• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.57-76
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• 2023

This study analyzes the factors and effects on the users' intention to switch from contact center-oriented to AI chatbot-oriented customer services by combining Push-Pull-Mooring Model and provides insights for companies considering the adoption of AI chatbots. To test the model, we surveyed users with experience using chatbots at least once across different age groups. Finally, we analyzed 176 cases for the analysis using IBM SPSS Statistics and SmartPLS 4.0. The results of hypotheses testing rejected the hypotheses for variables of inconsistent quality and low availability of push factors and low switching cost of mooring factor while accepting the hypotheses for the tardy response of push factors and all pull factors. Therefore, these findings provide important implications for researchers and practitioners who wish to conduct research or adopt AI chatbots. In conclusion, users do not feel inconvenienced by the contact center-oriented service but also perceive high trust and convenience with AI chatbot-oriented service. However, despite low switching costs, users consider chatbots a complementary tool rather than an alternative. So, companies adopting AI chatbots should consider what features the users expect from AI chatbots and facilitate these features when implementing AI chatbots.

• 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 Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.17-25
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• 2020

Based on the successful use of chatbot technology, this study examined what business values each company is creating. The chatbot service contributes to improving the productivity of the company by helping to answer or respond to the questions of employees inside the company or customers. And in the field of education, Instead of instructor, AI technology responds the questions and feedback of the students to reduce the work of the instructor. In the field of commerce, offline stores provide convenient and new purchasing experiences to customers by providing product purchasing services through artificial intelligence speakers and personalization service. Although chatbot service is creating business value in some business cases, it is still limited to the process of a specific company, and the spread rate is still slowing because the service scope, convenience, and usefulness are not greater than expected. Therefore, some chatbot development service providers is providing an integrated development platform to improve usability, Chatbots have the features and advantages of providing convenience instead of answering human questions. However, there is a disadvantage that the level of communication can be lowered by reducing various human subjective views and giving mainly objective answers. Through this study, we will discuss the characteristics, advantages and disadvantages of chatbot services by comparing them.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.303-308
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• 2022

A chatbot is a responsive chatting program that can communicate with people through text or voice. 'Siri' and 'Bixby' installed in smartphones are also representative artificial intelligences that use the chatbot system. With the rapid development of chatbots, users in various fields have also begun to pay attention to the food service industry. As machine learning technology developed, it became possible to use more flexible conversations, and it soon expanded to the realm of education. Userㄴs interact through conversations with chatbots, and active interactions stimulate users' desires and at the same time have a positive effect on learning motivation. Recommendation system programs using chatbots not only recommend products according to users' preferences, but also provide various additional information. This study planned a program that combined the chatbot system and tourism service. The chatbot curator will develop into a form of inducing interest and curiosity to users through learning, and then facilitating the desire for tourism. The purpose of this study is to lay the foundation for a chatbot curator based on previous studies.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.843-848
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• 2022

A chatbot is a responsive chatting program that can communicate with people through text or voice. 'Siri' and 'Bixby' installed in smartphones are also representative artificial intelligences that use the chatbot system. With the rapid development of chatbots, users in various fields have also begun to pay attention to the food service industry. As machine learning technology developed, it became possible to use more flexible conversations, and it soon expanded to the realm of education. Userㄴs interact through conversations with chatbots, and active interactions stimulate users' desires and at the same time have a positive effect on learning motivation. Recommendation system programs using chatbots not only recommend products according to users' preferences, but also provide various additional information. This study planned a program that combined the chatbot system and tourism service. The chatbot curator will develop into a form of inducing interest and curiosity to users through learning, and then facilitating the desire for tourism. The purpose of this study is to lay the foundation for a chatbot curator based on previous studies.

• Knowledge Management Research
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• v.20 no.4
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• pp.99-118
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• 2019

Online financial counseling services are increasingly expanding with the rise of artificial intelligence-based chatbots. It is very important to examine the effects of emoticons noted as alternatives for communicating emotions in online communication between consumers and companies. In this paper, we examine how the use of emoticons affects the consumer's response and investigate the moderating roles of type of counseling agents (human vs. chatbot) and the consumer's subjective financial knowledge. The results show that the use of emoticon in the conversation brings a positive effect on the consumer's intention to use of online chat counseling service. When participants had relatively low subjective financial knowledge, they had higher intention to use online chat counseling services with emoticons only when the agent type was chatbot. When the type of counseling agent was human, this positive effect of the emoticon did not occur. On the other hand, when participants had relatively high subjective financial knowledge, they had higher intention to use online chat counseling service with emoticons only when the agent type was human. This study contributes to providing practical implications to build online chat counseling service using chatbot in the financial industry by studying users' intention depending on the type of agents and the level of their subjective knowledge.

• Journal of Service Research and Studies
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• v.7 no.3
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• pp.37-55
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• 2017

Recently, many business organizations have been increasingly expanding the utilization of the intelligent chatbot services for effective customer relation management. The purpose of this study is to empirically investigate the factors which affect the use of the intelligent chatbot services. Above all, the research model and the hypotheses were derived through reviewing the major relevant theories such as UX(user experience) theory(Honeycomb model), TRA(theory of reasoned action), TAM(technology acceptance model) and ETAM(extended TAM). And then, structural equation analyses using SmartPLS 3.0 for 233 valid questionnaires replies collected through the field survey was performed to test the hypotheses. Theoretically, this study can contribute to providing the conceptual framework with regard to enhancing the use of intelligent chatbot services. And practically, this study sheds new light on suggesting the guidelines to designing the UX(user experience) of the intelligent chatbot services.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.106-116
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• 2024

Purpose: This paper conducts IoT and CCTV-based safety monitoring to analyze accidents and potential risks occurring at construction sites, and detect and analyze risks such as falls and collisions or abnormalities and to establish a system for early warning using devices like a walkie-talkie and chatbot service. Method: A safety management service model is presented through smart construction technology case studies at the construction site and review a relevant literature analysis. Result: According to 'Construction Accident Statistics,' in 2021, there were 26,888 casualties in the construction industry, accounting for 26.3% of all reported accidents. Fatalities in construction-related accidents amounted to 417 individuals, representing 50.5% of all industrial accident-related deaths. This study suggests implementing AI chatbot services for construction site safety management utilizing IoT-based health monitoring technologies in smart construction practices. Construction sites where stakeholders such as workers participate were demonstrated by implementing an artificial intelligence chatbot system by selecting major risk areas within the workplace, such as scaffolding processes, openings, and access to hazardous machinery. Conclusion: The possibility of commercialization was confirmed by receiving more than 90 points in the satisfaction survey of participating workers regarding the empirical results of the artificial intelligence chatbot service at construction sites.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.1-7
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• 2023

Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.