It’s a Match! The effects of chatbot anthropomorphization and chatbot gender on consumer behavior

Zogaj, Adnan; Mähner, Philipp M.; Yang, Long-Hao; Tscheulin, Dieter K.

doi:10.1016/j.jbusres.2022.113412

Cited by 36 publications

(14 citation statements)

References 51 publications

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“…For experiential learning, shared curiosity for the topic at hand emerged as a more significant goal-relevant factor, while variables such as personality traits and sociodemographic variables like gender and age are found to be less important. This finding is particularly intriguing regarding gender, as prior research has shown that gender congruence increases a sense of similarity with digital assistants (Romero et al, 2021;Zogaj et al, 2023). However, in the case of experiential learning, it appears that a companion's gender is not considered goal-relevant, suggesting that (virtual) friendship can transcend gender considerations in this particular context.…”

Section: Theoretical Implicationsmentioning

confidence: 87%

“…This important finding adds to the prior finding that goal‐relevant similarity is context‐dependent (Arndt et al, 2021). For digital assistants, attributes such as the same gender exerted positive effects (e.g., Romero et al, 2021; Zogaj et al, 2023), but the role of gender is not likely a key driver of goal‐relevant similarity perceptions for experiential learning with companions.…”

Section: Discussionmentioning

confidence: 99%

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Matching digital companions with customers: The role of perceived similarity

Gelbrich,

Kerath,

Chun

2023

Psychology and Marketing

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Digital companions are an advanced form of digital agents that do not only provide advice and support but accompany people on their day‐to‐day customer journeys. This article sheds light on the psychological processes underlying customers’ responses to these digital companions (i.e., virtual friends or co‐consumers). We propose that framing them as matched with customers on goal‐relevant attributes (i.e., attributes related to customers’ consumption goals) fosters positive customer outcomes (i.e., consumption enjoyment and positive word‐of‐mouth), mediated by perceived similarity in these attributes. Importantly, in this matching context, humanlikeness serves as a boundary condition for perceived similarity to occur. Furthermore, the effect of perceived similarity on customer outcomes is driven by perceived connectedness. In Study 1, in the context of experiential learning, we identified shared interest and personality as goal‐relevant attributes underlying perceived similarity. With the manipulation of the match frame and humanlike versus artificial voice of the digital companion, Study 2 supports our propositions and highlights shared interest, but not personality, as the core driver. We provide recommendations on how to design and market digital companions to foster connection and favorable customer outcomes.

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Section: Theoretical Implicationsmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Matching digital companions with customers: The role of perceived similarity

Gelbrich,

Kerath,

Chun

2023

Psychology and Marketing

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“…However, Study 3 reveals some encouraging insights related to personalization via AI types (Huang and Rust 2021): when consumers perceive their stigmatized condition to be controllable (vs. not), they prefer thinking AI (vs. feeling AI), as long as the stigmatizing attribute (e.g., health condition) elicits high involvement. These insights inform research on matching consumers with chatbot personalities (Zogaj et al 2023). For example, Shumanov and Johnson (2021) show that "consumer personality can be predicted during contextual interactions, and that chatbots can be manipulated to 'assume a personality' using response language," which improves consumer engagement with chatbots.…”

Section: Findings and Theoretical Implicationsmentioning

confidence: 91%

“…We share the optimism in the literature on the promise and importance of AI (e.g., Huang and Rust 2021). For example, recent research points to opportunities related to personalizing customer conversations with chatbots by imbuing bots with distinct personalities (Shumanov and Johnson 2021); other research goes further and proposes to match consumer-chatbot personalities (Zogaj et al 2023). This optimism about AI in the scholarly literature notwithstanding, we wanted to explore the potential of AI in the context of stigmatized consumers from service providers’ perspectives.…”

Section: Study 1: the Effects Of Message Source And Consumer Stigma O...mentioning

confidence: 99%

Personalized Communication as a Platform for Service Inclusion? Initial Insights Into Interpersonal and AI-Based Personalization for Stigmatized Consumers

Mende,

Scott,

Ubal

et al. 2023

Journal of Service Research

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Although calls for inclusiveness in services are becoming more vigorous, empirical research on how to design and implement service inclusion for stigmatized consumers remains scant. This paper draws on key questions of personalization (i.e., who personalizes what for whom?) to tailor the (a) source and (b) content of marketing messages in order to better include stigmatized consumers. The authors examine this idea in three experiments in healthcare/well-being settings. In terms of message source, the results show that, in interpersonal interactions, service companies can employ the principle of homophily to better engage stigmatized consumers (Study 1). In contrast, homophily-inspired personalized messages to stigmatized consumers can backfire in the context of consumer-artificial intelligence (AI)-interactions (human-to-avatar interactions; Study 2). Moreover, in terms of message content, Study 3 explores how, and under which conditions, companies can leverage thinking AI versus feeling AI for improved service inclusiveness. Finally, the studies point to anticipated consumer well-being as a crucial mediator driving effective service inclusiveness among stigmatized consumers. The results not only contribute to an emerging theory of service inclusiveness, but also provide service scholars and managers with initial empirical results on the role of AI in inclusive services.

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“…Regardless of the level of anthropomorphism, the chatbot had either a direct or averted gaze. Recent literature has noted that the gender of the chatbot interacts with anthropomorphism in determining the effectiveness of the chatbot's recommendations: when the gender of the chatbot matches the gender of the user, it exerts a stronger impact on consumer behavior (Zogaj et al, 2023). Accordingly, the present work manipulated the gender of the chatbot to test whether such a gender match effect also occurs to shape individuals' perceptions of the chatbot's warmth and competence.…”

Section: Methodsmentioning

confidence: 99%

I, chatbot! the impact of anthropomorphism and gaze direction on willingness to disclose personal information and behavioral intentions

Pizzi

Vannucci

Mazzoli

et al. 2023

Psychology and Marketing

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The present research focuses on the interplay between two common features of the customer service chatbot experience: gaze direction and anthropomorphism. Although the dominant approach in marketing theory and practice is to make chatbots as human‐like as possible, the current study, built on the humanness‐value‐loyalty model, addresses the chain of effects through which chatbots' nonverbal behaviors affect customers' willingness to disclose personal information and purchase intentions. By means of two experiments that adopt a real chatbot in a simulated shopping environment (i.e., car rental and travel insurance), the present work allows us to understand how to reduce individuals' tendency to see conversational agents as less knowledgeable and empathetic compared with humans. The results show that warmth perceptions are affected by gaze direction, whereas competence perceptions are affected by anthropomorphism. Warmth and competence perceptions are found to be key drivers of consumers’ skepticism toward the chatbot, which, in turn, affects consumers’ trust toward the service provider hosting the chatbot, ultimately leading consumers to be more willing to disclose their personal information and to repatronize the e‐tailer in the future. Building on the Theory of Mind, our results show that perceiving competence from a chatbot makes individuals less skeptical as long as they feel they are good at detecting others’ ultimate intentions.

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It’s a Match! The effects of chatbot anthropomorphization and chatbot gender on consumer behavior

Cited by 36 publications

References 51 publications

Matching digital companions with customers: The role of perceived similarity

Matching digital companions with customers: The role of perceived similarity

Personalized Communication as a Platform for Service Inclusion? Initial Insights Into Interpersonal and AI-Based Personalization for Stigmatized Consumers

I, chatbot! the impact of anthropomorphism and gaze direction on willingness to disclose personal information and behavioral intentions

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