• 한국콘텐츠학회논문지
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• 제22권1호
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• pp.138-147
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• 2022

최근 챗봇이 다양한 분야에 적용되어 좋은 성과를 보이면서 쇼핑몰 상품 추천 서비스에도 챗봇을 활용하려는 시도가 많은 이커머스 플랫폼에서 진행되고 있다. 본 논문에서는 사용자와 시스템간의 대화와 패션 이미지 정보에 기반해 사용자가 원하는 패션을 추천하는 챗봇 대화시스템을 위해, 최근 자연어처리, 음성인식, 이미지 인식 등의 다양한 AI 분야에서 좋은 성능을 내고 있는 트랜스포머 모델에 대화 (텍스트) 와 패션 (이미지) 정보를 같이 사용하여 추천의 정확도를 높일 수 있도록 개선한 멀티모달 기반 개선된 트랜스포머 모델을 제안하며, 데이터 전처리(Data preprocessing) 및 학습 데이터 표현(Data Representation)에 대한 분석을 진행하여 데이터 개선을 통한 정확도 향상 방법도 제안한다. 제안 시스템은 추천 정확도는 0.6563 WKT(Weighted Kendall's tau)으로 기존 시스템의 0.3372 WKT를 0.3191 WKT 이상 크게 향상시켰다.

• 한국의류학회지
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• 제46권3호
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• pp.464-480
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• 2022

With the steady development of Artificial Intelligence (AI), online stores are adopting chatbot services as virtual shopping assistants. This study proposes the concept of para-social presence to explore the undiscovered role of fashion chatbots' emotional and relational characteristics on service acceptance. Based on the Technology Acceptance Model (TAM), this study investigates the effect of a chatbot's para-social presence on service acceptance intention through consumers' beliefs. The web-based experiment was conducted on adult consumers who experienced chatbot services in an online shopping situation. A total of 247 responses were analyzed using confirmatory factor analysis, structural equation modeling, and multi-group SEM by AMOS 21.0 and SPSS 23.0. The findings illustrate that the chatbot's intimacy positively influenced consumers' perceived enjoyment, while the chatbot's understanding had a significant effect on perceived usefulness and ease of use. The chatbot's involvement had a positive effect on all consumer beliefs. Moreover, perceived ease of use had a positive influence on usefulness. A greater level of perceived usefulness and enjoyment positively heightened consumers' service acceptance intention. This study also verifies the moderating role of a need for human interaction. Consumers with a high need for human interaction have a relatively low tendency to perceive chatbot services as useful.

• 패션비즈니스
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• 제27권3호
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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.

• 패션비즈니스
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• 제25권4호
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• pp.79-91
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• 2021

Currently, chatbot, a conversational platform based on artificial intelligence, is drawing attention as a new marketing channel. This study attempted to verify the effect of the anthropomorphism, message type, and media self-efficacy level on purchase intention. The experimental design of this study was a 2 (anthropomorphism level of shopping chatbot: low vs. high) × 2 (message type: factual vs. evaluative) × 2 (media self-efficacy: low vs. high) three-way mixed analysis of variance (ANOVA). This study conducted a survey by the convenience sampling method of 402 women in their 20s and 30s living in Seoul and the Gyeonggi area who were aware of chatbot services. For the final analysis, 388 questionnaires were used. Data were analyzed with the SPSS 23 program and three-way ANOVA. Simple main effects analysis was conducted. The results of this study were as follows. First, there were statistically significant differences in purchase intention according to anthropomorphism level, message type, and media self-efficacy. Second, message type and media self-efficacy showed statistically significant interaction effects on purchase intention. Lastly, anthropomorphism and the media self-efficacy level and the message type of the shopping chatbots showed significant three-way interaction effects on purchase intention.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2021년도 제33회 한글 및 한국어 정보처리 학술대회
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• pp.467-472
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• 2021

본 연구는 패션앱 후기글에 나타나는 구매자의 의견에 대한 '평가분석(Evaluation Analysis: EA)'을 수행하여, 이를 기반으로 상품의 검색 및 추천을 수행하는 의류 검색추천 챗봇을 개발하는 LICO 프로젝트의 언어데이터 구축의 일환으로 수행되었다. '평가분석 트리플(EAT)'과 '평가기반요청 쿼드러플(EARQ)'의 구성요소들에 대한 주석작업은, 도메인 특화된 단일형 핵심어휘와 다단어(MWE) 핵심패턴들을 FST 방식으로 구조화하는 DECO-LGG 언어자원에 기반하여 반자동 언어데이터 증강(SSP) 방식을 통해 진행되었다. 이 과정을 통해 20여만 건의 후기글 문서(230만 어절)로 구성된 EVAD 평가주석데이터셋이 생성되었다. 여성의류 도메인의 평가분석을 위한 '평가속성(ASPECT)' 성분으로 14가지 유형이 분류되었고, 각 '평가속성'에 연동된 '평가내용(VALUE)' 쌍으로 전체 35가지의 {ASPECT-VALUE} 카테고리가 분류되었다. 본 연구에서 구축된 EVAD 평가주석 데이터의 성능을 평가한 결과, F1-Score 0.91의 성능 평가를 획득하였으며, 이를 통해 향후 다른 도메인으로의 확장된 적용 가능성이 유효함을 확인하였다.

• 한국의류산업학회지
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• 제24권2호
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• pp.229-240
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• 2022

This study explores the effect of anthropomorphism on fashion chatbot reliability, mediated by perceived intelligence and cognitive evaluation. The moderating effects of individuals' need for human interaction between chatbot anthropomorphism and perceived intelligence, cognitive evaluation, and chatbot reliability are also explored. Participants, who were recruited through the online research firm, responded to questions after watching a video clip showing a conversation with a fashion chatbot on a mobile screen. The data were collected through Mturk, a crowdsourcing platform with an online research panel. All responses (N = 212) were analyzed using SPSS 26.0 for the descriptive statistics, frequency analysis, reliability analysis, exploratory factor analysis, and PROCESS procedure. The results demonstrate that chatbot anthropomorphism increases chatbot reliability, and this is mediated by chatbot intelligence. Although chatbot anthropomorphism increases cognitive evaluation, the effect of cognitive evaluation on chatbot reliability is not significant; thereby, the effect of chatbot anthropomorphism on chatbot reliability is not mediated by the cognitive evaluation. The direct effect of anthropomorphism on chatbot reliability is also moderated by individuals' need for human interaction. For participants with a high need for human interaction, chatbot anthropomorphism increases chatbot reliability; however, anthropomorphism does not significantly affect chatbot reliability for participants with a low need for human interaction. The study's findings contribute to expanding the literature on consumers' new technology acceptance by testing the antecedents affecting service reliability.

• 한국의류학회지
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• 제44권4호
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• pp.573-593
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• 2020

This study analyzes consumers' responses toward chatbot services in a fashion retail context. Anthropomorphism and personalization of chatbots are proposed as critical features of a chatbot service that attract positive behavioral intentions from consumers. Social presence, trust, and enjoyment are expected to mediate associations among chatbot characteristics and consumers' acceptance of the service. The experiment was conducted in a controlled laboratory; participants were instructed to engage with a virtual shopping chatbot service via their cell phone and complete a questionnaire online. A total of 189 participants participated in this study along with and four experimental groups of 2 (anthropomorphism: high / low) × 2 (personalization: high / low) were formed with between-subject design. The collected data were analyzed using SPSS 25.0 and SPSS PROCESS Macro programs. The results show that the effect of anthropomorphism and personalization of chatbots on consumers' service acceptance intention when using fashion shopping chatbot service were mediated sequentially by social presence, trust, social presence and enjoyment. This study provides meaningful evidence on the effects of chatbots characterized by anthropomorphism and personalization on consumer responses, acceptance intention and associated psychological mechanisms by expanding the field of consumer behavior into chatbot services.

• 한국의류산업학회지
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• 제24권2호
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• pp.183-194
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• 2022

This study aims to understand the consumers' negative responses to communication failure of chatbots caused by their imperfections. Specifically, this study examines 1) the relationship among chatbot's communication failure, dissatisfaction, negative behavior (complaint, negative word-of-mouth (nWOM), and inertia); 2) the moderating effect of technostress on the relationship between chatbot's communication failure and dissatisfaction; 3) the differences in the negative responses between the generation MZ and the previous generations. Data were collected via an online survey. First, the participants interacted with the chatbot developed for this survey, to experience the chatbot's communication failure. Thereafter, they responded to a questionnaire. PLS-SEM was conducted using the R software environment to test the hypotheses. This study empirically identified that chatbot's communication failure positively affected dissatisfaction. In addition, the customers who were more dissatisfied with the chatbot's communication failures were more likely to complain than engage in nWOM. Compared to the generation MZ, chatbot's communication failure caused a higher level of dissatisfaction in previous generations. The results suggest that online shopping malls should carefully introduce an improved chatbot service after minimizing its communication failure rate. The chatbot developers of online shopping malls targeting middle-aged and elderly consumers should strive to develop and implement strategies to further alleviate consumers' dissatisfaction in the situation of chatbot's communication failure.

• 한국의류학회지
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• 제46권1호
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• pp.80-98
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• 2022

Artificial intelligent chatbot services have recently become common in fashion e-retailing and are expected to improve online shopping by making it easy to recommend products. This study examines whether the perceived quality of a fashion chatbot affects consumers' trust and perception of usefulness, which in turn influences satisfaction and intention to use, in accordance with the information system success model. The study also investigates differences in perceived quality and consumer response variables between high and low groups of self-efficacy. A total of 341 consumers participated in an online survey. The results revealed that information quality and system quality had a significant impact on perceived usefulness and trust, and that service quality significantly impacted trust. Perceived usefulness and trust had a positive effect on consumer satisfaction, which in turn had a positive effect on intention to use. In addition, the findings revealed that people who had higher self-efficacy showed higher scores on perceived usefulness, trust, satisfaction, and intention to use chatbots as compared to people who had lower self-efficacy. This study suggested theoretical implications by applying the information system success model theory to fashion chatbot studies. It also suggested practical implications for e-commerce marketers developing retail strategies.