The global population is experiencing a significant rise in cases of depressive disorders, which have been exacerbated by the COVID-19 pandemic. However, having limited resources and fear of social stigma have discouraged individuals from seeking professional psychological counseling or visiting hospitals. In response to this issue, psychiatrists have attempted the use of chatbots as a therapeutic aid. Therefore, in this study, users’ choice data about the mental healthcare AI chatbot are collected through conjoint analysis, and the collected data is analyzed using the mixed logit method to derive users’ preferences for the mental healthcare AI chatbot. Findings highlight a consistent preference among users for certain factors in both psychological counseling chatbots and traditional psychological counseling. At first, the findings indicate that users place the highest priority on pricing and the ability to connect with a professional counselor. Furthermore, users prefer chatbots that have a more human-like appearance and characteristics. By incorporating these preferences, chatbot developers can create a more user-centric mental healthcare AI chatbot.

The recent appearance of AI psychological counseling services is expected to lower physical, economic, and psychological burdens for individuals seeking psychological counseling and increase participation in the service. AI psychological counseling research is still in its infancy, and therefore it is important to consider client preference to achieve positive effects. However, no research has been conducted to investigate client preferences regarding AI therapists. Therefore, this study explores the characteristics of AI counselors preferred by clients (e.g., rapport, trust, expertise, and attraction), as well as which AI agent therapist characteristics have positive effects on the attitudes of clients (users). This study confirms the characteristics that affect client intention to use AI counseling. Groups were divided using the K-means clustering technique based on the individual’s degree of introversion/extroversion and depression because characteristics desired in AI counselors may differ depending on individual client inclinations and examined differences between groups. The results of this study will help enhance and supplement the capabilities of developers and actual counselors through client-tailored counseling.

This study explores the role of mobility platforms in mitigating issues arising from information asymmetry about taxi services in South Korea. We employed conjoint analysis from a cognitive fit perspective and analyzed the marginal utilities of platform features using a mixed logit model. Our results show that platformization addresses negative experiences associated with information asymmetry and resolves long-standing problems associated with taxi services. Specifically, consumers prioritize information visualization and safety services, underscoring the platforms’ role in enhancing trust and safety as well as convenience. Despite the expansion into premium mobility experiences, the fundamental expectation from consumers remains access to reliable, safe services. This research contributes to understanding the impact of digital transformation on the mobility sector, emphasizing the need for strategic and policy interventions to leverage mobility platforms for improved service delivery.

Since the launch of ChatGPT in November 2022, the number of services providing generative AI has been steadily increasing. As different services enter the market, the generative AI interfaces users experience become more diverse. However, none of the services has yet established itself as the dominant tool, and which interface component affects user preferences the most has yet to be identified. This study investigates user preferences based on the interface of generative AI services currently on the market. We investigated users’ preferred interface components by setting the output data type, generative style, output variation, reference style, and generation history provided by the current generative AI service as properties. We collected data from 500 users through a survey and conducted conjoint analysis. Users preferred the provision of 10 generation histories the most, and the second most preferred the provision of reference style in footnote format. In addition, it was found that there was no preference for the creative generative style, which can be interpreted as users being aware of the problem of hallucination in generative AI. The results of this study will help future generative AI services design interfaces that consider user experience.

Self-disclosure lowers one’s stress and anxiety and benefits their mental health. However, revealing one’s personal and unprotected information can be risky, and such a risk causes major practical difficulties in counseling services. People are reluctant to expose themselves because they are concerned about being negatively evaluated and judged by others, even professional counselors. Accordingly, this study designs and implements a fully automated text-based counseling chatbot that alleviates people’s self-disclosure burden. This chatbot is based on rapport-facilitating dialogue, which creates a mutually stable and favorable relationship between two interlocutors and eventually encourages people to self-disclose. Using 303 nonclinical samples, this study examines how rapport is activated between a user and the counseling chatbot and confirms whether it lowers psychological barriers to being judged and encourages self-disclosure. The findings offer practical implications for artificial intelligence (AI) psychotherapy service developers to design a counseling program to encourage people to reveal their mental issues without hesitation.

With the expansion of virtual spaces, the role of virtual influencers has become more important. Although virtual influencers are imaginary characters, people can become interested in their attractive appearances and human characteristics and values on social media. However, most existing studies on virtual influencers deal with external factors, such as their appearance. This study aimed to investigate whether virtual influencers and users’ self-congruity including their actual and ideal selves on emotional attachment and to verify the effects of emotional attachment to virtual influencers on attitudes towards virtual influencers. A survey was conducted of 344 users, and empirical results from structural equation modeling indicated that significant impacts of actual self-congruity between virtual influencers and users were found on emotional attachment when virtual influencers were divided into external and internal images. Additionally, the congruity between internal images of the virtual influencers and the user’s ideal self-congruity significantly affected emotional attachment. The study results demonstrated that self-congruity theory provides an accurate framework for describing the role of emotional attachment to virtual influencers.

The present study investigates the effects of a chatbot’s motivation support style on the learner’s experience and intention to continue the study in the context of online English lectures. Seventy-nine undergraduate students were recruited from a large private university in Seoul, South Korea, and assigned to one of three learning plan development groups: develop a plan alone, autonomy support (i.e., a chatbot stimulating intrinsic motivation), or control support (i.e., a chatbot promoting extrinsic motivation) groups. The learners were classified into two groups based on their learning motivation types (i.e., intrinsic and extrinsic), and by doing so, the present study created a chatbot’s matched and non-matched motivation support conditions in learning plan development. The two support strategies were compared with a control condition (i.e., learners’ own plan making), and the results suggest that a chatbot with a non-matched motivation strategy increases learner self-efficacy, enjoyment, and intention to continue using the lecture. Furthermore, the study also explores the moderation effect of learning motivation types, and reveals that a chatbot’s control support significantly improves the learning experience. The present study provides new insight into improving user evaluation by strategically differentiating a chatbot’s conversational style and a user’s characteristics.

The watching-eye effect proposes that others’ eyes cause people to behave in a prosocial manner. The current study tested this in the context of an online news website, by investigating whether a watching-eye icon influences users’ attention to themselves and expressions of their opinions in a comment section. In an online experiment, participants (N = 741) used an online news website in the presence (vs. absence) of a watching eye as a visual cue for an imagined audience, who reportedly presented their opinions in a comment section. Results showed that the watching eye did influence participants’ private and public self-awareness and the quality of their comments. Presence of the visual cues, compared to its absence, increased female participants’ self-awareness, specifically when others’ opinions revealed in the comment section were mixed or opposed to the news article topic. This increased private self-awareness was positively associated with the comment quality. These findings indicate the importance of social cues on interfaces in mitigating the negative consequences of anonymity in online environments.

The ambiguity of online text communication coming from the lack of audiences’ social cues often causes misunderstanding, which arouses a negative image of the message sender. Likewise, message senders feel social anxiety about whether their intentions are properly conveyed, or whether their messages may not sound offensive or impolite in communicating with text such as writing a self-introduction letter. In this paper, we design and develop a messaging assistant (Emoware) prototype which visualizes the audience’s predicted emotions to motivate the message sender to reveal more information. We conducted a user study comparing Emoware to plain text interface with 56 participants and found that Emoware positively affects writing by improving users’ self-disclosure intention, social support, and self-disclosure. This study contributes to overcoming the limitations of text modality in online communication.

The online environment for video conferencing lacks cues compared to offline, so one can hear the interlocutor's criticism more sensitively, and the fear of presenting in front of the camera can hinder participation in the meeting. It is known that interface design affords a role in improving public speaking and has a possibility of changing user behavior. To examine how the interface design of video conferencing affects video debating participation, 2 (visual anonymity: avatar vs. face) × 2 (self-affirmation vs. no self-affirmation) between-subjects experiment was conducted. Results showed that using an avatar, when properly used together with self-affirmation, has a positive effect on active participation in discussions, but derogating others’ critical messages. These results indicate unique underlying mechanisms of the effects of the avatar; the deindividuation effect of visual anonymity, and the effects of improving participation when customizing self-value reflected avatars.

This study observes the webtoon consumption behavior of users who wait and experience webtoon contents for free, and investigates factors that increase purchasing intention, focusing on changes in their intention. Existing studies have proven that users’ sharing intentions can affect purchase decisions and behavioral intentions. We assume that the sharing intention can affect the purchasing intention and that the effect on the purchasing can be confirmed by verifying the mediation effect of the sharing intention. The survey data of users who have experience watching webtoon contents (n=220) were analyzed to regression analysis by using SPSS PROCESS macro. The results were shown the indirect effect and the complete mediating effect of sharing intention and were indicated sharing intention improves the purchase intention by mediation. We discuss theoretical and practical implications that can be drawn from the effect of sharing intention on purchase intention