• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.136-148
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• 2022

This study aims to examine the effects of customer experience on the relationship between brand trust and customer experience. The survey was conducted on consumers who experienced chatbot service through internet shopping mall, and the research hypothesis was verified by analyzing the final 299 questionnaires. The results of the study showed that the customer experience using chatbot service had a positive effect on chatbot trust, had a positive effect on shopping mall trust, seller trust and brand trust through the mediating role of chatbot trust, and the social presence of chatbot had a moderating effect in the trust transfer. This study provides a theoretical basis that customer experience of chatbot service has positive effect on brand trust through chatbot trust, and suggests implications in that chatbot service can be an important means of marketing. In future studies, various studies related to chatbot trust are needed.

• 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.

• Journal of the HCI Society of Korea
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• v.12 no.4
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• pp.45-55
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• 2017

In recent years, some service providers have introduced chatbot agents to provide engagement in the healthcare field. However, current research on chatbot agents is still limited to designing various chatbot identities for healthcare services. By contrast, this study aims to investigate how various agent identities affect users' perceptions and behaviors differently. We developed three chatbot agents with different identities: a doctor (an individual), a hospital (an institution), and a virtual agent (a machine). Then, we recruited 36 users and divided them into three groups, each using a different chatbot agent. They were asked to track their behaviors and review advice from the chatbot agent for six days. Post-hoc surveys and interviews were conducted in order to investigate users' perceptions. The findings are as follows: participants felt more trusting and intimate with the doctor and hospital agents than with the virtual agent. Many of the participants preferred the hospital agent due to its higher reliability. However, all three agents did not lead the participants to change their behaviors. This study contributes to providing practical guidelines for designing chatbots in the healthcare field by studying users' perceptions and behaviors depending on chatbot identities.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.297-307
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• 2022

This study examined whether there was a difference in the attitude toward the recommended product and the effect on the choice deferral according to information sources. Experiment 1 examined the relationship between trust in information and product attitude, and between uncertainty and choice deferral according to information sources (AI chatbot vs. human). Experiment 2 examined the impact of social presence, perceived personalization, and choice deferral according to whether anthropomorphism of AI chatbots or not. The research results are as follows. First, consumers were found to have a more positive attitude toward products recommended by AI chatbots (vs. human). Second, consumers were more choice deferral whether to purchase products recommended by AI chatbots (vs. human). Third, it was found that consumers' selection of products recommended by anthropomorphic AI chatbots (vs. impersonated AI chatbots) increased. Also, the implications of this study and future research directions were discussed.

• Knowledge Management Research
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• v.22 no.1
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• pp.287-308
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• 2021

This study aims to explore how the effects of the perceived social presence on trust and live chat adoption intention vary with the types of live chats in e-commerce context. As technology develops, live chat with the seller in e-commerce is rapidly replaced by AI-assisted live chat called chat-bot. However, it is not well known how the buyers perceive the difference between the chat with seller and the chat-bot. This study therefore proposes first, the perceived social presence toward the seller will influence trust and the live chat adoption. Second, the effects of social presence will be stronger when using live chat with seller than using chat-bot. To validate, we collect data from 232 e-commerce users and confirm the first proposition. However, the higher level of the social presence effect of live chat with seller is not clearly revealed. This study is expected to provide researchers and managers who are interested in AI-based chatbots with useful theoretical and practical implications.

• Knowledge Management Research
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• v.21 no.4
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• pp.211-225
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• 2020

We investigate factors affecting chatbot use intention of online shopping mall users. We identify theoretical foundations from the literature and postulate that accuracy, personalization level, intelligence, intimacy, social presence, and piracy concern should affect intention to use more or negative intention to use. Based on 300 responses from online shopping mall chatbot users in Korea, we run the statistical analysis to assure the reliability and validity of the measurements. From the multiple regression analysis, we find that personalization level, intelligence, social presence, and privacy concerns significantly affect intention to use more. In contrast, we find that accuracy and privacy concerns significantly affect negative intention to use. This work will present pragmatic implications upon the design and management of chatbot in order to not only incent customers to use more but reduce factors that may cause negative use intention. Among functional factors, personalization and intelligence increases the intention to use more while accuracy decreases negative intention to use. Among emotional factors such as intimacy and social presence, we find that only social presence significantly increases intention to use more. Privacy concerns is found to decrease intention to use and increase negative intention to use.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.157-166
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• 2018

Communication between customers and service providers is an important issue at sites where various businesses and transactions take place. In particular, the ability to solve problems quickly and accurately when a problem arises and when an inquiry is received is directly linked to trust in the site. In this paper, we propose a method of handling complaints and inquiries of site users by using chatbot technology on talent market platform site. First, we implemented chatbot that can communicate with the inquirers in real time, so that users can use the site usage and word search functions. For various errors and problems of the site which can not be defined by a few words or sentences, I have specified an error code and database it. Users of the site were able to contact chatbot with the error code that was output when an error occurred and get the corresponding response in real time. The chatbot implemented in this study provided a satisfactory experience because that was able to provide quick and accurate answers to users who experienced errors or inquiries when using the site. This will have a positive impact on the credibility and favorability of the site over the long term, and will help reduce manpower and time costs for error inquiries.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.29-34
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• 2021

With the advent of the 4th industrial revolution era, IT technology is creating new services that have not existed by converging with various existing industries and fields. In particular, in the field of artificial intelligence, chatbots and the latest technologies have developed dramatically with the development of natural language processing technology, and various business processes are processed through chatbots. This study is a study on a system that provides a close answer to the question the user wants to find by creating a structural form for legal inquiries through Slot Filling-based chatbot technology, and inputting a predetermined type of question. Using the proposal system, it is possible to construct question-and-answer data in a more structured form of legal information, which is unstructured data in text form. In addition, by managing the accumulated Q&A data through a big data storage system such as Apache Hive and recycling the data for learning, the reliability of the response can be expected to continuously improve.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.411-416
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• 2023

The purpose of this study is to investigate the utilization of major learning tools among radiology science students and assess the accuracy of a conversational artificial intelligence service program, specifically a chatbot, in the context of the national radiologic technologist licensing exam. The survey revealed that 84.3% of radiology science students actively utilize electronic devices during their learning process. In addition, 104 out of 140 respondents said they use search engines as a top priority for efficient data collection while studying. When asked about their awareness of chatbots, 80% of participants responded affirmatively, and 22.9% reported having used chatbots for academic purposes at least once. From 2018 to 2022, exam questions from the first and second periods were presented to the chatbot for answers. The results showed that ChatGPT's accuracy in answering first period questions increased from 48.28% to 60%, while for second period questions, it increased from 50% to 62.22%. Bing's accuracy in answering first period questions improved from 55% to 64.55%, and for second period questions, it increased from 48% to 52.22%. The study confirmed the general trend of radiology science students utilizing electronic devices for learning and obtaining information through the internet. However, conversational artificial intelligence service programs in the field of radiation science face challenges related to accuracy and reliability, and providing perfect solutions remains difficult, highlighting the need for continuous development and improvement.

• Fashion & Textile Research Journal
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• v.24 no.2
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• pp.229-240
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• 2022

This study explores the effect of anthropomorphism on fashion chatbot reliability, mediated by perceived intelligence and cognitive evaluation. The moderating effects of individuals' need for human interaction between chatbot anthropomorphism and perceived intelligence, cognitive evaluation, and chatbot reliability are also explored. Participants, who were recruited through the online research firm, responded to questions after watching a video clip showing a conversation with a fashion chatbot on a mobile screen. The data were collected through Mturk, a crowdsourcing platform with an online research panel. All responses (N = 212) were analyzed using SPSS 26.0 for the descriptive statistics, frequency analysis, reliability analysis, exploratory factor analysis, and PROCESS procedure. The results demonstrate that chatbot anthropomorphism increases chatbot reliability, and this is mediated by chatbot intelligence. Although chatbot anthropomorphism increases cognitive evaluation, the effect of cognitive evaluation on chatbot reliability is not significant; thereby, the effect of chatbot anthropomorphism on chatbot reliability is not mediated by the cognitive evaluation. The direct effect of anthropomorphism on chatbot reliability is also moderated by individuals' need for human interaction. For participants with a high need for human interaction, chatbot anthropomorphism increases chatbot reliability; however, anthropomorphism does not significantly affect chatbot reliability for participants with a low need for human interaction. The study's findings contribute to expanding the literature on consumers' new technology acceptance by testing the antecedents affecting service reliability.