CEO vs. celebrity) on consumer engagement. Study 2 investigated the moderating effects of product innovativeness.

Results showed that CEO streamers could enhance consumer engagement by increasing consumers' cognitive trust, and celebrity streamers could enhance consumer engagement by increasing consumers' emotional trust. In addition, consumer engagement was higher for really new products (vs. incremental new products) in CEO streamers' (vs. celebrity streamers') live-streaming.

Compared with previous studies that focused on streamers based on the influencer marketing, this study expands the scope of research on the live-streaming ecosystem by exploring the effect of different streamer types on the brands' self-built live-streaming. By investigating consumer engagement, this study gives implications for the sustainable traffic issue in live-streaming e-commerce.