The Research Journal of the Costume Culture (복식문화연구)

The Costume Culture Association (복식문화학회)
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Impact of user evaluations of website attributes on recommendation intention for revitalizing B2B textile platform

B2B 섬유 플랫폼 활성화를 위한 웹사이트 평가속성이 추천의도에 미치는 영향

  • Mi-Hwa Choi (Dept. of Fashion Marketing, Keimyung University) ;
  • Munyoung Kim (Dept. of Fashion Marketing, Keimyung University)
  • 최미화 (계명대학교 패션마케팅학과) ;
  • 김문영 (계명대학교 패션마케팅학과)
  • Received : 2024.02.19
  • Accepted : 2024.03.23
  • Published : 2024.04.30
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Abstract

This study examines options to revitalize a B2B textile trading platform, exploring user satisfaction and perceptions of the importance of several website features. Between June 8 and June 21, 2023, fashion studies majors and domestic fashion brand product planners were asked to use the website of an open B2B textile platform for 30 minutes and then evaluate its features by responding to a survey. The final sample for analysis wad comprised of 150 questionnaires. To analyze the key textile website features, a paired t-test, Importance-Performance Analysis (IPA), and multiple regression analysis were utilized. The analysis classified the key textile website features related to user importance and satisfaction into the following categories: convenience, appearance, product information, and uniqueness. An analysis investigation of the differences in importance and satisfaction for each website evaluation attribute found significant differences in 12 attributes. The IPA analysis revealed that attributes such as product reliability, quality, a convenient search function, and convenient page movement are highly important to users and garner high user satisfaction; these findings demonstrate the importance of maintaining these elements. Images on the main screen, the latest trend information, and product prominence attributes also garner high importance ratings, but result in low user satisfaction, which signifies extensive revision is required. Finally, user evaluation of the convenience, appearance, and product information of the website was found to affect user recommendation intention.

Keywords

Acknowledgement

This work was supported by the Technology Innovation Program funded by the Korea Institute for Advancement of Technology (No. P0014711).

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