• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.211-229
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• 2022

In this study, we aimed to define the effects of anthropomorphism and conversational relevance of chatbots on user experience. In specific, the chatbot designed for this study was an online shopping assistant that recommends items for consumers. Levels of anthropomorphism was manipulated by the name, profile picture, word choices, and emojis, while conversational relevance was adjusted by the depth and accuracy of the recommendation. Three categories of user experience were measured: psychological distance, usability, and purchase intentions. The results implied a significant main effect of conversational relevance on all variables for the high anthropomorphized conditions, while all but psychological distance was significant for low anthropomorphized conditions. Although there was no significant main effect of anthropomorphism observed for the variables, the main effect of anthropomorphism on responsibility was marginally significant for a specific item. The results of this study may function as a guidance for future studies regarding usage of chatbots within a marketing setting.

• Journal of Information Technology Applications and Management
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• v.30 no.4
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• pp.11-28
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• 2023

This paper proposes a method of integrating ChatGPT with traditional chatbot systems to enhance conversational artificial intelligence(AI) and create more efficient conversational systems. Traditional chatbot systems are primarily based on classification models and are limited to intent classification and simple response generation. In contrast, ChatGPT is a state-of-the-art AI technology for natural language generation, which can generate more natural and fluent conversations. In this paper, we analyze the business service areas that can be integrated with ChatGPT and traditional chatbots, and present methods for conducting conversational scenarios through case studies of service types. Additionally, we suggest ways to integrate ChatGPT with traditional chatbot systems for intent recognition, conversation flow control, and response generation. We provide a practical implementation example of how to integrate ChatGPT with traditional chatbots, making it easier to understand and build integration methods and actively utilize ChatGPT with existing chatbots.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.85-110
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• 2018

A chatbot is an interactive assistant that utilizes many communication modes: voice, images, video, or text. It is an artificial intelligence-based application that responds to users' needs or solves problems during user-friendly conversation. However, the current version of the chatbot is focused on understanding and performing tasks requested by the user; its ability to generate personalized conversation suitable for relationship-building is limited. Recognizing the need to build a relationship and making suitable conversation is more important for social chatbots who require social skills similar to those of problem-solving chatbots like the intelligent personal assistant. The purpose of this study is to propose a text analysis method that evaluates relationships between chatbots and users based on content input by the user and adapted to the communication situation, enabling the chatbot to conduct suitable conversations. To evaluate the performance of this method, we examined learning and verified the results using actual SNS conversation records. The results of the analysis will aid in implementation of the social chatbot, as this method yields excellent results even when the private profile information of the user is excluded for privacy reasons.

• Journal of the korean academy of Pediatric Dentistry
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• v.51 no.3
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• pp.299-309
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• 2024

This study aimed to assess the competency of artificial intelligence (AI) in pediatric dentistry and compare it with that of dentists. We used open-source data obtained from the Korea Health Personnel Licensing Examination Institute. A total of 32 item multiple-choice pediatric dentistry exam questions were included. Two AI-based chatbots (ChatGPT 3.5 and Gemini) were evaluated. Each chatbot received the same questions seven times in separate chat sessions initiated on April 25, 2024. The accuracy was assessed by measuring the percentage of correct answers, and consistency was evaluated using Cronbach's alpha coefficient. Both ChatGPT 3.5 and Gemini demonstrated similar accuracy, with no significant differences observed between them. However, neither chatbot achieved the minimum passing score set by the Pediatric Dentistry National Examination. However, both chatbots exhibited acceptable consistency in their responses. Within the limits of this study, both AI-based chatbots did not sufficiently answer the pediatric dentistry exam questions. This finding suggests that pediatric dentists should be aware of the advantages and limitations of this new tool and effectively utilize it to promote patient health.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.17-36
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• 2018

In this study, we developed a chatbot (Dialogue agent) using small Q & A data and evaluated its performance. The chatbot developed in this study was developed in the form of an FAQ chatbot that responds promptly to customer inquiries. The development of chatbot was conducted in three stages : 1. Analysis and planning, 2. Content creation, 3. API and messenger interworking. During the analysis and planning phase, we gathered and analyzed the question data of the customers and extracted the topics and details of the customers' questions. In the content creation stage, we created scenarios for each topic and sub-items, and then filled out specific answers in consultation with business owners. API and messenger interworking is KakaoTalk. The performance of the chatbot was measured by the quantitative indicators such as the accuracy that the chatbot grasped the inquiry of the customer and correctly answered, and then the questionnaire survey was conducted on the chatbot users. As a result of the survey, it was found that the chatbot not only provided useful information to the users but positively influenced the image of the pension. This study shows that it is possible to develop chatbots by using easily obtainable data and commercial API regardless of the size of business. It also implies that we have verified the validity of the development process by verifying the performance of developed chatbots as well as an explicit process of developing FAQ chatbots.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.755-765
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• 2019

Purpose: Chatbots are widely diffusing across various industries to substitute human manpower in the industry. However as researchers only develop technology that is applied to chatbot, the diffusion is slow in progress. The purpose of this study is to propose useful implications to accelerate diffusion of chatbots across industries by analyzing the perception of customers. To achieve the research purpose this study analyzes causal effect relationship between characteristics of chatbot character, service quality, individual difference, and intention to use chatbot. Methods: This study developed a survey that contains various questionnaires for each construct based on literature review. Data collected through survey was tested for convergent validity and discriminant validity and further analyzed the relationship using PLS-SEM method to verify hypotheses. Results: Trustworthiness of the chatbot character, ease of use, application design, responsiveness, customization, assurance, inertia, and previous experience have significant influence on forming user satisfaction, consumer trust, and intention to use. The others, likability, appropriateness, technology anxiety, and need for interaction were not significant in this research. Conclusion: Although the constructs of the research model was significant in previous literatures, some do not have significant effect on intention to use chatbots. Based on the results, chatbot managers will be able to develop chatbot systems which are more appealing to users and more academic researchers will focus on analyzing user perception and intention.

• Child Health Nursing Research
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• v.28 no.4
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• pp.291-298
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• 2022

Purpose: This study aimed to identify students' awareness of the use of a chatbot (A-uC), a type of artificial intelligence technology, for violence prevention among elementary school students. Methods: The participants comprised 215 students in the fourth to sixth grades in Chuncheon, South Korea, and data were collected via a self-reported questionnaire. Results: The mean A-uC score was 3.43±0.83 out of 5 points. The mean scores for the 4 sub-dimensions of the A-uC tool were 3.48±0.80 for perceived value, 3.44±0.98 for perceived usefulness, 3.63±0.92 for perceived ease of use, and 3.15±1.07 for intention to use. Significant differences were observed in A-uC scores (F=59.26, p<.001) according to the need for the use of chatbots in violence prevention education. The relationships between intention to use and the other A-uC sub-dimensions showed significant correlations with perceived value (r=.85, p<.001), perceived usefulness (r=.76, p<.001), and perceived ease of use (r=.64, p<.001). Conclusion: The results of this study suggest that chatbots can be used in violence prevention education for elementary school students.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.2
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• pp.254-268
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• 2024

Human agents are increasingly being replaced by chatbots. However, like humans, chatbots can also make mistakes in service delivery by failing to provide accurate answers to customer questions while research on service recovery has been highly focused on human employees. Recognizing the necessity of research on effective chatbot service recovery strategies, this study investigated the relationships among service recovery messages (courteous apology vs. humorous apology), perceived sincerity, recovery satisfaction, and continuous usage intention. An online experiment was conducted with the participants randomly assigned to one of two experimental conditions (courteous apology vs. humorous apology). After using the chatbot developed for this study, the participants completed a questionnaire. The analysis results revealed that, in comparison to the humorous apology, the courteous apology had a higher positive predictive effect on perceived sincerity, Furthermore, perceived sincerity and recovery satisfaction sequentially mediated the relationship between the chatbot's courteous apology and continuous usage intention. In conclusion, this study demonstrates that the courteous apology was a more effective approach as a chatbot service recovery strategy. This study offers insights into crafting recovery service messages for chatbots.

• The Journal of Bigdata
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• v.3 no.2
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• pp.79-85
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• 2018

As the utilization of chatbots grows and the AI market grows, many companies are interested. And everybody is spurring growth by offering chatbot build services so that they can create chatbots. This makes chatbots easier to service on the messenger platform, which is changing the existing application market. In this paper, we present a methodology for designing and implementing existing DB-based applications as instant messenger platform-based applications, and summarize what to consider in actual implementation to provide an optimal system structure. According to this methodology, we design and implement a chatbot that serves as an teaching advisor who provides information to the students in the curriculum. The implemented application objectively visualizes the user's desired information from the user's point of view and delivers it through the interactive interface quickly and intuitively. By implementing these services and real service, it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. Enterprise legacy application will take chatbot technology as one of important digital transformation initiative.

• 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.