• Fashion & Textile Research Journal
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• v.24 no.2
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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.

• Journal of Fashion Business
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• v.25 no.6
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• pp.119-130
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• 2021

This study investigated the effects of the chatbot's level of anthropomorphism - closeness to the human form - and its self-disclosure - delivery of emotional exchange with the chatbot through its facial expressions and chatting message on the user's intention to accept the service. A 2 (anthropomorphism: High vs. Low) × 2 (self-disclosure through facial expressions: High vs. Low) × 2 (self-disclosure through conversation: High vs. Low) between-subject factorial design was employed for this study. An online survey was conducted and a total of 234 questionnaires were used in the analysis. The results showed that consumers used chatbot service more when emotions were disclosed through facial expressions, than when it disclosed fewer facial expressions. There was statistically significant interaction effect, indicating the relationship between chatbot's self-disclosure through facial expression and the consumers' intention to use chatbot service differs depending on the extent of anthropomorphism. In the case of "robot chatbots" with low anthropomorphism levels, there was no difference in intention to use chatbot service depending on the level of self-disclosure through facial expression. When the "human-like chatbot" with high anthropomorphism levels discloses itself more through facial expressions, consumer's intention to use the chatbot service increased much more than when the human-like chatbot disclosed fewer facial expressions. The findings suggest that chatbots' self-disclosure plays an important role in the formation of consumer perception.

• Fashion & Textile Research Journal
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• v.24 no.2
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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.

• 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 the Korean Society of Clothing and Textiles
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• v.44 no.4
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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.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.3
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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.

• 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 Fashion Business
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• v.25 no.4
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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.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.1
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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.