Intelligent AI devices have become a common presence in the business landscape, offering a wide range of services, from the medical sector to the hospitality industry. From an organizational ...perspective, AI devices have several advantages, by performing certain tasks quicker and more accurately in comparison to humans while at the same time being more cost-efficient. However, in order to maintain the high standards of a brand, they have to be accepted by consumers and deliver socially adequate performance. Therefore, it is important to determine the characteristics of AI devices which make them accepted and trusted by consumers. Based on the Computers as Social Actors (CASA) Theory, we have researched on the role of psychological anthropomorphic characteristics, perceived empathy, and interaction quality in the acceptance of AI devices in the service industry. The results show that anthropomorphic characteristics alone do not influence acceptance and trust towards AI devices. However, both perceived empathy and interaction quality mediate the relation between anthropomorphic characteristics and acceptance. A human-like AI device has higher acceptance when it has the ability to show empathy and interaction in relation to the human consumer. This result reveals the importance of developing forms of strong intelligence and empathetic behaviour in service robots and AI devices.
•Psychological anthropomorphic AI devices, which show empathy have a higher degree of consumers' acceptance.•Empathy mediates the relation between psychological anthropomorphic characteristics of AI and the consumers' acceptance.•Empathy mediates the relation between anthropomorphic characteristics of AI and their interaction quality with consumers.•Anthropomorphic AI devices which show empathy have a better interaction quality with consumers.•Interaction quality mediates the relation between AI's psychological anthropomorphic characteristics and their acceptance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The fourth industrial revolution is making possible augmented reality (AR), which has the potential, among other things, to alter profoundly the ways in which individuals purchase and consume goods. ...Yet despite significant growth in the AR industry, the impact of this technology on consumers and other stakeholders in the retail environment has been little explored. In particular, the influence of anthropomorphism on consumers’ perceptions of AR in the retail environment remains poorly understood. Specifically, randomly selected adults (n = 319) participated in a field based retail shopping experience using augmented reality on a mobile device, the findings presented here demonstrate that anthropomorphism indeed influences consumers’ experiences of AR and their attitudes toward brands that use it. This study therefore has important theoretical implications as well as practical implications for managers. We begin by elaborating a theory of anthropomorphism in the context of retail marketing that can account for consumers’ perceptions of AR in general. We then discuss how our findings can assist managers in the retail sector in leveraging the anthropomorphisation of AR as part of the effort to build effective relationships with their customers. Our findings further suggest that brands benefit when managers make AR a key part of the retail experience.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In movies, robots are often extremely humanlike. Although these robots are not yet reality, robots are currently being used in healthcare, education, and business. Robots provide benefits such as ...relieving loneliness and enabling communication. Engineers are trying to build robots that look and behave like humans and thus need comprehensive knowledge not only of technology but also of human cognition, emotion, and behavior. This need is driving engineers to study human behavior toward other humans and toward robots, leading to greater understanding of how humans think, feel, and behave in these contexts, including our tendencies for mindless social behaviors, anthropomorphism, uncanny feelings toward robots, and the formation of emotional attachments. However, in considering the increased use of robots, many people have concerns about deception, privacy, job loss, safety, and the loss of human relationships. Human-robot interaction is a fascinating field and one in which psychologists have much to contribute, both to the development of robots and to the study of human behavior.
Purpose
This paper aims to provide a better understanding of negative consumer–brand relationships in social-media-based anti-brand communities from a consumer culture theory (CCT) perspective. In ...particular, it investigates the purpose and the meaning of the consumer participation in online anti-brand communities, also through the analysis of the ways in which they express negative feelings toward the hated brands.
Design/methodology/approach
This study applies a “symbolic netnographic” method to six anti-brand communities related to four global brands, namely, Apple, Nestlé, Uber and McDonald’s. Moreover, several interviews were conducted with anti-brand community administrators.
Findings
The findings show that the main reason for consumers to join anti-brand communities is a desire to participate in the construction of new meanings and values of modern consumption, translating their ideological incompatibility with certain brands into negative engagement and activism aimed at destroying the hated brand’s image and reputation. Furthermore, the findings reveal that brand anthropomorphism is a frequent means of communication also used in the context of negative consumer–brand relationships, to strengthen the battle against the hated brand in a more frontal and direct manner.
Research limitations/implications
Although this research provides some initial insights into negative consumer–brand relationships in the social media anti brand communities, the paper also has some limitations. The netnographic approach should be analyzed within more and different anti-brand communities. In this investigation, the authors perceived how difficult it is to obtain feedback from communities and to secure the collaboration of their administrators. There is also a need for research on other potential factors that can play a key role in negative consumer–brand relationships in social-media anti-brand communities, such as cultural capital or the impact of cultural perceptions. Moreover, future research should focus on different types of products and brand services, such as hedonic vs. utilitarian brands, as these might generate different types of consumer behavioral responses. Finally, a further direction for future research would be to consider the set of “brand recovery strategies” that can be implemented by companies to deal with negative consumer–brand relationships, including the identification of situations in which “not acting” could be preferable.
Practical implications
Understanding the antecedents and types of negative consumer–brand relationships enables companies to identify “brand recovery strategies” for managing negativity in the appropriate manner. Moreover, negative feelings toward brand could even be an opportunity for improving branding management.
Originality/value
This research improves on previous few studies dealing with online anti-brand communities from a CCT perspective. Firstly, it provides a holistic perspective of negative consumer–brand relationships in general and specifically of brand hate, thus advancing our understanding of the sociocultural dynamics of negative consumer–brand relationships; secondly, it provides new insights into the brand anthropomorphism phenomenon emerging in the negative feelings context. Overall, this research contributes to knowledge for both academics and managers as to why, how and for what purpose consumers experience negative engagement toward certain brands in the specific context of social-media-based anti-brand communities.
A personal intelligent agent (PIA) is a system that acts intelligently to assist a human using natural language. Examples include Siri and Alexa. These agents are powerful computer programs that ...operate autonomously and proactively, learn and adapt to change, react to the environment, complete tasks within a favorable timeframe and communicate with the user using natural language to process commands and compose replies. PIAs are different from other systems previously explored in Information Systems (IS) due to their personalized, intelligent, and human-like behavior. Drawing on research in IS and Artificial Intelligence, we build and test a model of user adoption of PIAs leveraging their uique characteristics. Analysis of data collected from an interactive lab-based study for new PIA users confirms that both perceived intelligence and anthropomorphism are significant antecedents of PIA adoption. Our findings contribute to the understanding of a quickly-changing and fast-growing set of technologies that extend users’ capabilities and their sense of self.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
How educational media can support learning is a growing concern. This study examined the impact of age (4-year-olds vs. 6-year-olds) and informants (human vs. animal puppet vs. anthropomorphic ...language animal puppet) on children’s animal knowledge learning and anthropomorphic generalization. A total of 210 children aged 4 and 6 participated. Children learned equally well from each of the three types of informants. Six-year-olds learned more than did 4-year-olds and were also more curious to learn more about the animal after watching the videos. Four-year-olds were more likely to generalize anthropomorphic traits in animals than were older children. Finally, 4-year-olds in the animal puppet group showed a significantly higher preference for the informant than did 4-year-olds in the human and anthropomorphic language animal puppet groups. Overall, the findings showed that watching animal educational videos can promote children’s acquisition of animal knowledge and that children learn equally well from human and puppet informants. Additionally, younger children may enjoy learning from non-anthropomorphic language animal puppets more than from humans and anthropomorphic language animal puppets, but there are no significant differences in their learning.
•This paper looks at children's animal knowledge learning from human and puppet informants.•Children learned equally well from different informants.•Watching the anthropomorphic language video appeared to hinder children's generalization of anthropomorphic traits.•There were no differences in children’s learning despite differences in subjective liking toward informants.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Chatbots are replacing human agents in a number of domains, from online tutoring to customer-service to even cognitive therapy. But, they are often machine-like in their interactions. What can we do ...to humanize chatbots? Should they necessarily be driven by human operators for them to be considered human? Or, will an anthropomorphic visual cue on the interface and/or a high-level of contingent message exchanges provide humanness to automated chatbots? We explored these questions with a 2 (anthropomorphic visual cues: high vs. low anthropomorphism) × 2 (message interactivity: high vs. low message interactivity) × 2 (identity cue: chat-bot vs. human) between-subjects experiment (N = 141) in which participants interacted with a chat agent on an e-commerce site about choosing a digital camera to purchase. Our findings show that a high level of message interactivity compensates for the impersonal nature of a chatbot that is low on anthropomorphic visual cues. Moreover, identifying the agent as human raises user expectations for interactivity. Theoretical as well as practical implications of these findings are discussed.
•A compensation effect of high anthropomorphic visual cues on low message interactivity.•Another compensation effect of high message interactivity on low anthropomorphic visual cues.•An expectancy violation effects when the identity cue is combined with message interactivity.•Revealing the identity of the machine can capitalize on expectations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
38.
Measuring the Uncanny Valley Effect Chin-Chang, Ho; MacDorman, Karl F
International journal of social robotics,
01/2017, Volume:
9, Issue:
1
Journal Article
Peer reviewed
Open access
Using a hypothetical graph, Masahiro Mori proposed in 1970 the relation between the human likeness of robots and other anthropomorphic characters and an observer’s affective or emotional appraisal of ...them. The relation is positive apart from a U-shaped region known as the uncanny valley. To measure the relation, we previously developed and validated indices for the perceptual-cognitive dimension humanness and three affective dimensions: interpersonal warmth, attractiveness, and eeriness. Nevertheless, the design of these indices was not informed by how the untrained observer perceives anthropomorphic characters categorically. As a result, scatter plots of humanness vs. eeriness show the stimuli cluster tightly into categories widely separated from each other. The present study applies a card sorting task, laddering interview, and adjective evaluation (N=30) to revise the humanness, attractiveness, and eeriness indices and validate them via a representative survey (N=1311). The revised eeriness index maintains its orthogonality to humanness (r=.04, p=.285), but the stimuli show much greater spread, reflecting the breadth of their range in human likeness and eeriness. The revised indices enable empirical relations among characters to be plotted similarly to Mori’s graph of the uncanny valley. Accurate measurement with these indices can be used to enhance the design of androids and 3D computer animated characters.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
(HSRs) are human-made technologies that can take physical or digital form, resemble people in form or behavior to some degree, and are designed to interact with people. A common assumption is that ...social robots can and should mimic humans, such that human-robot interaction (HRI) closely resembles human-human (i.e., interpersonal) interaction. Research is often framed from the assumption that rules and theories that apply to interpersonal interaction should apply to HRI (e.g., the computers are social actors framework). Here, we challenge these assumptions and consider more deeply the relevance and applicability of our knowledge about personal relationships to relationships with social robots. First, we describe the typical characteristics of HSRs available to consumers currently, elaborating characteristics relevant to understanding social interactions with robots such as form anthropomorphism and behavioral anthropomorphism. We also consider common social affordances of modern HSRs (persistence, personalization, responsiveness, contingency, and conversational control) and how these align with human capacities and expectations. Next, we present predominant interpersonal theories whose primary claims are foundational to our understanding of human relationship development (social exchange theories, including resource theory, interdependence theory, equity theory, and social penetration theory). We consider whether interpersonal theories are viable frameworks for studying HRI and human-robot relationships given their theoretical assumptions and claims. We conclude by providing suggestions for researchers and designers, including alternatives to equating human-robot relationships to human-human relationships.
•Chatbots are increasingly used as substitutes for human service agents in online shops.•Anthropomorphizing chatbots increases perceived consumer-chatbot similarity.•Matching chatbot gender with ...consumer gender positively impacts consumer behavior.•First insights indicate that non-binary consumers prefer neutral chatbots.
Chatbots are increasingly used as substitutes for human service agents in online shops. This has led researchers to analyze how chatbot characteristics influence consumer responses. However, while the relevance of chatbot characteristics has been examined, to date, consumers’ personalities have remained unattended in the research on this innovative mode of online support. Therefore, this study aims to understand how the interaction of consumer characteristics and chatbot characteristics influences consumer behavior. In doing so, we focus on how chatbots’ visual cues (i.e., anthropomorphization, gender) influence consumer behavior while also considering consumers’ self-concept. To answer the research question, we first conceptually discuss why consumer behavior depends on perceived self-congruence between consumers and a chatbot, which can be reached by anthropomorphizing chatbots and giving them the “right” gender. Subsequently, based on multiple studies, we empirically test the hypotheses considering male, female, and non-binary consumers. Our results demonstrate the relevance of both chatbot anthropomorphization and chatbot gender.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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