TY - JOUR
T1 - Exploring the Key Factors that Lead to Intentions to Use AI Fashion Curation Services through Big Data Analysis
AU - Shin, Eunjung
AU - Hwang, Ha Sung
N1 - Publisher Copyright:
Copyright © 2022 KSII.
PY - 2022/2/28
Y1 - 2022/2/28
N2 - 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.
AB - 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.
KW - Artificial Intelligence (AI)
KW - Big Data
KW - Curation
KW - Fashion
KW - Text Mining
UR - http://www.scopus.com/inward/record.url?scp=85126540016&partnerID=8YFLogxK
U2 - 10.3837/tiis.2022.02.016
DO - 10.3837/tiis.2022.02.016
M3 - Article
AN - SCOPUS:85126540016
SN - 1976-7277
VL - 16
SP - 676
EP - 691
JO - KSII Transactions on Internet and Information Systems
JF - KSII Transactions on Internet and Information Systems
IS - 2
ER -