• Asia Marketing Journal
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• v.25 no.3
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• pp.99-110
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• 2023

Chatbot services have become an essential communication tool for interacting with consumers in e-commerce. To understand consumer behavior in the context of chatbot services, we apply the Theory of Planned Behavior (TPB) to analyze continuance intention to use and additional predictors to explain behavioral intention. An analysis of data collected from 300 digital shopping users who had experienced chatbot services revealed that an extended TPB model holds for the continuous use of chatbot services, driven by both interaction and information quality. Accordingly, these ndings provide a better understanding of consumer behavior toward chatbot services and valuable insights into digital customer relationship management.

• International Journal of Contents
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• v.16 no.4
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• pp.1-15
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• 2020

This study examined the impact of chatbot service quality (process quality, outcome quality, and servicescape quality) on user satisfaction and reliability by identifying the relationships between user satisfaction, reliability, immersion, and the paths of three variables influencing reuse intention. The survey was conducted of Korean users in their teens and 70s who had experience using chatbot services. A total of 218 convenience samples were extracted and the data analyzed. By the IS success and SERVQUAL model, the results of structural equation modeling revealed that the chatbot service quality did not affect user satisfaction and reliability. However, user satisfaction and reliability of the chatbot services were shown to lead to reuse intention, and user satisfaction was shown to affect immersion and immersion in reliability. The results showed that satisfaction, reliability, and immersion in the chatbot services were important factors in the chatbot reuse intention. Through the satisfaction and reliability gained through the service, the users wanted to reuse the chatbot services, especially the chatbot services that gained reliability, which will have a greater impact on reuse intention. We can use these results as marketing information to attract loyal customers by identifying the reuse intention of the chatbot service users.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.167-176
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• 2024

Chatbot services are used in various fields in connection with AI services. Security research on AI is also in its infancy, but research on practical security in the service implementation stage using it is more insufficient. This paper analyzes the security requirements for chatbot services linked to AI services. First, the paper analyzes the recently published papers and articles on AI security. A general implementation model is established by investigating chatbot services provided in the market. The implementation model includes five components including a chatbot management system and an AI engine Based on the established model, the protection assets and threats specialized in Chatbot services are summarized. Threats are organized around threats specialized in chatbot services through a survey of chatbot service managers in operation. Ten major threats were drawn. It derived the necessary security areas to cope with the organized threats and analyzed the necessary security requirements for each area. This will be used as a security evaluation criterion in the process of reviewing and improving the security level of chatbot service.

• 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.

• Journal of Korea Artificial Intelligence Association
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• v.2 no.1
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• pp.15-24
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• 2024

This study is about the effect of chatbot service quality on customer satisfaction and continuous use intention. Data collection was conducted for 13 days from October 23 to November 5, 2023, and a survey was conducted on customers who have used chatbot services. A total of 572 questionnaires were targeted, of which 545 valid data were used for analysis, excluding those that responded insincerely or did not meet the purpose of the study. The analysis results of this study are as follows: First, chatbot service quality partially had a significant effect on satisfaction. Second, customer satisfaction had a significant effect on continuous use intention. Therefore, in order to have a positive impact on continuous use intention, it is necessary to focus on marketing strategies related to chatbot service quality. Also, research focusing on data analysis and performance evaluation is crucial for enhancing chatbot services, necessitating studies that address real-time changes. Through sophisticated data analysis and variable measurement, chatbot services can be effectively improved, leading to enhanced customer satisfaction.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.14-17
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• 2022

Due to the development of IT technology and the on-going Coronavirus disease, non-face-to-face services have been activated. To overcome the inconvenience of non-face-to-face service, service providers have adopted chatbots as a way to feel like a human being. As the increasing chatbot services, chatbot builders have emerged, which can help non-developers to build them. Although its popularity has increased, its performance evaluation has not been conducted on such chatbot builders. In this paper, we implement a prototype chatbot that classifies hospital departments in the medical field using Dialogflow and Rasa, which are popular chatbot builders. By measuring the accuracy of the chatbot's classification of medical subjects, we evaluated the level of accuracy that the most used chatbot builder can have when they are used to build a chatbot service. The simulation results showed that Dialogflow had 87%, 65%, and 60%, and Rasa did 64%, 70%, and 63% in surgery dermatology, and otolaryngology, respectively.

• 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 the Korean Society for information Management
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• v.37 no.4
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• pp.151-179
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• 2020

This study explores the potential of using a library chatbot to improve the non-face-to-face digital reference services for academic library users by designing and implementing a library chatbot. Through data analysis, user needs and library services were analyzed, and a scenario was designed by selecting an appropriate development method. For user-friendly interaction, the personality of the chatbot and user interface was designed to evaluate its usability. In addition, the accuracy was verified through the response accuracy evaluation and performance evaluation of the chatbot, and the effectiveness of the chatbot was evaluated through a user satisfaction survey. In order to manage the operation and maintain service quality, the chatbot is improved by monitoring user-chatbot conversations and reflecting user feedback. Based on these findings, recommendations for designing and implementing a library chatbot were made to help improve library reference services.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1347-1356
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• 2017

Artificial intelligence-based services are expanding into a new industrial revolution. There is artificial intelligence technology applied in real life due to the development of big data and deep learning related technology. And data analysis and intelligent assistant services that integrate information from various fields have also been commercialized. Chatbot with interactive artificial intelligence provide shopping, news or information. Chatbot service, which has begun to be adopted by some public institutions, is now just a first step in the steps. This study summarizes the services and technical analysis of chatbot. and the direction of public administration service chatbot was presented.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.2
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• pp.183-203
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• 2023

This study was conducted to analyze the characteristics of the artificial intelligence chatbot service of the library and compare the usability of the chatbot service applied to the library, and to propose a plan to improve the usability of the artificial intelligence chatbot service in the library. In order to achieve this research purpose, usability comparison factors were extracted through previous studies on the usability evaluation of artificial intelligence chatbot services, and based on case studies, artificial intelligence chatbot services applied to libraries were classified into their own website-based and SNS-based chatbot services according to the platform. Experiments, questionnaires, and interviews were conducted to evaluate the usability of website-based and SNS-based chatbot services applied to the library. Based on the results of the usability evaluation, implications and improvement plans for the artificial intelligence chatbot service of the library were derived.