TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
Exploring the Key Factors that Lead to Intentions to Use AI Fashion Curation Services through Big Data Analysis |
| 영문제목(English Title) |
Exploring the Key Factors that Lead to Intentions to Use AI Fashion Curation Services through Big Data Analysis |
| 저자(Author) |
Eunjung Shin
Ha Sung Hwang
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| 원문수록처(Citation) |
VOL 16 NO. 02 PP. 0676 ~ 0691 (2022. 02) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
An increasing number of companies in the fashion industry are using AI curation services. The purpose of this study is to investigate perceptions of and intentions to use AI fashion curation services among customers by using text mining. To accomplish this goal, we collected a total of 34,190 online posts from two Korean portals, Naver and Daum. We conducted frequency analysis to identify the most frequently mentioned keywords using Textom. The analysis extracted “various,” “good,” “many,” “right,” and “new” at the highest frequency, indicating that consumers had positive perceptions of AI fashion curation services. In addition, we conducted a semantic network analysis with the top-50 most frequently used keywords, classifying customers’ perceptions of AI fashion curation services into three groups: shopping, platform, and business profit. We also identified the factors that boost continuous use intentions: usability, usefulness, reliability, enjoyment, and personalization. We conclude this paper by discussing the theoretical and practical implications of these findings. |
| 키워드(Keyword) |
Artificial Intelligence (AI)
Big Data
Curation
Fashion
Text Mining
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| 파일첨부 |
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