• 유통과학연구
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• 제22권2호
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• pp.103-113
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• 2024

Purpose: With the popularity of artificial intelligence (AI) in the service industry and occurrence ofservice failures in AI-based services, understanding human-robot interaction issues in service failure situations is especially important. Some issues which deserve further empirical investigation are whether consumers can develop the same tolerance for chatbots after service failure as they have for human agents, and the relationship between agent type and tolerance is mediated by the mechanisms of perceived warmth and perceived competence. Research Design, Data, and Methodology: This research experimentally collected and analyzed data from 119 university students who had experienced chatbots service failures. Differences in tolerance towards human agents and chatbots after experiencing service failures were explored, with a further examination of the mediating pathways between this relationship via perceived warmth and perceived competence. Results: Consumers are more tolerant ofservice failure with chatbots compared to service failure with human agents. Significant mediation of the relationship between service agent and service failure tolerance by perceived competence, while perceived warmth has no significant mediating effect. Conclusions: This research enhances our understanding of AI-assisted services, human-computer interaction, improves the service functionality of existing smart devices, and deepens the understanding of the relationship between consumer responses and behaviors.

• 산경연구논집
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• 제10권7호
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• pp.39-48
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• 2019

Purpose - The purpose of this study was to explore the impact of chatbots' innovation attributes on the innovation acceptance for consumers who have used chatbots to purchase fashion products that account for a large share of transactions in mobile shopping. Research design, data, and methodology - Data were collected from Korean consumers aged 20 to 49 who had experience using chatbots when purchasing fashion-related products via mobile circumstances. After a pilot survey of 31 customers, pre-questionnaire was revised for the final test, and the final questionnaire was distributed to 1,500 subjects. Out of these, 244 were retrieved. After excluding 48 inappropriate responses, 196 were used for statistical analysis. Frequency analysis, exploratory factor analysis, one-way ANOVA, regression analysis and independent t-test using SPSS 23.0 were employed for data analyses. Results - First, four factors of chatbots' attributes were extracted: relative advantages and compatibility, complexity, sensibility, and diversity. Second, two factors were extracted for fashion leadership: fashion opinion leadership and fashion innovativeness. Two groups based on the fashion leadership were identified: active innovation adopters and passive innovation adopters. Third, relative advantages and compatibility, diversity, sensibility of innovation attributes were found to have effects on the innovation acceptance in order. Fourth, significant differences were found in sensibility of innovation attributes and innovation acceptance in groups by marital status and age. The married in their 30s and 40s perceived sensibility as a more important attribute of chatbots than the unmarried in their twenties. Among the groups of different income levels, meaningful differences were found in diversity of innovation attributes and innovation acceptance. Fifth, there were significant differences found in relative advantages and compatibility, sensibility of innovation attributes, and acceptance of Innovation among the groups by fashion leadership. Active innovation adopters were found to be more aware of the importance of relative advantages and compatibility, and sensibility of innovation attributes, and innovation acceptance. Conclusions - The present study provides chatbots' marketing strategies for fashion items need to be modified by demographic characteristics and fashion leadership. Particularly, fashion leadership was found to be an important factor in determining the perception of innovation attribute as well as innovation acceptance.

• 인터넷정보학회논문지
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• 제24권4호
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• pp.37-45
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• 2023

Adaptive has gained significant attention in Education Technology (EdTech), with personalized learning experiences becoming increasingly important. Next-generation chatbots, including models like ChatGPT, are emerging in the field of education. These advanced tools show great potential for delivering personalized and adaptive learning experiences. This paper reviews previous research on adaptive learning and the role of chatbots in education. Based on this, the paper explores current and future chatbot technologies to propose a framework for using ChatGPT or similar chatbots in adaptive learning. The framework includes personalized design, targeted resources and feedback, multi-turn dialogue models, reinforcement learning, and fine-tuning. The proposed framework also considers learning attributes such as age, gender, cognitive ability, prior knowledge, pacing, level of questions, interaction strategies, and learner control. However, the proposed framework has yet to be evaluated for its usability or effectiveness in practice, and the applicability of the framework may vary depending on the specific field of study. Through proposing this framework, we hope to encourage learners to more actively leverage current technologies, and likewise, inspire educators to integrate these technologies more proactively into their curricula. Future research should evaluate the proposed framework through actual implementation and explore how it can be adapted to different domains of study to provide a more comprehensive understanding of its potential applications in adaptive learning.

• 디지털융복합연구
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• 제16권2호
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• pp.1-7
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• 2018

본 연구는 챗봇의 활용이 한국 대학생의 영어 어휘 학습에 미치는 영향을 조사한 것으로, 챗봇과의 채팅을 통해 실험 참가자의 영어 어휘 능력이 실제 상승하는지 여부와 영어 어휘 학습에 대한 인식이 어떻게 변하는지 알아보는 데 그 목적이 있다. 47명의 국내 대학생을 실험그룹과 통제그룹으로 나누어 총 8주 동안 실험을 진행하였고, 챗봇 활용의 효과를 파악하기 위해 실험 시작 전과 종료 후 사전 사후 어휘 평가를 실시하였으며, 사전 사후 설문조사를 통해 챗봇을 활용한 어휘 학습에 대한 참가자의 인식 변화를 조사하였다. 본 연구의 주요 결과 및 시사점은 다음과 같다. 사전 사후 어휘 평가 결과, 참가자의 어휘 능력은 실험 전에 비해 실험 종료 후 상승한 것으로 나타났고, 사전 사후 설문 결과, 챗봇의 활용은 참가자의 영어 어휘 학습에 대한 태도를 긍정적으로 변화시키는 데 중요한 역할을 하는 것으로 파악되었다. 테크놀로지의 발달과 함께 최근 영어 교육에 있어 챗봇의 활용이 증가하는데 비해 그에 대한 실증적 연구가 부족하다는 점을 고려해 볼 때, 본 연구가 갖는 시사점이 크다고 할 수 있다.

• 비교문화연구
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• 제48권
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• pp.223-252
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• 2017

본 연구의 목적은 서로 다른 두 유형의 챗봇(음성기반 챗봇 및 문자기반 챗봇)이 한국 EFL 학습자의 말하기 능력 및 학습자 인식에 미치는 영향을 파악하는데 있다. 실험 참가자는 총 80명으로, 한국에 있는 한 대학교의 신입생들이었으며, 모두 교양 영어 말하기 수업을 듣는 학생들이었다. 참가자들은 무작위 하게 두 실험집단으로 나뉘어 16주 동안 서로 다른 두 유형의 챗봇과 10번의 채팅에 참여하였다. 실험 전후 참가자의 말하기 능력에 변화가 있는지를 알아보기 위하여 사전사후 말하기 시험을 진행하였고, 챗봇을 이용한 영어학습에 대해 인식변화가 있는지를 살펴보기 위해 사전사후 설문조사를 실시하였다. 말하기시험결과, 챗봇을 이용한 한국 EFL 학습자들의 의사소통능력은 유의미하게 향상되었고, 그 중 문자기반 챗봇이 의사소통능력 향상에 더욱 도움이 되는 것으로 나타났다. 설문조사결과, 챗봇기반 영어학습에 대한 학습자들의 인식은 긍정적으로 변화하였고, 그 중 음성기반 챗봇에 대한 인식이 좀 더 호의적으로 바뀐 것으로 조사됐다. 본 연구는 EFL 상황에서 챗봇기반 영어학습에 대한 새로운 가능성을 모색하고, 효과적인 챗봇활용을 위한 제언을 도출하고 있다.

• 산경연구논집
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• 제11권12호
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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.

• 벤처혁신연구
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• 제7권3호
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• pp.101-121
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• 2024

전자 상거래 플랫폼에서 챗봇의 적용이 점점 더 널리 퍼지고 있다. 인공지능 기술의 급속한 발전과 함께, 이전 연구는 주로 챗봇 자체에서 발생하는 서비스 실패에 초점을 맞추었다. 그러나 판매자가 통제할 수 있는 서비스 실패를 챗봇이 처리하는 상황에 대한 연구는 제한적이다. 본 논문은 총 546명의 참가자를 대상으로 두 가지 실험을 통해 온라인 설문 조사를 실시했다. 연구 결과, 서비스 실패가 발생했을 때, 챗봇이 제공하는 서비스가 인간 고객 서비스 대표보다 더 많은 부정적인 구전을 유발하며, 재구매 의도도 낮아진다는 것을 나타냈다. 이는 고객들이 더 높은 수준의 분노를 경험하기 때문이다. 그러나 고객이 서비스 실패를 판매자가 통제할 수 없는 것으로 인식할 때, 고객 분노를 통해 고객 서비스 제공 유형이 부정적 구전에 미치는 영향이 약화되고, 소비자들이 그 서비스 실패를 판매자가 통제할 수 있는 것으로 인식할 때 서비스 제공 유형이 부정적 구전에 미치는 영향은 강화된다. 본 연구는 온라인 소매 기업이 지능형 고객 서비스를 적용함과 동시에 서비스 실패의 추가 악화를 방지하기 위한 이론적 기여를 제공한다.

• 반도체디스플레이기술학회지
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• 제18권3호
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• pp.93-99
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• 2019

It is a wine recommendation application service designed for people who sometimes drink wine but lack information and have no place to recommend. This study is to develop UI display design method of wine recommendation service using chatbot. The research method was a case study on Korean wine market, a case study on artificial intelligence market, SWOT analysis of wine-related chatbots, and a competitor analysis of related industries. In addition, surveys and in-depth interviews examined the level of interest and understanding of chatbots, and what kind of chatbots they had encountered and what requirements and goals they faced. After grasping the needs and requirements of users, we created a service concept sheet according to them and produced an application UI design that users can use most easily. Therefore, this study is meaningful in that it proposes a UI design that can search wine information more sophisticated and convenient than face-to-face communication through artificial intelligence service called chatbot and recommend wines that match the taste.

• 한국컴퓨터정보학회논문지
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• 제24권7호
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• pp.9-17
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• 2019

As the artificial intelligence technology has developed recently, researches on chatbots that provide information and contents desired by users through an interactive interface have become active. Since chatbots require a variety of natural language processing technology and domain knowledge including typos and slang, it is currently limited to develop chatbots that can carry on daily conversations in a general-purpose domain. In this study, we propose an artificial intelligence chatbot that can provide real-time public traffic information and route information. The proposed chatbot has an advantage that it can understand the intention and requirements of the user through the conversation on the messenger platform without map application.

• International Journal of Advanced Culture Technology
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• 제10권1호
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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.