• Journal of Information Technology Services
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• v.19 no.4
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• pp.31-47
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• 2020

Recently, as the COVID-19 has spread and prolonged worldwide, the 'Untact' society is becoming routinized, and various smart technologies are leading to the spread of the 'Ontact' culture. This is because the desire of consumers to purchase a product and use the service has increased while minimizing the direct contact. In order to quickly respond to this circumstance, the percentage of the companies which are adopting Chatbot in various fields such as orders, delivery, and inquiries is increasing and they are getting a positive result. However as the demand for building Chatbot increases dramatically, there are many confusions among the companies which want to introduce Chatbot to their system, due to the lack of professional technicians and difficulties in understanding AI technologies and how to build them effectively. I believe that in the post COVID-19 era, much more companies will adopt Chatbot, and this will intensify the problem. The purpose of this study was to derive the needs for a guide on the method of buiilding a Chatbot through considering the prior research on Chatbot and analysis of the recent surge in the use of Chatbot services related to COVID-19. There are implications to presenting 5 phases of universal Chatbot implementation methodology using the platform to the stakeholders who want to introduce Chatbot to their customer so that they can understand and build Chatbot more easily and use AI Chatbot actively in response to the POST COVID-19 era.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.215-226
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• 2020

Chatbot is emerging as an important interface window for business. This change is due to the continued development of chatbot-related research from NLP to NLU and NLG. However, the reality is that the methodological study of drawing domain knowledge and developing it into a user-friendly interactive interface is weak in the process of developing chatbot. In this paper, in order to present the process criteria of chatbot development, we applied it to the actual project based on the methodology presented in the previous paper and improved the development methodology. In conclusion, the productivity of the test phase, which is the most important step, was improved by 33.3%, and the number of iterations was reduced to 37.5%. Based on these results, the "3 Phase and 17 Tasks Development Methodology" was presented, which is expected to dramatically improve the trial and error of the chatbot development.

• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.29-38
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• 2020

Purpose: The purpose of this study is to empirically analyze the effect of chatbot service quality, chatbot trust, and chatbot satisfaction on chatbot reuse intention and store reuse intention. Research design, data, and methodology: We reviewed the literature on domestic and international chatbots, established hypotheses, and analyzed them. We empirically analyzed the process model in which chatbot service quality (interaction quality, information quality) has a positive effect on chatbot trust and chatbot satisfaction, and that chatbot trust and satisfaction positively affect chatbot reuse intention and store reuse intention. A survey was conducted on 212 people who had used shopping mall chatbots and financial service chatbots after demonstrating the shopping mall chatbot video. Structural equation modeling was conducted by using AMOS 24.0 to test the proposed relationships. Results: As a result of the empirical analysis, the effects of interaction quality on chatbot trust and information quality on chatbot satisfaction were not supported, but the rest of the hypotheses were statistically significant. It was found that the information quality of chatbot service had a positive effect on chatbot trust, but did not significantly affect chatbot satisfaction. In addition, the interaction quality of the chatbot positively affects the satisfaction of the chatbot, but it does not significantly affect the trust of the chatbot. Chatbot trust was found to have a positive effect on chatbot satisfaction. Chatbot trust and chatbot satisfaction were found to have a positive influence on the intention to reuse the chatbot. And, chatbot trust and chatbot satisfaction were found to have a positive influence on store reuse intention. Conclusions: The findings of this study offer significant theoretical and managerial contributions in the context of chatbot. Chatbots should enhance customer contact quality management from the perspective of total customer experience management rather than partial function. When providing a chatbot service, it is more desirable to give priority to providing accurate information to increase trust, and at the same time to improve customer satisfaction by increasing the quality of interaction. And in order to increase the competitive advantage of companies, the purpose of introducing chatbots should be clarified and approached strategically.

• The Journal of Information Systems
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• v.31 no.4
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• pp.123-143
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• 2022

Purpose The purpose of this study was to investigate the experience cues of chatbot services provided to existing customers familiar with the e-commerce environment, and to examine the effect of chatbot service's experience cues on customer experience and chatbot trust. Design/methodology/approach This study was conducted on consumers who experienced chatbot services in an e-commerce environment, the final 299 copies of valid data were obtained, and the research hypothesis was verified using PLS as a structural equation model. Findings As a result of the analysis, it was found that functional cues that cause customer experiences using chatbot services had a positive effect on cognitive and emotional experiences, human cues had a positive effect on cognitive, emotional and relational experiences, and customer experiences had a positive effect on chatbot trust.

• The Journal of Industrial Distribution & Business
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• v.13 no.8
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• pp.29-50
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• 2022

Purpose - This study aims to investigate factors affecting Chatbot service acceptance attitude. For wide use of Chatbot service, firms need to find barriers or obstacles for customers, if any, not to use Chatbot service. Research design, data, and methodology - We apply value-based accept model to investigate the quality of Chatbot, to verify the meaning of service value of Chatbot and to find the relationship among variables. To test hypotheses, we conducted survey. We collected 300 questionnaires. SPSS version 2.0 is used. Regression analysis, moderating effect test is conducted. Results - 4 Qualities of Chatbot, Ease of use, Usefulness, Enjoyment, Interaction are affecting acceptance attitude, and 5 service values, only interaction does not affect emotion. Trust, Specialty, Necessity, Social, Emotion moderating Chatbot service to accepting attitude. Regarding moderating effects by personal characteristics and personal tendency, innovation resistance, innovativeness, and social effects are turned to have influence while regulatory focus, construal level does not have moderating force. Also, the auxiliary service like Chatbot service affects customers' evaluation on the main service quality. Conclusions - Service firms adopt Chatbot service for various purposes. The results imply that customers are generally recognize the merits of Chatbot, but there are some barriers such as innovation resistance characteristic especially uncomfortable.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• The Journal of Industrial Distribution & Business
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• v.10 no.3
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• pp.45-58
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• 2019

Purpose - The purpose of this study was to investigate the effects of the chatbot's characteristics (ease of use, social presence, playfulness, usefulness) on service value, customer satisfaction and reuse intention when consumers purchased fashion products in the mobile shopping environments. Research design, data, and methodology - Data were collected from Korean consumers from ages 20 to 59 who have experienced using chatbot in a mobile shopping for fashion products. After a pilot survey to 53 customers, the preliminary questionnaire was revised for the final test, and the final questionnaire was administered to 1500 customers. Out of these, 300 were collected. After deleting 48 incomplete ones, 252 questionnaires were used in the statistical analysis. Frequency analysis and exploratory factor analysis using SPSS 23.0 and confirmatory factor analysis and structure equation analysis using AMOS 18.0 were employed for data analyses. Results - First, four factors were extracted for the chatbot's characteristics: ease of use, social presence, playfulness and usefulness. Second, regarding the effect of chatbot's characteristics on service value when purchasing fashion products in the mobile shopping environment, ease of use, playfulness and usefulness of chatbot significantly affected service value. Social presence did not have significant effects on service value. Third, in terms of the effect of the chatbot's characteristics on customer satisfaction when purchasing fashion products in the mobile shopping environment, social presence, playfulness and usefulness of chatbot significantly had an effect on customer satisfaction. Ease of use did not have a significant effect on customer satisfaction. Fourth, service value of chatbot when purchasing fashion products in mobile shopping environment was found to have an effect on customer satisfaction with chatbot. Fifth, service value of chatbot on reuse intention when purchasing fashion products in the mobile shopping environment was found to have an effect on reuse intention of chatbot. Sixth, customer satisfaction with chatbot had a significant impact on the reuse intention of the chatbot when purchasing fashion products in the mobile shopping environment. Conclusions - The present study provide dimensions on the chatbot's characteristics and these may provide helpful data for further studies in this area and for marketers as well.

• 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 Earthquake Engineering Society of Korea
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• v.27 no.6
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• pp.331-337
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• 2023

Due to the aging of a building, 38.8% (about 2.82 million buildings) of the total buildings are old for more than 30 years after completion and are located in a blind spot for an inspection, except for buildings subject to regular legal inspection (about 3%). Such existing buildings require users to self-inspect themselves and make efforts to take preemptive risks. The scope of this study was defined as the general public's visual self-inspection of buildings and was limited to structural members that affect the structural stability of old buildings. This study categorized possible damage to reinforced concrete to check the structural safety of buildings and proposed a checklist to prevent the damage. A damage assessment methodology was presented during the inspection, and a self-inspection scenario was tested through a chatbot connection. It is believed that it can increase the accessibility and convenience of non-experts and induce equalized results when performing inspections, according to the chatbot guide.

• 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.