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This paper aims to study the role of self-concept in consumer relationships with anthropomorphised conversational artificially intelligent (AI) agents. First, the authors investigate how the self-congruence between consumer self-concept and AI and the integration of the conversational AI agent into consumer self-concept might influence such relationships. Second, the authors examine whether these links with self-concept have implications for mental well-being.

This study conducted in-depth interviews with 20 consumers who regularly use popular conversational AI agents for functional or emotional tasks. Based on a thematic analysis and an ideal-type analysis, this study derived a taxonomy of consumer–AI relationships, with self-congruence and self–AI integration as the two axes.

The findings unveil four different relationships that consumers forge with their conversational AI agents, which differ in self-congruence and self–AI integration. Both dimensions are prominent in replacement and committed relationships, where consumers rely on conversational AI agents for companionship and emotional tasks such as personal growth or as a means for overcoming past traumas. These two relationships carry well-being risks in terms of changing expectations that consumers seek to fulfil in human-to-human relationships. Conversely, in the functional relationship, the conversational AI agents are viewed as an important part of one’s professional performance; however, consumers maintain a low sense of self-congruence and distinguish themselves from the agent, also because of the fear of losing their sense of uniqueness and autonomy. Consumers in aspiring relationships rely on their agents for companionship to remedy social exclusion and loneliness, but feel this is prevented because of the agents’ technical limitations.

Although this study provides insights into the dynamics of consumer relationships with conversational AI agents, it comes with limitations. The sample of this study included users of conversational AI agents such as Siri, Google Assistant and Replika. However, future studies should also investigate other agents, such as ChatGPT. Moreover, the self-related processes studied here could be compared across public and private contexts. There is also a need to examine such complex relationships with longitudinal studies. Moreover, future research should explore how consumers’ self-concept could be negatively affected if the support provided by AI is withdrawn. Finally, this study reveals that in some cases, consumers are changing their expectations related to human-to-human relationships based on their interactions with conversational AI agents.

This study enables practitioners to identify specific anthropomorphic cues that can support the development of different types of consumer–AI relationships and to consider their consequences across a range of well-being aspects.

This research equips marketing scholars with a novel understanding of the role of self-concept in the relationships that consumers forge with popular conversational AI agents and the associated well-being implications.

Smart technologies and connected objects are rapidly changing the organizational frontline. Yet, our understanding of how these technologies infuse service encounters remains limited. Therefore, the purpose of this paper is to update existing classifications of Frontline Service Technology (FST) infusion. Moreover, the authors discuss three promising smart and connected technologies – conversational agents, extended reality (XR) and blockchain technology – and their respective implications for customers, frontline employees and service organizations.

This paper uses a conceptual approach integrating existing work on FST infusion with artificial intelligence, robotics, XR and blockchain literature, while also building on insights gathered through expert interviews and focus group conversations with members of two service research centers.

The authors define FST and propose a set of FST infusion archetypes at the organizational frontline. Additionally, the authors develop future research directions focused on understanding how conversational agents, XR and blockchain technology will impact service.

This paper updates and extends existing classifications of FST, while paving the road for further work on FST infusion.

Customer service conversations are becoming increasingly digital and automated, leaving service encounters impersonal. The purpose of this paper is to identify how customer service agents and conversational artificial intelligence (AI) applications can provide a personal touch and improve the customer experience in customer service. The authors offer a conceptual framework delineating how text-based customer service communication should be designed to increase relational personalization.

This paper presents a systematic literature review on conversation styles of conversational AI and integrates the extant research to inform the development of the proposed conceptual framework. Using social information processing theory as a theoretical lens, the authors extend the concept of relational personalization for text-based customer service communication.

The conceptual framework identifies conversation styles, whose degree of expression needs to be personalized to provide a personal touch and improve the customer experience in service. The personalization of these conversation styles depends on available psychological and individual customer knowledge, contextual factors such as the interaction and service type, as well as the freedom of communication the conversational AI or customer service agent has.

The article is the first to conduct a systematic literature review on conversation styles of conversational AI in customer service and to conceptualize critical elements of text-based customer service communication required to provide a personal touch with conversational AI. Furthermore, the authors provide managerial implications to advance customer service conversations with three types of conversational AI applications used in collaboration with customer service agents, namely conversational analytics, conversational coaching and chatbots.

Chatbot users’ communication experience with disembodied conversational agents was compared with instant messaging (IM) users’ communication experience with human conversational agents. The purpose of this paper is to identify what affects users’ intention to reuse and whether they perceive any difference between the two.

A conceptual model was developed based on computer-mediated communication (CMC) and interpersonal communication theories. Data were collected online from four different continents (North America, Europe, Asia and Australia). Partial least squares structural equation modeling was applied to examine the research model.

The findings mainly reveal that media richness and social presence positively influence trust and reuse intention through task attraction and social attraction; IM users reported significantly higher scores in terms of communication experience, perceived attractiveness of the conversational agent, and trust than chatbot users; users’ trust in the conversational agents is mainly determined by perceived task attraction.

Customers’ evaluation of the communication environment is positively related to their perceived competence of the conversational agent which ultimately affect their intention to reuse chatbot/IM. The findings reveal determinants of chatbot/IM adoption which have rarely been mentioned by previous work.

Practitioners should note that consumers in general still prefer to interact with human conversational agents. Practitioners should contemplate how to combine chatbot and human resources effectively to deliver the best customer service.

This study goes beyond the Computer as Social Actor paradigm and Technology Acceptance Model to understand chatbot and IM adoption. It is among one of the first studies that compare chatbot and IM use experience in the tourism and hospitality literature.

To provide better services to customers, especially immediate responses and 24/7 availability, businesses are implementing text-based automated conversational agents, i.e. chatbots on their social platforms and websites. Chatbots are required to not only provide customers with necessary consultancy and guidance but also communicate friendly and socially. Based on the cognitive fit theory, this study attempts to examine the role of chatbot as a decision aid and how the match between information presentation in forms of decisional guidance and communication style and the shopping task influences consumers' perceived cognitive fit and decision performance outcomes.

A 2 x 2 x 2 between subject online experiment was conducted to identify which kind of decisional guidance (suggestive and informative guidance) and communication style (task-oriented vs social-oriented style) are the most appropriate for each type of shopping task (searching vs browsing task).

The findings show that when customers interact with chatbots, they will perceive higher cognitive fit if the chatbots provide them with suggestive guidance and communicate in a friendly style especially when they perform a searching task.

This study is the first attempt to understand the role of chatbots as a decision aid to customers using the communicative language. This study also tries to explore the cognitive fit theory in a novel way, and we propose the information presentation in forms of communicative language rather than matrices, tables and graphs.

The rapid progress of information and communication technologies enables business creators to access a wide variety of tools. These tools facilitate electronic exchanges and interactions with customers and companies. The purpose of this study is to test and compare the effectiveness of two virtual reality technologies, the avatar and anthropomorphic virtual agents, on consumers’ psychological states and perceived realism.

An experimental survey was conducted to measure the potential superiority of the anthropomorphic virtual agent over the avatar and to identify the determining characteristics of the anthropomorphic virtual agent’s effectiveness. An experimental website was designed for the purpose of the study. A total of 1,262 internet users participated in the experiment.

Results confirm the superiority of the anthropomorphic virtual agent over the avatar in affecting consumers’ flow state, telepresence experience and perceived realism. These findings can be explained by the humanized characteristics of this type of agent (i.e. verbal and nonverbal language).

The originality of this research lies in the study of different forms of social interactivity. This latter has been little studied and essentially treated with a dichotomous perspective (presence/absence of a virtual agent). New trends in digital marketing challenge entrepreneurs to be proactive and to anticipate customers’ behavior on their online stores. That is why, virtual reality technologies, namely, anthropomorphic agents, can be considered as a relevant tool to engage in efficient inbound marketing strategies. Today, the development of intelligent technologies encourages entrepreneurs operating online to design more interactive, realistic and humanized virtual merchant environments that are more adapted to the realities of the new consumption trends and environment.

This paper attempts to provide significant information on the increased growth of literature of chatbots and virtual assistants. Technological changes are dynamic and keep changing at regular intervals. Therefore, it becomes highly crucial to review the performance of chatbots and virtual assistants. This paper aims to review the literature by eminent researchers in the form of authors, keywords and major contributing organizations.

Systematic literature review and bibliometric analysis is used to analyze the growth of literature on chatbots. A sum of articles has been extracted from Scopus database with selected keywords and with certain filters. VOSviewer software is used for analysis of data. A total of 130 documents are extracted from Scopus database from 2017 to 2021 (31st August).

This study provides a significant contribution to an existing literature and provides the understanding of research in the area of chatbots and virtual assistants. The authors with maximum number of citations are Yan, Zaho, Bengio, Weizenbaum, Song, Zhou and Maedche with jointly 180 citations. Research is been contributed by different countries where the United States is the country with highest number of documents published. The United States contributes 17% of the total production in the area of chatbots and virtual assistants. The analysis shows that the area is gaining momentum as contribution in this area is been increasing in last few years.

The study shows that several branches of chatbots are also in mainstream like natural language processing, e-learning, behavioural research, conversational agents, virtual assistants, human–computer interaction, natural language and so on. It provides a wider scope to authors and researchers to gain useful insights. The bibliometric study will provide a broader spectrum in this area.

The developments in technology and also the effect of COVID-19 pandemic is boosting the adoption of technology in different sectors. Deployment of technology will uplift the economy and social infrastructure. Society can avail different services from their comfort area and also in real time. This will help in reducing wastage of resources like people visiting offices for routine jobs which can be easily availed from their workplace. Society may access better services without much human interaction.

This paper adds significant contribution to the existing literature by analysing the published papers from Scopus database. The study contains new and significant information as this study covers all industries where chatbots and virtual assistants are being applied whereas in previous literature only specific industry has been taken into consideration.

This article reports the results from a panel discussion held at the 2019 European Conference on Information Systems (ECIS) on the use of technology-based autonomous agents in collaborative work.

The panelists (Drs Izak Benbasat, Paul Benjamin Lowry, Stefan Morana, and Stefan Seidel) presented ideas related to affective and cognitive implications of using autonomous technology-based agents in terms of (1) emotional connection with these agents, (2) decision-making, and (3) knowledge and learning in settings with autonomous agents. These ideas provided the basis for a moderated panel discussion (the moderators were Drs Isabella Seeber and Lena Waizenegger), during which the initial position statements were elaborated on and additional issues were raised.

Through the discussion, a set of additional issues were identified. These issues related to (1) the design of autonomous technology-based agents in terms of human–machine workplace configurations, as well as transparency and explainability, and (2) the unintended consequences of using autonomous technology-based agents in terms of de-evolution of social interaction, prioritization of machine teammates, psychological health, and biased algorithms.

Key issues related to the affective and cognitive implications of using autonomous technology-based agents, design issues, and unintended consequences highlight key contemporary research challenges that allow researchers in this area to leverage compelling questions that can guide further research in this field.

Lockheed Martin has been a premier builder and developer of manned aircraft and fighter jets since 1909. Since then, aircraft design has drastically evolved in many areas including the evolution of manual linkages to fly-by-wire systems, and mechanical gauges to glass cockpits. Lockheed Martin's knowledge of manned aircraft has produced a variety of Unmanned Aerial Vehicles (UAVs) based on size/wingspan, ranging from a micro-UAV (MicroStar) to a hand-launched UAV (Desert Hawk) and up to larger platforms such as the DarkStar. Their control systems vary anywhere between remotely piloted to fully autonomous systems. Remotely piloted control is equivalent to full human involvement with an operator controlling all the decisions of the aircraft. Similarly, fully autonomous operations describe a situation that has the human having minimal contact with the platform. Flight path control relies on a set of waypoints for the vehicle to fly through. This is the most common mode of UAV navigation, and GPS has made this form of navigation practical.