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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.

Everyday users of professional networks such as LinkedIn are flooded by posts presenting the achievements of their connections (e.g. I got a new job/award). The present research takes a self-discrepancy perspective to examine the mixed-emotional and behavioral consequences of viewing such idealized self-promotional content on professional networks.

The emotional and behavioral consequences following viewership of idealized self-promotional content on LinkedIn are explored through one pilot study (N = 109) and one online experiment (N = 714), which is evaluated using structural equation modeling.

Viewership of idealized self-promotional content on professional social networking sites acts as an emotional double-edged sword for LinkedIn users. Users feel both dejection and symhedonia (i.e. happiness for others), dependent on their reported career-based self-discrepancy. We find the experience of symhedonia to be bound by the relational closeness of the poster (acquaintance vs close friend). Furthermore, we show how resultant emotions drive self-regulatory compensatory IT-use behaviors (i.e. direct resolution, fluid compensation, dissociation, and escapism).

We offer four distinct contributions. Firstly, we disentangle inconsistent findings of mixed emotions by introducing symhedonia to IT literature. Secondly, we investigate the boundary condition of relational closeness. Thirdly, we extend our findings by investigating compensatory-consumption behaviors that stem from mixed-affective outcomes. Finally, we do so in the context of professional networks, which are greatly understudied and are distinctive from personal networks. Practical implications are discussed.

Augmented reality (AR) has emerged as a new interactive technology, swiftly transforming the field of marketing. Driven by its rapid uptake in marketing practices, academic research on AR has proliferated. This study aims to offer a holistic view of the past, present and future of augmented reality marketing (ARM) scholarship by analyzing its current and evolving research profile as well as its social and conceptual structures to inspire further research.

This study enriches the ARM scholarship by integrating a quantitative bibliometric analysis with a chronological-thematic review and a qualitative content analysis to develop a more comprehensive understanding of this novel area and suggest future research courses.

The bibliometric analysis reveals the key performance indicators as well as the social and conceptual structure of the ARM research field. The chronological-thematic review exhibits the advancement of ARM research over time and forecasts the emerging trends for the domain. Finally, the content analysis of recent articles reveals the current research hotspots and provides future research directions.

The database limits the selection of literature, as the information in databases such as Scopus is updated regularly, resulting in alterations in the number of articles and citations.

AR developers and brand managers may use this study’s findings to understand the current ARM landscape better and make strategic decisions based on AR adoption and consumption patterns.

This study is singular in using a mixed methods approach by integrating the findings from bibliometric and content analyses for more reliable results and to offer a holistic perspective of the ARM sector, thereby significantly advancing the field of technology-led marketing.

This paper aims to bridge the extended reality framework and the luxury hospitality literature by providing insights into how immersive technologies using artificial intelligence (AI) can shape luxury value and consumer differentiation.

The authors conducted three experimental studies comparing immersive AI versus traditional hospitality across luxury contexts (hotels, restaurants and spas). Study 1 investigates the effect of immersive AI (vs traditional hospitality) on customers’ behavioral intentions and the need for differentiation using virtual-assisted reality. Study 2 tests the underlying mechanism of the need for differentiation and luxury value in an augmented reality context. Study 3 provides additional support for the proposed underlying mechanism using virtual-assisted reality in luxury hospitality.

The findings reveal that immersive AI (vs traditional) luxury hospitality reduces customers’ behavioral intentions of using such services and perceived luxury value. Moreover, the findings indicate that the intention to use immersive AI (vs traditional) luxury hospitality services is contingent upon customers’ need for differentiation.

The findings have important theoretical and managerial implications for immersive technologies in luxury hospitality. They shed light on the dynamics between integrating immersive AI into luxury hospitality and its impact on customers’ differentiation motives and perceived luxury value. The findings reveal the detrimental effect of using immersive AI (vs traditional hospitality) within this context.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

The authors' research examines how negative electronic word-of-mouth (e-WOM) alters focal customers' post-recovery justice perceptions and attitudes to determine their future behavior with the service provider. Specifically, this paper develops and tests a conceptual model to investigate how negative e-WOM alters focal customers' perceptual and attitudinal outcomes after the service recovery experience. It also examines the post-recovery effect of negative e-WOM on focal customers’ willingness to patronize the service after their recovery experience.

To test the hypotheses, two pretests and two experimental studies with created scenarios in the retail context were conducted.

The authors' findings reveal that services are judged during and well beyond failure and recovery occurrences. To maintain a loyal customer base, service managers should develop processes that address service complaints both within and beyond the service consumption stage. The authors also find that despite a favorable recovery, focal customers gravitate toward the failure experience and develop unfavorable attitudes toward the service provider, leading to likely defections.

The authors' research demonstrates the persuasive power of negative e-WOM at the post-service recovery stage, making a unique contribution to the service recovery literature. This research also contributes to the persuasive effect of negative e-WOM, demonstrating message context as a boundary condition of negative e-WOM effects. In general, the authors' work highlights the importance of understanding the psychological processes involved in eliciting the persuasive influence of negative e-WOM in the post-service recovery stage that may lead to the defection of “so-called” successfully recovered customers.

The purpose of this study is to investigate conceptually the relationship between the customer’s engagement and equity and to determine whether customer engagement could be positively enhanced by business-to-business (B2B) firms to maximize their customer equity, through examining the role of cognitive, emotional and behavioral engagement.

This paper is built on the evolving marketing literature and proposes a comprehensive framework that uses a multidimensional conceptualization for the customer’s engagement and equity constructs; examines the relationships between customer satisfaction, commitment, trust and involvement and customer engagement; and specifies the specific customer engagement dimensions – cognitive, emotional and behavioral – as key mediators of the engagement–equity relationship.

This paper indicated that customer engagement is a multidimensional construct with three dimensions: cognitive, emotional or behavior engagement. Customer’s satisfaction, commitment, trust and involvement would be regarded as antecedents to customer engagement, whereas customer equity would be regarded a consequence for customer engagement. In addition, this paper identified three drivers of customer equity – value, brand and relationship equities – based on reviewing the previous studies.

This paper integrates philosophies from previous marketing studies of customer relationship management and customer engagement and equity into a B2B environment in a more customer-centric approach.