What kind of chatbot do millennials prefer to interact with?

Meshing with the way in which young consumers socially interact, chatbots represent a key factor to address business efforts in enhancing the effectiveness of digital strategies. The conversational aspect of the human-chatbot interaction increases the necessity for this technology to present social behaviours typical of human-human conversations. This calls for a better knowledge of the social factors that enhance young consumers’ use of chatbots. From this perspective, the present study aims at understanding the impact of chatbots’ social characteristics. Through a between-participants factorial design we explore the extent to which the communication style and the visual cue influence perceived social presence and how this in turn, influences Millennials’ intention to adopt chatbots. Findings from 193 Millennials show that a social-oriented communication style increases social presence, which in turn enhances the intention to use the chatbot via perceived enjoyment and attitude.info:eu-repo/semantics/publishedVersio

The Effect of Social Chatbot Avatar Presentation on User Self-disclosure

The emergence of artificial intelligence has boosted the development and utilization of chatbots that can satisfy both users\u27 task-oriented needs, such as information search for purchase, and their social needs, such as self-disclosure for rapport-building. While much research has focused on its usage in the commercial context, little effort has been paid to examine social chatbots for psychotherapy, where facilitating relationship formation is crucial in chatbot design. Inspired by prevalent chatbot applications and drawing on the literature on visual cues and self-disclosure, this paper aims to 1) explore the effects of different presentations of social chatbot avatars (text, profile, and background) on users\u27 self-disclosure, along with the mediating role of self-awareness, and 2) understand the moderating role of chatbot gaze directions (direct gaze and averted gaze). The proposed studies will theoretically contribute to literature regarding human-robot interaction. Research findings will also provide substantial practical implications for chatbot design

A Study of Social Chatbots Affordances Mitigating Loneliness

Loneliness is a significant concern and is linked to negative health outcomes such as depression and anxiety. Chatbots are gaining attention as potential companions to militate against loneliness. However, IS studies on the effects of human-AI relationships on mental wellness are limited, leaving unclear what enables humans to find companionship and intimate relationships with chatbots, and under what conditions human-chatbot interaction can alleviate loneliness. This study aims to develop a model of how chatbots alleviate loneliness and test it using a longitudinal study. Specifically, this research argues that shared identity affordance and social support affordance help mitigate loneliness directly and indirectly through enhanced intimacy feeling. The effects of chatbots’ affordances on loneliness and intimacy depend on users’ emotion regulation beliefs. Upon successful completion, this research has the potential to offer insight into the design of chatbots and how to leverage AI for social good

Factors Predicting Consumer-AI Interactions

The involvement of Artificial intelligence (AI) in the everyday life of consumers has important implications on the way consumer and AI interact. AI and robots can have different roles in the interaction with consumers, from simple transactional exchange relationships to more complex empathetic ones. The present research focuses in finding the constructs that affect these consumer-AI relationships, by analyzing acceptance, trust, interaction quality, empathy, attachment, anthropomorphism, self-disclosing behavior, loyalty. Based on literature review, we focused on pointing out the factors that predict and affect consumerAI interactions. In the first part of the paper the role of trust was analyzed, while in the last part we focused in defining the way in which attachment and gender characteristics affect the relationship between consumer and AI. Our research shows that there are different types of relationships depending on the context, depending on trust, attachment, empathy, loyalty and gender characteristics. These results have important implications in the way robots and AI will be integrated in the shopping experience of consumer. Depending on the closeness of the relationship between consumer-AI, there will be different activities and roles that the AI will take over. For this reason, it is important to understand all facets of this relationship in order to implement it in an optimal way

ENGAGING WITH VIRTUAL INFLUENCERS: A NETNOGRAPHY STUDY

Virtual influencers on social media are an intriguing phenomenon on the rise. They are computer-generated characters that attract a large number of followers and audiences who interact and engage with virtual influencers. Audience engagement with virtual influencers is an interesting phenomenon; yet little is known about the motivation and essence of such engagement. This research takes a qualitative approach of netnography to study audience engagement with virtual influencers. Content analysis on audience comments left on three virtual influencers\u27 Instagram accounts (including Miquela, Noonoouri, and Guggimon) is conducted. Four major content themes emerge in audience comments: emotional attachment, source admiration, novelty, and expertise. We propose a conceptual model that postulates the impacts of these factors on engagement, moderated by the anthropomorphism of virtual influencers. This research reveals insights into drivers of audience engagement with virtual influencers, providing a theoretical model and practical implications

VIRTUAL INFLUENCER MARKETING: ANTHROPOMORPHISM AND ITS EFFECT

Virtual influencers, computer-generated characters who are followed by many social media users, are increasingly contracted to endorse products and brands. However, little research has examined their effectiveness in influencer marketing. Filling this gap, we study anthropomorphism, an important feature of virtual influencers, and its role in virtual influencer marketing. Particularly, drawing from the marketing literature, we study four anthropomorphic elements, appearance, moral virtue, cognitive experience, and conscious emotionality, and their effects on followers\u27 purchase intention. These effects are modelled via the mediation of parasocial relationship with and perceived credibility of virtual influencers. Influencer-product congruence is posited as a moderator on the links between two mediators and purchase intention. An online survey will be conducted to test our hypotheses. This research extends the influencer marketing literature by exploring virtual influencer features and their effects on marketing effectiveness and provides knowledge on the anthropomorphism design of virtual influencers

Knowledge Transfer between Humans and Conversational Agents: A Review, Organizing Framework, and Future Directions

Conversational agents (CAs) that use natural language to interact with humans are becoming ubiquitous in our daily lives. For CAs to perform effectively, knowledge transfer between human users and CAs is vital to complete tasks and to build common understanding with humans. While such knowledge transfer is important, relatively less research attention has been paid to it. Overall, we lack a systematic overview of how knowledge transfer can be facilitated between humans and CAs. Motivated thus, this article presents a literature review of empirical IS, HCI and Communications studies on the knowledge transfer between humans and CAs. We analyzed papers on this topic, synthesized the studies based on the antecedents, directions, processes, and outcomes of knowledge transfer. We contribute by providing a systematic understanding of research on knowledge transfer in human-CA interactions, proposing an organizing framework, identifying gaps in prior work, and outlining key future research directions

Using chatbots in e-retailing: how to mitigate perceived risk and enhance the flow experience

Purpose: Chatbots represent an undeniable player between online retailers and customers as they boost operational efficiency and bring cost savings to businesses while offering convenience for customers in terms of timing and immediacy. However, as chatbots represent a new-born online touchpoint in retailing, especially when it comes to online pre-purchase and purchase experience, this study examines whether and how effort expectation, facilitating condition, performance expectancy, social influence, trust, perceived risk and flow affect consumers' intention to use chatbots for online shopping. The purpose of this paper is to address this issue. Design/methodology/approach: A total of 226 respondents participated in an online survey. Participants were asked to try a new online service and interact with a chatbot designed using Chatfuel, a platform within the Facebook Messenger setting. Structural equation modelling was used to test the proposed research model regarding the intention to use chatbots. Findings: This study discusses the importance of offering useful and trustworthy conversational agents for online shopping and argues and explains the insignificant paths amongst other studied factors and intention to use chatbots concluding with the need to explore more drivers for such contemporary technologies. Moreover, the findings indicate that trust turns out to be an important predictor of behavioural intention towards chatbots, in addition to its role in mitigating perceived risk and enhancing flow experience. Originality/value: Given the lack of empirical evidence related to chatbots applied for business purposes, this paper fills a gap in this research field and provides a deeper understanding of what leverages consumers' intention to use chatbots for online shopping.Chatbots, E-Retailing, Flow, Social Influence, Trust, Perceived Riskinfo:eu-repo/semantics/acceptedVersio

“I Am Here to Assist You Today”: The Role of Entity, Interactivity and Experiential Perceptions in Chatbot Persuasion

Online users are increasingly exposed to chatbots as one form of AI-enabled media technologies, employed for persuasive purposes, e.g., making product/service recommendations. However, the persuasive potential of chatbots has not yet been fully explored. Using an online experiment (N = 242), we investigate the extent to which communicating with a stand-alone chatbot influences affective and behavioral responses compared to interactive Web sites. Several underlying mechanisms are studied, showing that enjoyment is the key mechanism explaining the positive effect of chatbots (vs. Web sites) on recommendation adherence and attitudes. Contrary to expectations, perceived anthropomorphism seems not to be particularly relevant in this comparison