• Journal of the HCI Society of Korea
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• v.12 no.1
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• pp.15-23
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• 2017

Applying the concept and components of human nature to the conversational agent in the smart home context, this study investigated the effects of the level of anthropomorphism and interaction type on the emotional user experiences and future use intention. The results of experiment study showed that the high-low condition of anthropomorphism and the voice-chatting interaction type have impacts on the perceived closeness, likability, and future use intention. That is, people evaluate the conversational agent as more close, likable, and useful when they perceive more human nature components and when in the voice interaction mode. Psychological resistance was lower in the voice than in the chatting mode regardless of the level of anthropomorphism. The results also demonstrated an interaction effect of anthropomorphism and interaction type on the future use intention: the effect of anthropomorphism existed only in the voice interaction mode. It leads to the conclusion that a conversational agent with the voice recognition interface should be designed with the higher level of human nature components for the continuous use.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.93-102
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• 2022

This study investigated the differences in smart speaker users' loneliness, social disconnection, and attachment, frequency of daily speaker usage, and anthropomorphic behavior depending on the level of smart speaker anthropomorphism. A total of 320 users participated in an online survey. Results showed significant differences between the high anthropomorphism group and the low anthropomorphism group in their level of loneliness, social disconnection, anxiety attachment, frequency of daily speaker usage, and anthropomorphic behaviors. However, no significant difference in avoidance attachment between the two groups was found. The findings imply that interaction design can possibly enhance positive social interaction with smart speakers.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.47-56
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• 2012

The purpose of this study is to test the effect of pedagogical agent realism and expertise on persona effect. There were two perspectives of the pedagogical agents' social interaction. Self-identification hypothesis argues that complexity of agent image is better to increase social interaction. Subjective identification insists that simplified image is more helpful to facilitate social interaction. However, from the cognitive load theory perspective, learners' expertise can be a major factor to determine persona effect. Sixty-eight college students (male=19 and female=49) participated. The independent variables were the degree of realism of pedagogical agent (detailed vs. simplified image) and the expertise (high prior knowledge group vs. low prior knowledge group). The dependant variables were comprehension test and the agent persona instrument (API). There was no significant difference in comprehension test score; however, there were significant interaction effect on the most constructs of API: 1) facilitating of learning, 2) credible, and 3) human-like. The follow-up analysis of simple main effect revealed that high expertise group showed significantly higher perception of the three construct with high realism of pedagogical agent. The results of study show that learners' expertise plays a key role of perception of persona effect.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.469-476
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• 2022

As the 3D modeling technology and conversational algorithm is developed, digital humans are being used in various fields, and also virtual bankers have begun to appear in banks, including major banks such as Shin-Han Bank and Nong-Hyup Bank. However, most of the research of digital human mainly focus on its appearance, and research on robot persona that should be considered in anthropomorphizing a robot is insufficient. In this study, an experiment was conducted to find out the user experience of three scenarios (student ID receipt, deposit and withdrawal account opening, leasehold loan consultation) in which the level of anthropomorphism of the speech strategy and the level of personal information use differed in the specific context of banking. As a result of the study, social presence and usefulness had an interactive effect on the scenario and the level of anthropomorphism. There was no interaction effect on intimacy, trustworthiness, and perceived intelligence, but a tendency could be confirmed.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.445-455
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• 2022

Financial service chatbots are hindering user experience with conversational errors and machine-like responses. This study aims to examine the effect of self-disclosure and emotional expression of an anthropomorphic chatbot on user experience before conversation errors occur in financial services. In financial inquiries, scenarios were designed based on self-disclosure type (positive vs. negative) and emotional expression level(high confident vs. low confident), and online experiments were conducted. The result revealed that when anthropomorphic chatbot provided self-disclosure and emotional expression, the main effect has been shown on trust, annoyance, service recovery, and intention to continuous use. In addition, interaction effects were significant in trust and annoyance. In conclusion, this paper demonstrated that anthropomorphic chatbot's positive self-disclosure and confident emotional expression influenced trust and annoyance.

• The Journal of Korean Association of Computer Education
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• v.15 no.1
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• pp.55-64
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• 2012

The purpose of this study is to identify how realism of pedagogical agent can have impacts on persona effect and cognitive load factors. Eighty-two college students participated, and the independent variables of this study were the degree of image details and presence of gesture. The degree of image details were picture, illustration, and line-drawing. The $3{\times}2$ factorial design was applied. There was a significant interaction effect on the engaging of agent persona instrument. When the learners were under the condition of line-drawing agent without gesture, they showed the highest score on engaging of the agent persona instrument. Regarding the cognitive load factors, when learners under the condition of line-drawing showed the highest score of self-evaluation.

• Information Systems Review
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• v.26 no.1
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• pp.119-149
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• 2024

This study investigates the antecedents and mechanisms influencing trust and behavioral intentions formation towards new AI chatbots, such as ChatGPT, as travel information searching services. Analyzing the roles of variables such as familiarity, novelty, personal innovativeness, information quality and perceived anthropomorphism, the research elucidates the impact of these factors on users' cognitive and affective trust, ultimately affecting their intention to adopt information and sustain the use of the AI chatbot. Results indicate that perceived familiarity and information quality positively influence both cognitive and affective trust, whereas perceived novelty contributes positively only to cognitive trust. Additionally, the personal innovativeness of new AI chatbot users was found to weaken the effect of familiarity on perceived trust, while the perceived level of anthropomorphism of the chatbot amplified the effects of novelty and familiarity on cognitive trust. These findings underscore the importance of considering factors such as familiarity, personal innovativeness, information quality and anthropomorphism in the design and implementation of AI chatbots, affecting trust and behavioral intention.

• Journal of Fashion Business
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• v.25 no.4
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• pp.79-91
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• 2021

Currently, chatbot, a conversational platform based on artificial intelligence, is drawing attention as a new marketing channel. This study attempted to verify the effect of the anthropomorphism, message type, and media self-efficacy level on purchase intention. The experimental design of this study was a 2 (anthropomorphism level of shopping chatbot: low vs. high) × 2 (message type: factual vs. evaluative) × 2 (media self-efficacy: low vs. high) three-way mixed analysis of variance (ANOVA). This study conducted a survey by the convenience sampling method of 402 women in their 20s and 30s living in Seoul and the Gyeonggi area who were aware of chatbot services. For the final analysis, 388 questionnaires were used. Data were analyzed with the SPSS 23 program and three-way ANOVA. Simple main effects analysis was conducted. The results of this study were as follows. First, there were statistically significant differences in purchase intention according to anthropomorphism level, message type, and media self-efficacy. Second, message type and media self-efficacy showed statistically significant interaction effects on purchase intention. Lastly, anthropomorphism and the media self-efficacy level and the message type of the shopping chatbots showed significant three-way interaction effects on purchase intention.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.205-219
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• 2021

The present study identified determinants to user acceptance of artificial intelligence(AI)-based news anchor. Our conceptual model included three constructs of ability, benevolence, and integrity to determine whether these three constructs are predictive of trust perceived from AI news anchor. This work further examined the influences of social presence, anthropomorphism, perceived usefulness, understanding as well as trust as immediate determinants to user acceptance. The conceptual model was validated on survey data collected from 513 respondents. A series of scale refinement process was conducted by the examination of data normality, common method bias, structure of latent variables as well as internal consistency. In addition, a confirmatory factor analysis was performed to assess the extent to which the sample data collected from survey study measures the constructs adequately. The results from the analysis of structural equation model indicated that, (1) two constructs of ability and integrity were found to be significantly predictive of perceived trust, and (2) anthropomorphism, perceived usefulness, and trust emerged as significant and positive predictors of user acceptance of AI-based news anchor.